Proceedings from the 2016 UR Forum Pr oceedings f r om t he 2016 UR For um This publication is made up of a series of submissions from session leads of the 2016 Understanding Risk Forum. These submissions were compiled by the Global Facility for Disaster Reduction and Recovery (GFDRR). The content and findings of this publication do not reflect the views of GFDRR and the World Bank Group. The World Bank does not guarantee the accuracy of the data in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Washington, DC, September 2016 Editor: Anne Himmelfarb Designed by Miki Fernández (miki@ultradesigns.com), Washington, DC ©2016 by the International Bank for Reconstruction and Development/The World Bank 1818 H Street, NW Washington, DC 20433 All rights reserved. Photo: On October 23, 2011 the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument on NASA’s Terra spacecraft captured the flood waters that were approaching Bangkok, Thailand as the Ayutthaya River overflowed its banks. Photo credit: NASA/GSFC/METI/ERSDAC/JAROS, and U.S./Japan ASTER Science Team. Contents 4 Acknowledgments 6 Foreword 8 Abbreviations 11 Overview 12 Major Disasters Since UR2014 n Connecting for Decision Making 17 “I Understand Risk, You Misunderstand Risk, S/he Fails to Act”: Learning to Anticipate Behavioral Challenges in Predisaster Decision Making 23 The Final Mile: Connecting an Impact-Based Warning Service to Decision Making 31 When Uncertainty Is Certain: Tools for Improved Decision Making for Weather and Climate 35 Communicating for Action: What’s Needed? 41 MapSlam: Revealing the Common Misperceptions about El Niño and La Niña n Data 49 Global School Safety: Reaching for Scale through Innovation 55 Bridging the Divide: Digital Humanitarians and the Nepal Earthquake 61 Breaking Barriers for the Common Good: Open Data and Shared Risk Analysis in Support of Multilateral Action n Modeling 69 Reading the Tea Leaves: When Risk Models Fail to Predict Disaster Impacts 75 Challenges in Developing Multihazard Risk Models from Local to Global Scale 81 Climate Extremes and Economic Derail: Impacts of Extreme Weather and Climate-Related Events on Regional and National Economies 2 n Vulnerability and Resilience 95 Checking the Vitals: Making Infrastructure More Resilient 101 Putting People First: Practices, Challenges, and Innovations in Characterizing and Mapping Social Groups 107 How Risks and Shocks Impact Poverty—and Why, When, and Where Better Financial Protection Can Help n The Future of Risk and Risk Assessment 117 Disruptors: Cutting-Edge Technologies That Are Changing the Way We Understand Risk 121 Building a Less Risky Future: How Today’s Decisions Shape Disaster Risk in the Cities of Tomorrow 127 The Domino Effect: The Future of Quantifying Compounding Events in Deltas 133 Understanding Risk Is Essential for the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030: Targeting the Future with Science and Technology 87 Climate Change Plenary Using Risk Information to Mitigate Climate Change Impacts —Challenges and Opportunities 3 Acknowledgments The energy and dynamism felt at the fourth global UR Forum would not have been possible without the continued support and enthusiasm of the UR community and those who came to Venice. Thank you for continually coming to UR events to contribute your passion, knowledge, and creativity to this important field. While the UR core team—Francis Ghesquiere, Dr. Alanna Simpson, Emma Phillips, Joaquin Toro, Simone Balog, and Julie Aaserud—cannot mention all the organizations and individuals who contributed their time and ideas, we would like to highlight some of our key partners whose support made UR2016 possible: the Italian Agency for Development Cooperation, Protezione Civile, the Global Facility for Disaster Reduction and Recovery (GFDRR), the World Bank Group, ERN International, ImageCat, WillisTowersWatson, CIMA Research Foundation, Nephila, RMSI, and Vela. Thank you to all the organizations that were involved in UR2016: Ambiental Technical Solutions Ltd., Arup, Asian Disaster Preparedness Center (ADPC), Australian Aid, BBC Media Action, Boston University, Ca’ Foscari University, Canadian Space Agency, Committee on Earth Observation Satellites (CEOS), Deltares, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Directorate-General for European Civil Protection and Humanitarian Aid Operations (ECHO) of the European Commission, EURAC Research, Euro-Mediterranean Centre on Climate Change, European Space Agency–ESRIN: Earth Observation Science & Applications, FM Global, GEM (Global Earthquake Model) Foundation, Geneva Association, Global Resilience Partnership, Humanitarian Data Exchange of UN OCHA, Institute for Environmental Studies (IVM) at VU University Amsterdam, International Federation of Red Cross Red Crescent Societies, International Research Institute for Climate and Society at Columbia University, International Water Management Institute, Joint Research Centre of the European Commission, Kartoza, Kathmandu Living Labs, King’s College London, NYU GovLab, RASOR Project, Red Cross Red Crescent Climate Centre, Resurgence, riocom, safehub, SecondMuse, Stanford University, United Kingdom Department for International Development (DFID), United Nations Development Programme (UNDP), United Nations Environment Programme (UNEP), United Nations Major Group for Children and Youth (UNMGCY), United Nations Office for the Coordination of Humanitarian Affairs (UN OCHA), United Nations Office for Disaster Risk Reduction (UNISDR), United States Agency for International Development (USAID), University College London (UCL), UK Met Office, and VU University Amsterdam. 4 We would also like to extend our gratitude to our keynote, opening, closing, and send-off speakers: Gianumberto Accinelli, Jamais Cascio, Fabrizio Curcio, Ermelinda Damiano, Laura Frigenti, Francis Ghesquiere, Polly Morland, John Roome, Pablo Suarez, and Laura Tuck. Thank you to those who contributed to our plenaries: Dareen Abughaida, Esther Baur, Stephen Briggs, Marianne Fay, Prema Gopalan, Claus Haugaard Sørensen, Kerri-Ann Jones, Jemilah Mahmood, Maite Rodriguez, Sheryl Sandberg (remotely), and Anna Wellenstein. Thank you to the inspiring speakers at the 5x15 event who provided a different perspective on risk: Benedict Allen, Misha Glenny, Francesco da Mosto, Jane da Mosto, and Marcus du Sautoy. Thank you to our session leads for putting extensive time and effort into organizing their sessions, and for writing the summaries for this publication: Amal Ali, Vica Rosario Bogaerts, Nama Budhathoki, Lorenzo Carrera, Pietro Ceccato, Daniel Clarke, Fernando Ramirez Cortes, Erin Coughlan, Lydia Cumiskey, Luigi D’Angelo, Paul Davies, Vivien Deparday, Mauro Dolce, Ron Eguchi, Pete Epanchin, Carina Fonseca Ferreira, Stu Fraser, Darcy Gallucio, Lisa Goddard, Lou Gritzo, Maryam Golnaraghi, Mark Harvey, Thomas Kemper, Randolph Kent, Andrew Kruczkiewicz, David Lallemant, Jennifer LeClerc, Olivier Mahul, Rick Murnane, Virginia Murray, Jaroslav Mysiak, Sophia Nikolaou, C. Dionisio Perez-Blanco, Angelika Planitz, Lisa Robinson, Tom Roche, Roberto Rudari, Peter Salamon, John Schneider, Rajesh Sharma, Robert Soden, Frederiek Sperna Weiland, Pablo Suarez, Andy Thompson, Andrew Thow, Emma Visman, Chadia Wannous, Philip J. Ward, Hessel Winsemius, and Jianping Yan. We would like to acknowledge the teams who were involved and the following individuals: Tahir Akbar, Elizabeth Alonso-Hallifax, Ghadeer Ashram, Jorge Barbosa, Sofia Bettencourt, Jack Campbell, Naraya Carrasco, Manuela Chiapparino, James Close, Rossella Della Monica, Vivien Deparday, Nicolas Desramaut, Tafadzwa Dube, Marc Forni, Stu Fraser, Tayler Friar, Habiba Gitay, Alistair Holbrook, Nicholas Jones, Brenden Jongman, Keiko Kaneda, Elif Kiratli, David Lallemant, Sonia Luthra, Henriette Mampuya, Rick Murnane, James Newman, Cristina Otano, Shaela Rahman, Sumati Rajput, Cindy Quijada Robles, Keiko Saito, Robert Soden, Luis Tineo, Vladimir Tsirkunov, Jon Walton, and Stephan Zimmermann. And last, but not least, a huge thank you to the core team’s stellar event production counterpart who created a dynamic and creative environment in Venice: Alan D’Inca’, Miki Fernández, Anne Mussotter, Andrea Dadda, Luca Domenicucci, Jimmy Ennis, Marcella Leonetti, Antonio Montanari, and Luigi Tortato; and the team’s Washington, DC support: Desy Adiati, Regianne Bertolassi, and Anne Himmelfarb. Thank you for your time, dedication, and consistent good nature in making this event a success. The UR core team—Francis Ghesquiere, Alanna Simpson, Emma Phillips, Joaquin Toro, Simone Balog, and Julie Aaserud 5 Foreword The fourth edition of the Understanding Risk Forum (UR2016) was a resounding success, bringing together practitioners from more than 100 countries to meet, learn, and share best practices. This was our most ambitious and global forum yet. More than 2,000 meetings and networking opportunities saw policy makers, risk modelers, urban planners, economists, psychologists, communicators, and others meet in the inspiring setting of the 12th-century Venetian Arsenale. The city of Venice hosted UR2016 with grace and hospitality, offering an inspiring location to showcase what is at stake in risk management, as well as all the advances that we as a community have achieved over seven years. Participants kicked off the week with some 40 Focus Day activities, from learning to build a mobile weather station to creating a new community of practice for climate resilience in small island states. On Wednesday, session leads welcomed participants to UR2016 through a series of Ignite Talks. Amal Ali passionately described how new technologies could disrupt the disaster risk management field, telling of how her own relatives in Somalia may be able to live more sustainably. Hessel Winsemius, a veteran of UR, convinced us of the need to address cascading hazards if we are to truly understand risk. The following days were packed with fascinating sessions as well as ample time to network within and across professional fields. In an intensely interactive session, Pablo Suarez led a series of games that inspired us to examine just how we make decisions, and how framing risks differently can influence reactions, decisions, and outcomes. A new “MapSlam” session, inspired by poetry slams, saw two individuals go head-to-head to communicate information on El Niño and La Niña. We learned lessons from Mozambique, the Philippines, and the United Kingdom on incorporating impact-based forecasting—including a recommendation to build a community of practice in this field that could be hosted at the next UR Forum. In a first for UR forums, the session “Communicating for Action” used the Glisser platform, a tool that allows for live engagement with audiences during presentations. 6 A little over a year since the devastating earthquake in Nepal, Nama Budhathoki shared lessons on incorporating data collection and management into projects now, before a disaster strikes, to enable better response when the worst does happen. John Roome led us through a Hard Talk with leaders in the insurance industry, the humanitarian sector, and a space agency. One thread was constant: we must continue to engage with stakeholders across all fields to build alliances that can drive understanding and action. Maybe the main innovations presented this year were in the area of big data and social media analytics. Several speakers showed how social media can be used to improve early warning systems, to map vulnerable infrastructure, or to monitor reconstruction programs. We are excited to track how this growing field evolves by our next forum in 2018. This forum saw the launch of many publications and tools. Among them, The Making of a Riskier Future underscores the need for future risks to be integrated into today’s development planning to prevent our growth patterns from concentrating assets and populations in the most threatened locations. Some highlights from the forum are not captured in these pages yet enriched the experience: Sheryl Sandberg, COO of Facebook, participated by video to launch our dialog on gender; futurist Jamais Cascio showed us that there continues to be good in the world; and participants released 300 butterflies above the canals of Venice as part of an effort to build corridors of sustainability. The success of UR2016 would not have been possible without the contribution of many individuals and organizations from around the world. We thank you for your generosity, curiosity, and passion! We hope you enjoy these UR2016 proceedings, and look forward to what’s to come in the next two years before UR2018. See you then! Francis Ghesquiere Head, GFDRR Secretariat 7 Abbreviations 1BC One Billion Coalition for Resilience CGE computable general equilibrium DRM disaster risk management DRMKC Disaster Risk Management Knowledge Centre DRR disaster risk reduction ECHO Directorate-General for European Civil Protection and Humanitarian Aid Operations EU European Union FEMA Federal Emergency Management Agency FOREWARN Forecast-based Warning Analysis and Response Network GEM Global Earthquake Model GFDRR Global Facility for Disaster Reduction and Recovery GFP Global Flood Partnership GIS geographic information system GTM Global Tsunami Model GVM Global Volcano Model HOT Humanitarian OpenStreetMap Team IAM integrated assessment model IBLI index-based livestock insurance ICL International Consortium on Landslides IO input-output IRI International Research Institute for Climate and Society KLL Kathmandu Living Labs KNMI Royal Netherlands Meteorological Institute MASDAP Malawi Spatial Data Portal 8 MoU memorandum of understanding NOAH National Operational Assessment of Hazards OCHA United Nations Office for the Coordination of Humanitarian Affairs OECD Organisation for Economic Co-operation and Development OpenDRI Open Data for Resilience Initiative OSM OpenStreetMap PacRIS Pacific Risk Information System PAGASA Philippine Atmospheric Geophysical and Astronomical Services Administration PARIS21 Partnership in Statistics for Development in the 21st Century PCRAFI Pacific Catastrophe Risk Assessment and Financing Initiative PHE Public Health England PIP prioritized investment plan SIDA structural integrity and damage assessment SOPAC SPC Applied GeoScience and Technology Division SOPs standard operating procedures SPC Secretariat of the Pacific Community STAG Scientific and Technical Advisory Group UNEP GRID United Nations Environment Programme Global Resource Information Database UNISDR United Nations Office for Disaster Risk Reduction UR Understanding Risk USAID U.S. Agency for International Development WMO World Meteorological Organization All dollar amounts are U.S. dollars unless otherwise indicated. 9 days in Venice % 57sessions 41 female participation 2000 meetings 101 countries represented 350 organizations 300 butterflies released 10 Overview The Understanding Risk (UR) community was born in 2010 out of the recognition that disaster risk assessment and identification are activities that cut across sectors and industries. What began with just five founding partners has grown into a community of over 6,500 experts and practitioners. This network has inspired innovation by sharing and applying best practices, developing technological solutions, and enabling cross-sector partnerships. This vibrant UR community meets every two years, bringing together a diverse group of people from the private, public, nonprofit, technology, nongovernmental, and financial sectors. Every iteration of the UR Forum has produced new ideas and partnerships that have improved risk assessments and helped to integrate them into policy and development planning. UR2016, “Building Evidence for Action,” was held in Venice, Italy, from May 16 to May 20, 2016. With financial support from 11 Major Disasters Since UR2014 UNITED KINGDOM USA 2015 2014 No data No data 48,000 No data $1,200,000 FRANCE $3,900,000 2015 3275 No data No data MEXICO 2014 HAITI 6 75,135 2016 No data $2,500,000 3,600,000 No data GUATEMALA 2015 350 1,112 $5,000,000 ECUADOR 2016 480 89,605 BRAZIL No data 2014 No data Year Fatalities 27,000,000 PERU $5,000,000 Total affected Est. damages (US$ million) 2014 505 Key 109,257 No data Cold wave Drought ARGENTINA Earthquake 2016 No data Fire 15,000 Please note, “no data” indicates $1,300,000 Flood where data does not exist and there is a data gap. Documenting the Heat wave impact of disasters is important for Landslide understanding risk in post-disaster forensic analysis, and thus we need Storm more information on disasters. 12 Between the third UR Forum, held in late June–early July 2014, and the fourth UR forum in May 2016, the world has seen hundreds of disasters that have killed almost 50,000 people, affected over 550 million people, and caused more than $150 billion in mostly uninsured damages. Below are some of the largest disasters in terms of economic losses and human impact. CHINA 2014 731 1,120,513 $5,000,000 BELGIUM 2014 No data 2015 410 27,500,000 No data AFGHANISTAN $2,500,000 No data 2014 431 2014 140,100 NEPAL 71 2015 9,960,099 No data 8,831 $4,200,000 PAKISTAN 5,639,722 JAPAN 2014 2015 $5,100,000 2014 255 1,229 37 2,530,673 80,000 2,800 $2,000,000 No data $5,900,000 MYANMAR ETHIOPIA INDIA 2015 2015 110 No data 2014 PHILIPPINES 9,000,000 10,200,000 45 $119,000 No data 920,000 2014 2014 $7,000,000 111 18 SOMALIA SRI LANKA 4,654,966 4,150,400 2015 2014 2016 $820,000 $110,000 No data 298 245 MALAWI 4,700,000 675,000 500,000 $16,000,000 PAPUA NEW 2015 No data $2,000,000 278 INDONESIA GUINEA No data 2015 2015 2015 $390,000 293 19 24 13,709,887 409,664 2,000,000 No data $1,000,000 $60,000 2015 325 1,801,000 AUSTRALIA SOUTH AFRICA $2,200,000 2015 2015 7 No data 2015 1,000 270,000 2248 $1,300,000 $2,000,000 No data No data 2016 No data 330,000,000 No data 13 14 Connecting for Decision Making “I Understand Risk, You Misunderstand Risk, S/he Fails to Act”: Learning to Anticipate Behavioral Challenges in Predisaster Decision Making [page 17] The Final Mile: Connecting an Impact-Based Warning Service to Decision Making [page 23] When Uncertainty Is Certain: Tools for Improved Decision Making for Weather and Climate [page 31] Communicating for Action: What’s Needed? [page 35] MapSlam: Revealing the Common Misperceptions about El Niño and La Niña [page 41] 15 Proceedings from the 2016 UR Forum Connecting for Decision Making “I Understand Risk, You Misunderstand Risk, S/he Fails to Act”: Learning to Anticipate Behavioral Challenges in Predisaster Decision Making Pablo Suarez, University College London Introduction the best option, and will act irrational choices made by accordingly. those who manage risks, and Despite remarkable progress suggested ways to use knowledge in our ability to model natural In this framing, if we want to about predictable behavior in hazards, we continue to see help people and organizations to order to improve design and too much inaction, or wrong understand and address risk, all we implementation of humanitarian action, in the field of disaster need to do is to share information and development work. risk management—in areas and explain how different actions ranging from individual reaction can lead to desirable outcomes. Of to forecasts to urban planning to course, there is an inconsistency Predictable Failures global policy. Yet the community between the assumption of rational to Understand of practice that convenes at the choice and the vastly suboptimal and Address Risk: Understanding Risk (UR) Forum, choices we see in the real world, Experiencing Decision like most practitioners who aim to as recent books—Predictably Errors link knowledge with action, tends Irrational (Ariely 2008) and Thinking to embrace the “rational” model of Fast and Slow (Kahneman 2011)— After hearing about the rational decision making. This model entails have shown. Unfortunately, the risk model of decision making, a series of beliefs: management sector still has a lot participants were invited to play to learn. “Storm Story,” a short game on l We will maximize outcome warnings and actions. Each team of of our choices. During an intensely interactive roughly 10 players stood in a circle l We always prefer “more” 90-minute session held at the and confronted the risk of a storm to “less.” 2016 UR Forum, approaches that followed a set of simple rules: and insights from decision l Our preferences are consistent. science, behavioral economics, l The storm grows in magnitude l We want perfect information. brain imaging, and other fields from 1 to 7. The number has l We can do the math to find revealed some of the allegedly to be stated loud and clear: the 17 “I Understand Risk, You Misunderstand Risk, S/he Fails to Act” first player says “one,” the next whose rules were much simpler the face. During the pre-debate says “two,” and so on. After than those of the real world and conversation with organizers, a number “seven,” the storm whose consequences nowhere waiter brings snacks. You happen loses its strength and becomes near as serious. to know that the food contains the a magnitude “one,” then starts allergen, and realize how helpful growing again. A short debrief examined the it would be for your cause if the l When confronting a storm of parallels between gameplay and opponent ate the food. . . category 1 to 6, a player has real-world experience. Players to invest in small protection by learned about recent findings Half of participants received a putting the right or left hand on from neuroscience showing that yellow survey that asked the the chest. When confronting a different parts of the brain engage following question: Do you pick category 7 storm, a player has in decision-making processes in up the tray and offer the snack to invest in large protection by different circumstances, which to your opponent? (you know the putting a hand on the head. The leads to certain predictable offer will be accepted) A = Yes; protection gesture has to be problems in choice expression. The B = No made while stating, immediately issue of geoengineering (a proposal after the preceding player, the to deliberately manipulate the The other half of participants number corresponding to storm global climate with sun-blocking received a white survey that asked magnitude. particles injected in the upper a related but different question: atmosphere in order to reverse Your opponent reaches out to the l The storm travels around global warming) was introduced tray and takes a snack. Do you the circle clockwise or as an opportunity for reflecting indicate that the food contains the counterclockwise depending on how assumptions of rationality allergen, and thus try to stop this? on the preceding player’s hand may play out in related decision- A = No; B = Yes gesture for protection (left hand on chest or head pointing making processes. According to classic economic right means counterclockwise, theory, the only thing that right hand means clockwise). The Role of Framing matters in a person’s choice is l If players make a mistake—wrong in Choice Preference: her preferences about the end number, wrong gesture, wrong From “the Allergic state (would you rather have time (too late, or out of place), or Snack” Question to an opponent affected by allergy hesitation (doubt in number or Improv or not?). It shouldn’t matter gesture)—they must pay for the how the end state is reached. consequences of bad disaster For the next activity, participants However, participants understood management by walking around were invited to examine the that framing a choice as action the circle behind other players following scenario: (yellow survey) versus framing it while the game keeps going. as omission (white survey) makes While frequent mistakes led to You will represent the views of the a difference. This is actually a loud laughter and team bonding, UR community in a televised debate predictable difference: people participants experienced firsthand about a proposed legislation that tend to favor omissions over the extent to which the rational would lead to unacceptable levels commissions. These preferences, model fails to explain how people of disaster risk. Your opponent is which behavioral scientists describe process information to make known for good debating skills. It with terms such as “omission decisions: in the fiction of the is less known that this opponent bias” and “status quo bias,” play a game, the many mistakes meant has a mild, non-life-threatening substantial role in risk management; failure to act correctly for disaster food allergy that leads to profuse for example, they affect how management—and this in a system coughing, itching, and swelling of forecasters communicate science- 18 Proceedings from the 2016 UR Forum Connecting for Decision Making based predictions (see Suarez and future conditions of high disaster by Tint, McWaters, and van Patt 2004). risk: people tend to stick to their Driel (2015), risk managers can original choice, whether it involves benefit from applied improvisation Omission bias and status quo bias building in a coastal floodplain through increased authenticity and are noteworthy because they when seas are rising, or staying presence, improved ability to think suggest that stakeholders will home when a hurricane warning on their feet, more-collaborative be reluctant to change decisions calls for evacuation. relationships, and greater based on new information about creativity and innovation. Despite remarkable progress in our ability to model natural hazards, we continue to see too much inaction, or wrong action, in the field of disaster risk management—in areas ranging from individual reaction to forecasts to urban planning to global policy. risks. A modified version of the Session participants also learned “Monty Hall” game demonstrated about gender dimensions of status Conclusions and this reluctance: The facilitator quo bias: experimental evidence Recommendations: showed four cards (an ace and reported by Patt, Daze, and Suarez Choice “Anomalies” three queens), shuffled them, (2009) shows not only that some Happen, and Process placed them face down, and men were unlikely to change their Matters invited a player to guess which choice, but also that they were All these activities immersed was the ace (the winning card). even more likely to stick to their session participants in experiences Before turning the chosen card, original choice when an advisor that highlighted the contrast however, the facilitator turned up suggested that they switch cards. between observed behavior and two of the other three cards and predictions from the rational showed them to be queens (losing A final activity drew from the choice theory of decision making. cards). This left two cards face improvisation talents of singer Several key concepts and lessons down—the card that the player Bobby McFerrin and the control- emerged from these activities: had indicated, and one remaining autonomy-cooperation triad card. The facilitator then gave the presented by Keidel (1995) in his l Bounded rationality. In decision player the choice to stay with her book on organizational design. making, the rationality of original pick, or to switch to the Participants first played a short individuals is limited by the finite other remaining card. game on framings for interaction amount of time they have to (“No,” “Yes, but. . .” and “Yes, and. . .”), make decisions, the cognitive Most players prefer to stick to the then reflected on a video of a limitations of their minds, and original choice, even when told by brief improvisational musical the information they have. an advisor that switching cards performance.2 This exercise greatly improves the chances of l Satisficing. Instead of optimizing enabled participants to experience winning.1 The situation is analogous all the time, people tend to and appreciate the value of applied “satisfice”—that is, define a to instances where scientists improvisation, a field that offers lower limit of acceptability share forecasts about likely individuals the skills, methods, for the outcome, and adopt and mind-set they need to feel an available option that is 1 The mathematics of the game are comfortable and connected in the surprising: switching cards will generate considered good enough. a winning outcome with a probability of face of the unknown. As argued 3 in 4, while staying with the original pick l Prospect theory. Our estimation will win only one-fourth of the time. This 2 “Bobby McFerrin Demonstrates the of probabilities is often is counterintuitive to most people, and Power of the Pentatonic Scale,” July very unreliable. Changes in indeed most people stayed with their 23, 2009, https://www.youtube.com/ original choice, and lost. watch?v=ne6tB2KiZuk. perspective may change the 19 “I Understand Risk, You Misunderstand Risk, S/he Fails to Act” relative desirability of options, Patt, A. G., A. Daze, and P. Suarez. 2009. References and “Gender and Climate Change Vulnerability: so that framing can influence Further Resources What’s the Problem, What’s the Solution?” choice. Decision-making errors In Distributional Impacts of Climate Ariely, D. 2008. Predictably Irrational: The should be not only expected, but Hidden Forces That Shape Our Behavior. Change and Disasters: Concepts and Cases, also predicted. New York: Harper Collins. edited by M. Ruth and M. E. Ibarraran, 82–102. Cheltenham, UK: Edward Elger. Kahneman, D. 2011. Thinking Fast and Slow. In the same way that hydrology New York: Farrar, Straus & Giroux. Suarez, P. and A. G. Patt. 2004. “Cognition, shows us predictable patterns Keidel, R. W. 1995. Seeing Organizational Caution and Credibility: The Risks of Climate in flooding, decision science Patterns: A New Theory and Language Forecast Application.” Risk, Decision and of Organizational Design. San Francisco: Policy 9, no. 1: 75–89. shows us predictable patterns Berret-Koehler. Tint, B. S., Viv McWaters, and Raymond van in human behavior, and helps us Moore, L. A., R. Romero-Canyas, P. Suarez, Driel. 2015. “Applied Improvisation Training understand how and why people M. Chu Baird, K. L. Bimrose, and R. Fujita. for Disaster Readiness and Response: 2015. “Lose a Day Off If You Don’t Read make decisions the way they do. This: Introducing Humanitarians and Preparing Humanitarian Workers and Insight into these patterns is of Environmentalists to ‘Decision Science’ Communities for the Unexpected.” Journal Insights.” Red Cross Red Crescent Climate of Humanitarian Logistics and Supply Chain great significance to disaster risk Management 5: 73–94. Centre Working Paper Series 5, The Hague, reduction and other humanitarian Netherlands. and development work. Participants get a taste of what’s to come in this interactive session during Pablo Suarez’s Ignite talk on May 18. 20 Photo credit: Emanuele Basso. Proceedings from the 2016 UR Forum Connecting for Decision Making In the same way that hydrology shows us predictable patterns in flooding, decision science shows us predictable patterns in human behavior, and helps us understand how and why people make decisions the way they do. 21 GAME OVER? Exploring the Complexity of Actionable Information through Gaming Wave height of the tsunami from the 2011 Tohoku earthquake off the east coast of Japan. Photo credit: NOAA. 22 Proceedings from the 2016 UR Forum Connecting for Decision Making The Final Mile: Connecting an Impact-Based Warning Service to Decision Making Lydia Cumiskey, Deltares Paul Davies, Met Office, UK Nyree Pinder, Met Office, UK Richard Murnane, Global Facility for Disaster Reduction and Recovery Introduction Background and of the forecast, but it also helps Concepts to manage users’ expectations Despite huge advances in about forecasting accuracy. This, in forecasting, climate science, and Generating Useful Science turn, enables those delivering the technology, it remains a challenge warnings to build trust with their Effective warnings require good to present early warnings in a users and ensure action is taken science both for predicting user-friendly way that initiates when needed. hazards and for estimating the protective actions. One approach associated impacts. The impacts to meeting this challenge is The World Meteorological (e.g., on the public and various impact-based forecasting, which Organization (WMO 2015a) has a sectors) can be understood by seeks to improve end-user’s useful graphic showing how the having forecasters work with decision making and prompt components of an impact-based sector representatives. Practically action by providing information forecast system relate to one this means making collaborative on the potential impacts of another and illustrating three hazard events. This approach decisions to set thresholds for different ways for estimating involves mainstreaming the use appropriate actions based on the a hydrometeorological hazard’s of exposure and vulnerability expected impacts, with thresholds impact (figure 1). The traditional information in forecasts, a step defined in terms of certain hazard approach (red arrows) relates the that presents its own challenges. parameters such as expected magnitude of the likely impact The discussion below looks at flood depths. The probability of directly to the magnitude of the how applying science to decision exceeding these thresholds needs hazard; it can contribute to risk making, building sustainable to be accurately forecasted with identification and reduction, but multisectoral partnerships, and sufficient lead times. Clearly accounts only for the magnitude of enabling effective coordination communicating the forecast’s the hazard itself, not the relevant and response can all contribute uncertainty is also essential. This exposure or vulnerability. A second to successful impact-based not only allows users to make modeling approach (solid arrows) forecasting. decisions in line with the reliability explicitly calculates each element 23 The Final Mile: Connecting an Impact-Based Warning Service to Decision Making Figure 1. Relationship between the different elements of an impact forecast system. Weather and climate extremes Exposure Geophysical Social and economic hazard impact Vulnerability Quantifying and reducing impact n Major uncertainty n Some progress, still a limiting factor n Considerable progress Secondary pathway Source: WMO 2015a. and so requires detailed data on The WMO works closely with voice for warning dissemination. vulnerability and exposure (possibly the Met Office UK, Deltares, Contingency planning before the available only from other agencies). A and other expert agencies to event will ensure that shelters third and more subjective approach support countries in establishing are available and are built in safe (dotted orange arrow) collects partnerships for impact-based places. Warning recipients need qualitative information from experts forecasting development and to learn how to interpret and use and estimates impact directly from in creating the relevant legal warning information to respond the magnitude of the hazard. frameworks, memorandums of effectively, and should also be understanding (MoUs), standard trained in how warning information Building Partnerships operating procedures (SOPs), and relates to the expected impacts on Multisectoral partnerships are communications strategies. See daily priorities such as health and needed to support an impact- the WMO (2012) guidelines for nutrition. based warning service. National more information. hydrometeorological agencies have expertise in weather and Promoting Effective Case Studies climate science, but they need Coordination and Response United Kingdom to partner with experts in risk SOPs outlining the different and disaster response, including roles and responsibilities of the Given the interdependency disaster management and other hydrometeorological agencies of natural hazards and the government agencies, scientific and other actors will encourage limitations of a segmented institutions, international a coordinated process and approach to hazard management, bodies, and local communities. ensure there is one authoritative countries have begun to seek 24 Proceedings from the 2016 UR Forum Connecting for Decision Making a unified approach to providing Figure 2. An impact matrix through which impact-based warnings and developing forecasting and can be developed. warning services. In the United Flood Risk Matrix Kingdom, the establishment of the River, tidal coastal, surface water, and groundwater flooding Flood Forecasting Centre, a joint High Likelihood Met Office–Environment Agency Medium ✔ initiative, is an important first step Low in providing joint scientific advice Very low for flood-related, impact-based Minimal Minor Significant Severe services and risk-based warnings Potential impacts to government and emergency Source: Met Office UK. responders. The center has built a cross-trained cohort of The Philippines color codes and a number scale to hydrometeorologists to facilitate describe the storm’s severity. The Philippine Atmospheric better emergency planning and Geophysical and Astronomical resourcing decisions. One of its PAGASA, with partners, has services, the Flood Guidance Services Administration (PAGASA) conducted workshops with Statement, presents an overview produces and disseminates official government agencies and the of flood risk for England and Wales, coastal warnings in the Philippines. public so as to better understand for all types of flooding, across As shown in figure 3, it works their service requirements and five days, and it assesses the with other related organizations the impact of severe weather on level of risk based on a likelihood to issue information. PAGASA specific regions. For example, in and impacts matrix (see figure faces many technical challenges— its work with the Metropolitan 2). The matrix definitions align not only in generating timely Manila Development Authority, to the severe weather warnings hazard-specific, area-focused, and which manages Manila’s transport issued by the Met Office, which impact-based warnings, but also in network, PAGASA has gained ensures a common picture and communicating uncertainties and information on the tipping points for understanding of the developing prompting effective responses. severe transport disruption based weather-flood risk. For example, it accurately on the volume of rain for a specific forecasted the extremely high time period. With this information, Another UK joint project that storm surge (7 m) during Typhoon PAGASA can now tailor bulletins reflects the importance of Haiyan, but the forecast area to specific agency requirements partnerships for impact-based was generalized, and the wave in comprehensible language—an forecasting is the Natural Hazards heights, inundation areas, and approach that prompts faster Partnership, which is led by the impacts were not included in the forecast. Moreover, although and more effective preparation Met Office and supported by the the lead times were sufficient and response following a severe Cabinet Office Civil Contingency for people to evacuate, many weather forecast. PAGASA is now Secretariat and other agencies. misunderstood the meaning of a extending these tailored services to The Natural Hazards Partnership’s storm surge and waited too long the other key sectors and continues collaborative environment enables before evacuating; among those to work to streamline its messaging the development of innovative who did evacuate, many died (focusing on color-coded warnings products and services that because evacuation centers were that are clearly understood by users). will provide governments and communities across the United built in unsafe areas. Finally, the Kingdom with better coordinated messages sent to decision makers Mozambique and more coherent assessments, and the public were potentially Weather forecasters in research, and advice. confusing, as they included both Mozambique face technical and 25 The Final Mile: Connecting an Impact-Based Warning Service to Decision Making institutional challenges. In order Figure 3. Warning and forecast information dissemination flow to move toward impact-based in the Philippines. forecasting, they need high- Office of the resolution models and equipment, President the ability to incorporate hydrological and inundation DRRMCs General public forecasting, and partnerships at NDRRMC/OCD the national, regional, and global PAGASA Local government units levels. The WMO is promoting PAGASA the necessary partnership by regional PAGASA supporting Mozambique’s efforts centers local stations to establish an MOU among the national meteorological agency, Local media National media the hydrological services, and the disaster risk management agency, National n Regional n Local n PAGASA ➞ NDRRMC ➞ OP ➞ and by taking the next steps to Source: PAGASA. operationalize the partnership. Note: NDRRMC = National Disaster Risk Reduction and Management Council; OCD = Office of Civil Defence; DRRMCs = Disaster Risk Reduction and Management Councils; OP = Office of Other forecasting challenges in the President. Mozambique are being addressed with the support of the Red and Mozambique’s disaster mechanism could be triggered to Cross. Efforts are being made risk management agency to allow disaster risk managers and to use multiple dissemination strengthen the early warning– communities to act effectively channels (e.g., social media, print, early action agenda. Moreover, to before a potential disaster. TV, and radio) to reach those improve the capacity to prepare living in the most remote areas. for tropical cyclones and floods in Jakarta, Indonesia Under a forecast-based financing a timely way, a detailed analysis of Jakarta’s Disaster Information framework, the Mozambique forecast, exposure, vulnerability, Management System hosts a Red Cross, German Red Cross, and early actions has been number of innovative systems, and and Red Cross Red Crescent conducted; the specific goal is to disseminates warnings via SMS, Climate Centre are working with determine the critical point at social media, websites and online hydrometeorological agencies which a forecast-based financing maps, and sirens. But generating Mozambique: Water level gauge (left); and WMO workshop on impact-based forecasting (right). Source: German Red Cross/Mozambique Red Cross; Forecast-Based Financing Mozambique. 