Results and Discussion Acknowledgements and Main References EGU2017-1880. A.295 wadi lab water-adaptive design & innovation lab Adaptation to Hydrological Extremes through Insurance: a Financial Fund Simulation Model under Changing Scenarios Diego A. Guzmán Arias a-b, Guilherme Mohor a, Clarissa Câmara a & Eduardo Mario Mendiondo a a Universidade de São Paulo, Escola de Engenharia São Carlos, Brazil. diego.guzman@usp.br, Clarissa.câmara@outlook.com, guisamor@gmail.com, emm@sc.usp.br b Pontificia Bolivariana University. Bucaramanga, Colombia. diego.guzman@upb.edu.co Introduction The methodology estimates the optimized premium as a function of willingness to pay (WTP) and the potential direct loss derived from hydrological risk. The proposed HRTM structures the watershed insurance scheme in three modules (Fig.3). First, the hazard module, which characterizes the hydrologic threat from the recorded or modelled input series under IPCC / RCM's generated scenarios. Second, the vulnerability module calculates the potential economic loss for each sector evaluated as a function of the return period "TR". Finally, the finance module determines the value of the optimal aggregate premium (Fig. 4), under intensive Monte Carlo’s simulation runs, by evaluating equiprobable scenarios of water vulnerability, using complementary HRTM variables: the maximum limit of coverage, deductible, reinsurance schemes, and incentives for risk reduction. Researches from around the world relate global environmental changes with the increase of vulnerability to extreme events, such as heavy and scarce precipitations, floods and droughts. Hydrological disasters have caused increasing losses in recent years. Thus, risk transfer mechanisms, i.e. insurance, are being implemented to: mitigate impacts, finance the recovery of affected population, and promote the reduction of hydrological risks. However, among the main problems in implementing these strategies, there are: first, the partial knowledge of natural and anthropogenic climate change in terms of intensity and frequency; second, efficient risk reduction policies require accurate risk assessment, with careful consideration of costs, and third, the uncertainty associated with numerical models and input data used. Figure 3. Overview of modules integrated by the proposed hydrological risk transfer model (HRTM) as adaptation option to hydrological extremes. Fig. 1. Upper Chart: Drought Cantareira System 2013/15 (~9 million affected, adapted from SABESP 2016) Lower chart: Sao Carlos city, SP, urban floods, showing storm event in 22 Nov., 2015 Results and Discussion The HRTM is being tested by members of the Integrated Group of River Basins (NIBH) and the new Water-Adaptive Design & Innovation Lab (WADI Lab), at São Carlos School of Engineering (EESC), University of São Paulo (USP), Brazil. On the one hand, HRTM presents adaptation options, as a non-structural measure, for management and planning. Thus, HRTM’s insurance funds simulate how to mitigate the impacts of hydrological extremes, like droughts and floods. On the other hand, the actual HRTM’s architecture is as friendly as flexible to elicit socio-economic information from INCT-water security case-studies at challenging biomes. For the South American context, a sequence of HRTM’s academic applications are being developed. Novel simulations, by coupling climate-hydrology-economy models under a diverse menu of stakeholder’ demands or markets, do bring new science questions to be shared with other similar worldwide initiatives. Methodology The objective of this work is to introduce and discuss the feasibility of the application of Hydrological Risk Transfer Models (HRTMs) as a strategy of adaptation to global climate change. The proposal addresses the development of a methodology for a collective and multi-sector vulnerability management, facing the hydrological risk in the long term, under an insurance funds simulator (Fig.2) Fig 4. Example of time-based scenarios of HRTM’s analysis and evaluation Acknowledgements and Main References 𝑭𝒑 𝒙 = 𝑨𝒗𝒈 𝑫 𝒙(𝑭,𝑫 ∗ 𝟏− 𝟏 𝑻 𝑹(𝑭,𝑫 𝒏 The authors would like to express their thanks for to the Administrative Department of Science, Technology and Innovation (COLCIENCIAS) Doctoral Program Abroad –Colombia; also to the Coordination for the Improvement of Higher Education Personnel (CAPES Foundation-PROEX) – Brazil; São Paulo Research Foundation (FAPESP) for the grant #2014/15080-2, and the National Council for Scientific and Technological Development (CNPq-GD) – Brazil and CNPq + FAPESP, INCT-II Project National Institute of Science and Technology in Climate Change, Water Safety Component (2016-2020). Botzen, J.W. (2013). Managing Extreme Climate Change Risk through Insurance. United Kingdom Cambridge University Press; 1 edition. Guzmán, D., Estrada, C., Freitas, C., Mohor, G., Mendiondo, E., & Salcedo, D. (2015). Rethinking Latin American resilient habitats to cope with water security through hydrologic risk transfer models. In RESURBE II. September 25/15 Bogotá-CO. Guzmán, D. Mohor, G., Câmara, C., Rosa, A. and Mendiondo, E. (2015). Water Risks Transfer as Adaptation and Planning Tool. Poster presentation at: International conference on water, megacities and global change Conférence international Eau, mégapoles et changement global UNESCO HQ - Paris - 1-4 December. Kunreuther, H., Pauly, M., McMorrow, S. (2013). Insurance Behavioral Economics: Improving Decisions in the Most Misunderstood Industry. New York. Cambridge University Press; 1 edition Salas, J., Obeysekera, J. (2014). “Revisiting the Concepts of Return Period and Risk for Nonstationary Hydrologic Extreme Events”, Journal of Hydrologic Engineering, 19(3), pp.554–568. Figure 2. Example of the HRTM approach using Avg Dx(F, D) as the average damage of flood and droughts at the “x” watershed from the equiprobable scenarios