Beyond optimality: Multistakeholder robustness tradeoffs for regional water portfolio planning under deep uncertainty

Water Resources Research

Volumn 50, Issue 10, 2014, Pages 7692-7713

  Herman, Jonathan D ^a   Zeff, Harrison B ^b   Reed, Patrick M ^a   Characklis, Gregory W ^b  

^a Cornell University   (United States)

^b University of North Carolina at Chapel Hill   (United States)

Author keywords

many objective robust decision making; multistakeholder robustness tradeoffs; regional water portfolio management

Indexed keywords

CLIMATE CHANGE; COMMERCE; FINANCIAL DATA PROCESSING; INVESTMENTS; REGIONAL PLANNING; RISK ASSESSMENT; UNCERTAINTY ANALYSIS; WATER RESOURCES; WATER SUPPLY;

MATHEMATICAL CONCEPTS; MULTI-STAKEHOLDER; MULTIPLE STAKEHOLDERS; PORTFOLIO MANAGEMENTS; ROBUST DECISIONS; RULE INDUCTION METHODS; WATER RESOURCES PLANNING AND MANAGEMENTS; WATER SUPPLY PLANNING;

DECISION MAKING;

DECISION MAKING; ECONOMIC ANALYSIS; REGIONAL PLANNING; STAKEHOLDER; TRADE-OFF; UNCERTAINTY ANALYSIS; VULNERABILITY; WATER DEMAND; WATER PLANNING; WATER RESOURCE;

NORTH CAROLINA; UNITED STATES;

EID: 84911408081     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/2014WR015338     Document Type: Article

References (73)