26 Proceedings from the 2016 UR Forum Connecting for Decision Making useful scientific information Figure 4. Peta Jakarta interface. remains a challenge for Jakarta. Updating of sectoral and thematic data is slow and complex, and accurate real-time information on the duration and intensity of events is insufficient. However, the use of satellite, weather radar, and sensor data offers opportunities for timely validation. Crowdsourcing, which currently supports the Peta Jakarta open source flood map (figure 4), could be further exploited to collect other useful information; this approach would require engaging with citizens in a lengthy learning process, but could also offer new opportunities such as collaborative mapping of response actions. Challenges Impact-based forecasting that Source: Peta Jakarta, https://petajakarta.org/banjir/en/. supports decision making faces several key challenges: between government agencies build trust in the forecasts requires legal documentation, and improves a community’s l Communication. Nationally and or if partnering agencies are response to warnings. regionally, the lack of uniformity unevenly funded. An additional However, fostering such in forecasting (varying lead challenge is the lack of a global participation requires a long- times, levels of accuracy, mechanism that allows early term commitment on the part certainty, and geographic scales) warning providers and users of government agencies, both makes it difficult to identify to collate, share, and generate to supporting contributors the right level of detail for knowledge, and the lack of and to using the community’s communicating information. a forum for joint efforts to contributions. l Partnerships. Building the increase availability of and partnerships needed to access to multihazard early bridge the scientific and user warning systems by 2030 (a stated goal under Target G Conclusions and communities takes time and Recommendations resources; new partnerships of the Sendai Framework for will struggle to secure Disaster Risk Reduction). To support the development of support unless the public and l Community participation. impact-based warning services, government feel the effort Local communities can play countries should has value. Partners may a significant role in collecting also struggle to collaborate real-time data and verifying l Increase scientific knowledge of effectively if exchange of data results. This participation helps hazards and impacts 27 The Final Mile: Connecting an Impact-Based Warning Service to Decision Making l Invest in sustainable Ponziani, M., and D. Bachmann. 2016. “Real- Session Contributors Time Monitoring and Forecasting of Dike partnerships between Strength.” International Journal of Safety hydrometeorological, disaster Paul Davies, Met Office UK and Security Engineering 6, no. 2: 122–31. management, and other http://www.witpress.com/elibrary/sse- Alfredo Mahar Francisco A. volumes/6/2/1156. government agencies Lagmay, National Operational Assessment of Hazards (NOAH) Werner, Micha, Hessel Winsemius, Laurens l Develop SOPs for effective Bouwer, Joost Beckers, and Ferdinand project, Philippine Department of coordination and response Science and Technology Diermanse. 2016. “Toward an Open Platform for Improving the Understanding l Build societal awareness so that Flavio Monjane, Red Cross Red of Risk in Developing Countries.” In The warnings are understood Current State of Risk Information: Models Crescent Climate Centre & Platforms. Global Facility for Disaster l Engage communities in warning Iwan Gunawan, World Bank Reduction and Recovery. https://www.gfdrr. Group, on behalf of Bambang org/sites/default/files/solving-the-puzzle- design and data collection, and contributions.pdf. Surya Putra, Controlling and continuously build their capacity Informatics Division, Jakarta WMO (World Meteorological Organization). to respond to warnings Disaster Management Agency, 2012. “Guidelines for Creating a On a broader scale, a community Indonesia Memorandum of Understanding and a Standard Operating Procedure of practice on impact-based between a National Meteorological or forecasts and warning is needed Hydrometeorological Service and a Partner Agency.” WMO-No. 1099 PWS-26. Geneva, to bring together practitioners References and WMO. https://www.wmo.int/pages/prog/ and scientists globally to exchange Further Resources amp/pwsp/documents/1099_PWS_26_ knowledge and share lessons. MOUNMSPA_en.pdf. Coughlan de Perez, E., B. van den Hurk, B., M. K. van Aalst, B. Jongman, T. Klose, and P. ———. 2015a. “Guidelines on Multi-hazard Suarez. 2015. “Forecast-Based Financing: Impact-based Forecast and Warning An Approach for Catalyzing Humanitarian Services.” http://library.wmo.int/pmb_ged/ Action Based on Extreme Weather and wmo_1150_en.pdf. Climate Forecasts.” Natural Hazards and Earth System Sciences 15, no. 4: 895–904. ———. 2015b. “Stakeholder’s Workshop to Implement a Pilot Project on Impact-Based Met Office. 2016. “Enhancing Preparedness Forecasting and Risk-Based Warnings and Response in the Philippines.” http:// (Maputo, Mozambique, 19-23 October www.metoffice.gov.uk/media/pdf/c/t/ 2015).” http://www.wmo.int/pages/prog/ PAGASA_case_study_FINAL_for_web.pdf. amp/pwsp/Stakeholders_Workshop_ Maputo.htm. Participants engage in a discussion during the main conference. Photo credit: Emanuele Basso. 28 Adam Smith International | Adaptation Climate Change for Coastal Zone | Addis Ababa University | AG Europe | Agriculture Sector Proceedings from the 2016 UR|Forum Development Unit | AIC | AIESEC Nigeria | AIR Worldwide | Aix-Marseille University | Allianz | Altamira Information Altamira Information | Ambiental | Applied Hydro Solutions | Aqualogic Consulting | Arab Urban Development Institute | ARGANS Ltd. Armada Ltd. | Arup International Development | Asian Development Bank | Asian Disaster Preparedness Center | Athena Global AU-ECOSOC, African Union Nigeria Home Office Abuja | Australian National University | Autorité de contrôle des assurances et de la prévoyance sociale | BBC Media Action | Blue Nile National Institute for Communicable Diseases | Bogazici University | Boston University | BRGM | British Geological Survey | Bureau Haus Ltd. | Canadian Space Agency | Çankırı Afet ve Acil Durum Müdürlüğü CARD Consult (P) Ltd | CEFDHAC | Cellule de Prévention et Gestion des Urgences | Center for Management Technologies of Yerevan | Center for Rural Development and Planning | Center for the Promotion of Science and Technology | Central European University | Centre for Disaster Mitigation and Management, VIT University | Centre for Disaster Risk and Crisis Reduction Centre National de l’Information Géo-Spatiale (CNIGS) | Centro Euro-Mediterraneo sui Cambiamenti Climatici | Christian Aid | CIMA Research Foundation | Cities Alliance | Climate Change Network Nigeria | Climate Decision | Climate Policy Initiative | Climate Resilience Improvement Project-Ministry of Irrigation & Water Resources Management | Climate Wednesday | Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response (CCOUC) | Comité Interministériel d’Aménagement du Territoire | Coordination of Afghan Relief - CoAR | Council for Geoscience | Coventry University | Daily Impact Emergency Management | Dalit Empowerment Center (DEC) | Dalit NGO Federation (DNF) | Dalit Welfare Association (DWA) Danish Red Cross | Deltares | Department of Education, The Philippines | Department of Foreign Affairs and Trade, Australia Department of Irrigation, Sri Lanka | Department of National Planning, Sri Lanka | Department of Planning and National Development, St. Lucia | Department of Surveys, Malawi | Desh Seba Sangstha | Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH | Diakonie Katastrophenhilfe (DKH) | Direction de Protection Civile, Haiti | Disaster Management, Maldives | Disaster Management and Finance, India | Disaster Reduction Nepal (DRN) | Divergent Group | DMInnovation | Dreams From the Slum | DRR Dynamics | EAE School | Earth Observatory of Singapore | Economic Community of Central Africa States (ECCAS) | Economic Community of West Africa State, Commission, ECOWAS Commission Ecorys Research and Consulting | Environment Agency Austria | ERN Evaluación de Riesgos Naturales | ERRA | Ethiopian Development Research Institute (EDRI) | Ethiopian Ministry of Environment, Forest and Climate Change | Ethiopian Red Cross Society | Euro-Mediterranean Centre on Climate Change | European Academy of Bozen/Bolzan (EURAC) | European Commission, Joint Research Centre | European Space Agency | eWASH Initiative EY | Federal Capital Territory, Abuja | Federal Department of Foreign Affairs, Switzerland | Federation of Youth Clubs (FYC) Floodtags | FMGlobal | Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) | Fondazione Edmund Mach Fondazione Eni Enrico Mattei | Food and Agriculture Organization (FAO) | Food for the Hungry | Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS | Freie Universität Berlin, interdisciplinary security research | Hans Ertel Centre for Weather Research (DWD) | Fujitsu Labs of Europe Ltd Fundación Guatemala Gambia Red Cross Society | GCC Emergency Management Centre | GEADIRR | GEM Foundation | General Direction of Civil Security | Geo Enviro Omega | GeoAdaptive LLC | Georgian Association for Protection of Natural and Energy Resources | GeoVille Information Systems | German Aerospace Center (DLR) German Red Cross | Giving Garage | Global Alliance of Disaster Research Institute(GADRI) | Disaster Prevention Research Institute, Kyoto University | Global Facility for Disaster Reduction and Recovery (GFDRR), World Bank Group | Global Volcano 29 Model | GNS GAME Uncertainty When Is Certain: OVER? Exploring Tools for of the Complexity Improved Actionable Decision Making through Information Gaming for Weather and Climate 30 Proceedings from the 2016 UR Forum Connecting for Decision Making When Uncertainty Is Certain: Tools for Improved Decision Making for Weather and Climate Pete Epanchin, Global Climate Change Office, U.S. Agency for International Development (USAID) Background and general public or specific sectoral Concepts users), and finally disseminated and adopted by those users, who can As mathematics professor John then manage risk by taking action Allen Paulos once said, uncertainty based on the information provided. is the only certainty there is. But while it may be easiest to This truth seems to apply to an comprehend this information increasingly erratic climate system, flow as a linear chain, in reality especially so when we are caught it is a complex, webbed network off guard by a weather or climate that requires coordination anomaly. It would be dangerously and collaboration across many foolish to try to sell climate organizations and interests. services, or the development and At the 2016 Understanding Risk provision of weather and climate Forum, our panel and audience information for decision making, as reflected components of the a simple solution to this challenging needed organizational diversity problem of uncertainty. But when associated with the pathway of a developed well, climate services successful climate service, from can help provide a solution to creation, to delivery, to use.1 In building resilience to weather and climate variabilities. 1 At the start of this session, Julie Arrighi (American Red Cross; Red Cross Red Climate services are sometimes Crescent Climate Centre) led an activity in which audience members self-sorted viewed as a linear process that along two axes: where they most closely starts with observation and identified in the climate services value chain, from climate information and data data collection, followed by data providers to communicators of action- curation, processing, and analysis. oriented information; and the frequency with which they engaged in work related Analyses must be interpreted and to climate services. The audience was tailored to end-users (whether the fairly evenly distributed across both axes. 31 When Uncertainty Is Certain: Tools for Improved Decision Making for Weather and Climate addition, the panel reflected the insight into farmers’ needs and where this model has been application of climate services can then point to opportunities implemented, action is being taken across a wide range of time scales, that a tailored climate service in the design and scaling of climate from early warning systems to could take advantage of for those services. 10-day and subseasonal outlooks, farmers. This type of analysis can to seasonal and multiseason also be used as a rapid assessment Responding to Forecasts forecasts, to predictions that span of an existing climate service’s The complexity of climate services multiple decades. effectiveness, specifically by and how climate data are best providing feedback that can be used was addressed by Andrew For a climate service to be used used to improve that climate Kruczkiewicz, who pointed out and valuable, such that it results service. that a good forecast may have no in an end-user’s positive behavioral value if end-users aren’t able to While providing climate services might seem like a great way to build a community’s resilience to climate change, we should beware of solutions in search of problems and not make assumptions about the problem. response, the provider of that Consulting with respond with appropriate actions. service needs to first understand Stakeholders This admission raises a question, the problem that the user faces. Pete Epanchin highlighted one that links data, time scales, While providing climate services several USAID activities in and action: what should come first, might seem like a great way to climate services, including the the forecast or the action? In build a community’s resilience to Climate Services for Resilient other words, is it better to start climate change, we should beware Development partnership. In with a forecast and hope it will of solutions in search of problems developing and providing climate trigger an appropriate response, and not make assumptions about services, this partnership first or to prepare an appropriate the problem. consults with local stakeholders response that anticipates a and end-users to understand forecast? While there may not the problem as it is perceived be a single right answer, this Case Studies by the users, and then identifies question has inspired the field of opportunities for cocreating forecast-based financing. Under Meeting Farmers’ Needs a demand-driven climate this approach, when a forecast Research by Amy Barthorpe and service solution. For example, hits a certain likelihood threshold Ben Lloyd Hughes points to a novel in Colombia, the partnership for an event, say flooding, then method of understanding the engaged in conversations with a set of predetermined actions needs of end-users. By exploring over 175 stakeholders (including must be taken immediately, in data posted via SMS text government agencies, academics, advance of the flood. In order for messaging on WeFarm, a farmer- farmer cooperatives, civil society this approach to work, the time to-farmer information sharing organizations, and the private needed to complete the action network, it is possible to take an sector) in order to understand must be accurately paired with incredibly rapid, virtual pulse check the landscape of existing climate the lead time for the forecasted of the farmers and their real- services and their use, to identify hazard. If the action is fortifying time, real-world issues, including priority needs, and to determine housing infrastructure against concerns about precipitation gaps in decision support that floods, and this action takes six patterns and water availability. could be filled by a climate service. months to complete, then it These posts give immediate In Colombia and other countries would be appropriate only when 32 Proceedings from the 2016 UR Forum Connecting for Decision Making the seasonal forecast indicates at to develop risk profiles and service; each entity provides an least a six-month window of no sectoral vulnerability analyses important contribution. No one flood risk. But actions can also be that are used to understand and single organization can deliver all of taken on shorter time scales: in manage risk. This approach was the elements needed to support a Peru, for example, a six-day flood used in planning for the present climate service’s successful results. forecast was sufficient to mobilize and future of San Jose, Costa As the field of climate information the procurement and distribution Rica. It included a multihazard services grows, there is much of hygiene kits in advance of the probability assessment model that we can learn from each other flood event. Having “no regrets” integrated with projected in order to create and promote plans of action in place can add scenarios of future climate sustainable information systems value to a forecast and can reduce change and urban growth, and a rooted in evidence-based best uncertainty in the process of participatory social vulnerability practices. By collaborating with translating a forecast into action. assessment. This approach informed relevant decision makers the network of climate service Improving Decision-Making about future risks and about ways stakeholders, we can cocreate Capacity to mainstream risk management solutions that build climate under responses that could be resilience. Enrico Ponte presented work covering the much longer time made now or in the future. scales useful for planning and for Session Contributors increasing preparedness, whether Conclusions Amy Barthorpe, WeFarm at the individual, community, or Ben Lloyd Hughes, Institute for national level. Decision-making Integrating weather and climate Environmental Analytics capacity can be improved by data into decision making helps Enrico Ponte, GeoAdaptive using an interdisciplinary, risk- us prepare for and minimize Andrew Kruczkiewicz, assessment approach—one that the impacts of natural hazards, International Research Institute synthesizes long-term climate including climate variability and for Climate and Society, Columbia projections and other data sets, change. There is a complex University both qualitative and quantitative, network underlying a climate A full house marks the beginning of UR2016 opening ceremony. Photo credit: Emanuele Basso. 33 GAME OVER? Exploring the Complexity of Actionable Information through Gaming 34 Proceedings from the 2016 UR Forum Connecting for Decision Making Communicating for Action: What’s Needed? Lisa Robinson, BBC Media Action Sophia Nikolaou, BBC Media Action Emma Visman, Independent consultant; Department of Geography, King’s College London Randolph Kent, Planning from the Future project; Policy Institute at King’s, King’s College London Mark Harvey, Resurgence Allan Vera, Christian Aid, Philippines Shared Approaches Lebidi project in Burkina Faso Box 1: The Zaman Lebidi Project to Developing Risk brings together climate scientists, Information meteorologists, social scientists, The Zaman Lebidi project in development and communications Burkina Faso is seeking to Effective communication underpins practitioners, and agro-pastoralists build the resilience of people risk and resilience. It influences how to co-produce decision-relevant to climate variability, extremes, experts develop and share data, climate information (see box and change by bringing together how professional users understand 1). Developing effective risk local populations, climate experts, the data and make decisions based communication has specific and media and development on it, and how ordinary people implications and requirements for practitioners to co-produce take actions to reduce risk in their each type of actor. relevant climate information. Part everyday lives.1 of the project focuses on linking The providers of risk information scientific data and traditional Developing risk information need (1) a clear mandate that ways of understanding and requires them to make relevant using weather signals, with requires new types of partnerships risk information available, (2) the aim of making weather between organizations that often the capacities to effectively and climate information more have only a limited understanding communicate risk, and (3) actionable, trustworthy, of one another’s approaches and the willingness to recognize legitimate, understandable, value systems. It can involve others’ risk knowledge systems. relevant, and timely. knowledge exchange among Rarely is risk communication national and international an integral part of scientific Sources: Rowling 2016; Christian Aid scientists, private sector actors, 2015. training, yet the consequences of humanitarian and development miscommunication are potentially organizations, community groups, great—not only for those at risk, and social networks (Visman but also for those communicating Among the users of risk 2014). For example, the Zaman risk. Following the 2009 information—including both those 1 earthquake in l’Aquila, Italy, for people who are directly affected E. Visman, R. Murphy, S. Evans, L. Pearson, and King’s College London Humanitarian example, six earthquake scientists as well as the local, national, and Futures Programme, “Dialogues for were convicted of manslaughter international agencies seeking to Disaster Anticipation and Resilience” (tumblr), http://dialoguesforresilience. for playing down the risks to the support them—there is a huge tumblr.com/.” public (Nosengo 2012). need to improve scientific literacy 35 Communicating for Action: What’s Needed? Figure 1. Different partners working to develop risk information have different flows through such dynamic priorities and few spaces for building collective understanding and sharing systems, it is often transformed knowledge. by those who can either validate and amplify it or (if it comes from certain actors and sources) Directly disqualify it. Scientists impacted decision takers When Information Shared understanding; regular Ecosystems Fail spaces for dialogue Functional information ecosystems and learning involve high production and circulation of risk information (Internews Center for Policy makers Innovation and Learning 2015). Poorly functioning information ecosystems lack efficient and inclusive information flows. Source: Adapted from Kniveton 2014. The importance of a well- functioning information so they can better understand those directly affected a seat at ecosystem can be seen by what information is available, the table where the risk research comparing government responses what degree of certainty it holds, agenda is determined. in Myanmar to two different and how it can be appropriately cyclones. Before Cyclone Nargis used. Risk information alone Given that actors such as in 2008, the government chose is not enough: it needs to be scientists, policy makers, and not to proactively circulate the accompanied by the resources and decision makers are shaped by information it had about the approaches to effectively use it. differing priorities, it is important oncoming cyclone, and as a result to ensure that efforts to communities were unprepared Enablers—such as the World strengthen resilience benefit for an extreme weather event Meteorological Organization’s the people most directly at risk. in which many thousands died. Global Framework for Climate Currently, there are few regular In 2015, however, during the Services,2 the United Nations spaces where these actors can worst flooding in a decade, the Office for Disaster Risk Reduction build joint understanding and government regularly broadcast (UNISDR), and the UNISDR where emerging learning can be information about the risks of disaster risk reduction (DRR) shared (figure 1). Cyclone Komen and explained platforms—need to support the how people could keep safe. This development of risk information frameworks that work across Stronger Information time there were fewer than sectors, time frames, levels of Ecosystems 200 fatalities, and although the intensity of the event was less decision making, and risk type. Viewing information landscapes as severe, the significantly lower They need to ensure that national ecosystems—as the international death toll was due in no small budgets support sustainable risk nongovernmental organization measure to the improved flow of communication services and allow Internews does—makes clear that information. risk information is generated and 2 See the video on how to communicate shared in a complex and dynamic risk effectively at https://vimeo. com/170965566. environment. When information 36 Proceedings from the 2016 UR Forum Connecting for Decision Making Mapping Information Figure 2. Eight critical dimensions of information ecosystems. Ecosystems Diagnosing information ecosystems 1 Information needs 2 Information landscape and making corrections to how they 3 function can improve information and reduce risk. Consider the experience of Jakarta, Indonesia, 8 Influencers Production and movement for example, in using a tool developed by Internews to map information ecosystems. The tool showed that there was no two- way flow of information between Indonesia’s provincial disaster management authorities and the communities in Jakarta most 7 Social trust 4 Dynamic of access prone to flooding; it also showed 6 5 that some of the most marginal Impact of Use of communities at risk did not consider information information intermediaries used by the city Source: Internews Center for Innovation and Learning 2015 (http://www.internews.org/); authorities entirely trustworthy or licensed under a Creative Commons License, https://creativecommons.org/licenses/by-nc- credible. Officials aimed to correct sa/4.0/. this by deploying crowdsourced flooding platforms that fed local in investing in flood mitigation is not necessarily to get vulnerable incident information into the schemes. In Chenai, India, for people to understand risk, but provincial disaster management example, it was only after the for different stakeholders to authority control room and by devastating 2015 floods that understand the underlying issues identifying alternative influencers the Chennai-based national behind people’s vulnerability. The who had the trust of the most newspaper The Hindu investigated discussion below describes how marginal communities. and reported on the possible improved communication in the role of the Chembarambakkam Philippines led to a better grasp of Building Risk Literacy in Reservoir in the flooding of the what makes certain communities Local Media city, and suggested that better especially vulnerable. The capacity of local media reservoir management might have outlets to create and distribute made the flooding less severe. Understanding Risk through information is a critical Greater investment in the risk Their Eyes determinant in how well literacy of journalists is one way to In 2009, when Christian Aid information ecosystems function. improve the accountability of city wanted to conduct a DRR Local media need to improve authorities to the communities consultation after a big flood, some they are protecting. their risk literacy in order to poor urban communities were help journalists understand largely resistant. Dialogue with how planning—both rural and Dialogue with People these communities revealed the urban—can create risk, how at Risk reason for their opposition: they infrastructure can be impacted feared there was a conspiracy to by extreme weather, and how In the Philippines, a highly demolish their houses and relocate legitimate political dynamics and disaster-prone country, disaster them to resettlement areas far dilemmas can come into play risk is a part of life. The challenge away. 37 Communicating for Action: What’s Needed? The urban poor were concerned for their livelihoods, which they would have to leave behind, and they foresaw having to return to the city or resorting to desperate activities such as illegal logging. People were also afraid of unknown risks. Many of the supposedly safer resettlement sites had undeveloped facilities and were prone to floods and landslides. The risk of fires—not only accidental fires but often deliberate fires designed to clear informal settlements—was also a concern. Urban poor leaders living along canals in Manila meet with community organizers to address their concerns about land and housing security. Dialogue also revealed that Source: Allan Vera. residents tend not to build durable houses because eviction were able to respond to various conversations and reaching people and demolition are so common. incidents quickly. Those who had at scale. To be effective, however, It showed further that for poor accepted relocation used their risk it must follow basic guidelines. urban residents living in danger knowledge and leadership skills to zones, where land rights are not negotiate for safe and acceptable l Know the target audience. protected, DRR becomes a threat, settlements. Media groups must understand not a life-saving strategy. who they are trying to These efforts to interact with the communicate with and how Building Trust and vulnerable, understand disaster to tailor their communication Supporting Action risk from their eyes, and build trust to different audiences. To build trust with these led to the use of more effective Demographic information can be vulnerable groups in the Philippines DRR strategies. The importance a useful starting point, though and to better understand the of looking at risks not from the it offers only a small part of context of their experience, disaster perspective but from the the picture. Understanding the community organizers lived among perspective of underlying issues “psychographics” (i.e., beliefs, them. They mentored leaders of poverty became a key lesson values, preferences) of target and helped to form grassroots of the Linking Preparedness, audiences will make it possible to organizations, thus creating Response and Resilience project.3 connect with them more deeply. knowledge hubs and community Understanding how different structures for information flow. audiences use media is also Leaders had dialogues with risk Effective Use of Media necessary for reaching target experts as legitimate and equal Mass media can complement groups effectively. Investing in stakeholders. Residents were community dialogue by prompting audience research is therefore supported in developing their own critical to deeply understanding community plans based on the 3 Start Network, “Linking Preparedness, target audiences and how to issues and risks that had been Response and Resilience in Emergency Contexts,” http://www.startnetwork. communicate with them. identified in consultation with the org/start-engage/linking-preparedness- experts. Some communities set up response-and-resilience-emergency- l Know what to change. Once emergency response teams that contexts. the audience is thoroughly 38 Proceedings from the 2016 UR Forum Connecting for Decision Making understood, it is easier to contributing to the perception Christian Aid. 2015. “Building Climate Resilience in Burkina Faso.” BRACED, consider what can feasibly be that risk reduction is either April 22. http://www.braced.org/ changed with mass media. Many too scary to think about or news/i/?id=b5d9bafc-8576-4b5c-abb5- media initiatives about DRR too boring to deal with. Media 8717c6235019. presume that people simply offers tremendous opportunity Harvey, Mark, and Lisa Robinson. 2016. need information. Yet changing to approach off-putting topics “Improving Risk Information Impacts via the Public Sphere and Critical ‘Soft’ one’s behavior often requires in fresh, novel ways. Investing Infrastructure Investments.” In Solving more than knowing what to in top-quality producers, the Puzzle: Innovating to Reduce Risk, do. It may require a shift in scriptwriters, and talent is edited by Global Facility for Disaster Reduction and Recovery, 108 –11. mind-set, or encouragement essential for ensuring that the Washington, DC: World Bank. and support to take action. output appeals to the audience. Internews Center for Innovation and For example, when BBC Media Learning. 2015. “Why Information Action conducted research Matters: A Foundation for Resilience.” in Bangladesh to understand Conclusion https://www.internews.org/sites/default/ files/resources/150513-Internews_ people’s perceptions of and WhyInformationMatters.pdf. reactions to climate change, Disaster risk specialists can improve the impact of their work Kniveton, Dominic. 2014. “Bridging Science it discovered that while some and Practice in Disaster Risk Management: of the biggest challenges by ensuring that information Towards Community Resilience.” were community-wide, people is developed through strong ASEAN Capacity Building Forum on Risk Assessment. Jakarta: ASEAN Secretariat. were not taking collective communication among different action to deal with them (Al actors, by understanding Nosengo, Nicola. 2012. “L’Aquila Verdict the ecosystems in which Row Grows: Global Backlash Greets Mamun, Stoll, and Whitehead). Sentencing of Italian Scientists Who In response, BBC Media information flows, and by using Assessed Earthquake Risk.” Nature, October Action launched a national media effectively to prompt 30. http://www.nature.com/news/l-aquila- verdict-row-grows-1.11683#auth-1. television program called Amrai conversations and reach people at Pari, which was designed to scale. Rowling, Megan. 2016. “What’s the Weather in Burkina Faso?” BRACED, motivate communities to work January 1. http://www.braced.org/ together to address common news/i/?id=34c3aea1-4933-4a24-9fb1- References and a93375659a3c. problems. After watching Further Resources the program, 81.8 percent of Visman, Emma. 2014. “Knowledge is viewers reported that their Al Mamun, Md Arif, Naomi Stoll, and Sonia Power: Unlocking the Potential for Whitehead. 2013. “Bangladesh: How the Science and Technology to Enhance understanding of resilience People of Bangladesh Live with Climate Community Resilience through Knowledge issues had improved, and 36.5 Change and What Communication Can Exchange.” Humanitarian Practice Network, percent reported that they had Do.” BBC Media Action/Climate Asia. January. http://odihpn.org/wp-content/ http://downloads.bbc.co.uk/mediaaction/ uploads/2014/01/NP_76_Annex_string.pdf. taken action to improve their pdf/climateasia/reports/ClimateAsia_ resilience (BBC Media Action BangladeshReport.pdf. Visman, Emma, and Dominic Kniveton. 2016. “Building Capacity to Use Risk Information 2015). BBC Media Action. 2015. “Reality TV for Routinely in Decision Making across Scales.” Resilience: Can Reality TV Help Communities In Solving the Puzzle: Innovating to l Be engaging. Media outputs to Better Cope with Climate Risks?” Reduce Risk, edited by Global Facility for for DRR must appeal to April. http://www.bbc.co.uk/mediaaction/ Disaster Reduction and Recovery, 97–101. their audience, yet too publications-and-resources/research/ Washington, DC: World Bank. summaries/asia/bangladesh/reality-tv-for- often productions fall flat, resilience. 