CLIMRISK-RIVER: Accounting for local river flood risk in estimating the economic cost of climate change

Abstract This study aims to improve the estimates of the economic impacts of climate change by developing a river flood risk model CLIMRISK-RIVER and introducing it into an existing climate-economy integrated assessment model (IAM). It operates on a local scale and can project climate change-related river flood damage for various socioeconomic, climate and flood adaptation scenarios. Whereas other IAMs have relied on temperature as a climate change proxy, we show that precipitation is a key variable in projecting river flood damage. The way adaptation is accounted for in our flood damage functions has a large influence on the results, highlighting the relevance of modelling local level adaptation in IAMs. Results presented at different spatial scales demonstrate the relevance of river flood damage functions for estimating the economic impacts of climate change and allows for exploration of the spatial distribution of impacts through local estimates.

[1]  Joeri Rogelj,et al.  Science and policy characteristics of the Paris Agreement temperature goal , 2016 .

[2]  W. Nordhaus.  A Question of Balance: Weighing the Options on Global Warming Policies , 2008 .

[3]  H. Winsemius,et al.  Global-scale benefit–cost analysis of coastal flood adaptation to different flood risk drivers using structural measures , 2020, Natural Hazards and Earth System Sciences.

[4]  William D. Nordhaus,et al.  A Regional Dynamic General-Equilibrium Model of Alternative Climate-Change Strategies , 1996 .

[5]  W. Botzen,et al.  A global economic assessment of city policies to reduce climate change impacts , 2017 .

[6]  Alexander Teytelboym,et al.  A Third Wave in the Economics of Climate Change , 2015 .

[7]  N. Stern.  The Structure of Economic Modeling of the Potential Impacts of Climate Change: Grafting Gross Underestimation of Risk onto Already Narrow Science Models , 2013 .

[8]  Brian C. O'Neill,et al.  Regional, national, and spatially explicit scenarios of demographic and economic change based on SRES. Technol Forecast Soc Chang , 2007 .

[9]  Reto Knutti,et al.  The end of model democracy? , 2010 .

[10]  Elmar Kriegler,et al.  Future growth patterns of world regions – A GDP scenario approach , 2017 .

[11]  R. Tol.  The Economic Impacts of Climate Change , 2018, Review of Environmental Economics and Policy.

[12]  J. Eom,et al.  The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview , 2017 .

[13]  T. Wigley,et al.  Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration , 2011 .

[14]  Brenden Jongman,et al.  Assessing flood risk at the global scale: model setup, results, and sensitivity , 2013 .

[15]  H. Diaz,et al.  Urbanization: Its Detection and Effect in the United States Climate Record , 1988 .

[16]  Keywan Riahi,et al.  IMAGE and MESSAGE Scenarios Limiting GHG Concentration to Low Levels , 2008 .

[17]  Ben Bond-Lamberty,et al.  An open-access CMIP5 pattern library for temperature and precipitation: description and methodology , 2017 .

[18]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[19]  W. J. Shuttleworth,et al.  Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional Reference Crop Evaporation over Land during the Twentieth Century , 2011 .

[20]  William D. Nordhaus,et al.  Revisiting the social cost of carbon , 2017, Proceedings of the National Academy of Sciences.

[21]  T. Carter,et al.  Climate and socio-economic scenarios for climate change research and assessment: reconciling the new with the old , 2014, Climatic Change.

[22]  Delavane B. Diaz,et al.  Quantifying the economic risks of climate change , 2017 .

[23]  W. Botzen,et al.  The Economic Impacts of Natural Disasters: A Review of Models and Empirical Studies , 2019, Review of Environmental Economics and Policy.

[24]  Zbigniew W. Kundzewicz,et al.  Large floods in Europe, 1985–2009 , 2013 .

[25]  Jean Chateau,et al.  Long-term economic growth projections in the Shared Socioeconomic Pathways , 2017 .

[26]  Gerald Mills,et al.  Urban climatology: History, status and prospects , 2014 .

[27]  W. Nordhaus.  The 'DICE' Model: Background and Structure of a Dynamic Integrated Climate-Economy Model of the Economics of Global Warming , 1992 .

[28]  William D. Nordhaus,et al.  The Climate Casino , 2013 .

[29]  Richard S. J. Tol,et al.  AD-DICE: An Implementation of Adaptation in the DICE Mode , 2007 .

[30]  Jesus Crespo Cuaresma,et al.  Income projections for climate change research: A framework based on human capital dynamics , 2017 .

[31]  Minh Ha-Duong,et al.  Optimal growth with adaptation to climate change , 2013, Climatic Change.

[32]  K. Calvin,et al.  The RCP greenhouse gas concentrations and their extensions from 1765 to 2300 , 2011 .

[33]  Jeroen C. J. H. Aerts,et al.  FLOPROS: an evolving global database of flood protection standards , 2016 .

[34]  P. Bates,et al.  Usefulness and limitations of global flood risk models , 2015 .

[35]  Claudia Tebaldi,et al.  Pattern scaling: Its strengths and limitations, and an update on the latest model simulations , 2014, Climatic Change.

[36]  Valentina Bosetti,et al.  The WITCH Model: Structure, Baseline, Solutions , 2007 .

[37]  Reto Knutti,et al.  Risks of Model Weighting in Multimodel Climate Projections , 2010 .

[38]  J. Aerts,et al.  Declining vulnerability to river floods and the global benefits of adaptation , 2015, Proceedings of the National Academy of Sciences.

[39]  H. Winsemius,et al.  A framework for global river flood risk assessments , 2012 .

[40]  T. Oke.  City size and the urban heat island , 1973 .

[41]  B. Kravitz,et al.  Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models , 2016 .

[42]  Niels Drost,et al.  PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model , 2017, Geoscientific Model Development.

[43]  W. J. Wouter Botzen,et al.  A lower bound to the social cost of CO2 emissions. , 2014 .

[44]  Richard S. J. Tol,et al.  The Social Cost of Carbon , 2011 .

[45]  D. Vuuren,et al.  Global drivers of future river flood risk , 2016 .

[46]  Jeroen C. J. H. Aerts,et al.  A global framework for future costs and benefits of river-flood protection in urban areas , 2017, Nature Climate Change.