1. Bankes, S. C., (2002), Tools and techniques for developing policies for complex and uncertain systems, Proc. Natl. Acad. Sci. U. S. A., 99 (Suppl 3), 7263-7266.
2. Bankes, S. C., R. J. Lempert, and, S. W. Popper, (2001), Computer-assisted reasoning, Comput. Sci. Eng., 3 (2), 71-77.
3. Ben-Haim, Y., (2004), Uncertainty, probability and information-gaps, Reliab. Eng. Syst. Safety, 85 (1), 249-266.
4. Brill, E. D., (1979), The use of optimization models in public-sector planning, Manage. Sci., 25 (5), 413-422.
5. Brown, C., and, M. Carriquiry, (2007), Managing hydroclimatological risk to water supply with option contracts and reservoir index insurance, Water Resour. Res., 43, W11423, doi: 10.1029/2007WR006093.
6. Brown, C., Y. Ghile, M. Laverty, and, K. Li, (2012), Decision Scaling: Linking bottom-up vulnerability analysis with climate projections in the water sector, Water Resour. Res., 48, W09537, doi: 10.1029/2011WR011212.
7. Bryant, B. P., (2009), sdtoolkit: Scenario Discovery Tools to Support Robust Decision Making, R package, Version 2.31. [Available at http://cran.r-project.org/web/packages/sdtoolkit/index.html.]
8. Bryant, B. P., and, R. J. Lempert, (2010), Thinking inside the box: A participatory, computer-assisted approach to scenario discovery, Technol. Forecasting Soc. Change, 77, 34-49.
9. Caldwell, C., and, G. W. Characklis, (2014), Impact of contract structure and risk aversion on inter-utility water transfer agreements, J. Water Resour. Plann. Manage., 140 (1), 100-111, doi: 10.1061/(ASCE)WR.1943-5452.0000317.
10. Clemen, R. T., (1996), Making Hard Decisions: An Introduction to Decision Analysis, Duxbury, Belmont, Calif.
11. Clímaco, J. C., (2004), A critical reflection on optimal decision, Eur. J. Oper. Res., 153 (2), 506-516.
12. Cohon, J., and, D. Marks, (1973), Multiobjective screening models and water resource investment, Water Resour. Res., 9 (4), 826-836.
13. Deb, K., and, H. Gupta, (2006), Introducing robustness in multi-objective optimization, Evol. Comput., 14 (4), 463-494.
14. Deb, K., M. Mohan, and, S. Mishra, (2005), Evaluating the epsilon-domination based multiobjective evolutionary algorithm for a quick computation of Pareto-optimal solutions, Evol. Comput., 13 (4), 501-525.
15. Frederick, K. D., and, G. Schwarz, (1999), Socioeconomic impacts of climate change on U.S. water supplies, J. Am. Water Resour. Assoc., 35 (6), 1563-1583.
16. Friedman, J. H., and, N. Fisher, (1999), Bump hunting in high-dimensional data, Stat. Comput., 9, 123-143.
17. Friedman, M., (1976), Price Theory, Aldine Publ. Co., Chicago, Ill.
18. Gleick, P. H., (2002), Soft water paths, Nature, 418, 373.
19. Gleick, P. H., (2003), Global freshwater resources: Soft-path solutions for the 21st century, Science, 302 (5650), 1524-1528.
20. Griffin, M. T., B. E. Montz, and, J. S. Arrigo, (2013), Evaluating climate change induced water stress: A case study of the lower cape fear basin, NC, Appl. Geogr., 40, 115-128.
21. Groves, D. G., and, R. J. Lempert, (2007), A new analytic method for finding policy-relevant scenarios, Global Environ. Change, 17 (1), 73-85.
22. Hadjigeorgalis, E., (2008), Managing drought through water markets: Farmer preferences in the Rio Grande basin, J. Am. Water Resour. Assoc., 44 (3), 594-605.
23. Hadka, D., and, P. Reed, (2012), Diagnostic assessment of search controls and failure modes in many-objective evolutionary optimization, Evol. Comput., 20 (3), 423-452.
24. Hadka, D., and, P. Reed, (2013), Borg: An auto-adaptive many-objective evolutionary computing framework, Evol. Comput., 21 (2), 231-259.
25. Hadka, D., P. M. Reed, and, T. W. Simpson, (2012), Diagnostic assessment of the Borg MOEA for many-objective product family design problems, in 2012 IEEE Congress on Evolutionary Computation (CEC), pp. 1-10, IEEE, Brisbane, Australia.
26. Haimes, Y. Y., and, W. A. Hall, (1977), Sensitivity, responsivity, stability, and irreversability as multiple objectives in civil systems, Adv. Water Resour., 1 (2), 71-81.