39 Proceedings from the 2016 UR Forum Connecting for Decision Making MapSlam: Revealing the Common Misperceptions about El Niño and La Niña Andrew Kruczkiewicz, International Research Institute for Climate and Society, Columbia University; Red Cross Red Crescent Climate Centre Lisa Goddard, International Research Institute for Climate and Society, Columbia University Introduction Background Does society really understand “ENSO” refers to the El the risks and potential impacts Niño–Southern Oscillation, associated with El Niño and La the interaction between the Niña? Are decision makers and atmosphere and the equatorial risk managers leveraging the Pacific Ocean that results in a information that is available? Risks somewhat periodic variation associated with long-term climate between below-normal and above- change are increasingly managed normal sea surface temperatures. by risk managers, but is the same El Niño is the name for periods happening for risks associated with of above-average sea surface short- or medium-range modes temperatures in this region, and of climate variability? Traditional La Niña is the name for periods approaches are driving efforts of below-average temperatures. to answer these questions, but The sea surface temperature they are perhaps struggling to variations initiate a domino-effect capture the full geophysical and reaction through the atmosphere socioeconomic complexities they which, over time, travels around confront. New interactive methods the globe. This domino effect of addressing these questions are is what leads to shifts in drier in development, including one, the and wetter conditions in places MapSlam, that excites emotion, significantly distant from the sparks creativity, and depends on equatorial Pacific. The connections confrontation. of global shifts in weather and climate driven by El Niño and La Niña are called teleconnections. 41 MapSlam: Revealing the Common Misperceptions about El Niño and La Niña Just as forecasts are available and decision makers around the information is used correctly. for the potential development world, but stories still emerge that Traditional methods succeed in of El Niño and La Niña, seasonal demonstrate lingering confusion communicating a portion of the and shorter-term forecasts are about how to assess and interpret climate risk to a subset of users, available to explore the impact El Niño and La Niña information. with an even smaller subset of teleconnections. Through As a potential event, such as integrating risk information into interactive tools, bulletins, and the current possible La Niña, their decision-making processes maps, physical and social scientists approaches, risk managers have (and a smaller subset still doing have taken steps to communicate an opportunity to use uncertain, so correctly and efficiently). shifts in risk and to inform risk yet potentially extremely valuable, Acknowledging the need to managers both about impacts on pieces of climate information develop new ways to communicate weather and climate and about in their decision making. But climate risk, with an emphasis their level of confidence in the instead of leading to improved on affording a two-way conduit potential shifts. It would seem decision making, the available between user and developer obvious that these tools have led climate information can lead and fostering emotive critical to a deeper knowledge of risks to the perception of a wicked associated with El Niño and La discussion, the MapSlam was problem of climate information Niña, but there is growing evidence conceived. saturation—one that could drive Acknowledging the need to develop new ways to communicate climate risk, with an emphasis on affording a two-way conduit between user and developer and fostering emotive critical discussion, the MapSlam was conceived. that gaps remain in leveraging the risk managers to reject potentially MapSlam available information to assess and valuable climate information as too mitigate risk. complex and intrinsically uncertain The MapSlam is an interactive and rely instead on simpler, activity inspired by poetry slams, Climate researchers in the in which poets battle head to head potentially incorrect information. social and physical sciences have This failure to understand the in a structured event. In short struggled to address these value of the climate information (two- to five-minute) rounds, gaps in both academic and available could lead to a failure to each competitor presents his or applied contexts. With many include the data, or worse, to use her piece and has an opportunity papers penned on relevant data incorrectly. Either error could for rebuttal. The rebuttal portion topics—from calculating forecast potentially increase vulnerability to is usually not planned, as the skill, to assessing methods of climate risk. participants cannot be certain of communicating uncertainty, to classifying styles of representing the material that the opponent will present; this aspect of the spatiotemporal impacts globally— New Methods of competition demands acute there would perhaps seem Exploring Climate Risk to be a consensus on how to improvisational skills from each. manage El Niño and La Niña Linking users of climate Like a poetry slam, a MapSlam risk. With each passing event, information with developers of involves a moderator to ensure substantial progress is made climate information will likely that each side respects the with communities, organizations, increase chances that the agreed-upon rules of battle. The 42 Proceedings from the 2016 UR Forum Connecting for Decision Making winner of the MapSlam is the Lisa battles back, explaining that Paul started out steady, person who has the most useful the maps offer useful seasonal scrutinizing Philip’s map like a map in the context of representing forecast information, but just how synthetic aperture radar sensor and communicating El Niño and La useful depends on the time scale collecting a backscatter of data Niña risk. of the decisions and size of the in order to build his case. But area to which they are applied. instead of denouncing Philip’s Two iterations of MapSlam Referencing the Sahel situation, map, he starts out by praising were featured at the 2016 she states that on a regional scale, his own, particularly the easy- Understanding Risk Forum. First, decisions may be shifted: when to-understand categorical map user was pitted against map outcomes are averaged overall probability of parameters that developer in a four-round contest. they will likely fall along the lines inform users if they can expect Second, two map developers of the teleconnection, while at the normal, below normal, or above went head to head to debate the community level they may not be normal streamflow during El Niño usefulness of their respective even the same sign. events. Further, his maps capture products. predictive capabilities at fairly high Momentarily pushed back against resolution, which may be useful for MapSlam 1: Map Developer the ropes by Lisa’s assertion of subnational decision makers. versus Map User the map’s value, Julie regains poise Lisa Goddard of the International and explains part of the problem: Deflecting the initial charge from Research Institute for Climate action needs to be taken on a Paul, Philip comes back with strong and Society (IRI) explains the spatial scale, but the maps need jabs, touting his map’s ability to advantages of IRI’s El Niño to focus more on the temporal directly link to risk assessment maps. These maps feature elements of the signal, as well as decisions. Citing its ability to be teleconnections, or shifts in the magnitude. Does increased combined with information on the temperature and precipitation rainfall mean floods? Is there an probability of an upcoming El Niño over certain areas of the globe equal chance of floods over the and La Niña, he contends that his during certain months, to convey entire region? map can identify areas likely to how risk shifts during El Niño. see an increase in damages and Lisa goes on the offensive in MapSlam 2: Map Developer impacted population. noting how forecasts are more versus Map Developer skillful during El Niño and La Niña, Pietro steps in before tempers compared to a year with average The second MapSlam event features a battle of El Niño and La flare, citing a question from a conditions. “user” in the audience: if the end Niña global streamflow maps, with Paul Block from the University goal is to influence decision making, Julie Arrighi of the Red Cross of Wisconsin facing off against why is there so much more time fights back. She emphasizes the spent on developing the maps absence of data at the spatial Philip Ward of VU University compared to interacting with the resolution needed for community- Amsterdam. To moderate this users? This is a great point that based decision making, and sure-to-be-rambunctious event, will surely be brought up in the reiterates the need for higher- Pietro Ceccato of IRI steps into discussion after the slam. resolution data. She jabs with the ring to maintain order and concerns about the skill that went ask the tough questions. For this into making the maps, as many of event, the audience was asked Conclusions and Next her decisions impact livelihoods in to take the role of users, tasked Steps low-income areas. She challenges with voting for which map better her opponent: can these maps be informed decision makers of shifts Bringing climate information used to justify shifts in funding? in flood risk during El Niño. users and developers together 43 MapSlam: Revealing the Common Misperceptions about El Niño and La Niña in a fun, energetic, yet thought- would lead to shifts in resources, producing differentiated products provoking forum afforded a new such as allocating funds away to debate their methods and type of discussion on the topic. from projects that could be approaches, and would offer But a MapSlam alone might not less effective if implemented in observers exposure to available have been able to accomplish a very rainy period. Resources products. With increased forecast the goals of the session without could instead be shifted to target skill, a better understanding a rich follow-up discussion. actions that might thrive in rainy of user perceptions, and more The interactive peer learning conditions, such as particular frequent and unique modes of conversation that followed the agricultural or dam management interaction between users and MapSlam brought the fast-paced practices. developers, misconceptions about event down to a level where slams climate risk could be addressed on potentially deficient maps could In addition to illuminating the and risk management improved. be digested and scrutinized, and benefits of increased forecasting where a number of important skill, the interaction between Session Contributors points could emerge. users and developers could lead Jemilah Mahmood, International to a better understanding of Federation of Red Cross and Red Floods and drought may come thresholds. Many users would like Crescent Societies to mind when thinking about to take action based on forecast Pietro Ceccato, International El Niño and La Niña, but it is information, but action usually Research Institute for Climate important to note that increased requires funding—and funding and Society, Columbia University forecasting skill could drive demands accountability and an Erin Coughlan de Perez, Red increased socioeconomic growth if understanding of uncertainty. In Cross Red Crescent Climate uncertainty is properly managed. a developing country context, the Centre In a year without El Niño or La opportunity cost of reallocation Julie Arrighi, American Red Cross; Niña, seasonal forecasts have of funds could be high if the Red Cross Red Crescent Climate less confidence to indicate where risk is not properly understood Centre and in which months rainfall and accounted for. Increased Paul Block, Civil and will be above or below average. dialogue between users and Environmental Engineering, But shifts in rainfall may still be developers could lead to the joint University of Wisconsin–Madison substantial in these “normal” years development of thresholds within Philip Ward, Institute of and thus potentially important for maps and other communication Environmental Studies, VU risk managers to acknowledge. products that could directly inform University Amsterdam In years where El Niño or La users when to take action. Niña is present, the ability to predict the shifts in rainfall is With forecasts increasing in skill, typically much greater, and thus opportunities for interaction the certainty of realizing those between the user groups are shifts can drastically increase. increasing and could lead to a more With knowledge that increased optimal use of the available climate rainfall is highly probable over information. A common space for the next three months, risk developers using similar climate managers could take action that data sets would allow developers 44 Science | Google | Hellenic Ministry of Environment and Energy | Heriot-Watt University | HiView | Human Orientation Movement Proceedings from the for Environment | IBM | Ikorodu Metropolitan Hospital | ImageCat, Inc. | Institute for Environmental Analytics UR Forum of | Institute 2016 Biodiversity and Protected Areas | Institute of Geology, Earthquake Engineering and Seismology, Tajik Academy of Sciences Insurance Supervisory Authority, Ministry of Finance of Vietnam | Integrated Research on Disaster Risk (IRDR) | International Federation of Red Cross & Red Crescent Societies International Relief & Development (IRD) | International Research Institute for Climate and Society, Columbia University | International Water Management Institute (CGIAR) | ISS | Istituto del Consiglio Nazionale delle Ricerche, stituto sull’inquinamento Atmosferico (CNR - IIA) | Istituto di Ricerca sulle Acque (IRSA), Consiglio Nazionale delle Ricerche (CNR) | Istituto Nazionale di Geofisica e Vulcanologia | IUSS Pavia | Jakarta Province Disaster Management Agency Jamaica Social Investment Fund | Japan International Cooperation Agency (JICA) Bangladesh Office | JBA Group Limited Karlsruhe Institute of Technology, CEDIM | Kartoza Kathmandu Living Labs KIKMA P.L.C | Kinetic Analysis Corp | King’s College London | Kotebe University College Kroll Associates | Latin American Social Science Faculty, LA RED and GIZ | Lawrence Livermore National Laboratory | Local Disaster Management Agency, Indonesia | LUBW Landesanstalt für Umwelt, Messungen und Naturschutz Baden-Württemberg | Maastricht University | Mapbox | Masaryk University | Mercator Fellowship on International Affairs | Mercy Corps | Mining and Geology University | Ministerio de Economía y Finanzas, Peru | Ministery of Environment, Forest and Climate Change, Ethiopia | Ministry of Agriculture, Guyana | Ministry of Economic Planning, Sustainable Development, Industry, Internal Trade, Information and Labour, St. Vincent and the Grenadines | Ministry of Economy and Finance, Cambodia | Ministry of Economy and Finance, Panama | Ministry of Economy and International Cooperation, Sao Tome and Principe | Ministry of Economy, Gabon | Ministry of Emergency Situations, Kyrgyz Republic | Ministry of Environment, Climate Change, Disaster Management and Meteorology, Solomon Islands | Ministry of Environment, Sustainable Development, and Disaster and Beach Management, Mauritius | Ministry of Environmental and Sustainable Development, Cote d’Ivoire | Ministry of Finance, Armenia | Ministry of Finance, Ecuador | Ministry of Finance, Guyana | Ministry of Finance, Republic of Tajikistan | Ministry of Finance, Vietnam | Ministry of Finances and Budget, Comoros | Ministry of Irrigation and Water Resources Management, Sri Lanka | Ministry of Land Use and Housing, Seychelles | Ministry of Meteorology, Energy, Information, Disaster Management, Climate Change and Communications, Tonga | Ministry of Natural Resources and Environment, Samoa | Ministry of Physical Development, Housing and Urban Renewal, United Kingdom | Ministry of Public Works Transport and Communications, Haiti | Ministry of Public Works, Transport and Communications, Haiti | Ministry of Transport and Works, St. Vincent and the Grenadines | Ministy of Finance and Economic Cooperation, Ethiopia | Minsterio de Hacienda y Credito, Colombia | Monash College (UCL) Colombo | Mozambique Red Cross | MSB Muhammad Akram & Sons Trading & Investment | Munich Re | Nanyang Technological University NASA | NASA, Jet Propulsion Laboratory | Nasarawa State University | National Centre of Public Administration and Local Government, Greece | National Disaster Management Authority (BNPB), Indonesia | National Disaster Risk Reduction and Management Centre, Mauritius | National Earthquake Engineering Research Center, Algeria | National Emergency Management Office, Tonga | National Institute Disaster Management, Mozambique | National Institute of Disaster Management, Ministry of Home Affairs, India | National Institute of Geological Science, University of the Philippines | National Institute of Rural Development, India | National Intelligence Academy ”Mihai Viteazul”, Romania | National Solidarity Program, Afghanistan | National Youth Assembly, Pakistan | NatRisk-University of 45 Modeling Turin | Nepalese Army | Nephila Advisors | Nigerian Red Cross Society, Lagos State Branch, Youth Wing | Oasis Loss GAME OVER? Exploring the Complexity of Actionable Information through Gaming 46 Proceedings from the 2016 UR Forum Data Global School Safety: Reaching for Scale through Innovation [page 49] Bridging the Divide: Digital Humanitarians and the Nepal Earthquake [page 55] Breaking Barriers for the Common Good: Open Data and Shared Risk Analysis in Support of Multilateral Action [page 61] 47 GAME OVER? Exploring the Complexity of Actionable Information through Gaming In Nepal, the Safer Schools Program is working closely with the government and partners like ADB, JICA, UNICEF, and USAID 48 to help protect the lives of students and keep educational disruptions to a minimum. Photo credit: NayanTara Gurung Kakshapati. Proceedings from the 2016 UR Forum Data Global School Safety: Reaching for Scale through Innovation Fernando Ramirez Cortes, World Bank Group Vica Rosario Bogaerts, World Bank Group Carina Fonseca Ferreira, World Bank Group The Incomplete One reason is that the data and Bridge for Global tools required to move beyond Safety pilot projects are often unavailable. Most ministries of education do Education is not only a basic not have the georeferenced school human right, but also fundamental infrastructure inventory that is to development and growth. needed for analyzing the level of Recognizing this truth, countries schools’ exposure and vulnerability. around the world have been Thus countries have trouble increasing investment in determining what their needs are, education. Over the last decade, and trouble developing multiyear governments, multilateral and risk-informed school infrastructure bilateral development institutions, strategies. In addition, many and nongovernmental agencies countries lack the tools and have been engaged in efforts processes to collect vulnerability to make schools resilient to information after a disaster; natural hazards. Nevertheless, the large-scale assessments of most countries continue to affected school infrastructure demonstrate limited progress. generally focus only on damage. With a few exceptions, most Without this vulnerability efforts have not gone beyond the information, the opportunity to pilot stage. plan and implement long-term risk-informed school infrastructure If countries can make a few programs can be easily lost. hundred schools safe, why are they unable to adopt a long-term approach that would make 15,000 or 150,000 schools safe? 49 Global School Safety: Reaching for Scale through Innovation Making the Case to Ongoing Innovative Foursquare, and Facebook. Reach Scale Efforts to Reach Analyzing this information requires Scale in the Education revising billions of social media Scale on global safety can be Sector: Case Studies activities from across the world in reached both for baselines and for many languages. planning: Using Big Data to Establish a Global Baseline for School An unprecedented effort to l In countries where information is Safety use data mining to build a global unavailable, scale can be reached In seeking to improve school georeferenced school database for baselines by using global data safety, the starting point for any has been undertaken by Courage to inform school infrastructure country is the quantification of Services. This geospatial programs. Countries can the number of schools exposed to analytics company has used also scale up from pilots to disasters. An enormous amount of automated mining, web scraping, nationwide programs. information about school locations and automated geocoding to l Scale can be reached for identify the location of about 2.5 is scattered across platforms planning by preparing the basis million schools for more than 30 and social media networks, such for long-term risk reduction countries (see e.g. figure 1). as OpenStreetMap, Wikimapia, programs while planning postdisaster recovery and Figure 1. Schools identified in India through data mining. reconstruction efforts or short- term risk reduction efforts. Scaling up risk reduction projects requires increased access to financing as well as improvements related to planning and implementation. These improvements include use of a systematic approach to identifying and prioritizing schools for reconstruction and retrofitting, and optimization of engineering solutions. Scaling up risk reduction projects also requires that discussion of available new holistic approaches and technologies be integrated and open to governments, the development community, academia, and the private sector. How can innovation be used to accelerate and scale up the Education Facilities in India implementation of risk reduction l Private programs? The case studies l Public l Unknown described below provide some answers to this question. Source: Courage Services, 2016. 50 Proceedings from the 2016 UR Forum Data Figure 2. Components of the prioritized investment plan (PIP): Intervention plan, which defines the interventions by automatically running an intervention algorithm against the SIDA database; investment needed to implement the intervention plan; and prioritization criteria. SIDA App includes info on Optimization of the Damage SIDA DATABASE implementation Vulnerability Exposure Function Prioritization School access Criteria INTERVENTION CODE Identification of interventions PIP Investment over time INTERVENTION ALGORITHM Intervention Investment Plan Source: World Bank/GFDRR Global Program for Safer Schools. Reaching Scale While Department of Education and Thinking Differently about Ensuring Quality of other development partners and Prioritization of Schools at Postdisaster Structural NGOs involved in planning the Risk to Accelerate the Pace Integrity and Damage reconstruction and prioritizing the of Retrofitting: The Case of Assessments: The Case of implementation; they also provided Peru Nepal the vulnerability information Based on the first (2014) The 7.8 Mw earthquake that needed to plan long-term risk nationwide School Infrastructure struck Nepal on April 25, 2015, reduction programs in the Census conducted by Peru’s affected more than half of the education sector. An innovative Ministry of Education, there are country’s 75 districts. Under tool has been developed that over 40,000 public school facilities the Global Program for Safer automatically analyzes the SIDA with 300,000 school buildings in Schools, the World Bank and Global results and prepares a prioritized Peru. The World Bank and GFDRR Facility for Disaster Reduction investment plan (PIP) for use through the Global Program for and Recovery (GFDRR) have been in planning the reconstruction Safer Schools supported the providing technical advice and and retrofitting of school first probabilistic seismic risk support to the Department of infrastructure (figure 2). The tool assessment of Peru’s public school Education on the planning for makes it possible to quantify the infrastructure at the national level reconstruction and recovery of investment needed in the short (figure 3). the education sector. The Safer and medium terms to recover Schools program has trained 70 from the disaster, the investment This assessment, carried out Nepali engineers to conduct a needed in the long term to by Universidad de los Andes, detailed structural integrity and improve the resilience of school quantified the risk associated damage assessment (SIDA) of infrastructure, and the changes in with all structural typologies of 18,000 public school buildings—an the investment over time. This tool school infrastructure, identifying effort enabled by innovation in and the results of the SIDA have the most vulnerable cases data collection and analysis. been integrated into a web-based and quantifying the benefit of platform for long-term support to risk reduction interventions The results of the SIDA not only risk-informed decision making in over time throughout the served as essential inputs for the the education sector. country. These results served 51 Global School Safety: Reaching for Scale through Innovation Figure 3. Probabilistic risk assessment showing ratio of annual average loss to exposure value per school (percent) in Lima Metropolitan Area. Ratio of Annual Average Loss to Exposure Value per School (%) l 0.1–3.0% l 3.0–6.0% l 6.0–9.0% l 9.0–12.0% l 12.0–15.4% Source: World Bank/GFDRR Global Program for Safer Schools. as a fundamental input for the Bringing Retrofitting and Turkey has already successfully planning and prioritization of Reconstruction of School implemented a risk reduction national risk reduction programs Infrastructure Up to Scale: program for 600 schools in in the education sector by the The Case of Turkey Istanbul; schools are being reconstructed and retrofitted at a Ministry of Education and regional Turkey, one of the most rate of 200 per year. The Ministry governments. earthquake-prone countries in of Education is now preparing a the world, has a large student program that will scale this effort In order to enhance and community of 17.5 million and up to cover thousands of schools accelerate the implementation a vast stock of 85,000 schools. across the country, while also of these programs, an innovative Over 60 percent of students aiming to build 8,000 new safer solution based on incremental attend schools located in areas schools in the next decade. retrofitting is being implemented with the highest hazard levels in for the first time in Peru. In To scale up the reconstruction and the country. According to studies line with this approach, the retrofitting efforts, the Ministry conducted by the Ministry of of Education is using prioritization Safer Schools program has also Education, Turkey has at least criteria—based on multiple convened the best universities in 30,000 schools built before 1998 parameters, such as hazard level, Peru to devise, test, and validate (when advanced regulations for number of students, significance retrofitting solutions for one of earthquake resistance were first to emergency planning, and the most common and vulnerable enforced) and therefore likely to technical specifications of school typologies. be highly vulnerable. the buildings—to assess the 52 Proceedings from the 2016 UR Forum Data Table 1. Challenges and Recommendations for Reaching Scale on Global School Safety Challenge Recommendation Merge big data with government data, when government data are lacking or incomplete Lack of up-to-date school infrastructure inventories In postdisaster contexts, collect both the information required to plan the reconstruction and the information Building Dispersed information on school required to plan long-term risk reduction programs, whenever evidence infrastructure that is not fit for the the latter is lacking or is not updated on global purpose of risk analysis safety Integrate the information in a consistent and systematic Data gaps arising from uneven georeferenced database that can effectively support long- access to technology (urban vs. term risk-informed decision making in the education sector rural/remote areas) Implement a monitoring strategy to effectively update information regularly Modification/adaption of established Open the discussion to government, academia, development practices community, and private sector Using innovation Institutional and regulatory Open channels for dissemination of knowledge and capacity for scaling up reforms building between academia/research institutions/private action Lack of local capacity to implement sector and Ministry of Education and other government innovative approaches agencies Apply an evidence-based prioritization strategy to implement Large building stock requiring school infrastructure programs over time, with clearly Planning intervention identified intermediate goals and quantified costs/benefits of school Multiple implementing agents Develop dynamic tools and methods that allow optimization of infrastructure solutions and improvement of the plans over time programs Diverse local contexts requiring alternative approaches Open the discussion to national and local governments, development partners, and private sector vulnerability of schools and innovation is a key means to implementing agents have access design interventions to improve foster the implementation of to the tools it has given rise to— their safety. With the technical these reforms, innovation triggers the potential to make all school support of the World Bank, a new challenges in itself. Table 1 facilities safe from natural hazards georeferenced inventory of school summarizes challenges presented in one generation is great. infrastructure and probabilistic risk by efforts to scale up global school assessment are being prepared safety as well as recommendations Session Contributors to plan a long-term investment for meeting these challenges. A. Hakan Mutlu, Ministry of strategy for reducing risk National Education of Turkey nationwide. Conclusions Luis E. Yamin, Los Andes University Challenges and The synergy of technology Hayley Gryc, ARUP Recommendations and knowledge has spurred Courage Services unprecedented levels of innovation Reaching scale on global and progress in improving the school safety requires the safety of schools. If this synergy implementation of a strategic is effectively harnessed to plan approach that normally includes and implement reconstruction technical, institutional, financial, and risk reduction programs in and/or social reforms. While the education sector—and if local 53 GAME OVER? Exploring the Complexity of Actionable Information through Gaming Youth from Nepal Scouts from Kaski District learn to map in OpenStreeetMap. Photo credit: Kathmandu Living Labs. 54 Proceedings from the 2016 UR Forum Data Bridging the Divide: Digital Humanitarians and the Nepal Earthquake Nama Budhathoki, Kathmandu Living Labs Robert Soden, Global Facility for Disaster Reduction and Recovery Introduction the difficulty was the ongoing evolution of the postdisaster The earthquake that hit Nepal on situation. April 25, 2015, killed over 8,000 people and injured over 20,000. The experience of the digital This is the worst natural disaster response in Nepal raises important in Nepal’s history since the 1934 questions: earthquake. With its epicenter in Gorkha District, it destroyed l How do we collect such a over half a million houses and massive volume of rapidly left hundreds of thousands of changing georeferenced data? people homeless. It also triggered l Since the response and relief avalanches in mountainous areas work need to be carried out that buried hundreds of people rapidly, what are the fastest and caused landslides in hilly areas sources of information? that made already difficult-to- l How can we use data to ensure access rural villages even harder the most effective coordination to reach. and resource mobilization among response and relief agencies? The authorities planning and coordinating the postdisaster While these questions have been response and relief work needed a asked during other major disasters, full understanding of the situation, the 2015 Nepal earthquake specifically about damages, offers some insights toward their victims, and victims’ needs. answer. Data obtained through Because the earthquake affected citizen mapping, crowdsourcing, over 30 of Nepal’s 75 districts, and social media were heavily collecting these data—most of used in responding to the Nepal them georeferenced—became earthquake. The discussion one of the most challenging tasks below describes how the formal for authorities. Compounding response agencies and digital 55 Bridging the Divide: Digital Humanitarians and the Nepal Earthquake volunteer communities were parties were organized, and within the first 24 hours after brought together to make optimal several hundred local mappers the earthquake and partnered use of emerging sources of data, were trained in mapping. In late with the international mapping technology, and people. 