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

被引:121
作者
Woodward, Michelle [1 ]
Kapelan, Zoran [2 ]
Gouldby, Ben [1 ]
机构
[1] HRWallingford, Wallingford OX10 8BA, Oxon, England
[2] Univ Exeter, Coll Engn Math & Phys Sci, Exeter EX4 4QF, Devon, England
基金
英国工程与自然科学研究理事会;
关键词
Decision tree analysis; economics; flood risk management; multiobjective optimization; real options; ROBUST OPTIMIZATION; SENSOR PLACEMENT; THAMES ESTUARY; ADAPTATION; METHODOLOGY; STRATEGIES; DESIGN;
D O I
10.1111/risa.12088
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:75 / 92
页数:18
相关论文
共 71 条
[1]   Are there social limits to adaptation to climate change? [J].
Adger, W. Neil ;
Dessai, Suraje ;
Goulden, Marisa ;
Hulme, Mike ;
Lorenzoni, Irene ;
Nelson, Donald R. ;
Naess, Lars Otto ;
Wolf, Johanna ;
Wreford, Anita .
CLIMATIC CHANGE, 2009, 93 (3-4) :335-354
[2]  
Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2004.12.005, 10.1016/j.gloenvcha.2005.03.001]
[3]  
[Anonymous], 2000, P INT C PAR PROBL SO
[4]  
[Anonymous], 2009, Technical report
[5]  
[Anonymous], 2003, GREEN BOOK APPR EV C
[6]  
[Anonymous], FLOOD RISK MAN AM RI
[7]  
[Anonymous], 1996, RISK BAS AN FLOOD DA
[8]  
[Anonymous], 2010, Flood and Coastal Erosion Risk Management appraisal guidance
[9]   Flood risk assessment and associated uncertainty [J].
Apel, H ;
Thieken, AH ;
Merz, B ;
Blöschl, G .
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2004, 4 (02) :295-308
[10]   Stochastic sampling design using a multi-objective genetic algorithm and adaptive neural networks [J].
Behzadian, Kourosh ;
Kapelan, Zoran ;
Savic, Dragan ;
Ardeshir, Abdollah .
ENVIRONMENTAL MODELLING & SOFTWARE, 2009, 24 (04) :530-541