27. Hall, J., R. J. Lempert, K. Keller, A. Hackbarth, C. Mijere, and, D. J. McInerney, (2012), Robust climate policies under uncertainty: A comparison of robust decision making and Info-Gap methods, Risk Anal., 32 (10), 1657-1672, doi: 10.1111/j.1539-6924.2012.01802.x.
28. Hine, D., and, J. W. Hall, (2010), Information gap analysis of flood model uncertainties and regional frequency analysis, Water Resour. Res., 46, W01514, doi: 10.1029/2008WR007620.
29. Hitch, C. J., (1960), On the choice of objectives in systems studies, Tech. Rep. P-1955, The RAND Corp, Santa Monica, Calif.
30. Kasprzyk, J. R., S. Nataraj, P. M. Reed, and, R. J. Lempert, (2013), Many objective robust decision making for complex environmental systems undergoing change, Environ. Modell. Software, 42, 55-71, doi: 10.1016/j.envsoft.2012.12.007.
31. Keim, D., F. Mansmann, J. Schneidewind, and, H. Ziegler, (2006), Challenges in visual data analysis, in Proceedings of Information Visualization, pp. 9-16, IEEE Comput. Soc., London, U. K.
32. Kirsch, B. R., G. W. Characklis, and, H. B. Zeff, (2013), Evaluating the impact of alternative hydro-climate scenarios on transfer agreements: A practical improvement for generating synthetic streamflows, J. Water Resour. Plann. Manage., 139 (4), 396-406, doi: 10.1061/(ASCE)WR.1943-5452.0000287.
33. Knight, F. H., (1921), Risk, Uncertainty and Profit, Hart, Schaffner and Marx, N. Y.
34. Kollat, J. B., and, P. M. Reed, (2007a), A framework for Visually Interactive Decision-making and Design using Evolutionary Multiobjective Optimization (VIDEO), Environ. Modell. Software, 22 (12), 1691-1704.
35. Kollat, J. B., and, P. M. Reed, (2007b), A computational scaling analysis of multiobjective evolutionary algorithms in long-term groundwater monitoring applications, Adv. Water Resour., 30 (3), 335-353.
36. Lane, M. E., P. H. Kirshen, and, R. M. Vogel, (1999), Indicators of impacts of global climate change on U.S. water resources, J. Water Resour. Plann. Manage., 125 (4), 194-204.
37. Langlois, R. N., and, M. M. Cosgel, (1993), Frank knight on risk, uncertainty, and the firm: A new interpretation, Econ. Inquiry, 31 (3), 456-465.
38. Laumanns, M., (2002), Combining convergence and diversity in evolutionary multiobjective optimization, Evol. Comput., 10 (3), 263-282.
39. Lempert, R. J., (2002), A new decision sciences for complex systems, Proc. Natl. Acad. Sci., 99, 7309-7313.
40. Lempert, R. J., and, M. Collins, (2007), Managing the risk of an uncertain threshold response: Comparison of robust, optimum, and precautionary approaches, Risk Anal., 27 (4), 1009-1026.
41. Lempert, R. J., and, D. G. Groves, (2010), Identifying and evaluating robust adaptive policy responses to climate change for water management agencies in the American west, Technol. Forecasting Soc. Change, 77, 960-974.
42. Lempert, R. J., S. W. Popper, and, S. C. Bankes, (2003), Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis, RAND, Santa Monica, Calif.
43. Lempert, R. J., D. G. Groves, S. W. Popper, and, S. C. Bankes, (2006), A general, analytic method for generating robust strategies and narrative scenarios, Manage. Sci., 52 (4), 514-528.
44. Lempert, R. J., B. P. Bryant, and, S. C. Bankes, (2008), Comparing algorithms for scenario discovery, Tech. Rep. WR-557-NSF, RAND, Santa Monica, Calif.
45. Leung, L., B. Collins, and, J. Famiglietti, (2013), Community Modeling and Long-Term Predictions of the Integrated Water Cycle, U.S. Dep. of Energy Off. of Sci., Washington, D. C.
46. Liebman, J. C., (1976), Some simple-minded observations on the role of optimization in public systems decision-making, Interfaces, 6 (4), 102-108.
47. Lund, J. R., and, M. Israel, (1995), Optimization of transfers in urban water supply planning, J. Water Resour. Plann. Manage., 121 (1), 41-48.
48. Maass, A., M. M. Hufschmidt, R. Dorfman, H. A. Thomas, Jr,., S. A. Marglin, and, G. M. Fair, (1962), Design of Water-Resource Systems: New Techniques for Relating Economic Objectives, Engineering Analysis, and Governmental Planning, Harvard Univ. Press, Cambridge, Mass.