2013, when the OpenDRI project community to map the districts ended, the project members affected by the earthquake. For decided to institute Kathmandu the Nepal response, over 9,000 Background and Living Labs (KLL). global mappers joined the local the Case mapping community to map or KLL has continued to expand and improve data in key areas as In summer of 2011, a group deepen OpenStreetMap work in coordinated by the KLL team. of open source and open data Nepal. It has worked with major HOT and KLL collaborated with enthusiasts met in Nepal to humanitarian organizations, business partners (including Digital discuss how to start and advance including the Nepal Red Cross, Globe, Airbus, and Mapbox) to OpenStreetMap (OSM). A series of National Society of Earthquake obtain and process postdisaster presentations, mapping workshops, Technology, and Rotary Clubs. imagery. There were numerous and university outreach activities While KLL’s wheelchair mapping mapping parties organized in followed. In late 2012, the Global was carried out in different parts cities around the world, including Facility for Disaster Reduction and of the country, its on-the-ground the one at the White House in KLL understood that maps serve as vital information infrastructure in response and relief work following a major disaster. Recovery started its Open Data work focused mostly in cities in Washington, DC. Those mapping for Resilience Initiative (OpenDRI) southern Nepal (e.g., Bharatpur, parties were mainly organized by in Kathmandu. OpenDRI helped Biratnagar, and Rajbiraj). OSM communities, universities, to stimulate Nepal’s then-nascent and the Missing Maps community OSM community. It made it Unfortunately, with the exception with support from the American possible to assemble and train of the Kathmandu Valley, the Red Cross, British Red Cross, and districts that were hard hit by the Medicine Sans Frontieres. a few full-time mappers and a 2015 earthquake had not been project lead who were already well mapped before the event. In addition to OpenStreetMap, passionate about OSM and open Although OSM data were missing KLL deployed a crowdsourced data. The team mapped and for these districts, KLL had the reporting site—Quakemap.org—to collected exposure data for all staff, experience, and expertise enable people to report victims’ schools and most health facilities needed to carry out the mapping. needs as well as the fast-changing in the Kathmandu Valley. The team KLL understood that maps serve local situation. A large digital also raised awareness among as vital information infrastructure humanitarian contingent worked Nepal’s larger youth community in response and relief work on all aspects of Quakemap and mobilized youth in mapping following a major disaster. It also information management, including other features such as road understood that the international sharing actionable social data. networks, financial institutions, mapping community was KLL worked to the utmost to and sources of food. The OpenDRI available to help. KLL therefore ensure that the loops between project continued for about a established communication with information creation and use year, and during this period, the the Humanitarian OpenStreetMap were closed—that is, that every Kathmandu Valley was mapped Team (HOT)—a part of the report coming to Quakemap.org quite well: dozens of mapping greater OSM community— was looked into and acted upon, 56 Proceedings from the 2016 UR Forum Data and that OSM data were used by and execute their operations, example, we had already worked response agencies. they did not always update with the Ushahidi platform the status of the reports. to map schools; we had an This failure to provide status existing network with local Challenges updates increased the chances youth through mapping parties; that multiple agencies would and we had supported HOT in This effort to provide needed seek to provide relief materials mapping previous disasters in mapping data postdisaster entailed to the same victims. other countries. a number of challenges: l Dealing with organizational l Identify local champions, create l Coordination. It was challenging and group positioning. Some local institutions, and develop to coordinate different types organizations and groups in-country capacity. All these of groups working at different positioned themselves to steps are crucial. Disasters are levels, such as international gain visibility and access to local events, and the actual volunteers, local volunteers resources. This behavior made first responders are the local and self-organizing groups, it difficult to predict the people who observe and government and other formal organizations’ trajectory in experience the situation, inform response agencies, and earthquake response space. and report to authorities, and technical groups. Different l Exhaustion of the digital team. help victims. Local groups have time zones, diverse knowledge This effort was KLL’s first the advantage of language, and processes, and different direct involvement in a digital culture, local networks, and cultural backgrounds made the response, and team members trust. The most valuable coordination task challenging. worked almost around the clock information comes from local for the first several days in the people and institutions. Creating l Ensuring effective use of midst of chaos, fear, and several local groups and institutions data. With different groups other practical difficulties. and supporting their capacity and institutions producing Saving the team from getting building should be considered data after the disaster, it was burnout yet mobilizing them in cornerstones of effective digital difficult for response agencies effective response work was a response. to identify good sources of challenge. l Value agility. Everything needs data. This situation strained agencies’ limited capacity and to be done swiftly after a experience to process, manage, disaster. Being able to provide Recommendations critical information quickly not and effectively use data in their operation. only reduces human casualties, Based on the experience in Nepal, suffering, and loss of property, l Data validation and curation. we recommend the following: it also helps to gain the trust of Most people were more l Invest beforehand. Don’t wait both the response community interested in creating data than for a disaster. The major reason and victims. Coordination of carrying out the more tedious why KLL could effectively digital information and data tasks of validating and curating coordinate with formal response needs is an ongoing global data. HOT and other digital agencies, international volunteer effort. From coordinated communities are developing technical communities, and data scrambles to online and trainings and processes to in-person training, there are self-organizing local groups overcome these obstacles. opportunities to meet some is that it had an established l Updating status (especially in network, technical experience, of the technical goals set out Quakemap). While agencies used and credibility developed by the Sendai Framework, the Quakemap reports to design through years of work. For Sustainable Development Goals, 57 Bridging the Divide: Digital Humanitarians and the Nepal Earthquake and various partnerships and together needed technology, Ongoing challenges for digital alliances as established at the data, and people along with their disaster response include World Humanitarian Summit. network. In the case of the 2015 coordinating participants and l Minimize bureaucracy. No single Nepal earthquake response, there organizations, differentiating individual or institution can were at least two vital assets between information and noise, respond to a disaster alone, but already in place: a vibrant civic tech motivating and managing the local garnering contributions from team with relevant experience and tech teams, and ensuring that the large numbers of people requires expertise, and open map data for data created through the efforts openness to new ideas. This major cities hit by the earthquake. of multiple digital volunteers are flexibility will help in harnessing The experience in Nepal actually used in operation on the people’s collective power. demonstrated the possibility of ground. The Nepal earthquake has bringing global digital communities helped to advance our collective like HOT, teams like Humanity understanding for a more effective Road, technical companies like disaster response in the future. Conclusions Mapbox, humanitarian groups Every disaster is different, and like Missing Maps, and broader Session Contributors hence it is difficult to plan in digital humanitarian communities Heather Leson, QCRI and detail ahead of time for effective together with teams like KLL Humanitarian OpenStreetMap response. Investment beforehand on the ground. The potential of Team in creating and sustaining a vibrant combining digital surge support Maning Sambale, Mapbox and local tech group can prove to be globally with focused efforts by Humanitarian OpenStreetMap the most useful approach. The local tech groups continues to be Team prior experience of such groups a large opportunity for effective Pradeep Sapkota, Nepal Army will enable them to quickly put disaster response. Vivien Deparday, part of GFDRR’s OpenDRI team, trains UR2016 attendees on OpenStreetMap to assist in the response to the Sri Lanka 58 floods that started on May 14. Photo credit: Emanuele Basso. Framework | Ocean Conservancy | ODA PMU of Can Tho City | OECD | Office of Disaster Preparedness and Emergency Management, Proceedings from the Jamaica | Office of the Prime Minister, Uganda | Ohaha Family Foundation | Onur Seemann Consulting Overseas Development 2016 UR Forum Institute | OYO Corporation Palisade | PAMCZC Project Implementation Unit | Peace Development Awareness Campaign | Perastra Management Group | Perkins+Will | Philippine Disaster Resilience Foundation | Piensa Labs S.A.S | Planning from the Future Politecnico di Milano Politecnico di Torino | Potentiel 3.0 | PREDICT Services | Prime Ministry Disaster and Emergency Management Authority, Turkey | Project Coordination Unit, Ministry of Finance, Grenada | Projonma Academy | Protezione Civile, Italia | Public Health England | Punjab Emergency Service (Rescue1122) | Purdue University | Qatar Computing Research Institute | Red Cross Denmark | Red Cross Red Crescent Climate Centre | RenaissanceRe | Resurgence | Revenue (Disaster Management) Dept., Govt. of Andhra Pradesh, India | Rice University | riocom | Risk Society | RMS (Risk Management Solutions) | RMSI Private Limited Rosenbauer International AG | Rural Uplift Centre | Rwanda Youth Alliance for Climate Actions | Secretariat of the Pacific Community | Sécurité Civile | Seychelles, Division of Risk and Disaster Management | Skoll Global Threats Fund | Society For Idea In Rural & Social Development | Sriwijaya University | St Mary’s College of Maryland | Stanford University | Start Network | State Ministry of Disaster Relief and Humanitarian Assistance, Afghanistan | Superintendencia de Banca, Seguros y AFP, Perú | Sustainable Futures Suza | Swayam Shikshan Prayog | Swiss Reinsurance Company Ltd. | Taha Enterprises | Techno Angle International Ltd Technology Managment Center of Yerevan City | Tekirdağ AFAD | The Geneva Association | The GovLab @New York University The Open University | The State Service for Regulation and Supervision of Financial Market under the Government, Kyrgyz Republic | Tulane University’s Disaster Resilience Leadership Academy | Uganda Bureau of Statistics | Uganda Red Cross Society UK Department for International Development | UK Met Office | UK Research Councils UME School-IUSS Pavia-INGV-JRC Ispra UN Development Programme (UNDP) | UN Economic and Social Commission for West Asia | UN Environment Programme | UN Institute for Training and Research (UNITAR)-UN Operational Satellite Applications Programme (UNOSAT) | UN Major Group for Children and Youth (UN MGCY) | UN Office for Project Services (UNOPS) | UN Office for the Coordination of Humanitarian Affairs (UNOCHA) | UN World Food Programme (WFP) | UNESCO-IHE Institute for Water Education | UNICEF | Unilever Indonesia | Unite de Coordination de Projet de la Direction de la Protection Civile, Haiti | United Nations | United Nations University (UNU) | United Nations University, Institute for Environment and Human Security (UNU-EHS) | United Technique d’Execution-Ministere de l’Economie et des Finances, Haiti | Università Ca’Foscari Venezia | Università di Napoli Federico II-Centro Studi PLINIVS-LUPT Universitat Politechnica de Catalunya | Universite de Lausanne | Université Libre de Bruxelles | University College London University IUAV of Venice | University of Amsterdam | University of Annaba-Algeria University of Auckland | University of Bristol | University of Canterbury | University of Padova | University of Pavia-EUCENTRE | University of Portsmouth, UK | University of South Carolina University of Strasbourg | University of Strathclyde | University of Tokyo | University of Wisconsin-Madison | Urban Job Creation and Food Security Agency, Ethiopia | US Agency for International Development (USAID) | Ushahidi | Venice International University Vietnam, Disaster Management Center | Vizonomy | VU Amsterdam, Institute for Environmental Studies | WeFarm | Women In Slum Economic Empowerment (WISEEP-GHANA) | World Bank Group | World Meteorological Organization | World Resources Institute | World Vision | Yale University, School of Forestry and Environmental Studies | Youth Entrepreneurship for Emerging 59 Africa | Zambia, Disaster Management and Mitigation Unit | Zurich Insurance GAME OVER? Exploring the Complexity of Actionable Information through Gaming 60 Proceedings from the 2016 UR Forum Data Breaking Barriers for the Common Good: Open Data and Shared Risk Analysis in Support of Multilateral Action Andrew Thow, United Nations Office for the Coordination of Humanitarian Affairs Robert Soden, Global Facility for Disaster Reduction and Recovery Vivien Deparday, Global Facility for Disaster Reduction and Recovery Introduction disaster risk, and involve a broader section of the population in the As advances in open data and challenge of building resilience. shared risk analysis take place, it is possible to envisage a future To be most effective, risk where they underpin collaborative information needs to be translated and coordinated action between into shared analysis that government, the private sector, governments and their partners civil society, and the international can use together to manage risks. community. Open and shared risk analysis can help overcome institutional barriers between governments, Background and development institutions, disaster Concepts risk reduction (DRR) practitioners, and humanitarian and other The quality of risk information multilateral actors. for crisis and disaster prevention, preparedness, and response is increasing. However, it is often Case Studies sector-specific and not widely available to decision makers and The following projects suggest other stakeholders. Open data the range of work currently being policies and practices can increase done to advance open data and the quality and availability of shared risk analysis. information for managing crisis and 61 Breaking Barriers for the Common Good: Open Data and Shared Risk Analysis in Support of Multilateral Action OpenDRI Compiled by the SPC Applied MASDAP GeoScience and Technology The Open Data for Resilience The Malawi Spatial Data Portal Division (SOPAC) under the Pacific Initiative (OpenDRI) is a project (MASDAP) was established in Catastrophe Risk Assessment of the Global Facility for Disaster 2012 to increase access to spatial and Financing Initiative (PCRAFI), Reduction and Recovery (GFDRR). data in Malawi and to improve PacRIS is a geographic information Launched in 2011, OpenDRI collaborative use of the data by system (GIS) platform designed to seeks to bring the philosophies the government of Malawi, the provide Pacific Island Countries, and practices of the global public, and other key stakeholders. development partners, and the open data movement to bear In order to set up, manage, and private sector with the data and on the challenges of reducing maintain the technical platform tools needed to develop DRR vulnerability to natural hazards and its data, a MASDAP working applications. and the impacts of climate group was created comprising change. OpenDRI has been active the key stakeholders involved in SOPAC encourages member in over 35 countries around countries, partners, and the private producing or using risk information. the world in efforts to improve sector to use the PacRIS platform Originally, the working group was the sharing, collection, and to develop DRR solutions—including created around the technical team communication of risk information. and implementation agencies Disaster risk data should be open by default; accessible, licensed, and documented; cocreated; locally owned; and communicated in ways that meet needs of diverse users. OpenDRI’s 2016 Policy Note integrated financial, technical, involved in the Shire River Basin and Principles (GFDRR 2016) and planning solutions—that Management Program, the project describes the approach taken by will reduce the vulnerability of MASDAP originally supported. the OpenDRI team to designing Pacific Island Countries to natural Over time, as the working group and implementing impactful and disasters and climate change. has undertaken more general sustainable projects with partner PCRAFI is supporting the first set management of the platform at organizations and communities. It of applications using the PacRIS the national level, it has expanded lists nine principles, five on how platform. These include the to include institutions such as the risk information should be created, development of a risk financing National Statistics Office, Surveys managed, and used, and four on and insurance pool for the Pacific, Department, Department of how projects should be designed disaster response planning Climate Change and Meteorological and institutional partners should applications for selected locations, Services, Agricultural Development interact. Examples from past and a postdisaster assessment tool. Division, Department of Disaster OpenDRI projects and suggestions Management, Water Resources, for relevant resources are also PCRAFI is a joint initiative of and Malawi’s Polytechnic College included. SOPAC/SPC, the World Bank, and and Chancellor College. the Asian Development Bank; it PacRIS receives financial support from Examples of activities undertaken The Secretariat of the Pacific the government of Japan and by the working group include Community (SPC) has partnered the GFDRR, and technical support (1) holding regular meetings with the Open Data for Resilience from AIR Worldwide, GNS Science, and sharing communications; (2) Initiative since 2011 to develop Geoscience Australia, Pacific holding awareness campaigns and manage the Pacific Risk Disaster Center, OpenGeo, and for different stakeholders; Information System (PacRIS). GFDRR Labs. 62 Proceedings from the 2016 UR Forum Data (3) conducting trainings and l Start Network’s partnership support decisions about where building capacity on the use with a forecasting group to to focus programs designed to of the MASDAP platform and adapt research on prediction reduce risk. other related tools; (4) providing techniques to humanitarian l Trend analysis. The results of feedback to improve the action. The FOREWARN group INFORM are available for at functionality of the MASDAP will be trained in forecasting least five years. This allows platform; (5) developing a policy techniques and will take part trend analysis on the level of framework for sharing geospatial in a forecasting tournament risk and its components. and other required data among aimed at shedding light on how The INFORM risk assessment stakeholders, and defining humanitarian agencies can methodology and development minimum metadata and data forecast more effectively and process can also be used to quality requirements; (6) ensuring thus improve risk management produce regional or national risk that baseline data required for and early response. models. These have the same postdisaster assessments are features and benefits as the global collated and are available in INFORM model, but are subnational (at the ready-to-use open format; and (7) INFORM is a global, open source level of the province, municipality, coordinating and developing the index that assesses countries’ or village) in resolution. Developing strategy for the collection and risk of humanitarian crises an INFORM subnational model use of the data gathered using and disasters. It provides a is a locally owned and managed community mapping techniques. In common evidence base to enable process that is supported by the southern region of Malawi, a governments and organizations the global INFORM initiative. subgroup of the national forum has to work together to reduce This approach ensures that each been created to focus specifically countries’ risk, build resilience, model has local buy-in, is used on issues of data access and and prepare for crises. Resource in local analysis and decision- availability in this area. allocation for preparedness, making processes, and is adapted resilience, and risk reduction is not according to local risks; but also Start Network Projects currently aligned with actual crisis ensures that it can draw on global Start Network is undertaking risk. INFORM can provide actors resources and expertise and is several projects demonstrating with risk information and analysis validated according to global collaborative analysis, with a that will allow them to better standards and best practice. focus on preparedness and early prioritize their interventions. warning: INFORM can be used for several Conclusions and l Start Fund’s experiment with purposes: Recommendations applying blockchain technology. This project aims at enabling l Prioritization. The results of l Open data can increase the radical transparency of decision INFORM can be used to rank availability of risk information. making and funding flows. countries by risk, or by any Government open data l The Forecast-based Warning dimension or component of risk. initiatives and other data- Analysis and Response Network, This information can support sharing platforms are or FOREWARN. This is the Start decisions on resource allocation. fundamental in providing access Network’s interagency risk l Risk profiling. The results of to this information. analysis group, which fulfills a INFORM for a single country l Disaster risk data should be technical advisory role to the are a risk profile that shows the open by default; accessible, Start Fund Crisis Anticipation level of individual components licensed, and documented; Window. of risk. This information can cocreated; locally owned; and 63 Breaking Barriers for the Common Good: Open Data and Shared Risk Analysis in Support of Multilateral Action communicated in ways that shared risk analysis helps them meet needs of diverse users. work better together. Session Contributors l Open data projects in the l An open and transparent Sachindra Singh, Geoscience Division of the Secretariat of the disaster risk space should methodology and use of Pacific Community be designed to engage user publicly available data make risk Gumbi Gumbi, Malawi communities, develop strong analysis more credible. When Department of Surveys institutional partnerships, organizations and governments Luke Caley, Start Network prioritize open source can see what data risk analysis is approaches, and set clear, long- based on and how it is produced, Andrew Thow, Information Services Branch of OCHA; term goals. they are more likely to use the INFORM l Resource allocation for data and adapt them for their preparedness, resilience, and own purposes. risk reduction is not currently l Risk analysis needs to be References aligned with crisis risk. All actors accessible to strategic GFDRR (Global Facility for Disaster should increase the use of risk decision makers. Although Reduction and Recovery). 2016. “Open Data information and analysis for organizations may need to carry for Resilience Initiative: Policy Note and Principles.” World Bank, Washington, DC. prioritizing their interventions. out their own more detailed l Risk analysis is most useful and technical risk analysis when it is developed jointly by to support programming, a the relevant actors. Shared simple and shared analysis analysis is critical for ensuring can support coordination and that the priorities, objectives, strategic decision making and and strategies of the different policy making—and need not be actors are complementary. expensive. Different actors have different expertise and focus, but a Attendees explore what is on offer at the UR2016 Expo. Photo credit: Federica Zambon. 64 Proceedings from the 2016 UR Forum Resource allocation for preparedness, resilience, and risk reduction is not currently aligned with crisis risk. All actors should increase the use of risk information and analysis for prioritizing their interventions. 65 Credit: Joshua Stevens and Jesse Allen, using data provided by the NASA/GSFC/JPL, MISR Team. Modeling Reading the Tea Leaves: When Risk Models Fail to Predict Disaster Impacts [page 69] Challenges in Developing Multihazard Risk Models from Local to Global Scale [page 75] Climate Extremes and Economic Derail: Impacts of Extreme Weather and Climate-Related Events on Regional and National Economies [page 81] 68 Proceedings from the 2016 UR Forum Modeling Reading the Tea Leaves: When Risk Models Fail to Predict Disaster Impacts Ron Eguchi, ImageCat, Inc. Alanna Simpson, Global Facility for Disaster Reduction and Recovery Kelvin Berryman, GNS Science, New Zealand John Bevington, ImageCat, Inc. David Lallemant, Nanyang Technological University Keiko Saito, Global Facility for Disaster Reduction and Recovery Fumio Yamazaki, Chiba University, Japan Risk models are built on the best too late to highlight the aphorism often require more sophisticated available data—but the best data that “all models are wrong but modeling—and that when not are often less than ideal. It is only some are useful.”1 If decision considered will underestimate the when a disaster occurs that we makers are not well versed in true impact of a disaster. can retrospectively assess how the purpose and scope of model accurately a risk model predicted results, they will not be able to use Third, technological advances the extent and magnitude them to prioritize critical response such as remote sensing and of disaster impacts. Models activities or to guide longer-term emerging approaches such as sometimes surprise us with their recovery operations such as crowdsourcing have not had the accuracy, but more often, they “building back better.” Thus, the expected transformative impact over- or underestimate the scale effective communication of loss on modeling. This is in large part of the disaster. Postdisaster modeling results is paramount to due to lack of experience and forensics offers an opportunity practical implementation. validation. Remote sensing has the for determining why a risk model potential to improve loss modeling has failed, but in our experience Second, the dimensions of through developing exposure this information is not being catastrophe loss modeling have data—i.e., generating inventory effectively utilized to improve risk evolved considerably since models of buildings and critical models. modeling was introduced in the infrastructure using moderate- early 1980s (Steinbrugge 1982). and high-resolution imagery. But The effort to understand model Where early estimates of loss advances in this area will depend efficacy raises several key issues. were essentially limited to reports on robust sensor deployments and of building damage caused by a detailed validation studies using First, model results are often single peril, assessments now imagery at all spatial resolutions not well understood by decision consider an array of secondary and inventory data sets collected makers. The failure of a perfect and higher-order effects that from field surveys. prediction of loss is often viewed 1 This saying is commonly credited to as a failure of the whole model. George Box. See for example Box and Fourth, the technological Once a disaster has occurred, it is Draper (1987, 424). advances that have accelerated 69 Reading the Tea Leaves: When Risk Models Fail to Predict Disaster Impacts improvement in many areas formats (a problem that is also The experience of the 2010 Haiti of loss estimation modeling critical in proprietary models). earthquake is instructive. Decision have not been equal across all makers reported feeling that constitutive models. To ensure The discussion below examines the data (loss results) were just the most robust estimates of risk each of these issues and suggests “parachuted in” and that they and loss, a balanced investment specific steps for improving our had no time to change existing in the development of the ability to accurately estimate the protocols to effectively include constitutive hazard, vulnerability, impacts of future disasters. them (World Bank, GFDRR, and and exposure models is needed. ImageCat 2013). Appropriate That is, the reliability of an overall and effective use of the data loss estimate is often modulated Effectively would require (1) creating an by the reliability of the least Communicating umbrella framework to unite understood component of the the Results of Loss multilateral agencies in a crisis model. With unlimited resources, Modeling and to allow materials to be exposure and vulnerability could combined and collectively used Although loss modeling for be accurately quantified, but by all; (2) establishing response natural disasters has been around substantial fundamental research protocols that specifically include for decades, its application is still required to better constrain satellite-derived loss estimates; during the actual response the physics of perils such as and (3) training first responders to an event is fairly new and earthquakes, volcanic eruptions, to use the loss estimate data poses a particular challenge for storm surge, etc. This is especially sets. A disaster or crisis is the communication of model results. true in developing countries, worst time to introduce new where long-term investment in With the rapid development of analytics and tools, as people fundamental science and research loss modeling and the emergence will inevitably rely on the tested is particularly limited. of large-scale sensor networks, and trusted approaches of their including ubiquitous monitoring standard operating procedures. Finally, loss modeling has been (satellites), researchers have To ensure that decision makers dominated by proprietary models pushed the notion of near real- use information from risk models often used for quantifying insured time loss estimation as a key and real-time analysis during a losses after major disasters. That tool in the disaster responder’s crisis, we need to build capacity situation seems to be changing, toolbox (Eguchi et al. 1997). Loss and trust in this information long however, and efforts are under estimates for recent disasters, before a disaster strikes. way to develop open source including earthquakes in Haiti models that provide transparent (2010), Tohoku, Japan (2011), and access to hazard, vulnerability, and Nepal (2015), have demonstrated Modeling Secondary exposure data for many developing that this type of information Effects regions that go beyond insured can aid in the physical planning losses to include social and full for the recovery process. For Differences in modeled versus economic impact. Developing decision makers to use the actual damage are in some cases these newer models entails some outputs appropriately, however, due to limitations and uncertainties expense because the framework they need to better understand in the data. In other cases, for accepting, sharing, updating, the development and reliability of however, they are due to more and disseminating information this information; in addition, they fundamental issues, such as the must be developed and must need to adapt response protocols failure to model secondary effects. be robust enough to work with so that this information becomes Experience from the 2010–2011 constitutive models that may be an integral part of the postevent Canterbury earthquake sequence disparate in resolution and data workflow process. and the 2011 Tohoku earthquake 70 Proceedings from the 2016 UR Forum Modeling indicates that loss models and actionable recommendations. Balancing Model underestimated damage and During the earthquake response Accuracies in Overall economic losses principally because in both Haiti and Christchurch, Loss Estimates secondary perils and consequential a large international community Currently, there is little guidance effects were not modeled. In of engineers and scientists was for determining the right level of Canterbury, damage associated mobilized to perform near real- detail or accuracy for the three with liquefaction and rockfall was time damage assessments through constitutive models in the loss not included in loss models; and crowdsourcing. This approach gave estimation process—that is, the the loss models associated with hundreds of individuals access to hazard model, which defines the subduction earthquakes in Tohoku thousands of satellite and aerial severity and frequency of the omitted a larger-than-expected images so they could identify hazard (e.g., flood heights and tsunami and the consequential collapsed or damaged structures. frequencies); the exposure model, nuclear accident at Fukushima. This These experiences taught two which quantifies the number or same discrepancy exists for major important lessons: given the many value of assets exposed to the flood or cyclone events, where volunteers who want to help in the hazard (e.g., number of residential models capture the impact from response to a large disaster, damage buildings); and the vulnerability fluvial events relatively well, but fail assessment protocols must be model, which relates the exposed to include the pluvial events (e.g., simple, clear, and easily implemented; assets’ susceptibility to damage or landslides or flash floods). To ensure that decision makers use information from risk models and real-time analysis during a crisis, we need to build capacity and trust in this information long before a disaster strikes. Enabling Disaster and those using crowdsourced loss to specific hazard intensities. results to make critical response Response through In practice, these constitutive decisions must fully understand Technology models are convolved to estimate their limitations. Two other lessons loss parameters (such as average There is no question that emerged through postevent annual loss or maximum probable technology can help provide analysis:2 (1) the assignment of loss) or scenario-based losses. In situational awareness during the damage grades of 4 or 5 (EMS-98 most cases, data sets reflecting response to a disaster, and decision damage scale) has high reliability mean values or algorithms that makers often indicate that any (greater than 70 percent), but “false assume average trends are used information is better than no negatives” are relatively common; to calculate resulting losses. information at all. But there is also and (2) to extrapolate the results of However, the level of uncertainty no question that uncoordinated, crowdsourced damage assessments in each model can vary widely; repetitive, and nonvalidated to lower damage grades, extensive and these uncertainties can information is confusing; it cannot field calibration is necessary using greatly affect the reliability or be helpful, for example, to receive the same damage states and “believability” of the final results. 400 maps per day at the height descriptions. These lessons point to Thus loss estimates with large of a crisis. Adoption and use of the importance of using postevent bands of uncertainty, where the information technologies in disaster forensics that helps to validate and drivers of those uncertainties are calibrate the models and procedures response requires a thorough largely unknown, are common. used to estimate disaster losses. postdisaster review of the success and failure of these technologies, 2 See Booth et al. (2011); Ghosh et al. Recently, there has been an including extraction of key lessons (2011); and Foulser-Piggott et al. (2016). attempt to quantitatively 71 Reading the Tea Leaves: When Risk Models Fail to Predict Disaster Impacts estimate the contribution that they still face many technical References constitutive model uncertainties challenges. For example, while Booth, Edmund, Keiko Saito, Robin Spence, have on an overall loss estimate access to individual models may Gopal Madabhushi, and Ronald T. Eguchi. (Taylor 2015). “Robust simulation” be straightforward, ensuring that 2011. “Validating Assessments of Seismic allows analysts to use simulation models are compatible is more Damage Made from Remote Sensing.” Earthquake Spectra 27, no. S1 (October): methods to (1) quantitatively difficult. Constitutive models are S157–S178. account for model uncertainties built on different data sets—some Box, George E. P., and Norman R. Draper. in complex convolutions of loss, for different regions of the world, 1987. Empirical Model-Building and (2) identify where individual model and some from different time Response Surfaces. John Wiley and Sons. uncertainties drive the reliability periods—so integrating these Eguchi, Ronald T., James D. Goltz, Hope of the overall results, and most models means checking model A. Seligson, Paul J. Flores, Neil C. Blais, importantly, (3) determine where input-output requirements and in Thomas H. Heaton, and Edward Bortugno. 1997. “Real-Time Loss Estimation as an model improvements can help some cases developing translational Emergency Response Decision Support drive down the overall uncertainty interfaces. Once these obstacles System: The Early Post-Earthquake of a loss result. This type of are overcome—likely in the next Damage Assessment Tool (EPEDAT).” Earthquake Spectra 13, no. 4 (November): approach can facilitate a more several years—we will be able to 815–32. balanced investment in model evaluate firsthand the benefits, Foulser-Piggott, Roxane, Robin Spence, development and enhancement. costs, and efficacies of open source Ronald T. Eguchi, and Andrew King. 2016. modeling approaches. “Using Remote Sensing for Building Damage Assessment: GEOCAN Study and Validation Ensuring Effective for 2011 Christchurch Earthquake.” Earthquake Spectra 32, no. 1 (February): Open Source Solutions Summary 611–31. In the last several years, Although risk or loss models Ghosh, Shubharoop, Charles K. Huyck, Marjorie Greene, Stuart P. Gill, John practitioners have promoted sometimes fail to predict the Bevington, Walter Svekla, Reginald open source solutions in response impacts of large disasters, DesRoches, and Ronald T. Eguchi. 2011. to the limited access offered by the progress made after each “Crowdsourcing for Rapid Damage Assessment: The Global Earth Observation proprietary and expensive loss event has been noteworthy. In Catastrophe Assessment Network (GEO- models. Most existing models are many cases, new and innovative CAN).” Earthquake Spectra 27, no. S1 (October): S179–S198. embedded in proprietary platforms technologies did indeed designed to address (re)insurance contribute to better response Steinbrugge, Karl V. 1982. Earthquakes, applications. Typical issues that and recovery results. The next Volcanoes, and Tsunamis: An Anatomy of Hazards. New York: Skandia America Group. arise in this environment are decade will see further advances “black box” modeling (i.e., lack of in model development and Taylor, Craig E. 2015. Robust Simulation for Mega-Risks: The Path from Single Solution transparency), proprietary data data collection. With a prudent to Competitive, Multi-Solution Methods for formats, inability to mix and match program of data archiving and Mega-Risk Management. Springer. the best models, difficulty in a meaningful commitment to World Bank, GFDRR (Global Facility comparing model outputs from model enhancement, our ability to for Disaster Reduction and Recovery), different modeling vendors, and accurately predict the effects of and ImageCat. 2013. “The 2010 Haiti Earthquake—Final Report: Post-Disaster inability to apply these models to disasters should rise exponentially. Building Damage Assessment Using noninsurance situations. Satellite and Aerial Imagery Interpretation, Field Verification and Modeling Techniques.” https://www.gfdrr.org/sites/gfdrr/files/ Several international initiatives publication/2010haitiearthquakepost- have been established that seek disasterbuildingdamageassessment.pdf. to make risk data and assessment tools openly available,3 although Model (GEM) Foundation (https://www. globalquakemodel.org/) and the Oasis Loss Modeling Platform (http://www. 3 Examples include the Global Earthquake oasislmf.org/). 