Adaptive Flood Risk Management Under Climate Change Uncertainty Using Real Options and Optimization

It is well recognized that adaptive and flexible flood risk strategies are required to account for future uncertainties. Development of such strategies is, however, a challenge. Climate change alone is a significant complication, but, in addition, complexities exist trying to identify the most appropriate set of mitigation measures, or interventions. There are a range of economic and environmental performance measures that require consideration, and the spatial and temporal aspects of evaluating the performance of these is complex. All these elements pose severe difficulties to decisionmakers. This article describes a decision support methodology that has the capability to assess the most appropriate set of interventions to make in a flood system and the opportune time to make these interventions, given the future uncertainties. The flood risk strategies have been explicitly designed to allow for flexible adaptive measures by capturing the concepts of real options and multiobjective optimization to evaluate potential flood risk management opportunities. A state-of-the-art flood risk analysis tool is employed to evaluate the risk associated to each strategy over future points in time and a multiobjective genetic algorithm is utilized to search for the optimal adaptive strategies. The modeling system has been applied to a reach on the Thames Estuary (London, England), and initial results show the inclusion of flexibility is advantageous, while the outputs provide decisionmakers with supplementary knowledge that previously has not been considered.

[1]  Kourosh Behzadian,et al.  Stochastic sampling design using a multi-objective genetic algorithm and adaptive neural networks , 2009, Environ. Model. Softw..

[2]  Tao Wang,et al.  Real Options by Spreadsheet: Parking Garage Case Example , 2006 .

[3]  Stephen P. Boyd,et al.  Extending Scope of Robust Optimization: Comprehensive Robust Counterparts of Uncertain Problems , 2006, Math. Program..

[4]  Zoran Kapelan,et al.  Risk-Based Sensor Placement for Contaminant Detection in Water Distribution Systems , 2010 .

[5]  Bernhard Sendhoff,et al.  Robust Optimization - A Comprehensive Survey , 2007 .

[6]  T. Copeland Real Options: A Practitioner's Guide , 2001 .

[7]  R. Lempert,et al.  Identifying and evaluating robust adaptive policy responses to climate change for water management agencies in the American west , 2010 .

[8]  Moshe Sniedovich,et al.  A classical decision theoretic perspective on worst-case analysis , 2011 .

[9]  M. Schlesinger,et al.  When we don't know the costs or the benefits: Adaptive strategies for abating climate change , 1997 .

[10]  Ben Gouldby,et al.  An automated method for costing flood risk mitigation measures for use with flood risk management decision support systems , 2012 .

[11]  Tao Wang,et al.  Building Real Options into Physical Systems with Stochastic Mixed-Integer Programming , 2005 .

[12]  Dragan Savic,et al.  Genetic Algorithms for Least-Cost Design of Water Distribution Networks , 1997 .

[13]  Paul Sayers,et al.  Representing fragility of flood and coastal defences: Getting into the detail , 2008 .

[14]  Zoran Kapelan,et al.  Multiobjective sampling design for water distribution model calibration , 2003 .

[15]  Zoran Kapelan,et al.  SLOTS: Effective Algorithm for Sensor Placement in Water Distribution Systems , 2010 .

[16]  Sarah Lavery,et al.  Flood risk management in the Thames Estuary looking ahead 100 years , 2005, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[17]  F. Black,et al.  The Pricing of Options and Corporate Liabilities , 1973, Journal of Political Economy.

[18]  D. S. Gill,et al.  Fluvial design guide , 2010 .

[19]  Matthew D. Collins,et al.  UK Climate Projections Science Report: Climate Change Projections , 2009 .

[20]  Berry Gersonius,et al.  Managing the flooding system's resiliency to climate change , 2010 .

[21]  Jim W. Hall,et al.  Decision making under severe uncertainties for flood risk management: a case study of info-gap robustness analysis , 2009 .

[22]  W. Adger,et al.  Successful adaptation to climate change across scales , 2005 .

[23]  Ben Gouldby,et al.  Multiobjective optimisation for improved management of flood risk , 2014 .

[24]  E. Prescott,et al.  Investment Under Uncertainty , 1971 .

[25]  Wolfgang Fischer,et al.  Climate change mitigation and adaptation , 2018, Environmental Performance Review: Bosnia and Herzegovina.

[26]  D. Dantzig Economic decision problems for flood prevention , 1956 .

[27]  David G. Groves,et al.  A General, Analytic Method for Generating Robust Strategies and Narrative Scenarios , 2006, Manag. Sci..

[28]  Leo Dobes,et al.  Getting Real about Adapting to Climate Change: Using 'Real Options' to Address the Uncertainties , 2008 .

[29]  Eduardo S. Schwartz,et al.  Real Options and Investment under Uncertainty: Classical Readings and Recent Contributions , 2004 .

[30]  R. Stouffer,et al.  Stationarity Is Dead: Whither Water Management? , 2008, Science.

[31]  S. Ross,et al.  Option pricing: A simplified approach☆ , 1979 .

[32]  Simon Dietz,et al.  Adaptation in the UK: a decision-making process , 2010 .

[33]  R. Dawson,et al.  Plausible responses to the threat of rapid sea-level rise in the Thames Estuary , 2008 .

[34]  Richard Washington,et al.  Issues in the interpretation of climate model ensembles to inform decisions , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[35]  R. McDonald,et al.  The Value of Waiting to Invest , 1982 .

[36]  A. Wald Statistical Decision Functions Which Minimize the Maximum Risk , 1945 .

[37]  M.J.P. Mens,et al.  Long-term strategies for flood risk management: Scenario definition and strategic alternative design , 2008 .

[38]  Stephane Hallegatte,et al.  Strategies to adapt to an uncertain climate change , 2008 .

[39]  Y. Ben-Haim Doing Our Best: Optimization and the Management of Risk , 2012, Risk analysis : an official publication of the Society for Risk Analysis.

[40]  Kalyanmoy Deb,et al.  A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II , 2000, PPSN.

[41]  R. C. Merton,et al.  AN INTERTEMPORAL CAPITAL ASSET PRICING MODEL , 1973 .

[42]  Chung-Li Tseng,et al.  Valuing Flexibility in Infrastructure Expansion , 2003 .

[43]  B. Gouldby,et al.  A methodology for regional-scale flood risk assessment , 2008 .

[44]  W. Adger,et al.  Are there social limits to adaptation to climate change? , 2009 .

[45]  A. Ingham,et al.  Climate change, mitigation and adaptation with uncertainty and learning , 2007 .

[46]  Zoran Kapelan,et al.  Real Options in flood risk management decision making , 2011 .

[47]  Nicholas S. Vonortas,et al.  THE VALUE OF FLEXIBILITY IN ADAPTING TO CLIMATE CHANGE: A REAL OPTIONS ANALYSIS OF INVESTMENTS IN COASTAL DEFENSE , 2012 .

[48]  D. vanDantzig,et al.  Economic decision problems for flood prevention , 1954 .

[49]  E. Evans,et al.  Foresight : future flooding : scientific summary : volume I : future risks and their drivers , 2004 .

[50]  Jim W. Hall,et al.  Fluvial flood risk management in a changing world , 2010 .

[51]  Paul D. Bates,et al.  Quantified Analysis of the Probability of Flooding in the Thames Estuary under Imaginable Worst-case Sea Level Rise Scenarios , 2005 .