49. Matrosov, E., A. Woods, and, J. Harou, (2013), Robust decision making and Info-Gap decision theory for water resource system planning, J. Hydrol., 494, 43-58.
50. Moody, P., and, C. Brown, (2013), Robustness indicators for evaluation under climate change: Application to the upper Great Lakes, Water Resour. Res., 49, W20228, doi: 10.1002/wrcr.20228.
51. Palmer, R. N., and, G. W. Characklis, (2009), Reducing the costs of meeting regional water demand through risk-based transfer agreements, J. Environ. Manage., 90, 1703-1714, doi: 10.1016/j.jenvman.2008.11.003.
52. Polasky, S., S. R. Carpenter, C. Folke, and, B. Keeler, (2011), Decision-making under great uncertainty: Environmental management in an era of global change, Trends Ecol. Evol., 26 (8), 398-404.
53. Popper, K. R., (1963), Conjectures and Refutations, vol. 28, Routledge, London, U. K.
54. Postel, S. L., (2000), Entering an era of water scarcity: The challenges ahead, Ecol. Appl., 10 (4), 941-948.
55. Reed, P. M., and, J. R. Kasprzyk, (2009), Water resources management: The myth, the wicked, and the future, J. Water Resour. Plann. Manage., 135 (6), 411-413.
56. Reed, P. M., and, J. B. Kollat, (2013), Visual analytics clarify the scalability and effectiveness of massively parallel many-objective optimization: A groundwater monitoring design example, Adv. Water Resour., 56, 1-13.
57. Reed, P. M., D. Hadka, J. D. Herman, J. R. Kasprzyk, and, J. B. Kollat, (2013), Evolutionary multiobjective optimization in water resources: The past, present, and future, Adv. Water Resour., 51, 438-456.
58. Renwick, M. E., and, R. D. Green, (2000), Do residential water demand side management policies measure up? An analysis of eight California water agencies, J. Environ. Econ. Manage., 40 (1), 37-55.
59. Rittel, H., and, M. Webber, (1973), Dilemmas in a general theory of planning, Policy Sci., 4, 155-169.
60. Roy, B., (1971), Problems and methods with multiple objective functions, Math. Program., 1, 239-266.
61. Schneller, G., and, G. Sphicas, (1983), Decision making under uncertainty: Starr's domain criterion, Theory Decision, 15 (4), 321-336.
62. Scudder, T., (2005), The Future of Large Dams, Cromwell Press, London, U. K.
63. Seager, R., A. Tzanova, and, J. Nakamura, (2009), Drought in the southeastern United States: Causes, variability over the last millennium, and the potential for future hydroclimate change, J. Clim., 22 (19), 5021-5045.
64. Simon, H. A., (1959), Theories of decision-making in economics and behavioral science, Am. Econ. Rev., 49 (3), 253-283.
65. Starr, M. K., (1962), Product Design and Decision Theory, Prentice Hall, Englewood Cliffs, N. J.
66. Thomas, J., and, K. A. Cook, (2006), A visual analytics agenda, IEEE Comput. Graphics Appl., 26 (1), 10-13.
67. Thomas, J., and, J. Kielman, (2009), Challenges for visual analytics, Inform. Visualization, 8 (4), 309-314.
68. Tsoukias, A., (2008), From decision theory to decision aiding methodology, Eur. J. Oper. Res., 187 (1), 138-161.
69. Weaver, C. P., R. J. Lempert, C. Brown, J. A. Hall, D. Revell, and, D. Sarewitz, (2013), Improving the contribution of climate model information to decision making: The value and demands of robust decision frameworks, Wiley Interdisciplinary Rev.: Clim. Change, 4 (1), 39-60.
70. Wilchfort, O., and, J. R. Lund, (1997), Shortage management modeling for urban water supply systems, J. Am. Water Resour. Assoc., 123 (4), 250-258.
71. Woodruff, M. J., P. M. Reed, and, T. W. Simpson, (2013), Many objective visual analytics: Rethinking the design of complex engineered systems, Struct. Multidisciplinary Optim., 48, 201-219.
72. Zeff, H. B., and, G. W. Characklis, (2013), Managing water utility financial risks through third-party index insurance contracts, Water Resour. Res., 49, W20364, doi: 10.1002/wrcr.20364.
73. Zeff, H. B., J. Kasprzyk, J. Herman, P. Reed, and, G. Characklis, (2014), Navigating financial and supply reliability tradeoffs in regional drought portfolios, Water Resour. Res., 50, 4906-4923, doi: 10.1002/2013WR015126.