72 Madagascar | Cote d’Ivoire | Spain | St. Lucia | Niger | Ecuador | Australia Spain | Colombia | Sweden | Switzerland | Haiti Proceedings from the Indonesia Mauritius Seychelles | Korea, Rep. | Uganda | United Arab Emirates | Solomon Islands Switzerland | Seychelles | Tonga 2016 UR Forum Guatemala Honduras | Burkina Faso Japan | Malaysia | Grenada | United Kingdom | Uzbekistan | Cameroon Tajikistan | Canada Niger Argentina Bangladesh | United Arab Emirates | Zambia | China | Sri Lanka | Tajikistan | Zambia | Solomon Islands Ethiopia Vietnam | Bangladesh Mozambique | Samoa | Germany | Syrian Arab Republic | South Africa | Guinea-Bissau | Uzbekistan Portugal United States | Indonesia | Sao Tome and Principe | Djibouti Gambia, The | Mauritius | Netherlands | Tunisia | Cambodia | Colombia Burundi | Switzerland | Romania | Denmark | Portugal | Iran, Islamic Rep. Pakistan | China | Rwanda | Mexico | Vietnam | Slovak Republic | Guyana Malawi | New Zealand | Guatemala | Kuwait | Mexico | Georgia | Vietnam | St. Vincent and the Grenadine Tanzania | Tajikistan | Philippines | Algeria | China | Romania | Tonga | Kyrgyz Republic | Nepal | India | Poland | Haiti | Lithuania Luxembourg | Canada | Oman | Burkina Faso | Peru | Guyana | Guinea-Bissau | United States | United Arab Emirates | Guyana Ethiopia | Australia | Austria | Georgia | Gabon | Uganda | Sudan | Armenia | United Kingdom | Afghanistan | Guatemala | Venezuela, RB | Norway | Malawi Gambia, The | Costa Rica | Cameroon | Seychelles | Bulgaria | Pakistan | South Africa | Belgium | Jamaica Comoros | Gambia, The | Nepal Bangladesh | Sri Lanka | Paraguay | Fiji | Sudan | Tunisia | Croatia | Korea, Rep. | Ireland | Portugal Syrian Arab Republic | Kuwait | Morocco | Ghana Hong Kong SAR, China | Slovak Republic | Turkey | Fiji | Maldives | Ireland Slovak Republic | Ethiopia | Nigeria | Jamaica | Lithuania | Gabon | Uganda Philippines | France | Uzbekistan | New Zealand | Hondura Belgium Tunisia | Poland | Nigeria | India | Cambodia | France | United Kingdom Luxembourg | Bhutan | Russian Federation | Bahrain Tanzania | Armenia Gabon | Afghanistan | Niger | Paraguay | Poland | Bahrain | Morocco France | Bolivia | Argentina | Madagascar Kyrgyz Republic | Sao Tome and Principe | St. Lucia | Saudi Arabia | Rwanda | Morocco | Ireland | Greece | Italy | Afghanistan Venezuela, RB | Algeria | Sao Tome and Principe Comoros | Venezuela, RB | Denmark | Malawi | Sweden | Mozambique | Austria Togo | United States | Malaysia | Haiti | Colombia | Ethiopia Ghana | Nepal | Oman | Sri Lanka | Romania | Lithuania | Iran, Islamic Rep. | Norway | Brazil | Zimbabwe | Japan | St. Vincent and the Grenadines Burkina Faso | Ghana | Paraguay | Italy | Maldives Sudan | Zimbabwe | Croatia | Indonesia | India | Russian Federation | Honduras | Guyana Russian Federation | Japan | Hong Kong SAR, China | Kenya | Mexico New Zealand | Cote d’Ivoire | Croatia | Bulgaria | Lebanon | Austria St. Vincent and the Grenadines Panama | Greece | Malaysia | Tonga | Kenya | Grenada | Togo | Brazil | Greece | Zambia | Togo | Burundi | Germany | Bhutan | Saudi Arabia | Comoros | Armenia | Ecuador | Panama Denmark | Djibouti | South Africa | Netherlands | Argentina | Spain Pakistan | Peru Netherlands | Madagascar | Nigeria | Canada | Belgium Kuwait | Fiji | Georgia | Panama | Kenya | Syrian Arab Republic | Cameroon Kyrgyz Republic | Iran, Islamic Rep. | Lebanon | Solomon Islands | Mauritius | Bolivia | Ghana | Korea, Rep. | Cambodia | Ecuador Djibouti Philippines | Samoa | Saudi Arabia | Cote d’Ivoire | Burundi | Rwanda Mozambique | Italy | Lebanon | Norway | Bolivia | Peru Australia | Grenada | Sweden | Maldives | Bhutan | Algeria | Bahrain | Costa Rica | Brazil | Samoa | Jamaica | Bulgaria | Zimbabwe Germany | Tanzania | Italy | Uzbekistan | Cameroon Tajikistan | Canada | Niger | Argentina | Bangladesh | United Arab Emirates Zambia | China | Sri Lanka | Tajikistan | Zambia | Solomon Islands Ethiopia | Vietnam | Bangladesh | Mozambique | Samoa | Germany Syrian Arab Republic | South Africa | Guinea-Bissau | Uzbekistan Portugal | United States | Indonesia | Sao Tome and Principe Djibouti Gambia, The | Mauritius | Netherlands | Tunisia | Cambodia | Colombia Burundi | Switzerland | Romania | Denmark | Portugal Iran, Islamic Rep. Pakistan | China | Rwanda | Mexico | Vietnam | Slovak Republic | Guyana Malawi | New Zealand | Guatemala 73 | Romania Kuwait | Mexico | Georgia | Vietnam | St. Vincent and the Grenadines | Tanzania | Tajikistan | Philippines | Algeria | China This illustration depicts synthetic aperature radar patterns of seismic deformations associated with a model earthquake 74 on the San Francisco section of the San Andreas Fault (depicted in yellow). Photo credit: NASA/JPL/UCDavis. Proceedings from the 2016 UR Forum Modeling Challenges in Developing Multihazard Risk Models from Local to Global Scale John Schneider, GEM Foundation Mauro Dolce, Italian National Civil Protection Department Roberto Rudari, CIMA Foundation Introduction risk information needed to inform A Stakeholder disaster risk reduction is limited, Perspective The Sendai Framework for Disaster and the level of interaction across Risk Reduction 2015–2030 global initiatives is not very well Civil protection decision makers (UNISDR 2015b) calls for the developed. intuitively adopt a multihazard development of risk information approach in everyday practice to support risk monitoring and All of the challenges in modeling and at all scales. In Italy in disaster risk reduction at global, single hazards are compounded particular, the civil protection regional, national, and local for multihazard risk analysis. system works side by side with levels. One particular need is for For instance, risk assessment scientists and other stakeholders open, transparent, and credible methodologies for different toward achieving a quantitative multihazard risk assessment and probabilistic multihazard risk hazards often produce risk methods, models, and tools. But analysis capability. metrics that are not comparable. developing tools and making them In addition, hazard interactions available to those who need them At its simplest, a multiple-risk (e.g., simultaneous occurrence of is challenging; difficulties include scenario includes two (or more) a flood and landslide) are generally limited availability of and access uncorrelated events occurring, neglected, resulting in strongly to data, insufficient capacity, and simply by chance, at the same underestimated risk in the most problems communicating risk place, at the same time, or exposed areas. information to decision makers separated by a lapse of time (OECD Global Science Forum 2012). limited enough to observe an The discussion below looks at some overlap of the effects. More Several global initiatives for of the demands for understanding complex scenarios must consider different hazards have begun to multihazard risk within the civil cases linked by a cause-effect address these issues by building protection community and at how relationship; examples like global networks of collaborators several global natural hazard/risk cascading effects and natural and by sharing information, tools, initiatives are helping to meet hazards triggering technological and methodologies to promote this demand. It also identifies disasters show how complex the development of standards key actions required to develop a and challenging implementing and improved capacity at national comprehensive global risk modeling a fully multirisk model can be. to local level. Thus far, however, capability to meet risk information But as modern society grows the availability of comprehensive needs at various scales. more complex, analysis of such 75 Challenges in Developing Multihazard Risk Models from Local to Global Scale cases is needed for the design building a risk model, analyzing different authorities and decision of prevention strategies and the risk, and interpreting and pathways in order to strengthen contingency planning. understanding the risk analysis preparedness and response and results. The OpenQuake tools and reduce disaster losses. methodologies have been utilized Global Modeling The GFP has increased situational worldwide by over 1,000 users Initiatives awareness for partners (through from more than 100 countries to The global initiatives described prepare a range of earthquake sharing of information and analysis) below seek to meet stakeholders’ hazard and risk models at various and has exploited innovation and need for data, models, and tools scales. GEM engages in capacity- scientific advances, but its latest for risk assessment, though building projects in developing challenge is to develop multi- primarily within the context of countries and is now developing a hazard early warning systems and single hazards. As multihazard global earthquake risk model. risk information. risk modeling develops, it will draw on the tools, methodologies, and The Global Flood Partnership The Global Volcano Model networks of these initiatives and The Global Flood Partnership The Global Volcano Model (GVM) is encourage greater collaboration (GFP) has brought together the a growing international network of between them. scientific community (De Groeve 50 (public and private) institutions As multihazard risk modeling develops, it will draw on the tools, methodologies, and networks of these initiatives and encourage greater collaboration between them. The Global Earthquake et al., 2015), service providers and organizations that collectively Model (satellite, weather, and hydrology), aim to identify and reduce The GEM (Global Earthquake national flood and emergency volcanic risks.3 GVM includes the Model) Foundation is a public- management authorities, World Organization of Volcano private partnership that seeks humanitarian organizations, Observatories, in recognition of to improve understanding of development agencies, and donors the key role played by volcano earthquake risk globally.1 It in a partnership to better predict observatories at various scales. includes about 40 partner and manage flood disaster impacts Many volcano observatories deal organizations as sponsors, project and flood risk.2 The GFP provides with multiple natural hazards partners, or advisors. operational, globally applicable (earthquakes, landslides, tsunamis, flood risk management tools and etc.), because volcanoes, and GEM’s OpenQuake computational services as a complement to frequently their environments, are modeling platform, officially national capabilities. Furthermore, multihazardous. launched in January 2015, freely the partnership promotes provides access to a dozen global sharing of relevant data and Embracing collaboration, data sets and a variety of hazard/ information, fosters in-country scientific excellence, open access risk models at local to regional capacity building, and seeks to approaches, and public good, GVM scales. It also provides tools for improve flood risk management produced a substantial collective models and products across contribution to the 2015 Global 1 For more information see the 2 3 GEM website at https://www. For more information see the GFP For more information see the GVM globalquakemodel.org/; see also Keller website at http://gfp.jrc.ec.europa.eu/; website at at http://globalvolcanomodel. and Schneider 2015. see also De Groeve et al. 2015. org/. 76 Proceedings from the 2016 UR Forum Modeling Assessment Report (UNISDR good practices, and transparent Challenges 2015a), which includes a global analysis processes; and that will comparison of volcanic threats. develop tsunami hazard and risk Despite the growing demand It also conducted the first global assessment products, tools, and for multihazard risk assessment assessment of ash fall hazard, and approaches for use at various capabilities worldwide, and is developing a series of relational scales. the many global initiatives and databases with consideration of networks that develop and ontologies, standards, access, and The International deliver natural hazard and risk management. Nonetheless, the Consortium on Landslides information, the global initiatives understanding of volcanic risks have to date focused mainly on is still limited, and volcanic risk The International Consortium on hazards and individual hazard assessments are in their infancy, Landslides (ICL) is an international domains. Moreover, while existing owing to challenges related to nonprofit organization that global initiatives recognize the the multitude of hazards, data promotes landslide research and importance of partnerships with availability, model representation, capacity building, particularly local experts, connecting hazard and resources. in developing countries, and and risk information from local coordinates international expertise to global scales remains a major The Global Tsunami Model in landslide risk assessment and challenge. A new understanding of the threat mitigation.5 The network has about posed by tsunamis, developed 70 members worldwide, mainly in In order to move to a multihazard since the devastating 2004 Indian Asia and Europe. approach for comprehensive risk Ocean and 2011 Tohoku events, assessment, the natural hazard has shown the need for revised The ICL has focused considerable communities need to address a procedures to assess tsunami attention on landslide monitoring few key priorities: hazard and risk. During the last 10 and disaster response, including years or so, probabilistic methods organizing about 30 international l Common principles and have been developed to assess missions to postdisaster locations collective action. Collaboration tsunami hazard and risk, and this worldwide. As part of this effort, by different networks and continues to be a rapidly developing the landslide community has initiatives should be founded branch of tsunami science. on openness, public good, and carried out short-term forecasting credibility. Collective action is that relies on both satellite- and The origins of the Global Tsunami required across hazard and risk land-based technologies. By Model (GTM) are in the multi- communities, across public and contrast, probabilistic modeling institutional work leading to a private interests, and from local for long-term landslide risk is global tsunami risk analysis for the to global scales. Multihazard not well-developed, perhaps 2015 Global Assessment Report risk assessments require both because landslides are most (UNISDR 2015a).4 As a result interdisciplinary perspectives often triggered by other hazards, and discipline-specific expertise. of this successful collaboration, especially severe rainfall/floods Networks need to be able a global group of institutions is and earthquakes. Thus advances in to bridge public and private now creating a formal network probabilistic modeling and long- interests and to balance that will have the most up-to- term forecasting depend heavily differing needs (for levels of date tsunami science; that will define, test, and apply standards, on the inclusion of landslide within detail, scale, and complexity and a multihazard modeling framework. for the types of applications and 4 For more information see the GTM decisions to be made). Flexibility 5 website at http://globaltsunamimodel. For more information see the ICL github.io/2015_06_IUGG/GAR_GTM_ website at http://icl.iplhq.org/category/ and compromise are required to IUGG_presentation_updated_distr.pdf. home-icl/. achieve consensus and to move 77 Challenges in Developing Multihazard Risk Models from Local to Global Scale forward in a mutually beneficial and considering uncertainties l Addresses the likelihood and manner. remain a challenge). Moreover, consequences of independent, l Understanding and accounting the fundamental elements of concurrent, and triggered for hazard interactions. exposure and vulnerability that events A consistent multihazard form the basis for risk analysis l Takes a holistic and approach should address both are common to all natural hazard comprehensive approach to independent and concurrent models. In terms of vulnerability, assessing hazards and risks hazard events, as well as calculation of damage costs, l Incorporates tools and dependent (or triggered) events injury and mortality, and social methodologies that are scalable vulnerability and resilience While existing global initiatives recognize the importance of partnerships with local experts, connecting hazard and risk information from local to global scales remains a major challenge. that produce collateral damage. can all be integrated into a from global to regional, national, For example, interactions multihazard expression of risk. and local levels between storm surges and river l Making information useful at all l Provides the opportunity flooding, which are common in scales and for all stakeholders. to involve developers, river deltas, are neither well To avoid any disconnect practitioners, and stakeholders known nor well studied. between decision makers and in a common framework for l Harmonization of data and risk modeling and assessment assessing, communicating, and development of standards. To experts, the scale and breadth reducing risk to communities meet the demand for high- of multirisk assessments needs worldwide quality data and models that to be identified and defined jointly. It is important to be are openly available, emphasis able to offer data sets, models, at the global level should be on Session Contributors and tools for developing hazard developing standards, such as Stefano Lorito, National and risk models, analyzing for common input and output Institute for Geophysics and the risk, and interpreting and formats, for sharing of data Volcanology understanding the analysis and results, and ultimately for Peter Salamon, European results. quality assurance and credibility. Commission Joint Research Ensuring that databases are Centre, Ispra accessible and meet certain Melanie Duncan, British standards, for instance, will Conclusions Geological Survey Organization allow a variety of users to The demand for complex Filippo Catani, University of directly access information. Florence multihazard risk assessment l Harmonization of risk metrics capabilities that can address the and computational approaches. needs of diverse stakeholders There is much common ground is increasing. At the same time, in the numerical algorithms multiple global hazard/risk for scenario and probabilistic modeling initiatives have advanced hazard and risk analysis, which to a point where it is now possible are largely transferrable across to develop a consistent, global, hazard domains (although multihazard modeling capability methodologies for treating that does the following: 78 Proceedings from the 2016 UR Forum Modeling References and Further Resources De Groeve, T., J. Thielen-del Pozo, R. Model.” GRF Davos Planet@Risk 3, no. 2 UNISDR (United Nations Office for Brakenridge, R. Adler, L. Alfieri, D. Kull, F. (October). https://planet-risk.org/index.php/ Disaster Risk Reduction). 2015a. Making Lindsay, et al. 2015. “Joining Forces in a pr/article/viewFile/215/415. Development Sustainable: The Future Global Flood Partnership.” Bulletin of the of Disaster Risk Management. Global American Meteorological Society 96, no. 6: OECD (Organisation for Economic Co- Assessment Report on Disaster Risk ES97–ES100. doi: http://dx.doi.org/10.1175/ operation and Development) Global Science Reduction. Geneva: UNISDR. BAMS-D-14-00147.1. Forum. 2012. “Global Modelling of Natural Hazard Risks: Enhancing Existing Capabilities ———. 2015b. Sendai Framework for Keller, N., and J. Schneider. 2015. “Working to Address New Challenges.” http://www. Disaster Risk Reduction 2015–2030. Together to Assess Risk from Global to oecd.org/science/Final%20GRMI%20 Geneva: UNISDR. http://www.unisdr.org/ Local: Lessons from the Global Earthquake report.pdf. files/43291_sendaiframeworkfordrren.pdf. UR2016 attendees register at the start of the main conference on May 18. Photo credit: Miki Fernández. 79 GAME OVER? Exploring the Complexity of Actionable Information through Gaming 80 Proceedings from the 2016 UR Forum Modeling Climate Extremes and Economic Derail: Impacts of Extreme Weather and Climate-Related Events on Regional and National Economies Lorenzo Carrera, World Bank Group Jaroslav Mysiak, Fondazione Eni Enrico Mattei; Euro-Mediterranean Centre on Climate Change Elco Koks, Institute for Environmental Studies, VU University Amsterdam Accounting for The Sendai Framework for and Predicting the Disaster Risk Reduction (UNISDR Economic Impacts of 2015b) has made substantial Natural Hazards reduction of disaster losses a top priority of international efforts. Natural hazard risks, including To assess the progress toward weather- and climate-related this end, the global disaster risk extreme events, are able to undo reduction (DRR) community will sizable development and poverty have to fill the gaps in the loss reduction efforts, upset financial data records and substantially and economic stability and growth, improve the practice of damage and devastate communities and and loss assessment. Moreover, individual lives. The 2015 Global the DRR community will need to Assessment Report (UNISDR link up with the climate change 2015a) valued the global annual community in order to value the average losses from natural economic impacts of climate hazards as topping $300 billion, change and the costs of extreme more than any previous estimate. weather and climate events. There But even this value does not is ample scope for the two groups account for the whole magnitude to learn from one another—and to of tangible and intangible damage advance knowledge beneficial to and losses. both. 81 Climate Extremes and Economic Derail: Impacts of Extreme Weather and Climate-Related Events on Regional and National Economies The Sendai Framework represents to model the rare phenomena industry: one based in scientific a commitment to a transformative that lie outside the range of any and technical knowledge, and change in how natural and available observation, and cannot more affordable to buyers. In human-made risks are dealt be accounted for in extreme value turn, this change has allowed the with (van der Vegt et al. 2015; theory methods. development of new financial Wahlström 2015). Because instruments for disaster risk Catastrophe models—computer- management and climate change disaster accountancy was largely based representations that adaptation, including capital neglected in the past, it is not estimate the potential damage of market products and international an easy task, or sometimes even disasters (Grossi and Kunreuther risk pooling. Although in the possible, to portray the spatial 2005)—are able to perform past catastrophe models have and temporal patterns of disaster extreme value analysis. This is focused on a limited set of perils, damage and losses with reasonable usually done by overlaying the such as hurricanes, earthquakes, precision. For years, the United properties or assets at risk and extreme precipitation, more Nations Office for Disaster Risk (the exposure module, such as and more applications are being Reduction and the international classification based on a land cover developed for other perils, such as community have worked to fill data set) on the potential sources drought, terrorism, and pandemics, in the knowledge gaps and to of natural hazards (hazard module) and for areas of the world that promote a culture of evidence- in a specific geographical area. A have been neglected in the past. We should not waste the opportunity to collect information and knowledge on the full economic costs of disasters, including their ripple and spillover effects on the increasingly interconnected economies. and knowledge-based DRR. But vulnerability module estimates the Assessing Wider as we try to compensate for damage (e.g., of a hurricane) that Economic Impacts past negligence, we should not occurs based on a function of the waste the opportunity to collect hazard intensity (e.g., wind speed), On the other hand, the estimation information and knowledge on the the environmental conditions of wider economic impacts of full economic costs of disasters, (e.g., the region’s terrain), and the extreme weather and climate including their ripple and spillover exposed value characteristics (e.g., events has been less exploited effects on the increasingly the structural types). by disaster risk management interconnected economies. practitioners than damage Because of their outputs—the estimates. Typically, models such potential damage to the stock as input-output (IO), computable Understanding the of assets—catastrophe models general equilibrium (CGE), social Potential Impacts of are mainly used in the insurance accounting matrix (SAM), and Natural Hazards industry. Over the last three econometric models are able to There are multiple approaches decades (since the late 1980s), provide the impacts of extreme to estimating the distributions catastrophe models have been weather and climate events on of natural hazard economic risks. quite effective in contributing the economic flows—for example Statistical approaches look at to the shift from reactive on the production of economic the past records of loss data, and catastrophe reinsurance pricing sectors and the regional or estimate risk from historical loss to technically informed pricing. national gross domestic product data using extreme value theory. This shift has led to a more (GDP). Although these models have A fundamental challenge is how resilient catastrophe reinsurance advanced over time, their effective 82 Proceedings from the 2016 UR Forum Modeling applicability to real-world cases The assessment of the impacts of of economic and financial risk has been constrained by a number climate change on human welfare models to reproduce systems’ of factors, including their intrinsic are generally performed by using dynamics is still limited. High level of uncertainty (arising from integrated assessment models levels of uncertainty, particularly the number of assumptions) and (IAMs), such as GCAM (GCAM under changing conditions, still the difficulty in modeling the 2012). IAMs are mathematical characterize the outcomes of complex dynamics of a system in computer models that integrate the models. The recent critique the aftermath of a disaster. both social and economic of integrated assessment models components with biogeochemical (Pindyck 2013; Stern 2013)— Standard IO models are relatively cycles to assess the resultant echoed by the Intergovernmental simple, static, and linear models effect of greenhouse gas Panel on Climate Change Fifth imitating the interrelationships emissions. Economic losses are Assessment Report (IPCC 2014)— between economic branches within mainly determined by a damage voices a growing frustration a national or regional accounting function that relates temperature with contemporary models system. CGE models are nonlinear and precipitation variations to the reckoned too simple and arbitrary. models of circular flows of goods economic effects across different Contemporary economic risk and services between agents, hypothetical futures, also called analysis and assessment practices where representative households Shared Socioeconomic Pathways could face comparable critiques. It and firms choose their demand (O’Neill et al. 2015). Compared remains the case that disaster risk and supply following constrained to disaster risk models, IAMs assessments are rarely dynamic optimization problems, taking are generally used to assess the exercises and cannot represent prices as given. Prices are effects of slow-onset changes, the overall and interrelated determined by market equilibrium such as temperature increase, with systems’ reaction to and recovery conditions, allowing substitution few experiences on catastrophic from a disaster, the multifaceted effects and more realistic risk (Bosello, De Cian, and Ferranna conditions of fast-growing behavioral content and working of 2015; Pindyck and Wang 2013). economies, or changes in land use both factor and product markets and the environment. compared to IO models (Rose 2004). Econometric models, based Old Issues and New on time-series data, have the Challenges: Modeling Looking Forward advantages of being statistically under Changing rigorous and possessing Conditions Over the lasts decades, forecasting capabilities, but they catastrophe models have made can provide only estimates of the Many studies have already substantial improvements in their total impacts. Thus they are often highlighted the increase in value of capacity to assess the physical unsuitable for a detailed analysis of global annual average losses from damage of extreme weather and the specific losses of a disaster. natural hazards (see for example climate events. This success has Munich Re 2014). Evidence shows contributed to the development of Models of this type may also be that, in the future, the increasing a number of financial instruments used to inform policy making exposure and vulnerability of targeting disaster risk. Despite in some areas of disaster risk assets, economic activities, and this accomplishment, our management, such as flood risk population to natural hazards understanding of the full economic management (Koks and Thissen will continue contributing to cost of disasters is still limited. 2014) and water resources the increase of global losses. Economic risk models can help management under scarcity Moreover, climate change will to fill this gap, but if real-world conditions (Distefano and Kelly further exacerbate this trend. policies and investments are to 2016). Unfortunately, the capacity be based on them, they need 83 Climate Extremes and Economic Derail: Impacts of Extreme Weather and Climate-Related Events on Regional and National Economies to be more robust and reliable. General for European Civil References and Moreover, there is a need for Protection and Humanitarian Aid Further Resources tools that are affordable, credible, Operations (ECHO) to promote a standardized European disaster Bosello, F., E. De Cian, and L. Ferranna. transparent, and open access, as 2015. “Catastrophic Risk, Precautionary well as tailored to specific perils loss database are steps in the right Abatement, and Adaptation Transfers.” and scales of analysis (regional to direction. With better disaster FEEM Nota di Lavoro 108-2014. http:// www.feem.it/userfilesattach/2015115109 municipal). Recent experiences of loss data, more improvements will 64NDL2014-108.pdf. model coupling have demonstrated surely come in the near future. the capacity of economic risk Carrera, L., Gabriele Standardi, Elco E. Koks, Luc Feyen, Jaroslav Mysiak, Jeroen models to provide outputs at Bridging the gap between the Aerts, and Francesco Bosello. 2015. local scale. For example, Carrera disaster risk management and “Economic Impacts of Flood Risk in Italy climate change adaptation under Current and Future Climate.” CMCC et al. (2015) coupled spatial Working Paper. Euro-Mediterranean Centre analysis and regionally calibrated communities will be key to on Climate Change. http://www.cmcc.it/ CGE models to assess climate improving our ability to assess and wp-content/uploads/2016/06/rp0272- ecip-12-2015.pdf. change effects on flood risk at estimate the economic effects of regional level in Italy. For the same disasters and climate change—with Distefano, T., and S. Kelly. 2016. “Are We in a specific focus on the scope and Deep Water? Water Scarcity and Its Limits country, Pérez-Blanco et al. (2016) to Economic Growth.” Slide presentation. coupled a revealed preference scale of analysis and consideration https://understandrisk.org/wp-content/ model calibrated at local level and of the complexity of dynamic and uploads/DiStefano.pdf. a regional CGE model to inform interconnected systems. GCAM. 2012. The GCAM Model. Technical water resources management Report. College Park, MD: University of policies under drought conditions. Session Contributors Maryland. Other models (CGE) have also Laura Bonzanigo, Climate Change Grossi, P., and H. C. Kunreuther, eds. 2005. been developed at municipal scale, Group, World Bank Group Catastrophe Modeling: A New Approach to Managing Risk. New York: Springer. for example to assess flood risk Grant Cavanaugh, Nephila Capital in São Paulo, Brazil (Haddad and Ltd. Haddad, E. A., and E. Teixeira. 2015. Teixeira 2015). Recent efforts to “Economic Impacts of Natural Disasters Tiziano Distefano, Polytechnic of in Megacities: The Case of Floods in São add realistic behavioral features, Turin Paulo, Brazil.” Habitat International 45, pt. through evolutionary methods C. Dionisio Pérez-Blanco, 2: 106–13. such as agent-based modeling Fondazione Eni Enrico Mattei; IPCC (Integovernmental Panel on (Safarzyńska, Brouwer, and Euro-Mediterranean Centre on Climate Change). 2014. Working Group II Hofkes 2013), network analysis, Climate Change Contribution to the IPCC Fifth Assessment Report (AR5). Climate Change 2014: and supply chain principles (Rose David Simmons, Willis Re Impacts, Adaptation and Vulnerability. et al. 2016), hold promise for Analytics Edited by C. B. Field et al. Cambridge and improving models’ capacities to New York: Cambridge University Press. capture systems’ response in the Koks, E., and M. Thissen. 2014. “The We gratefully acknowledge funding Economic-wide Consequences of Natural aftermath of a disaster. received for the organization of this Hazards: An Application of a European session from the European Union’s Interregional Input-Output Model.” Paper Better evidence of economic presented at the 22nd Input-Output Seventh Framework Programme Association Conference, July 14–18, Lisbon. losses and ex post analysis of (FP7/2007-2013) under grant https://www.iioa.org/conferences/22nd/ disasters’ effects are needed papers.html. agreement no. 308438 (ENHANCE— to improve models’ robustness, Enhancing risk management Munich Re. 2014. Topics GEO: Natural through calibration and partnerships for catastrophic Catastrophes 2013. Analyses, verification. This need becomes Assessments, Positions. Munich Re. http:// natural hazards in Europe). www.munichre.com/site/corporate/ more and more pressing under get/documents_E1043212252/mr/ global change conditions. The assetpool.shared/Documents/5_Touch/_ ongoing efforts of the Directorate Publications/302-08121_en.pdf. 84 Proceedings from the 2016 UR Forum Modeling UR2016 participants spending time in the Expo area: Deepti Bhatnagar of RMSI (left), Stuart Fraser of GFDRR (middle), and Sushil Gupta of RMSI (right). Photo credit: Emanuele Basso. O’Neill, B. C. et al. 2015. “The Roads Ahead: Rose, A. 2004. “Economic Principles, UNISDR (United Nations Office for Narratives for Shared Socioeconomic Issues, and Research Priorities in Hazard Disaster Risk Reduction). 2015a. Making Pathways Describing World Futures in the Loss Estimation.” In Modeling Spatial and Development Sustainable: The Future 21st Century. Global Environmental Change. Economic Impacts of Disasters, edited by of Disaster Risk Management. Global doi.org/10.1016/j.gloenvcha.2015.01.004. Yasuhide Okuyama and Stephanie E. Chang, Assessment Report on Disaster Risk 13–36. Springer. Reduction. Geneva: UNISDR. Pérez-Blanco, C. D., G. Standardi, J. Mysiak, R. Parrado, and C. Gutiérrez- Rose, A., I. S. Wing, D. Wei, and A. Wein. ———. 2015b. Sendai Framework for Martín. 2016. “Incremental Water 2016. “Economic Impacts of a California Disaster Risk Reduction 2015–2030. Charging in Agriculture: A Case Study Tsunami.” Natural Hazards Review 17, Geneva: UNISDR. http://www.unisdr.org/ of the Regione Emilia Romagna in Italy.” no. 2. doi.org/10.1061/(ASCE)NH.1527- files/43291_sendaiframeworkfordrren.pdf. Environmental Modelling and Software 78: 6996.0000212. 202–15. doi:http://dx.doi.org/10.1016/j. Van der Vegt, G. S., P. Essens, M. envsoft.2015.12.016. Safarzyńska, K., R. Brouwer, and M. Hofkes. Wahlström, and G. George. 2015. 2013. “Evolutionary Modelling of the “Managing Risk and Resilience.” Academy of Pindyck, R. S. 2013. “Climate Change Macro-economic Impacts of Catastrophic Management Journal 58, no. 4: 971–80. Policy: What Do the Models Tell Us?” NBER Flood Events.” Ecological Economics 88: Working Paper 19244, National Bureau of 108–118. http://linkinghub.elsevier.com/ Wahlström, M. 2015. “New Sendai Economic Research, Cambridge, MA. retrieve/pii/S0921800913000360. Framework Strengthens Focus on Reducing Disaster Risk.” International Journal of Pindyck, R. S., and N. Wang. 2013. “The Stern, N. 2013. “The Structure of Disaster Risk Science, 6, no. 2: 200–201.  Economic and Policy Consequences of Economic Modeling of the Potential Catastrophes.” American Economic Journal: Impacts of Climate Change: Grafting Economic Policy 5, no. 4: 306–39. Gross Underestimation of Risk onto Already Narrow Science Models.” Journal of Economic Literature 51, no. 3: 838–59. http://pubs.aeaweb.org/doi/abs/10.1257/ jel.51.3.838. 85 GAME OVER? Exploring the Complexity of Actionable Information through Gaming ESA 86 is developing a new family of missions called Sentinels specifically for the operational needs of the Copernicus program. Photo credit: European Space Agency. Proceedings from the Climate Change Plenary 2016 UR Forum Climate Change Plenary Using Risk Information to Mitigate Climate Change Impacts—Challenges and Opportunities Introduction reinsurance industry, humanitarian To understand the accumulation donors and service providers, and of risks posed by climate change, Climate change is one of the space agencies—view efforts to reinsurance companies look biggest challenges of the 21st integrate risk information into every few years at evidence of century. It increases global decision making. As providers of secular changes in climate that vulnerability to natural disasters, key information, these groups all are increasing the level of hazard, and could push an additional 100 play a role in how organizations such as increases in the frequency million people into poverty by 2030 and communities around the world of disasters, and adjust their risk (Hallegatte et al. 2016). Taking will react to climate change risk. models accordingly. Firms convey action to mitigate the impacts of The discussion and case studies this risk information through the climate change can be challenging, below suggest both how they price of the insurance contract. partly because the specific impacts comprehend risk and how risk This price signal also reflects are uncertain, and partly because communication can propel action. changes in human responses forecasting what might happen in to climate change; for instance, a specific location in a specific year failure to maintain flood barriers Background is difficult. Furthermore, with rapid may cause an increase in price. urban development and economic The insurance and reinsurance growth, global hazards are industry is in a unique position Humanitarian organizations constantly in flux. This complexity relative to climate change provide life-saving postdisaster requires a paradigm shift, from because uncertainty and risk are aid, but also understand that static assessments of today’s risk fundamental to its core business. proactive, longer-term efforts to dynamic risk assessments that Reinsurance companies engaged to mitigate risk can save lives policy makers and business leaders early with scientific institutions to and money. The Red Cross Red can use to plan for the future. assess climate change impacts and Crescent Movement, for example, price risk appropriately; their models established its Climate Centre in To provide a spectrum of views have included climate change as The Hague to better understand on tackling climate change, we a factor of uncertainty for more climate change risks and in turn describe how three groups—the than 25 years. help vulnerable communities 87 GAMERisk Using Information OVER? the Exploring to Mitigate Complexity Climate Change Impacts—Challenges of Actionable and Information through Opportunities Gaming grapple with them. The movement The Copernicus program, a no indirect disaster loss, such as has also established forecast- partnership between the European business interruption (von Dahlen based financing initiatives and Space Agency and the European and von Goetz 2012). Disaster a Disaster Resilience Fund that Union, guarantees environmental risk insurance has also been found invests in preparedness, training, monitoring services over the next to act as a mitigant to potential logistics, supplies, and education to 30 years. During this period, data downgrades of sovereign ratings help communities understand and on atmospheric chemistry and (Standard & Poor’s Rating Services reduce climate change impacts. many of the parameters critical 2015). to understanding climate risk As part of its humanitarian mission Establishing trust with vulnerable will be free and publicly available. and more generally, the European populations—which is critical The program guarantees the Union (EU) has for many years to the success of insurance availability of the entire suite of anticipated the risks of climate products—requires partnership environmental and climate data change and used its considerable and collaboration. With this beyond 2030 by providing multiple resources to address them. All understanding, SwissRe has copies of each series of spacecraft, budgets reflect climate issues, developed and invested in a launched in sequence over the including those for humanitarian collaborative process methodology coming years. funds. This mainstreaming of Imagine a hypothetical scenario: you are a humanitarian in an elevator with the minister of finance from a developing country, with 30 seconds to convince her of the need to act to mitigate the effects of climate change. What do you say? climate change in the design called Economics of Climate Perspectives in of sector programs improves Adaptation, and has completed 10 Tackling the Impacts communities’ resilience. such projects with KfW in Asia and of Climate Change Latin America. Space agencies provide roughly Trust and Collaborative three-quarters of the information Reinsurance Models Build The Economics of Climate needed to understand the Resilience Adaptation is a collaboration earth system information of with local stakeholders in which Insurance penetration is low climate change. These data are communities assess their own provided through a critical suite among unstable and poor countries, risks and a cost-benefit analysis of 50 sensory and image-based even though there are insurance is conducted—both to identify parameters defined by the and reinsurance products to solve climate adaptation measures to Global Climate Observing System some of the biggest economic reduce risks and to determine as Essential Climate Variables. obstacles those countries face. This the benefits of averted losses. In addition to providing basic contradiction arises in part because Communities can then potentially information to assess the progress some individuals, communities, and transfer their risk to reinsurance of climate change, space agencies’ governments believe that insurance firms with the financial capacity priority is to look for indicators could exacerbate financial hardship, to absorb it. Finally, the complete of change, of future risk, and of despite evidence to the contrary. model is handed over to local adaptation, and then to collaborate In fact, countries with high stakeholders, allowing them to with other institutions to provide insurance penetration (60 percent calculate the risk, costs, and services to help local communities or more) suffer much less after benefits of future economic adapt to the known change of disasters than those with lower development, given the additional climate. penetration, and experience almost risk of climate change. 88 Proceedings from the Climate Change Plenary 2016 UR Forum Village-Level Responses to communities to devise detailed Politicians, businesses, and those Climate Change Matter resilience plans. However, says working in the humanitarian the minister, development aid and development sectors need Imagine a hypothetical scenario: as it relates to climate change information about the likelihood you are a humanitarian in an risk underestimates the risks to of disaster events to decide elevator with the minister of the underprivileged and is tied how to act. Consider the 2003 finance from a developing country, to infrastructure projects—the heat wave in France that caused with 30 seconds to convince her minister wishes she was able focus 30,000–70,000 excess deaths. As of the need to act to mitigate the on vulnerabilities in the villages. the climate system stood in 1900, effects of climate change. What do This scenario gets to the heart that heat wave was a 1-in-100- you say? of what is needed: government, year event. In 1990, it was a 1-in- international, local, development, 50-year event. By 2005, it was You start with the fact that and humanitarian actors working politicians’ political survival 1-in-5. Insurance risk is modeled in steadily together and focusing on depends on what goes on in the terms of likelihood of events, and if village-level needs. villages. You explain that detailed, climate projections used the same sustained, village-led responses method, the consequences of Ethiopia offers an example of a are needed. You say that when climate risk would be clearer. successful link between national land and livelihoods are lost and and local disaster risk reduction. villagers have nowhere to go, they Moreover, this approach aligns The government’s social safety will become a rural proletariat. with the increasingly complex net program uses satellite imagery The blunt truth is that without questions that space agencies and of different regions to observe appropriate action, there will be other organizations are addressing rainfall and investigate the risk not only crop failure, flooding, about the interaction between of a bad harvest, in dialogue with and an increase in disease-related physical systems and society, local tribe leaders. With El Niño deaths, but also other risks demography, and demographic kicking in, the effects of this beyond the finance minister’s planning are observable. Local-level shifts such as migration. For remit. Villagers who lack food risk awareness combined with example: To what extent is the or livelihoods might join violent supplementary foreign assistance crisis in Syria related to climate groups. You finish your pitch has saved lives. change? In 2006–2007, a major by mentioning how much more drought forced 2–3 million people unpleasant it would be to receive an elevator pitch from one of How to Use Space in Syria to move to cities. This these groups than from you. Agency Data: Show the mass migration placed cities under Consequences intense strain. Would Syria be In response, the finance minister Many models of climate change in its current position had the from the developing country says focus on basic predictions, such global community acted in 2006? she has already looked at the as the probability of a two-degree What would be the consequence harvest figures, observed the temperature change in the next for Europe if a similar climate global climate change systems, and 30 years. But risk communication event were to occur in the Sahel understands how her country’s is more effective when it focuses region? What might that lead to demography as it relates to on consequences and answers in terms of economic migration? climate change may create a pressing questions about how the The best models demonstrate the recipe for disaster. Along with the increasing likelihood of events will increasing likelihood of disaster and agriculture minister, the planning affect societies. Those models catastrophe events, and link them minister, and local humanitarian tell a more relevant, and more to the consequences those events agencies, she has worked with the dramatic, story. will have on our lives. 89 GAMERisk Using Information OVER? the Exploring to Mitigate Complexity Climate Change Impacts—Challenges of Actionable and Information through Opportunities Gaming Challenges and do not know which national > Focus on good governance. or international organizations to Efforts to mitigate climate A number of challenges confront contact for help. change impacts will be in vain institutions and communities without good and reasonably > Communicating risk can be wishing to mitigate climate change uncorrupt institutions. This is a difficult. Modelers still struggle impacts: vast agenda but crucial. to communicate risk effectively. Models showing a 0.3 degree > Create partnerships for > Most sectors have difficulty anticipatory assistance increase over 10 years, for deciding how to act. The and innovative modeling example, may produce nothing development and humanitarian approaches. Thoughtful more than a shrug of the sectors do not share a model partnerships should be formed shoulders, even when such for responsible action to to develop new products and a change can have serious balance saving lives with services to meet the needs of consequences. risk-informed development; vulnerable populations. Space politicians have constraints on agencies have data; insurance their attention and budgets; Recommendations companies have expertise and private companies can in cost-benefit analysis; and have difficulty finding the > Bring the humanitarian and humanitarian actors have right information to guide development communities community-level knowledge. investments to safeguard together. This step would > Push for insurance coverage against future potential risks. encourage humanitarian for the most vulnerable. > Insurance coverage is low organizations to focus on Reinsurance companies can help among the most vulnerable. prevention and preparedness reduce exposure. For instance, Households in poor countries and allow them to share their they can insure countries tend to rely on agriculture and substantial on-the-ground at risk, communities living in other income sources that knowledge of risks with floodplains, and agricultural are vulnerable to hazards, but development actors. This in companies in regions where these households are at the turn would promote more risk- drought risk is significant. same time far less likely to have informed development. > Communicate risk information insurance coverage. > Improve the regulatory effectively. Better > Stakeholders do not trust framework and collaborate communication can be achieved or communicate with one with business. The opportunity by methods that look at another. Communities, donors, exists to take advantage consequential events such humanitarians, development of businesses’ efficiency, as the likelihood of flooding agencies, private industry, and technological innovations, and or cyclones, using value- government could potentially customer demand for products added information such as work together. Despite the and services that promote demographic and social shifts. wealth of data, innovation, and resilience. Businesses should be This approach may entail the political will, however, many encouraged to see the first- difficult conversations that often feel that “others” must mover advantages in climate can sway politicians and other do more. change scenarios. Unilever’s power brokers to act on risk. > Communities do not know how carbon-neutral manufacturing, > Communicate in schools and to act. Communities can often for instance, makes the capitalize on the skills of anticipate the next disaster, company enormously resilient— youth. Getting young people but are hampered in preparing independent of changes in to understand the risks they because they lack needed tools energy policy and energy costs. face—not as victims but as 90 Proceedings from the Climate Change Plenary 2016 UR Forum problem solvers—is crucial. building is key; if communities The Red Cross Red Crescent do not trust the source of Session Contributors Movement and the European information, they will not John Roome, Climate Change Space Agency have programs believe the information. Group, World Bank Group focused on educating youth, > Resolve to act now and in the Esther Baur, Swiss Re Group but more can be done in this future. The world needs both Claus Haugaard Sørensen, area. to adapt to the consequences European Political Strategy Center > Address the details and listen of change and to prepare for to community needs. Viable the changes that will happen in Jemilah Mahmood, International development means bringing the future. This is not a trade- Federation of Red Cross and Red Crescent Societies development into villages and off. addressing village-level details. Stephen Briggs, European Space Agency This step requires placing trust in communities, which means Conclusions giving local civil society and To address the challenges posed References community leaders a chance to by climate change, international show what they do or do not Hallegatte, Stephane, Mook Bangalore, agreements matter but are Laura Bonzanigo, Marianne Fay, Tamaro understand about their own Kane, Ulf Narloch, Julie Rozenberg, David not enough. Stakeholders must risk. Treguer, and Adrien Vogt-Schilb. 2016. seek sometimes unexpected Shock Waves: Managing the Impacts of > Join the One Billion Coalition for partnerships; they must build trust Climate Change on Poverty. Washington, Resilience (1BC).1 This coalition at all levels, from the community DC: World Bank. seeks to bring one billion level to the international; and Standard & Poor’s Rating Services. 2015. people together both to look at they must bring people together “Storm Alert: Natural Disasters Can Damage Sovereign Creditworthiness.” threat-specific resilience and to to share understanding and September 10. http://unepfi.org/pdc/wp- build trust and understanding knowledge, to plan, and to act. content/uploads/StormAlert.pdf. among coalition members. Trust Von Dahlen, Sebastian, and Peter von Goetz. 2012. “Natural Catastrophes and 1 See the One Billion Coalition for Global Reinsurance: Exploring the Linkages.” Resilience website at ifrc-media.org/ BIS Quarterly Review (December): 23–35. interactive/one-billion-coalition. Jemilah Mahmood addresses the audience during the climate change plenary with (from left) John Roome, Esther Baur, Stephen Briggs, and Claus Haugaard Sørenson. Photo credit: Emanuele Basso. 91 GAME OVER?and Vulnerability resilience Exploring the Complexity of Actionable Information through Gaming Construction workers in Luxor, Egypt, build stronger river banks along the Nile River. Photo credit: Dominic Chavez/World Bank. 92 Proceedings from the 2016 UR Forum Vulnerability and Resilience Checking the Vitals: Making Infrastructure More Resilient [page 95] Putting People First: Practices, Challenges, and Innovations in Characterizing and Mapping Social Groups [page 101] How Risks and Shocks Impact Poverty—and Why, When, and Where Better Financial Protection Can Help [page 107] 93 GAME OVER? Exploring the Complexity of Actionable Information through Gaming 94 Proceedings from the 2016 UR Forum Vulnerability and Resilience Checking the Vitals: Making Infrastructure More Resilient Tom Roche, FM Global Introduction Background The scene after catastrophes Infrastructure systems around like a violent storm, powerful the world are under increasing earthquake, or devastating fire pressure—from growing is all too familiar. People offer populations, growing urbanization, and changing demands. These comfort and shelter to those pressures play out differently, in need and tend to the injured. however, in developing and This initial reaction is quickly developed countries. followed by efforts to bring critical infrastructure back on line, In the developing world, strong, starting with the vital elements of effective systems for power and power and water. Those involved water infrastructure are needed in such restoration efforts know to facilitate economic growth that the immediate effects of a and to sustain burgeoning and disaster can be intensified should concentrating populations. One they fail. challenge to providing these systems is often simply time, The long road to recovery after as populations grow and land a catastrophe depends on is developed rapidly. A second having critical infrastructure in challenge is finding the resources place to support the process of to prepare and deliver this infrastructure when budgets are rebuilding the community and already stretched. Compounding helping industry to recover. But both these challenges is the fact the best time to strengthen that these regions are particularly this infrastructure is before susceptible to natural disasters a catastrophe strikes. The due to their geographies. For goal should be to make the example, developing Asian and infrastructure resilient—resistant Pacific countries incur more than to collapse and engineered to $50 billion in disaster costs each recover quickly. year (ADB 2013). 95 Checking the Vitals: Making Infrastructure More Resilient In the developed world, where there are complex systems Box 1: How Resilience Depends on Hazard Information of ownership and funding for The 2007 flooding in the United Kingdom highlighted the vulnerability of infrastructure, aging systems the water and power networks. Inundation of a water treatment facility present their own challenges— left 350,000 people without potable water for 17 days, and a flooded specifically ongoing maintenance, substation left 42,000 people without power. The government review continued performance, and large that followed called for better flood information and more investment financial decisions around their by utility companies to protect key infrastructure sites (Pitt 2008). renewal. According to the American In response, a number of agencies have collaborated to improve the Society of Civil Engineers, there is a understanding of flood hazard and the exposure of critical infrastructure growing infrastructure investment in the United Kingdom. gap in the United States. Failure to close this gap will impact the Following the 2011 earthquake in Christchurch, New Zealand, other ability to update and expand U.S. cities sought to understand the impact of an earthquake on their own infrastructure, which in turn will infrastructure. In Wellington, groups representing local government and cause a $4 trillion loss in gross utility providers collaborated to define the likely events that might occur domestic product by 2025 (ASCE and determine the infrastructure recovery times (Wellington Lifelines 2016). Group 2012). They concluded it would take 20 to 65 days before power and water utilities would be recovered across the city’s suburbs. This In response to these pressures we work has helped to promote action to improve the resilience of the city’s are seeing unprecedented interest infrastructure. and investment in infrastructure globally. Estimates place the need for global investment up to 2030 some areas of the world, this will can be identified and analyzed. at $57 trillion (McKinsey Global mean mapping hazards for the This information can help to set Institute 2013). The challenge for first time. But even in areas that operational parameters and inform governments, their agencies, and have been mapped, it is important emergency planning in the future. businesses is to ensure that these that potential hazards are well investments build the concept of understood. To meet the challenge of a resilience into their projects. hazard-resilient infrastructure, Ensuring that infrastructure governments need the right is resilient to hazards means hazard information (geological, The Vitals taking account of the whole meteorological, etc.) and sufficient interconnected system or network. technical expertise to properly When looking to build resilience The behavior and performance identify and assess vulnerabilities into projects for power and of the network when subject to (see box 1). Often this requirement water, several elements are vitally a particular hazard needs to be necessitates partnering with a important: hazard assessment, modeled; the same is true for the spectrum of professionals who codes and standards, operations behavior and performance of the have expertise in a full range and maintenance, and emergency network’s individual components. of hazards and understand response plans. What will be the wider impact if their consequences for the this particular pipe bridge collapses infrastructure. Increasingly, Hazard Assessment in a flood, this power plant drops open source models and global Hazard assessment provides offline in a storm, or this reservoir collaborations (public-private- crucial information for siting of is breached by an earthquake? In academic partnerships) are infrastructure and for identifying this way key nodes as well as critical changing the landscape of hazard and assessing vulnerabilities. In and alternative supply routes assessment. Once the hazard is 96 Proceedings from the 2016 UR Forum Vulnerability and Resilience assessed, the performance criteria in Chile and Haiti in 2010. In Operation and Maintenance and specifications can be adapted response to damaging earthquakes Operation and maintenance of to suit the defined hazard. in the 1960s, Chile had developed infrastructure is as important as and implemented a complete its physical attributes. From its Codes and Standards scheme of seismic building codes first minutes of operation any The use of strong codes and and standards. Haiti had limited system will start to degrade; this standards is key to delivering building codes and no seismic is perfectly normal. Appropriate a resilient infrastructure. standards for buildings. The death maintenance and carefully managed Codes and standards are tolls highlight this difference: more operation are both needed to developed and delivered by a than 200,000 were people killed ensure that the desired level of variety of institutions, including in Haiti and fewer than 1,000 in performance continues to be industry, trade associations, delivered. Improper operation Chile. Although both events were and government agencies. or operational changes can make catastrophes, the use of strong Their purpose is to help ensure systems more vulnerable, as well seismic codes and standards in minimum criteria are met for the as slower to respond and recover Chile helped to lessen the impact. design, construction, operation, after disruption. Systematic and ongoing maintenance of training and management of change Enforcement plays a key role in any the infrastructure elements. is essential to avoid these issues. When infrastructure developers code’s effectiveness. Deviations The potential effects of improper know how codes and standards from code—whether using an operation and maintenance are are developed, and know their alternative or falling short of the highlighted in box 2. intended outcomes, they gain a standard—can lead to delivering deeper understanding of how to a system or structure that has Operators and regulators must design and build resilient facilities. increased vulnerabilities. Analysis have the expertise, capacity, and of the 1999 earthquakes suffered integrity to ensure that codes, Based on hazard information, in Izmit, Turkey (USGS 2000), standards, and best practices codes specify the materials, and Jiji, Taiwan (the so-called 921 are followed. There is always a capacities, redundancies, and safety earthquake) (SSC 2000) highlights balance to be struck between factors for the desired resilient the importance of enforcement. appropriate maintenance, infrastructure. For critical buildings Both areas had building codes in operational efficiency, and costs, and equipment, there is often a place that acknowledged the local but the desired resilience needs need for the design to include an seismic hazard, but there were gaps to be given importance in this increased safety factor, or even in enforcement for new buildings. equation to ensure that it is not go beyond the code should it fail In both areas, the buildings and compromised. to offer the appropriate level of infrastructure not built to code resilience. performed badly. Locales seeking to Emergency Response Plans The importance of strong codes enforce codes over the life of the Strong designs and equipment, and standards can be seen when infrastructure need individuals with suitable locations, and appropriate we compare the performance of the right skills and expertise as well operation and maintenance can infrastructure and buildings in two as institutions with the required all help to minimize the impact different events—the earthquakes capacity and integrity. on infrastructure. The true test For critical buildings and equipment, there is often a need for the design to include an increased safety factor, or even go beyond the code should it fail to offer the appropriate level of resilience. 97 Checking the Vitals: Making Infrastructure More Resilient l To improve the system’s ability Box 2: Why Operation and Maintenance Matters to treat raw water coming from The largest electricity blackout in the Tome and Arakawa Rivers, North America occurred in August a second raw water connection 2003, when a combination of between the main water events and a 345 kV power line treatment facilities of Asaka to tripping due to tree contact led to a Higashimurayama is planned—via cascade failure. The blackout, which an earthquake-resistant 2,000 impacted over 50 million people, was mm pipe. investigated by a joint task force l The performance of key from Canada and the United States elements of the water supply (U.S.-Canada Power System Outage network—reservoirs, pumping Task Force 2004). According to stations, etc.—was evaluated the task force report, operational issues with vegetation clearance and against the expected seismic alarm systems and an inadequate understanding of the network were event, and an active program contributing factors; among many things, the report called for establishing of upgrading and retrofitting to and enforcing reliability standards. the latest earthquake standards is now being undertaken. l Using the latest standards, comes in an emergency or when the Case Study in Resilient a 10-year program is under anticipated hazard is realized—the Infrastructure: Tokyo way to promote earthquake- earthquake strikes, the windstorm Waterworks Bureau resistant joints on key pipe hits, or the floodwaters rise. Having networks. a plan is a good start, but to ensure Japan has had extensive l Emergency training has been that operations continue with experience with large and set up with the local community minimal interruption, an operational devastating earthquakes. Following to ensure that residents culture that trains, tests, and the 2011 Tohuku earthquake, understand plans for water in prepares for these events is the Tokyo Waterworks Bureau the event of an earthquake. This essential. There must be no question evaluated the potential impact of training also allows for testing of who will watch the weather and an earthquake on the city’s water of the emergency facilities decide when to shut the power off supply network. This analysis that have been put in place during a flood or when to swap to an highlighted potential damage to for permanent and temporary alternative system to maintain the critical water treatment facilities water supplies, and provides stability of the power supply. and disruption of supply to key valuable feedback so plans can zones, and it led to a multiyear plan be improved. As the example of the North to improve the resilience of the American blackout shows (box 2), water infrastructure supplying the it is essential to train operators city. More specifically: so they thoroughly understand the infrastructure and can make l The analysis highlighted the appropriate decisions when they need to improve the resilience matter. Those overseeing critical of the connection from the infrastructure must ensure that Tome and Arakawa Rivers, which businesses and public facilities provide water for 80 percent have emergency plans in place and of Tokyo’s needs, by adding a well-trained operators who can second water intake. help to carry them out. 98 Proceedings from the 2016 UR Forum Vulnerability and Resilience Conclusion Pitt, Michael. 2008. “The Pitt Review: Learning Lessons from the 2007 Floods.” Session Contributors http://webarchive.nationalarchives. Deliberately working to address John Schneider, Global gov.uk/20100807034701/http:/ the vital elements in power and Earthquake Model Foundation archive.cabinetoffice.gov.uk/pittreview/ thepittreview/final_report.html. water infrastructure can increase Tuna Onur, Onur Seemann resilience and help to minimize Consulting Inc. SSC (Seismic Safety Commission California). 2000. “A Report to the Governor and potential interruptions in supply. Suresh Vasuvenden, National the Legislature on Lessons Learned from As efforts are made to deliver the Building Code of India Recent Earthquakes in Turkey, Greece, and infrastructure needed to meet the Taiwan.” http://www.seismic.ca.gov/pub/ Nagahisa Hirayama, Disaster CSSC_2000-03.pdf. growing demand across the globe, Mitigation Research Center, there is a great opportunity to Nagoya University U.S.-Canada Power System Outage Task Force. 2004. “Final Report on the August utilize available expertise to ensure 14, 2003 Blackout in the United States and that resilience is built in. No single Canada: Causes and Recommendations.” agency is responsible for meeting http://energy.gov/sites/prod/files/oeprod/ this goal, but it can be met when References DocumentsandMedia/BlackoutFinal-Web. pdf. various government, industry, ADB (Asian Development Bank). 2013. Investing in Resilience: Ensuring a USGS (United States Geological Survey). and private sector experts work 2000. “Implications for Earthquake Risk Disaster-Resistant Future. Mandaluyong collaboratively. City, Philippines: Asian Development Bank. Reduction in the United States from the http://www.adb.org/sites/default/files/ Kocaeli, Turkey, Earthquake of August 17, publication/30119/investing-resilience.pdf. 1999.” U.S. Geological Survey Circular 1193. While infrastructure can’t always http://pubs.usgs.gov/circ/2000/c1193/ emerge unscathed from the ASCE (American Society of Civil Engineers). c1193.pdf. worst-case catastrophe, the 2016. Failure to Act: The Impact of Current Infrastructure Investment on America’s Wellington Lifelines Group. 2012. “Lifeline majority of extended power Economic Future. Reston, VA: ASCE. http:// Utilities Restoration Times for Metropolitan and water interruptions are news.asce.org/asce-report-estimates- Wellington Following a Wellington Fault failure-to-act-on-infrastructure-costs- Earthquake.” http://www.gw.govt.nz/ preventable, not inevitable. families-3400-a-year/. assets/Emergencies--Hazards/Emergency- Planning/12-11-13-WeLG-report-to- McKinsey Global Institute. 2013. CDEM-Joint-Committee-restoration-times- “Infrastructure Productivity: How to Save FINAL.pdf. $1 Trillion a Year.” http://www.mckinsey. com/industries/infrastructure/our-insights/ infrastructure-productivity. 99 GAME OVER?and Vulnerability resilience Exploring the Complexity of Actionable Information through Gaming Child refugee standing in front of his village, which was destroyed by the Mount Merapi eruption in Klaten, central Java, Indonesia. 100 Photo credit: © Akbar Solo | Dreamstime.com. Proceedings from the 2016 UR Forum Vulnerability and Resilience Putting People First: Practices, Challenges, and Innovations in Characterizing and Mapping Social Groups Jianping Yan, United Nations Development Programme Introduction Five typical definitions of social vulnerability can been found in the Disasters impact different people literature: differently. The socially vulnerable are most at risk from disasters 1. Social vulnerability refers and consequently also suffer to potential harm to people. most from their impacts. The It involves a combination of assessment of disaster impacts factors that determines the on vulnerable population groups is degree to which someone’s life now possible; however, we do not and livelihood are put at risk yet systematically quantify the by a discrete and identifiable social dimensions of vulnerability or event in nature or society. integrate these aspects in disaster risk assessments. The discussion 2. Social vulnerability refers to below looks at how vulnerability is the characteristics of a person currently understood, describes some or group in terms of their of the challenges involved in better capacity to anticipate, cope understanding vulnerability, and with, resist, and recover from proposes a framework for integrating the impact of a natural hazard social vulnerability assessment (Wisner et al. 2004). within a disaster risk assessment. 3. Social vulnerability refers to the resilience of communities when confronted by external Background and (natural or man-made) Concepts stresses on human health. Social vulnerability does not Reducing social vulnerability have a single uniform definition. can decrease both human 101 Putting People First: Practices, Challenges, and Innovations in Characterizing and Mapping Social Groups suffering and economic loss.1 Figure 1. Vulnerability as the flip side of resilience. 4. Social vulnerability refers to the inability of people, Vulnerability vs. Resilience organizations, and societies Disaster or Shock to withstand adverse impacts from multiple stressors to Vulnerability Resilience which they are exposed. These impacts are due How does the damage and How does a social group in part to characteristics loss to people occur and maintain its functions inherent in social interactions, what are its causes? and/or recover from the disruption? institutions, and systems of cultural values.2 5. Social vulnerability refers to Social characteristics or indicators the susceptibility of social Income, access to basic services, access to social protection, attitude and culture of risk/disasters, availability of social capital, etc. groups to potential losses from hazard events (Hewitt 1997). hazard-specific. For example, social or indicators as the study of These definitions reflect a groups in one community might vulnerability (box 1). number of critical issues in be vulnerable to earthquakes, the understanding of social but not necessarily vulnerable The study of social vulnerability vulnerability. First, they mix to floods. Even within the same should explain how certain social notions of social vulnerability community, the vulnerability of characteristics contribute to and resilience. For example, the social groups may differ depending people’s worsening situation during frequently cited second definition on groups’ actual exposure. Third, a disaster. It should explain, for seems more about societal social vulnerability should be example, why over 70 percent resilience than social vulnerability, distinguished from the specific of the dead in Hurricane Katrina while the fourth definition simply needs of socially vulnerable groups were over the age of 65, and includes the notion of resilience following a disaster, which arise why African Americans suffered a as part of social vulnerability. out of the crisis or disaster itself disproportionate number of deaths But while they are related, the and are relatively short term. relative to whites and to their local concepts of social vulnerability population numbers; why of the and resilience address different The correct understanding of 300,000 people killed in the 2004 characteristics of social groups. the concepts of vulnerability and Indian Ocean tsunami, 240,000 Social vulnerability addresses the resilience is critical. As illustrated were women and children; and susceptibility of social groups to in figure 1, vulnerability relates why in the Great East Japan potential losses caused by hazard to how certain social groups earthquake of 2011, more than events, whereas resilience reflects suffer damage and loss; the half (56 percent) of the victims the ability of social groups to deal study of vulnerability aims to were aged 65 or older. with a disaster or shock. Second, explain what makes these groups the concept of social vulnerability vulnerable. Resilience on the To some extent, social vulnerability and resilience is context- and other hand relates to how social is the socioeconomic and political 1 Agency for Toxic Substances and Disease groups maintain their functions root cause of risk and disaster. For Registry, Social Vulnerability Index, or recover from a disruption. example, the elderly are fragile, http://svi.cdc.gov/. 2 Wikipedia, “Social Vulnerability,” https:// The study of resilience uses the but age alone does not create en.wikipedia.org/wiki/Social_vulnerability. same set of social characteristics vulnerability; vulnerability also 102 Proceedings from the 2016 UR Forum Vulnerability and Resilience l Identify the exposure of social Box 1: Dimensions of Social Vulnerability and Resilience groups to specific hazards 1. Level of poverty l Clearly understand the social 2. Access to resources such as information, knowledge, and vulnerability, societal resilience, technology and specific needs of these 3. Access to political power and representation (marginalization, social groups relative to exclusion) disasters 4. Social capital including social networks and connections l Identify options to reduce the 5. Social beliefs, customs, and attitude in response to risk or disasters underlying conditions of the 6. Vulnerable residential settings (i.e., weak structure, poor risks they face protection, poor maintenance, etc.) 7. Presence of frail and physically limited individuals 2. How to categorize socially 8. Access to critical services such as communication, transportation, vulnerable groups in terms power supply, water supply, sanitation, etc. of context Source: Adapted from Cutter et al. 2003. The first step in social vulnerability study is to understand the composition of the society, that arises from society’s failure to of a jurisdiction. Social groups is, to categorize social groups in recognize that limited mobility categorized by race/ethnicity, a proper and meaningful manner. impedes timely evacuation. When language/literacy, education, Common classifications—race/ disaster managers and political etc. are used as proxies for social ethnicity, gender, age, etc.— leaders fail to design warning vulnerability. The index-based are intrinsically connected to systems that reach people who approach is generally not linked to opportunity, inequality, and are deaf or to provide paratransit the actual exposure of the social oppression, and thus reflect social systems to evacuate wheelchair groups to different hazards. Most users, society bears responsibility vulnerability in any given society. studies aim to compare the relative for the consequences. Social Disaster situations can expose vulnerability of different jurisdictions, vulnerability thus results from these systems of stratification and and do not address why certain processes of social inequality and vulnerabilities in many ways. groups are at risk or how their historic patterns of social relations situation will worsen after a disaster. that manifest as deeply embedded But classification needs to social structures resistant to recognize that social groupings However, the study of social are complex and context-specific, change. vulnerability should be a diagnostic i.e., the groups identified as socially process that aims to identify the vulnerable are different in different Challenges root causes of the risks associated countries. For example, while with socially vulnerable groups and developed countries may consider The study of social vulnerability the implications of the risks. Policy the elderly a socially vulnerable faces at least four distinct makers and emergency/disaster group, in developing countries, challenges: management practitioners need children and youth are especially evidence of social vulnerability. vulnerable. The 2013 Haiyan 1. How to select indexing or Efforts to characterize social Typhoon, the deadliest rapid- analytic approaches to social groups’ vulnerability should do the onset disaster the Philippines has vulnerability assessment following: experienced, killed 6,000 people Most studies of social vulnerability and affected 6 million children. use an index-based approach to l Categorize social groups in Understanding why Typhoon Haiyan profile the social composition terms of the context impacted working children (or child 103 Putting People First: Practices, Challenges, and Innovations in Characterizing and Mapping Social Groups laborers) and adolescents in the To address this challenge, the hazard-specific social protection country is crucial; the root causes Organisation for Economic Co- mechanisms (Costella 2015). of their differential vulnerability, operation and Development resilience, and needs must be (OECD) established the Partnership considered in developing disaster in Statistics for Development Recommendations risk reduction solutions. in the 21st Century (PARIS21), To integrate social vulnerability an international consortium assessment within a disaster 3. How to systematically that seeks to build statistical risk assessment, a contextual collect social data and keep capacity in developing countries. framework is proposed for them current PARIS21 engages national characterizing and mapping statistical systems in coordinating Social vulnerability is dynamic socially vulnerable groups, as the systematic collection and and its study generally requires shown in figure 2. Assessing social extraction of data on spatially four types of data: census data, and sociodemographically vulnerability should be a four- predisaster and postdisaster disaggregated characteristics. step process that is based on studies, data created within the key outputs of a disaster risk the community (such as actual 4. How to use information on assessment, such as hazard maps, information on households and social vulnerability and plausible risk and disaster their income, population mobility, scenarios, and that aims to identify Most studies of social vulnerability etc.), and surveys with special the root causes that put people remain academic and produce purposes. National census data at risk: outputs that are not applicable can be used to categorize socially to actual decision making. On the vulnerable groups, while the other l Step 1: Categorizing and other hand, policy makers and types of data have to be collected identifying socially vulnerable disaster risk reduction practitioners and updated from time to time. groups in terms of context urgently need evidence-based How to keep all the data current data and information on social l Step 2: Mapping the exposure is a big challenge to the study of vulnerability and resilience of the targeted groups to social vulnerability. for developing context- and different hazards Figure 2. A contextual framework for characterizing and mapping social vulnerability and resilience to disasters in a disaster risk assessment process. Risk/Disaster Hazard maps scenarios Social vulnerability Strategy for Indicators SVGs’ policy solutions Social for categorizing exposure for managing resilience SVGs to hazards SVGs’ risks and Special disaters needs Social characteristics or indicators Note: SVG = socially vulnerable group. 104 Proceedings from the 2016 UR Forum Vulnerability and Resilience l Step 3: Assessing the social in the Pacific Island Countries.” Social of Agriculture, Forest Service, Rocky Protection and Labor Discussion Paper Mountain Research Station. vulnerability, resilience, and 1507, World Bank, Washington, DC. special needs of these groups Sharma, R. 2015: “Child Labor and Natural to specific disaster scenarios, CSS (Center for Security Studies) and CRN Disasters: What Lessons for Emergency in terms of a set of social (Crisis and Risk Network). 2010. “Factsheet: Preparedness? The Case of Typhoon Haiyan Social Vulnerability to Disasters.” CSS, and the Eastern Visayas.” Dissertation, indicators (as in box 1) Zurich. Graduate Institute of Geneva, Switzerland. l Step 4: Identifying context- Cutter, S. L., B. J. Boruff, and W. L. Shirley. Singh, S. R., M. R. Eghdami, and S. Singh. and hazard-specific strategy and 2003. “Social Vulnerability to Environmental 2014. “The Concept of Social Vulnerability: policy solutions to mitigate the Hazards.” Social Science Quarterly 84, no. A Review from Disaster Perspectives.” vulnerability and resilience of 2: 242–61. International Journal of Interdisciplinary these groups. and Multidisciplinary Studies 1, no. 6: 71–82. Enarson, E. 2007. “Identifying and Addressing Social Vulnerabilities.” In Sumadiwiria, C. 2015. “Putting Vulnerable Session Contributors Emergency Management: Principles and Communities on the Map: A Research Practice for Local Government, edited by Report on What Influences Digital Stephane Hallegatte, Climate W. L. Waugh and K. J. Tierney, chap. 13. Map-Making with Young Volunteers in Change Group, World Bank Group Washington, DC: ICMA Press. Bangladesh.” Care International. Krunoslav Katic, UNDP Croatia Hallegate, S., M. Bangalore, and A. Vogt- Thomas, D. S. K., B. D. Phillips, W. E. Richa Sharma, consultant Schilb. 2016. “Assessing Socioeconomic Lovekamp, and A. Fothergill. 2013: Social Cecilia Costella, Red Cross Red Resilience to Floods in 90 Countries.” Policy Vulnerability to Disasters. 2nd Edition. Boca Crescent Climate Centre Research Working Paper 7663, World Bank, Raton, FL: CRC Press. Washington, DC. Till Zbiranski, OECD UNDP Croatia. 2015: “Comparative Social Hewitt, K. 1997. Regions of Risk: A Vulnerability Profiling: A Case from Croatia.” Geographical Introduction to Disasters. UNDP Project Report. Harlow, UK: Longman. References and Wisner, B., P. Blaikie, T. I. Cannon, and I. Further Resources Murphy, D. J., C. Wyborn, L. Yung, and D. R. Davis. 2004. At Risk: Natural Hazards, Williams. 2015. Key Concepts and Methods People’s Vulnerability, and Disaster. 2nd ed. Costella, C., and O. Ivaschenk. 2015. in Social Vulnerability and Adaptive London: Routledge. “Integrating Disaster Response and Climate Capacity. General Technical Report RMRS- Resilience in Social Protection Programs GTR-328. Fort Collins, CO: U.S. Department Attendees participate in a mapping exercise during the UR2016 Focus Day event, “Let’s Shake Your Community—Earthquake Hazard Mapping Approach for Community Resilience.” Photo credit: Andrea Basso. 105 GAME OVER?and Vulnerability resilience Exploring the Complexity of Actionable Information through Gaming Cattle for sale at Babile, Ethiopia, one of the largest livestock markets in the Horn of Africa. Photo credit: © Ilia Torlin | Dreamstime.com. 106 Proceedings from the 2016 UR Forum Vulnerability and Resilience How Risks and Shocks Impact Poverty—and Why, When, and Where Better Financial Protection Can Help Daniel Clarke, World Bank Group Johanna Avato, World Bank Group Background and risk finance aims to increase the Concepts resilience of vulnerable countries to the financial impact of disasters Recent data indicate a sharp rise in as part of a comprehensive natural disasters over the last 50 approach to disaster risk years (figure 1). Despite poverty management. By increasing declining on average, many people resilience, disaster risk finance are only one disaster away from offers the promise of protecting poverty. Tropical Storm Agatha against poverty and promoting (2010) increased poverty 14 development. percent in Guatemala, for example, and over half the rural population Yet empirical evidence showing in Afghanistan, India, Lao People’s whether this approach actually Democratic Republic, Malawi, works in practice is only emerging. Uganda, and Peru have reported Such evidence is key to better exposure to one or more recent guiding investments in sovereign shocks, with natural disasters cited disaster risk finance programs, as the primary culprit (Baez et al. to maximizing their expected 2016). impacts, and to ensuring that public investments deliver value Direct financial loss from natural for money. disasters reached an average of $165 billion per year during It is also key for understanding 2002–2012, with losses exceeding the relationship between natural $100 billion in six of those years hazards and poverty: better (Clarke and Dercon 2015). Disaster financial protection might dull 107 How Risks and Shocks Impact Poverty—and Why, When, and Where Better Financial Protection Can Help • All continents Source: D. Guha-Sapir, R. Below, and Ph. Hoyois, EM-DAT: The CRED/OFDA International Disaster Database, Université Catholique de Louvain, Brussels, Belgium, www.emdat.be. the impact of natural hazards on science and financial economics to Sadoulet (2016), who show that poverty, and hence change the public finance, social protection, reconstruction of infrastructure nature of the poverty risk profile microeconomics, development assets (made possible by disaster significantly. economics, and behavioral risk finance through Mexico’s economics. FONDEN program) contributes on The Disaster Risk Financing and average to a 2−4 percent increase Insurance Program, a joint initiative The Disaster Risk Finance Impact in postdisaster local economic of the World Bank Group’s Finance Analytics Project has succeeded activity. and Markets Global Practice and the in bringing new insights to the Global Facility for Disaster Reduction relationship between natural The project also developed and and Recovery, has attempted to hazards and poverty. For example, then applied a methodology to improve precisely this evidence work carried out under the project quantify the costs of different base through its Disaster Risk by de Janvry, Ramirez Ritchie, combinations of budgetary and Finance Impact Analytics Project. and Sadoulet (2016) finds that financial instruments used to This project is supported by the drought insurance payouts to finance disaster response (Clarke, UK Department for International Mexican farmers (made possible Coll-Black, et al. 2016; Clark, Development’s Humanitarian by disaster risk financing through Cooney, et al. 2016; Clarke, Mahul, Innovation and Evidence the CADENA program) increase et al. 2016). The approach results Programme, and brings together farmers’ income by 38 percent and in a simple formula to capture the the practices of catastrophe risk their consumption by 27 percent. opportunity cost of risk-financing modeling, insurance, and disaster Evidence on the magnitude of strategies and to help decision risk management with academic the total economic benefit is makers choose the least-cost disciplines ranging from actuarial offered by De Janvry, del Valle, and approach. Better financial protection might dull the impact of natural hazards on poverty, and hence change the nature of the poverty risk profile significantly. 108 Proceedings from the 2016 UR Forum Vulnerability and Resilience Case Studies The case studies described below—carried out by experts from academia, government, and the private sector— illuminate the relationship between extreme natural events and poverty, and provide evidence on whether predisaster financial decisions can change this relationship, dulling the impact of disasters on the vulnerable. Catastrophe Risk Modeling also reveal that access to a safety the derived drought-poverty and Economic Analysis of net (Ethiopia’s Public Safety Net relationship demonstrates Vulnerability to Poverty in Programme) mitigates the drought some level of external and Ethiopia impact by 0.5 percentage points— internal validity. Therefore, this that is, households with access relationship could form the basis Catherine Porter and Emily White to the program experience a 1.5 of a vulnerability module in a present evidence from Ethiopia percent decrease in consumption catastrophe risk model. that brings together two strands rather than a 2 percent decrease. of research that have thus far The results suggest that the Rainfall Index Insurance been developed independently: relationship between drought and in India catastrophe (cat) risk modeling consumption is fairly homogeneous The design of financial protection (figure 2) and economic analysis and stable, so that it is possible against shocks matters significantly of vulnerability to poverty. This to conclude (with caveats) that for poverty reduction. Research approach seeks to take advantage of the power that probabilistic cat risk models could have if applied Figure 2. Probabilistic cat risk modeling modules and sample output to the assessment of household The hazard module shows historical cyclone tracks for generating stochastic events (from the United Nations Environment Programme Global Resource Information poverty outcomes. The challenge Database, UNEP GRID) and ShakeMap of the Tohoku earthquake for local intensity in applying cat risk models in this (from the U.S. Geological Survey). The exposure module shows population density (from way is quantifying the relationship UNEP GRID). The vulnerability module shows vulnerability curves for damage estimation (from CoreLogic’s EQECAT platform). The probabilistic impact curve is for earthquake between hazard and outcome in a and tropical cyclone (from the Pacific Catastrophe Risk Assessment and Financing poverty context—the vulnerability Initiative). module in a cat risk model. The researchers attempt to derive such vulnerability relationships for the impact of drought on households in Ethiopia; they ask whether a relationship can be derived between drought and household consumption that has internal and external validity and, if so, whether it can help (1) model risk (in a probabilistic framework) and (2) shed light on the benefits of interventions, including early response. This study finds that the impact of drought is significant; for every 10 percent worsening of the drought, consumption falls on average by 2 percentage points. The results Source: Porter and White 2016. 109 How Risks and Shocks Impact Poverty—and Why, When, and Where Better Financial Protection Can Help by Javier Baez analyzes the Figure 3. Estimated insurance treatment effect on labor demand. welfare effects of a rainfall index 6 insurance product offered to Indian farmers. Because index insurance products have novel features 5 but may also have unintended Agricultural laborers offered insurance consequences, properly evaluating their welfare effects requires 4 moving beyond effects on the Agricultural laborers In (Daily wage) not offered insurance treated population and determining the general-equilibrium effects on 3 both wage levels and volatility. In fact, the insurance may change risk-taking behavior and hiring 2 practices by cultivators, and in turn affect the output and wages of landless laborers who make up 1 a sizable proportion of the world’s impoverished population. Baez 0 finds that output becomes more 3 4 5 6 7 8 9 10 11 12 13 sensitive to rainfall for insured Average rainfall per day during the monsoon season (mm) farmers, and that output is actually lower for the insured than the Source: Mobarak and Rosenzweig 2014. uninsured in the lower half of the can help in developing evidence- increases income from milk, and rainfall distribution. Hence harvest based policy recommendations. results in reduced herd sizes labor demand may also be lower Focusing on results from an index- (consistent with precautionary in the low state for the insured based livestock insurance (IBLI) savings). cultivators. product, which covers drought- l Postdrought coping. IBLI related mortality and morbidity improves postdrought coping. Figure 3 plots the estimated risks for pastoralist livestock After the catastrophic 2011 insurance treatment effect on labor demand across the in Kenya and Ethiopia, Andrew drought, there was a 36 entire rainfall distribution in Mude shows that insurance has percent reduction in the the sample. Labor demand by a beneficial impact on a range of likelihood of distress livestock insured cultivators is statistically socioeconomic outcomes: sales overall, and a 64 percent significantly higher (relative to the reduction among modestly uninsured) for almost all positive l Herd mortality risk. Purchasing better-off households. In rainfall shocks. The study also IBLI increases herd survival addition to this, there was a 25 finds that marketing insurance rates by considerably reducing percent reduction in the overall to landless laborers reduces the the risk of catastrophic loss, and likelihood of reducing meals sensitivity of wages to rainfall. the majority of households are as a coping strategy, and a 43 better off as a result. percent reduction among those Index-Based Livestock l Livestock productivity and with small or no herds. Insurance in Kenya and household income. IBLI l Welfare. Households purchasing Ethiopia coverage increases investments IBLI showed reduced child Studying the impacts of social in maintaining livestock through malnutrition, had higher incomes protection programs on poverty expenditures on veterinary care, per adult, and felt generally 110 Proceedings from the 2016 UR Forum Vulnerability and Resilience A farmer sorts tomatoes in Ethiopia. Photo credit: World Bank. more at ease and satisfied. Jamaica, including detailed conclusions and possible further information on consumption and research: Overall, the evidence identified expenditure as well as on location IBLI as a cost-effective social and buildings, for 9,500 households l Financial protection can help protection tool. Yet positive IBLI from 1990 to 2012. Although the to increase financial resilience impacts do not necessarily justify findings support a negative impact against natural disasters, investing scarce development of hurricanes on consumption per but the design of products is or social-protection funds in capita, the cross-sectional data critical. For example, basis risk in insurance products; to know overstate the impact; the effect agriculture insurance products whether they do, it is necessary to lasts only one year and is not reduces their value. understand the opportunity cost very large. Several explanations relative to the interventions. are possible for this, including l While essential for answering the possibly poor damage proxy questions about shocks, data Impact of Hurricanes and households’ use of informal collection can be challenging, on Household Poverty in insurance and budget reallocation as shocks by their nature are Jamaica mechanisms (such as receipt of unpredictable. There is a general understanding remittances). l The insurance industry has that the impact of hurricanes on an established framework for household poverty is negative, assessment and pricing of risk, Conclusions but little consensus on to what which can be used to inform degree. Research by Eric Strobl The case studies described decision making; a key challenge uses household panel data from here suggest some interesting for the development community 111 How Risks and Shocks Impact Poverty—and Why, When, and Where Better Financial Protection Can Help is establishing parameters opposed to costing) money, Clarke, D. J., O. Mahul, R. Poulter, and T.-L. Teh. 2016. “Evaluating Sovereign Disaster to increase resilience, and further work needs to be Risk Finance Strategies: A Framework.” thus promote and protect done to “package” the findings Project Working Paper 7721. World Bank, development. that are emerging on financial Washington, DC. l To ensure that key decision protection’s benefits. De Janvry, A., A. del Valle, and E. Sadoulet. makers (such as ministries of 2016. “Insuring Growth: The Impact of Disaster Funds on Economic Development finance) see financial protection interventions as saving (as References in Mexico.” Project Working Paper Series No. 7714. World Bank, Washington, DC. Baez, J. L. Lucchetti, M. Salazar, and M. De Janvry, A., E. Ramirez Ritchie, and E. Genoni. 2016. “Gone with the Storm: Session Contributors Rainfall Shocks and Household Wellbeing in E. Sadoulet. 2016. “Weather Indexed Insurance and Shock Coping: Evidence Emmanuel Skoufias, Poverty Guatemala.” World Bank, Washington, DC. from Mexico’s CADENA Program.” Project and Equity Global Practice, World Working Paper 7715. World Bank, Clarke, D. J., S. Coll-Black, N. Cooney, and Bank Group A. Edwards. 2016. “A Methodology to Washington, DC. Ian Branagan, RenaissanceRe Assess Indicative Costs of Risk Financing Mobarak, A. M., and M. Rosenzweig. 2014. Holdings Ltd. Strategies for Scaling Up Ethiopia’s “Risk, Insurance and Wage in General Productive Safety Net Programme.” Javier Baez, Poverty and Equity Equilibrium.” NBER Working Paper 19811, Project Working Paper 7719. World Bank, Global Practice, World Bank Group Cambridge, MA. Washington, DC. Andrew Mude, Kenya Porter, Catherine, and Emily White. 2016. Clarke, D. J., N. Cooney, A. Edwards, and A. International Livestock Research Jinks. 2016. “Evaluating Sovereign Disaster “Potential for Application of a Probabilistic Institute Risk Finance Strategies: Guidance and Case Catastrophe Risk Modelling Framework to Poverty Outcomes: General Form Catherine Porter, Heriot-Watt Studies.” World Bank, Washington, DC. Vulnerability Functions Relating Household University Poverty Outcomes to Hazard Intensity in Clarke, D. J., and S. Dercon. 2015. Dull Eric Strobl, Ecole Polytechnique Disasters? How Planning Ahead Will Make a Ethiopia.” Policy Research Working Paper Difference. Oxford: Oxford University Press. 7717. Washington, DC, World Bank. Francis Ghesquiere, head of the GFDRR, addresses participants in the closing ceremony. Photo credit: Miki Fernández. 112 Direct financial loss from natural disasters reached an average of $165 billion per year during 2002–2012, with losses exceeding $100 billion in six of those years (Clarke and Dercon 2015). Disaster risk finance aims to increase the resilience of vulnerable countries to the financial impact of disasters as part of a comprehensive approach to disaster risk management. 113 k risk risk isk risk r isk risk ris risk risk risk risk r isk ris k risk risk risk risk r risk risk risk risk risk risk risk risk risk risk risk risk risk risk risk risk risk The Future of Risk and Risk Assessment Disruptors: Cutting-Edge Technologies That Are Changing the Way We Understand Risk [page 117] Building a Less Risky Future: How Today’s Decisions Shape Disaster Risk in the Cities of Tomorrow [page 121] The Domino Effect: The Future of Quantifying Compounding Events in Deltas [page 127] Understanding Risk Is Essential for the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030: Targeting the Future with Science and Technology [page 133] GAME OVER? Exploring the Complexity of Actionable Information through Gaming 116 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment Disruptors: Cutting-Edge Technologies That Are Changing the Way We Understand Risk Amal Ali, Global Facility for Disaster Reduction and Recovery Introduction Background Disruptive innovation is arguably Confronted with unpredictable the sexiest concept across all weather patterns and an increase industries today. The term, first in the frequency and severity coined by Harvard professor of natural hazards, disaster Clayton Christensen, is defined risk managers are looking to as “a process by which a product disruptive innovations for faster or service takes root initially and cheaper solutions to the in simple applications at the problems of understanding and bottom of a market and then responding to disaster risk. relentlessly moves up market, Emerging technologies have eventually displacing established changed the field of disaster competitors.”1 History affords risk management in the last few us many examples of disruptive years, and a variety of initiatives innovations, from the steamship, are further encouraging the automobile, and personalized development and employment computer to mobile phones and of disruptive innovations in the Netflix. From these examples, one field. The Challenge Fund of the thing is clear: disruptive innovation UK Department for International revolutionizes the way we live, Development (DFID) and Global work, and communicate with Facility for Disaster Reduction and others. Recovery (GFDRR), for example, spurs innovation by funding projects to improve decision makers’ access to and use of risk information. 1 The definition is from Clayton Christensen’s website at http://www. claytonchristensen.com/key-concepts/. 117 Disruptors: Cutting-Edge Technologies That Are Changing the Way We Understand Risk Case Studies deploy a particular tool to technologies. Given this situation, alleviate an observed constraint it is possible to question the Innovative tools and technologies in a developing country’s validity of the data derived from now available range from mobile understanding and implementation such technologies, particularly weather stations, which provide of risk information. The developing when they are aggregated to a timely information on rainfall country decision makers are national level. intensity through SMS, to Think often not consulted during the Hazard!, a simple robust tool that development stage, yet they are enables development specialists expected to make use of the data Recommendations to determine the likelihood and generated from the tools once impact of a natural hazard in their launched. Thus neglect of the The challenges posed by disruptive given project area. demand side can result in tools innovations present major that are underutilized or that obstacles in the application of The potential to apply innovative don’t meet users’ actual needs. the tools and their outputs. But tools from other sectors is these challenges need not take also promising. IBM Watson, a Another challenge is that adopting away from the power of these cognitive computing system now disruptive technologies can be innovations, because simple being used by cancer researchers, difficult for decision makers solutions are often available to the transport sector, and the accustomed to traditional meet them. For example, co- intelligence community, could have established mechanisms. The tools production is one way of bypassing a huge impact if applied in the may be perceived as too simplistic the issue of supply-driven disaster risk management field, and thus unable to address critical technologies. When tools are largely because of the richness social or environmental challenges. co-produced with decision makers, of risk information that would be It is important to note that developing country governments this challenge is not specific to derive a sense of ownership, produced. developing countries but can be and the chances of uptake are found globally in large bureaucratic improved. Challenges institutions. It is also possible to overcome the While disruptive innovations can The exclusionary tendency of some challenge that archaic bureaucratic provide experts and decision disruptive innovations also poses systems pose for the uptake of makers alike with ample and a challenge. Tools that operate disruptive innovations. This can be unparalleled opportunities, there on mobile applications or pull done if the producers of innovation are numerous challenges to data from social media platforms, clearly outline a robust business employing such technologies in for example, may exclude the case for employing the product disaster risk identification. portion of the population that and outputs. lacks access to the necessary One key challenge is that the devices. Although there is a great Finally, it is important to highlight tools are often driven by supply proliferation of smart phones in to beneficiaries that disruptive as opposed to demand. The developing countries, nonurban innovations should not be viewed developers of these technologies, dwellers (the largest majority of as a replacement of traditional who often hail from developed any developing country population) mechanisms. For example, although countries, decide to build and can neither afford nor access such mobile weather stations produce One thing is clear: disruptive innovation revolutionizes the way we live, work, and communicate with others. 118 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment real-time data quickly and cheaply, innovations will continue to be the banking system as such, but by they cannot be a substitute for instrumental. With seed funding extending basic financial services more traditional weather stations; for pilot projects, disruptors to those traditionally excluded, it rather they should be viewed can test their ideas, refine has filled a gap in the market that as complementary to existing them, and scale them globally. the established financial sector systems. The transformational role that could not. challenge funds can play is evident in the M-PESA case in Kenya. Conclusion M-PESA is an electronic payment that allows users to withdraw, The application of disruptive Session Contributors deposit, and transfer cash through innovations in the disaster risk Jurjen Wagemaker, FloodTags their mobile phones. The channel management field will inevitably Soumya Balasubramanya, started as a pilot project funded continue to grow. As the nature International Water Management by the DFID’s Financial Deepening of hazards changes, it will be Institute Challenge Fund. Today, more than incumbent upon us as practitioners Jan van Til, FutureWater two-thirds of Kenyans use the to think of faster, smarter, and channel—both in rural and urban Justin Fessler, IBM simpler solutions for identifying centers—and the innovation Hessel Winsemius, Deltares and responding to risks. has changed the possibilities Alanna Simpson, GFDRR The role that challenge funds of financial inclusion programs play in the development of these globally. M-PESA hasn’t replaced Attendees examine the Red Cross Red Crescent Climate Centre’s datasculpture, “Go with the Flow,” which visualizes river flow data in Togo from 2005 to 2015. Photo credit: Andrea Basso. 119 GAME OVER? Exploring the Complexity of Actionable Information through Gaming Rubble-strewn streets of Chautara, Sindhupalchok, Nepal.. Photo credit: © IOM 2015. 120 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment Building a Less Risky Future: How Today’s Decisions Shape Disaster Risk in the Cities of Tomorrow Stuart Fraser, Global Facility for Disaster Reduction and Recovery David Lallemant, Nanyang Technological University Disaster risk is constantly and land-use planning take into areas or on reclaimed, low-lying evolving due to changes in hazard, account growing urban populations land immediately places more exposure, and vulnerability. and evolution in cities’ size and people at risk, but there is also Urbanization and population structure. In many other cities, a feedback effect in which the growth (figure 1) are part of the pace of change is too rapid initial stages of development this evolution—they have been for formal governance systems encourage further activity. In key drivers of the observed to keep up, and development other words, increases in exposure increase in disaster losses over takes place in an unregulated, and vulnerability can propagate in recent decades—and in 2008, ad hoc manner. In both cases, a location as the initial populations urban dwellers outnumbered new development influences or assets attract further rural dwellers for the first time. future levels of risk and resilience development and economic Changes in the drivers of risk by creating new exposure or activity around them. By the same are having especially profound prompting investments with token, developments that locate impacts in cities, which are long life spans, which effectively high-density populations outside often located in areas prone to lock in levels of disaster risk for of hazard zones can alleviate risk flooding, earthquakes, and other decades to come. If decisions for many years to come. It is thus hazards; nearly 1 billion people are are taken with disaster risk and possible to incorporate disaster estimated to live in areas prone to future climate conditions in mind, risk reduction considerations into flooding, an increase of 90 percent they may help to mitigate further decision-making processes and so from 1970 (Jongman, Ward, and increases in risk. If not, they may ensure that development helps Aerts 2012). More frequent and unintentionally increase future risk. to reduce risk over the coming intense weather-related hazards years and decades. This is true due to climate change are also not only for known risks but also contributing to the evolution Urban Development for emerging risks that have been of disaster risk and may further and Risk thus far neglected in many areas. aggravate the situation of the For example, planning decisions Currently, unregulated poorest urban citizens. and construction methods could development often occurs on land parcels that may be available account for hazards that are The future of disaster risk is at a low cost precisely because becoming more frequent or severe being written now. In some they are prone to hazards. Rapid in our changing climate, particularly cities, decisions on urban design construction of buildings in such extreme heat and fire in cities. 121 Building a Less Risky Future: How Today’s Decisions Shape Disaster Risk in the Cities of Tomorrow Figure 1. The increase in global urban population between 1970 and 2030 Source: David Lallemant using data from UN World Urbanization Prospects (inspired by Population Reference Bureau infographic). But if the importance of risk- the influence of policy decisions But effective use of these informed decision making is clear, and investments on those drivers, approaches itself also relies in practice there are multiple will we be able to improve the heavily on knowing what the challenges involved in making risk- effectiveness of policies focused future riskscape might look like informed decisions and applying on reducing risk. In turn, dynamic with and without the design in urban design principles to manage risk assessment depends on place—a fact that reemphasizes a city’s risks. One major challenge having reliable sources of data the need for robust and dynamic is ensuring accurate assessment that reflect the dynamic nature assessment of future risk. Designs and continuous reevaluation of of population, in terms of overall that account for projected risk, which are required to enable growth, movement of people, and changes in climate and population effective risk reduction and population socioeconomics. The can incorporate factors of safety prevent drastic increases in future need for data also extends to the into infrastructure to ensure it losses. To be most useful for assessment of coping capacity is robust enough to cope with decision makers, risk assessments in order to monitor and reduce future conditions, or they can use must demonstrate the impacts welfare losses, and ultimately no-regret strategies (Hallegatte of investment on future risk reduce risk to lives and livelihoods. 2009), which provide benefits and hence must be dynamic (i.e., regardless of whether climate quantify future risk) rather than As a key part of the development change increases the disaster risk. static (i.e., quantify current risk process, urban design should based on a snapshot of data from be aware of risk and make use Multiple emerging technologies the recent past). Only when we are of urban greening strategies, can help us take control of a city’s able to identify and model the main innovative flood defense risk trajectory through planning drivers of risk, and demonstrate structures, and similar approaches. and design. To match patterns 122 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment of services and patterns of at high spatial and temporal Case Studies urbanization, planners can turn to resolution—is needed. In this earth observation technologies, regard, the importance of open Risk-Aware Flood Defense which provide new methods data and open mapping to inform Design in Manhattan for monitoring population and future planning and forecasting To promote risk-aware design that infrastructure growth, and cannot be overstated. includes great urban amenities which can be used to understand within resilient infrastructure, it dynamics of risk linked with The vast majority of urban is important to link risk modelers urbanization and other changes residential construction in today’s with designers. Design systems in exposure. While regional scale growing cities occurs through the should be adaptable so they can modeling of urban trends exists ad hoc, incremental expansion of grow to match an inherently (see figure 2, for example), such buildings over time. New structural uncertain risk. One way of analyses must be downscaled engineering tools are beginning to promoting adaptability is through to the city and subcity scale simulate these changes in buildings small design interventions that to shed light on development over time and their effect on facilitate learning over time patterns at the scale required building vulnerability (Lallemant et through an experimental approach. by urban developers. Machine- al. forthcoming). These tools enable Smaller projects (or projects with learning approaches to population us, for instance, to assess the small, modular components) can mapping, which can project future potential influence of construction be easier to manage in terms of urbanization and service needs, quality policy on future earthquake governance and implementation; offer tremendous potential. Since risk (figure 3). In parallel, time- and if they are independent of most future urban growth will varying hazards are increasingly other components in the larger occur in low-income countries being measured and monitored at system, they can be constructed where data are sparse, improved a scale useful for city-level decision to leave redundancy in the data collection—particularly making (e.g., urban land subsidence, defenses (i.e., designed so that focused on integration of data flood frequency monitoring). not all components fail at once). Figure 2. Simulated change in population density between 2010 and 2020 in Uganda 2010 2020 Source: Catherine Linard. 123 Building a Less Risky Future: How Today’s Decisions Shape Disaster Risk in the Cities of Tomorrow One example of this approach Figure 3. A demonstration of the potential impact of increasing construction is the “Big U” flood defense in quality on earthquake damage. Manhattan, New York City, in which Number of buildings sustaining heavy damage communities are protected by 400,000 Predicted risk individual flood defense cells that Predicted risk assuming together form a continuous flood 300,000 increased quality of all 20% new construction EXPECTED defense. This approach also has REDUCTION the benefit of individual defense 200,000 IN 15 YEARS cells that are easily adapted, managed, and governed rather 100,000 than very large infrastructure spanning multiple governance geographies (figure 4). 1990 1995 2000 2005 2010 2015 2020 2025 2030 Source: David Lallemant. Figure 4. Compartmentalized flood defense design for Manhattan, New York. City. Each compartment enables flexibility because it encourages a design and risk mitigation plan relevant to that community. Source: BIG/One Architecture. Losses in the 2005 Mumbai on their relative coping capacities. people were disproportionately Floods: Welfare and Assets Analysis of the 2005 Mumbai affected by the floods (39 percent floods, which differentiated versus 18 percent of the nonpoor While there is much focus on asset between total asset losses and population) and lost relatively more losses in cities, and though the welfare losses for various urban (13 percent of income versus 9 risk community is acutely aware of communities, suggests that the percent of income). Furthermore, the impact of disasters on urban urban poor are more exposed, overall welfare losses, estimated populations, risk analysis rarely suffer greater impacts, and have at Rs 60 billion ($890 million), were accounts adequately for welfare less recovery capacity than other much higher than asset losses, losses, which can vary hugely populations (Hallegatte, Bangalore, estimated at Rs 35 billion (over between communities depending and Vogt-Schilb 2016). Poor $500 million). 124 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment A socioeconomic resilience tool people, but better communication messages and success stories developed by the World Bank between analysts and local with decision makers. This can (Hallegatte, Bangalore, and Vogt- authorities or communities would be done only with increasingly Schilb 2016), which includes help to show the value of detailed effective communication, via modeled coping capacity, can be data and enable sharing to improve multiple avenues that tell a used as a policy tool to estimate assessment. story of changing risk—and make the impact of policies on welfare clear what could happen if a losses. The tool shows that certain decision is or is not made. disaster-based social protection Conclusion Underlying this approach is a need can decrease welfare losses, for some quantification of future This discussion highlights just a even in cases where asset losses risk to assess the range of options few of the issues and challenges increase (figure 5). A key challenge objectively: which options increase involved in better measuring and to improving consideration of risk, which options reduce risk, and predicting future risk. Collectively, welfare losses is data availability by how much relative to their cost? the approaches can guide risk- at the detailed level—for example, sensitive urban policy and planning data on which groups of people by demonstrating potential Session Contributors live in which houses. Such high- trajectories of cities’ risk and the Catherine Linard, University of resolution exposure data are not impact of policies made today on Brussels and University of Namur ordinarily captured in typical risk these trajectories. Julie Arrighi, Red Cross Red models, particularly those covering Crescent Climate Centre a regional or national domain. Asset An immediate goal is to incentivize Matthijs Bouw, University of inventories exist to assess impacts risk-based decision making Pennsylvania on poor people versus wealthy by sharing risk management Adrien Vogt-Schilb, Climate Change Group, World Bank Group Figure 5. Impact of several strategies to reduce welfare losses in Mumbai. 1.1 0.0 0.0 References Hallegatte, S. 2009. “Strategies to Adapt Relative change (%) to an Uncertain Climate Change.” Global Environmental Change 19, no. 2: 240–47. -3.7 -3.5 doi:10.1016/j.gloenvcha.2008.12.003. -5.0 -5.0 Hallegatte, S., M. Bangalore, and A. Vogt- Schilb. 2016. “Assessing Socioeconomic Resilience to Floods in 90 Countries.” Policy Research Working Paper 7663, World Bank, Washington, DC. n Asset losses Jongman, B., P. J. Ward, and J. C. J. H. n Welfare losses -9.8 Aerts. 2012. “Global Exposure to River and Coastal Flooding: Long Term Trends and Changes.” Global Environmental Change 22, no. 4: 823–35. doi:10.1016/j. Reduce Cut Duoble Increase gloenvcha.2012.07.004. exposure reconstruction post-disaster income of bottom by 5% duration by support quintile by 10% Lallemant, D., H. Burton, L. Ceferino, Z. a third Bullock, A. Kiremidjian, and G. Deierlein. Forthcoming. “A Framework for Collapse Probability Assessment of Buildings Growing and Extending Incrementally Over Source: Hallegatte, Bangalore, and Vogt-Schilb 2016. Time.” Earthquake Spectra. 125 GAME OVER? Exploring the Complexity of Actionable Information through Gaming The Parana River delta is a huge forested marshland about 20 miles northeast of Buenos Aires, Argentina. This image highlights the striking 126 contrast between dense forest and wetland marshes, and the deep blue ribbon of the Parana River. Photo credit: USGS EROS Data Center. Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment The Domino Effect: The Future of Quantifying Compounding Events in Deltas Hessel C. Winsemius, Deltares Philip J. Ward, Institute for Environmental Studies, VU University Amsterdam Peter Salamon, European Commission Joint Research Centre Frederiek Sperna Weiland, Deltares Mirianna Budimir, Natural Hazard Consulting Ltd. Melanie Duncan, British Geological Survey Bart J. J. M. van den Hurk, Institute for Environmental Studies, VU University Amsterdam; Royal Netherlands Meteorological Institute (KNMI) Antonia Sebastian, Rice University Toward Multihazard vulnerability. For example, one Interacting Risk natural hazard could increase the Assessment Methods likelihood of another kind, could leave society more exposed to the Priority 1 of the Sendai Framework next, or could leave the exposed for Disaster Risk Reduction society more vulnerable to impacts 2015–2030 (Understanding from the next. Disaster Risk) advocates moving research and development in disaster risk management toward Case Studies more comprehensive multihazard Case studies on interactions approaches (UNISDR 2015). between natural hazards in the Currently, however, there exist Philippines, the Netherlands, and limited guidelines or methods the United States are presented in science for assessing natural below. They raise significant hazard risks while also considering questions about the impacts of hazards’ complex dynamics and compounding events on society, interactions. Interactions between the way in which an “event” should different natural hazards (e.g., be presented to stakeholders, and floods, volcanos, earthquakes) the importance of collecting more can exacerbate their associated evidence and data that can relate risks by influencing one or more impacts to a multihazard cascade. of the three factors of the risk framework: hazard, exposure, and 127 The Domino Effect: The Future of Quantifying Compounding Events in Deltas Figure 1. Ruins of homes destroyed by the lahars and floods on Mount Mayon in 2012. Source: © Melanie Duncan. Reproduced with permission from Melanie Duncan; further permission required for reuse. Philippines: Cascading on society. In 2011, the two levels in Lauwersmeer, a lake in the Hazards hazards—a heavy surge event northern Netherlands, changes and a concomitant heavy when compound surge and rainfall The Philippines is exposed to rainfall—coincided in the northern events are accounted for (Van den multiple natural hazards. In the Netherlands. Individually, the Hurk et al. 2015). area surrounding the active surge and rainfall were not volcano Mount Mayon (figure United States: Tropical extreme, but their compounding 1), the impact of typhoons is Cyclones and Rainfall impacts resulted in a serious aggravated by increases in the and long-lasting impediment to The Houston, Texas, region of probability of lahars (volcanic mud free drainage, which almost led the United States is exposed flows). In 2006, the area was hit to severe flooding in the area, to tropical cyclones and heavy by typhoons in September and which is well known for its high rainfall events. A study of this November. The second and more flood protection standards. Figure region shows that the U.S. intense typhoon struck while 2 shows how the probability Federal Emergency Management communities were still recovering distribution of extreme water Agency’s (FEMA’s) 1 percent from—and experiencing increased vulnerability as a result of—the first typhoon. The second typhoon Figure 2. Return level of inland water level at Lauwersmeer without consideration triggered intense lahars that of compound flooding (grey) and with (blue). The red dashed line indicates the killed over 1,000 people living highest warning level for this station. on the slopes and at the foot of the volcano. These consecutive 1/50 yr 1/200 yr events showed that communities’ Inland water level (meters) vulnerability is dynamic and dependent on earlier hazard events. Netherlands: Storm Surge and Rainfall With compound events Without compound events When storm surge and heavy rainfall occur jointly in a coastal area of the Netherlands, the Return period (years) resulting floods can have a particularly severe impact Source: Van den Hurk et al. 2015. 128 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment floodplain, which is used as a watersheds, current policy is because storm surges are often primary flood risk marker, does allowing for—and potentially modeled at the regional scale, not incorporate the risk from driving—development in already while pluvial floods are modeled compound flood processes. This flood-prone areas, hence making at the local scale, it is difficult to boundary, representing the extent communities more susceptible to combine these two hazards into a of either riverine or storm surge cascading hazards. single evaluation. But by focusing flooding, drives policy decisions on the impact, the two hazards regarding flood mitigation, do not need to be communicated insurance purchases, local planning, Stakeholder-Centered separately, and instead they can be and building construction. But Approach evaluated by their combined effect while the flood hazard from both In order to solve the puzzle of in one and the same unit. riverine and surge hazards are compounding events, it is essential mapped individually, they are not All three case studies show the to start the conversation at the mapped jointly, and this failure impact side: what causes societal importance of starting with the may be contributing to much disruption, damage, and loss of particular impacts to particular higher numbers of insurance claims life? This approach also helps stakeholders in order to better than anticipated. The empirical to circumvent the problem of understand compounding evidence indicates that in some considering different natural events. This focus showed that coastal watersheds, more than hazards together when they in the Philippines, compounding 50 percent of flood claims occur are measured using different events play a role in creating outside of the mapped floodplain metrics or at different scales. dynamic vulnerability, that in the boundaries. Research suggests By focusing on the impact, Netherlands, they can lead to that by neglecting to consider different natural hazards and unanticipated extreme water the interaction between storm their combined effects are more levels, and that in the Houston, surge and rainfall-runoff in coastal readily comparable. For example, Texas, region, they may call into Flooding in Raymondville, another area of Texas prone to floods, during Hurricane Dolly (July 2008). The FEMA floodplain demarcates where development should occur, how high to build structures, and whether to buy flood insurance. Source: Jacinta Quesada/FEMA. 129 The Domino Effect: The Future of Quantifying Compounding Events in Deltas question the accuracy of current also allows scientists to overcome to the key drivers or variables in flood mapping approaches. difficulties in measuring hazards the system. Development of more across different scales and integrated risk models to assess This focus on impacts on disciplines. combined impacts is required. stakeholders also suggests the importance of local knowledge Information about natural hazard for hazard assessment. Early Conclusions and interactions and the attribution participation by local stakeholders Looking Forward of societal impacts to multiple makes it possible to identify which hazards is still limited. This is real-world events (e.g., floods, fires, Scientists and consultants are first of all due to the fact that failed infrastructure) cause societal accustomed to identifying risks databases of natural hazard events disruption. Communities exposed in a single causal way. We tend to generally attribute damages to the to multiple natural hazards may start with a typical model cascade primary hazard, while secondary already be dealing with interacting and evaluate the direct impacts hazards may in fact cause equally hazards, and therefore their insight of a single hazard. Hydrologists, large impacts. For example, the and experience can help inform for example, may start with major earthquake in Christchurch, future research. As the magnitudes meteorological data, feeding into New Zealand, triggered large-scale by which we measure impacts can hydrological models, hydraulic liquefaction, and this liquefaction be equal across all disciplines, such models, and consequently impact caused about 50 percent of the a bottom-up approach to assessing models. Significant advances have total damage—but most databases multihazard risk can make future been made toward developing record these losses as due to interdisciplinary risk modeling more probabilistic approaches to the primary earthquake event. successful. We advocate that the hazard assessment, but further To support the assessment of research community take this advances are necessary if we probabilities, we should begin by stakeholder-centered approach wish to address the interactions describing disasters in terms of to defining probabilistic event between, and compounding effects their impacts and associate these sets based on their impacts. As of, multiple natural hazards. The with the full set of natural hazards it becomes increasingly apparent starting point should be a dialogue that occurred. Guidelines and that the most devastating “events” between local stakeholders principles on how to do this need are a function of multiple hazards and experts about the impacts to be further developed in the occurring in sequence (by triggering that lead to societal disruption. years to come. or aggravation), studying cascading These local impacts could be natural hazards will become an very different for different stakeholders, and are highly References interdisciplinary field. dependent on the local context UNISDR (United Nations International One challenge presented by and system properties. This Strategy for Disaster Reduction). 2015. Sendai Framework for Disaster Risk this approach is communicating dialogue should reveal which real- Reduction 2015–2030. Geneva: UNISDR. ht multihazard risk to end-users. We world events have the strongest tp://?www.?wcdrr.?org/?uploads/?Sendai_? Framework_?for_?Disaster_?Risk_?Reducti believe that focusing on direct real- societal impacts, and which on_?2015-2030.?pdf, 2015. world impacts (e.g., loss of life, failed models and data are required to infrastructure, impeded economy) investigate these. A check on the Van den Hurk, B., E. van Meijgaard, P. de Valk, K.-J. van Heeringen, and J. Gooijer. as a result of multihazards is key robustness of a multihazard risk 2015. “Analysis of a Compounding Surge to communicating multihazard assessment should be applied by and Precipitation Event in the Netherlands.” Environmental Research Letters 10, risk to the end-user. As already testing the sensitivity of impacts no. 3: 035001. doi:10.1088/1748- noted, focusing on the end impact to smaller or larger perturbations 9326/10/3/035001. 130 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment The starting point should be a dialogue between local stakeholders and experts about the impacts that lead to societal disruption. 131 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment Understanding Risk Is Essential for the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030: Targeting the Future with Science and Technology Virginia Murray, UNISDR Scientific and Technical Advisory Group (STAG) and Public Health England (PHE) H. E. Musa Ecweru, Minister of Relief, Disaster Preparedness and Refugees, Office of the Prime Minister, Uganda Daniele Ehrlich, European Commission Joint Research Centre Alastair Norris, Risk Management Solutions Introduction and by implementation of the l Priority 1: Understanding Background framework, based in part on the disaster risk outcome of the UNISDR (United l Priority 2: Strengthening The Sendai Framework for Nations Office for Disaster disaster risk governance to Disaster Risk Reduction 2015– Risk Reduction) Science and manage disaster risk 2030 was adopted by 187 United Technology Conference on the Nations (UN) member states in Implementation of the Sendai l Priority 3: Investing in disaster March 2015 and was endorsed Framework for Disaster Risk risk reduction for resilience by the UN General Assembly in Reduction 2015–2030,1 held in l Priority 4: Enhancing disaster June 2015. The main outcome January 2016, and on the launch preparedness for effective of the Sendai Framework is “the of the UNISDR Science and response and to “Build substantial reduction of disaster Technology Partnership and the Back Better” in recovery, risk and losses in lives, livelihoods Science and Technology Road Map rehabilitation and reconstruction and health and in the economic, to 2030. The UNISDR Science (UNISDR 2015). physical, social, cultural and and Technology partnership environmental assets of persons, will focus on the need for businesses, communities and local, national, regional, and Case Studies countries” (UNISDR 2015). international collaboration and on the four priorities identified in the National: How Uganda Has The discussion below describes framework: Domesticated the Sendai some of the work being done Framework 1 under the Sendai Framework. Information about the conference Since the Hyogo Framework is available at http://www.unisdr. It also highlights the challenges org/partners/academia-research/ for Action 2005–2015 was first and opportunities presented conference/2016/. endorsed, Uganda’s National 133 Understanding Risk Is Essential for the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030 Platform for Disaster Risk Figure 1. Map showing drought vulnerability of populations Reduction has been fine-tuned in different parts of Uganda and made more robust, in part by increasing the diversity of stakeholders to include decision makers, professionals, scientists, and members of the private sector. More generally, Uganda has acted to improve disaster preparedness and mitigate disaster risk in a number of ways: l The National Policy for Disaster Preparedness and Management has been undergoing continuous review since 2011 to ensure alignment to the Sendai Framework, and it will soon be developed into an Act of Parliament. l With the support of the United Nations Development Programme, Uganda has mapped hazard, risk, and vulnerability within the country. Drought, one of the most common hazards in Uganda (see figure 1), has been a particular focus of these efforts. Drought risk for the Karamoja subregion has been mapped according to severity, allowing interventions and Source: © Department of Relief, Disaster Preparedness and Management, Office of the Prime Minister, Uganda. Used with permission; further permission required for reuse. resources to be directed toward the most vulnerable. Cash interventions for vulnerable of Meteorology has been respond to infectious disease individuals have been designed reconstituted as the Uganda outbreaks. The minister by the World Bank. National Meteorological anticipates the establishment of Authority, with new investments a new Parliament for Disaster l In 2014, Uganda launched in scientists, procurement, and Risk Reduction, which would the National Emergency technology, and is becoming require the input of scientists Coordination and Operations a focal institution for the and diverse experts. Centre, which aims to provide Intergovernmental Panel on early warning information, carry Climate Change. Challenges in addressing out modeling and forecasting, l The Ministry of Health has disaster risk still persist, such and coordinate emergency improved its capacity and as inadequate dissemination of response. The Department manpower to monitor and weather forecast information to 134 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment stakeholders, decentralization Figure 2. Expected outcomes of the DRMKC of disaster preparedness and response to local authorities, and lack of investment in science and technology to deliver risk assessments to local end-users. But there has also been notable progress, seen in the development of contingency funding to those most at risk, and in the establishment of partnerships with the wider global scientific community to ensure science is useful, usable, and used. Regional: Disaster Risk Management Knowledge Centre The Disaster Risk Management Knowledge Centre (DRMKC) is a Source: Joint Research Centre of the European Commission. European Commission initiative to improve the science and modeling, which is outlined by improvement of local capacity policy interface in the area of Priority 1 under the Sendai and development of national disaster risk reduction. Launched Framework, is evident in the work and regional risk data and risk in September 2015, the DRMKC of Risk Management Solutions platforms. is founded on three pillars— (RMS).2 RMS uses a catastrophe partnership, knowledge, and modeling framework to perform innovation—and works under estimates on losses due to a Challenges six expected outcomes (shown catastrophic event. The RMS There are a number of challenges in figure 2), mainly to improve modeling framework includes five that face countries as they seek to communication between policy modules: exposure, event, hazard, implement the Sendai Framework: makers and scientists and offer vulnerability, and financial analysis. European Union countries Currently, the framework is mostly l One of the biggest challenges scientific and technical advice. used in the insurance industry, is increasing policy makers’ but RMS anticipates an expansion awareness of scientific, The DRMKC makes all its data in which high- and middle-income technological, and industrial and publications public, and invites governments use it to better plan knowledge and skills. all interested parties to submit resources and infrastructure for Partnerships between policy events, research project results, imminent hazards. In the further makers and the scientific and success case studies to build up future, RMS hopes to engage community should provide its library. More details can be found governments to develop their opportunities for increasing at http://drmkc.jrc.ec.europa.eu/. own models that best suit their access to information. individual needs. However, such l While the Hyogo Framework for International: The Role for expansions would require the Action focused on processes, Risk Modeling the constructed indicators did 2 For more information, see the RMS The important role of risk website at http://www.rms.com/. not lead to the achievement of 135 Understanding Risk Is Essential for the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030 goals. To ensure that the goals storage, and dissemination of interface for effective of the Sendai Framework are disaster loss data. With the help decision making in disaster risk met, research must be targeted of organizations such as the management. and scientists must work with DRMKC, some of the project’s l Engaging industry. Industry has policy makers toward the same work can be shared more widely. solved many of the challenges goals. Instead of focusing l Hazard-prone and vulnerable faced today by the public on hazards and emergency island states face particular sector, and it can provide a response as in the past, the challenges in reducing disaster valuable source of expertise scientific community should risk. They may be omitted and knowledge for successfully adopt an integrated approach from global tools, and because implementing the Sendai and undertake all-hazards of financial constraints have Framework.  The insurance research. This change could difficulty collaborating with like industry, for example, operates lead to integrated policy making countries. on the basis of its ability to Although each country may be different, the global community must work together; scientists’ research and outputs can help to support this approach. measure and manage risk, and focused on risk; Mozambique, for Recommendations similar methods could be applied example, instituted a dramatic more broadly for disaster risk change in approach in moving Implementation of the Sendai reduction. from the Hyogo Framework Framework can be furthered by for Action to the Sendai the following: l Engaging the young. Children Framework. are the owners of the future l National leadership and regional and should understand a little l Standardizing disaster data collaboration. One of the about disaster risk reduction around the world, which keys to success in the swift and management before would considerably benefit implementation of the Sendai they assume positions of implementation of the Sendai Framework is identifying responsibility. To ensure they Framework, remains a challenge. national leaders who will involve have the necessary knowledge, Projects are under way to a wide range of stakeholders in interactive workshops about address this challenge, including planning actions. These leaders disaster risk reduction can be the Integrated Research on should partake in regional and incorporated into the school Disaster Risk project, which is global partnerships to address curriculum. Young people should sponsored by the International cross-border issues, establish also be educated about local Council for Science, the global standards, exchange best hazards in order to build local International Social Science practices, and benefit from capacity and enable them to Council, and the United Nations pooled resources. work in an all-hazards approach. International Strategy for Disaster Reduction. This project l Integrated research. It aims to provide a forum for is important to promote information dissemination, and improve dialogue and Conclusions networking, and collaboration cooperation among scientific As countries seek to implement for the growing number of and technological communities, the Sendai Framework, the stakeholders from different other relevant stakeholders, following should be kept in mind: disciplines and sectors who study and policy makers in order issues related to the collection, to facilitate a science-policy l Although each country may be 136 Proceedings from the 2016 UR Forum The Future of Risk and Risk Assessment different, the global community l To improve collaboration, an must work together; scientists’ all-hazard approach—and the Session Contributors* research and outputs can help rejection of the term “natural H.E. Musa Ecweru, Ugandan to support this approach. disasters”—could be useful. Directorate of Relief, Disaster Preparedness and Refugees l Establishment of knowledge Daniele Ehrlich, European centers should facilitate Reference Commission Joint Research the periodic review of what Centre knowledge is available and what UNISDR (United Nations Office for Disaster Risk Reduction). 2015. Sendai Framework Alastair Norris, RMS knowledge gaps persist. Centers for Disaster Risk Reduction 2015–2030. should also support open access, Geneva: UNISDR. http://www.unisdr.org/ Organizers multihazard data platforms, and files/43291_sendaiframeworkfordrren.pdf. Thomas Kemper, European standardized approaches and Commission Joint Research tools for mapping and using data Centre and scenarios. Virginia Murray, UNISDR STAG/ PHE Chadia Wannous, UNISDR * Additional thanks are due to Catherine Ahimbisibwe, Department of Relief, Disaster Preparedness and Management, Kampala, Uganda; and Tiffany Yeung, PHE/Hong Kong Jockey Club Disaster Preparedness and Response Institute. 137 Francis Ghesquiere, Alanna Simpson, Emma Phillips, Joaquin Toro, Simone Balog, Julie Aaserud, Gianumberto Accinelli, Jamais Cascio, Fabrizio Curcio, Ermelinda Damiano, Laura Frigenti, Francis Ghesquiere, Polly Morland, John Roome, Pablo Suarez, Laura Tuck, Dareen Abughaida, Esther Baur, Stephen Briggs, Marianne Fay, Prema Gopalan, Claus Haugaard Sørensen, Kerri-Ann Jones, Jemilah Mahmood, Maite Rodriguez, Sheryl Sandberg (remotely), Anna Wellenstein, Benedict Allen, Misha Glenny, Francesco da Mosto, Jane da Mosto, Marcus du Sautoy, Amal Ali, Vica Rosario Bogaerts, Nama Budhathoki, Lorenzo Carrera, Pietro Ceccato, Daniel Clarke, Fernando Ramirez Cortes, Erin Coughlan, Lydia Cumiskey, Luigi D’Angelo, Paul Davies, Vivien Deparday, Mauro Dolce, Ron Eguchi, Pete Epanchin, Carina Fonseca Ferreira, Stu Fraser, Darcy Gallucio, Lisa Goddard, Lou Gritzo, Maryam Golnaraghi, Mark Harvey, Thomas Kemper, Randolph Kent, Andrew Kruczkiewicz, David Lallemant, Jennifer LeClerc, Olivier Mahul, Rick Murnane, Virginia Murray, Jaroslav Mysiak, Sophia Nikolaou, C. Dionisio Perez-Blanco, Angelika Planitz, Lisa Robinson, Tom Roche, Roberto Rudari, Peter Salamon, John Schneider, Rajesh Sharma, Robert Soden, Frederiek Sperna Weiland, Pablo Suarez, Andy Thompson, Andrew Thow, Emma Visman, Chadia Wannous, Philip J. Ward, Hessel Winsemius, Jianping Yan, Tahir Akbar, Elizabeth Alonso-Hallifax, Ghadeer Ashram, Jorge Barbosa, Sofia Bettencourt, Jack Campbell, Naraya Carrasco, Manuela Chiapparino, James Close, Rossella Della Monica, Vivien Deparday, Nicolas Desramaut, Tafadzwa Dube, Marc Forni, Stu Fraser, Tayler Friar, Habiba Gitay, Alistair Holbrook, Nicholas Jones, Brenden Jongman, Keiko Kaneda, Elif Kiratli, David Lallemant, Sonia Luthra, Henriette Mampuya, Rick Murnane, James Newman, Cristina Otano, Shaela Rahman, Sumati Rajput, Cindy Quijada Robles, Keiko Saito, Robert Soden, Luis Tineo, Vladimir Tsirkunov, Jon Walton, Stephan Zimmermann, Alan D’Inca’, Miki Fernández, Anne Mussotter, Andrea Dadda, Luca Domenicucci, Jimmy Ennis, Marcella Leonetti, Antonio Montanari, Luigi Tortato, Desy Adiati, Regianne Bertolassi, Anne Himmelfarb, Francis Ghesquiere, Alanna Simpson, Emma Phillips, Joaquin Toro, Simone Balog, Julie Aaserud, Gianumberto Accinelli, Jamais Cascio, Fabrizio Curcio, Ermelinda Damiano, Laura Frigenti, Francis Ghesquiere, Polly Morland, John Roome, Pablo Suarez, Laura Tuck, Dareen Abughaida, Esther Baur, Stephen Briggs, Marianne Fay, Prema Gopalan, Claus Haugaard Sørensen, Kerri-Ann Jones, Jemilah Mahmood, Maite Rodriguez, Sheryl Sandberg (remotely), Anna Wellenstein, Benedict Allen, Misha Glenny, Francesco da Mosto, Jane da Mosto, Marcus du Sautoy, Amal Ali, Vica Rosario Bogaerts, Nama Budhathoki, Lorenzo Carrera, Pietro Ceccato, Daniel Clarke, Fernando Ramirez Cortes, Erin Coughlan, Lydia Cumiskey, Luigi D’Angelo, Paul Davies, Vivien Deparday, Mauro Dolce, Ron Eguchi, Pete Epanchin, Carina Fonseca Ferreira, Stu Fraser, Darcy Gallucio, Lisa Goddard, Lou Gritzo, Maryam Golnaraghi, Mark Harvey, Thomas Kemper, Randolph Kent, Andrew Kruczkiewicz, David Lallemant, Jennifer LeClerc, Olivier Mahul, Rick Murnane, Virginia Murray, Jaroslav Mysiak, Sophia Nikolaou, C. Dionisio Perez-Blanco, Angelika Planitz, Lisa Robinson, Tom Roche, Roberto Rudari, Peter Salamon, John Schneider, Rajesh Sharma, Robert Soden, Frederiek Sperna Weiland, Pablo Suarez, Andy Thompson, Andrew Thow, Emma Visman, Chadia Wannous, Philip J. Ward, Hessel Winsemius, Jianping Yan, Tahir Akbar, Elizabeth Alonso-Hallifax, Ghadeer Ashram, Jorge Barbosa, Sofia Bettencourt, Jack Campbell, Naraya Carrasco, Manuela Chiapparino, James Close, Rossella Della Monica, Vivien Deparday, Nicolas Desramaut, Tafadzwa Dube, Marc Forni, Stu Fraser, Tayler Friar, Habiba Gitay, Alistair Holbrook, Nicholas Jones, Brenden Jongman, Keiko Kaneda, Elif Kiratli, David Lallemant, Sonia Luthra, Henriette Mampuya, Rick Murnane, James Newman, Cristina Otano, Shaela Rahman, Sumati Rajput, Cindy Quijada Robles, Keiko Saito, Robert Soden, Luis Tineo, Vladimir Tsirkunov, Jon Walton, Stephan Zimmermann, Alan D’Inca’, Miki Fernández, Anne Mussotter, Andrea Dadda, Luca Domenicucci, Jimmy Ennis, Marcella Leonetti, Antonio Montanari, Luigi Tortato, Desy Adiati, Regianne Bertolassi, Anne Himmelfarb, Francis Ghesquiere, Alanna Simpson, Emma Phillips, Joaquin Toro, Simone Balog, Julie Aaserud, Gianumberto Accinelli, Jamais Cascio, Fabrizio Curcio, Ermelinda Damiano, Laura Frigenti, Francis Ghesquiere, Polly Morland, John Roome, Pablo Suarez, Laura Tuck, Dareen Abughaida, Esther Baur, Stephen Briggs, Marianne Fay, Prema Gopalan, Claus Haugaard Sørensen, Kerri-Ann Jones, Jemilah Mahmood, Maite Rodriguez, Sheryl Sandberg (remotely), Anna Wellenstein, Benedict Allen, Misha Glenny, Francesco da Mosto, Jane da Mosto, Marcus du Sautoy, Amal Ali, Vica Rosario Bogaerts, Nama Budhathoki, Lorenzo Carrera, Pietro Ceccato, Daniel Clarke, Fernando Ramirez Cortes, Erin Coughlan, Lydia Cumiskey, Luigi D’Angelo, Paul Davies, Vivien Deparday, Mauro Dolce, Ron Eguchi, Pete Epanchin, Carina Fonseca Ferreira, Stu Fraser, Darcy Gallucio, Lisa Goddard, Lou Gritzo, Maryam Golnaraghi, Mark Harvey, Thomas Kemper, Randolph Kent, Andrew Kruczkiewicz, David Lallemant, Jennifer LeClerc, Olivier Mahul, Rick Murnane, Virginia Murray, Jaroslav Mysiak, Sophia Nikolaou, C. Dionisio Perez-Blanco, Angelika Planitz, Lisa Robinson, Tom Roche, Roberto Rudari, Peter Salamon, John Schneider, Rajesh Sharma, Robert Soden, Frederiek Sperna Weiland, Pablo Suarez, Andy Thompson, Andrew Thow, Emma Visman, Chadia Wannous, Philip J. Ward, Hessel Winsemius, Jianping Yan, Tahir Akbar, Elizabeth Alonso-Hallifax, Ghadeer Ashram, Jorge Barbosa, Sofia Bettencourt, Jack Campbell, Naraya Carrasco, Manuela Chiapparino, James Close, Rossella Della Monica, Vivien Deparday, Nicolas Desramaut, Tafadzwa Dube, Marc Forni, Stu Fraser, Tayler Friar, Habiba Gitay, Alistair Holbrook, Nicholas Jones, Brenden Jongman, Keiko Kaneda, Elif Kiratli, David Lallemant, Sonia Luthra, Henriette Mampuya, Rick Murnane, James Newman, Cristina Otano, Shaela Rahman, Sumati Rajput, Cindy Quijada Robles, Keiko Saito, Robert Soden, Luis Tineo, Vladimir Tsirkunov, Jon Walton, Stephan Zimmermann, Alan D’Inca’, Miki Fernández, Anne Mussotter, Andrea Dadda, Luca Domenicucci, Jimmy Ennis, Marcella Leonetti, Antonio Montanari, Luigi Tortato, Desy Adiati, Regianne Bertolassi, Anne Himmelfarb,Francis Ghesquiere, Alanna Simpson, Emma Phillips, Joaquin Toro, Simone Balog, Julie Aaserud, Gianumberto Accinelli, Jamais Cascio, Fabrizio Curcio, Ermelinda Damiano, Laura Frigenti, Francis Ghesquiere, Polly Morland, John Roome, Pablo Suarez, Laura Tuck, Dareen Abughaida Thank YO See you in 2018! Understanding Risk (UR) is a global community of over 6,500 experts and practitioners in the field of disaster risk assessment and risk communication. This vibrant community—a diverse group of people from the private, public, nonprofit, technology, nongovernmental, and financial sectors—meets at the UR Forum every two years. Each iteration of the UR Forum has produced new ideas and partnerships that have improved risk assessments and helped to integrate them into policy making and development planning. This publication captures the experiences, lessons, and best practices in the field discussed at the fourth UR Forum, held in Venice, Italy, from May 16 to May 20, 2016. “The key to good disaster and climate risk management is a better understanding of the risks we need to manage. It was fantastic to see a global cross-section of the risk community come together in Venice to advance the innovations and best practices that will facilitate informed decision making and help increase countries’ resilience now and into the future. UR2016 was an inspiring and engaging event that will be remembered for years to come.” —Laura Tuck, Vice President for Sustainable Development, World Bank Group “It was an honor to welcome the fourth Understanding Risk global forum to Venice, Italy. We saw a dynamic group of individuals and organizations that are key to advancing resilience in cities and countries around the world. Congratulations on the success of this year’s forum!” —Letizia Fischioni, Legal Advisor, Italian Agency for Development Cooperation “The opportunity that the Understanding Risk Forum provides is instrumental in forming new contacts outside my field. These contacts will help us serve our clients and better manage their disaster and climate risk. It was a delight to be a part of an exciting event like UR2016.” —Esther Baur, Director, Global Partnerships, Swiss Re “Through the Understanding Risk community, I have met over a dozen people and organizations that I later collaborated with. We have bid on projects together, developed new ideas for the evolution of risk management tools, created geographic partnerships, and replicated and scaled projects. UR events are an efficient means to meet with a broad network of disaster risk management users and practitioners.” —Andrew Eddy, President and Chief Executive Officer, Athena Global “The participants in the conference came from a fascinating variety of backgrounds in science, policy, the insurance industry, emerging economies, and many others. Discussion of the contribution of space observation to understanding risk had a receptive and lively audience—the connections and contacts I made have already been followed up in my work and will contribute to greater innovation in the future. Thank you for the opportunity to be a part!” —Stephen Briggs, Senior Adviser for Earth Observation, European Space Agency; and Chairman, Global Climate Observing System “Understanding Risk has helped expand the space of possibility in how we design and facilitate sessions and context for meetings. I would recommend this conference to others, as UR cares for the importance of informal interactions—fun, cool, vibrant events enable new friendships and trusted relationships.” —Pablo Suarez, Associate Director for Research and Innovation, Red Cross Red Crescent Climate Centre