Abstract
Droughts continue to be a major natural hazard, and mounting evidence of global warming confronts society with a pressing question: Will climate change aggravate the risk of drought at the local scale? Are current infrastructures sufficient to mitigate the damage of future drought, or is in-advance infrastructure expansion needed for future drought preparedness? To address these questions, this study presents a decision-support framework based on a coupled simulation and stochastic optimization model through a case study area, the Frenchman Creek basin (FCB), part of the Republican River basin. A complex watershed simulation model is established and converted into a statistical surrogate model for computational feasibility. Decisions for drought preparedness include traditional short-term tactical measures (e.g., facility operation) and long-term or in-advance strategic measures, which require capital investment. A scenario-based, three-stage stochastic optimization model assesses the roles of strategic measures and tactical measures in drought preparedness and mitigation. Modeling scenarios of the future climate are developed from multiple general circulation models (GCMs) and regional climate models (RCMs) under different greenhouse gas emission scenarios to represent the various possible climatic conditions in the midterm (2040s) and long-term (2090s) time horizons. The result of the case study shows that current facilities are not enough to mitigate the damage under future climate conditions, indicating the requirement for infrastructure investment; meanwhile, socioeconomic factors (represented by the discount rate) complicate the decision along the planning horizon.
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Acknowledgments
This study was financially supported by U.S. National Science Foundation grant CMMI 0825654. The authors appreciate the discussion with Dr. Mashor Housh. The authors appreciate the comments from the reviewers.
References
Arabi, M., Frankenberger, J. R., Engel, B. A., and Arnold, J. G. (2008). “Representation of agricultural conservation practices with SWAT.” Hydrol. Processes, 22(16), 3042–3055.
Arabi, M., Govindaraju, R. S., and Hantush, M. M. (2006). “Cost-effective allocation of watershed management practices using a genetic algorithm.” Water Resour. Res., 42(10), W10429.
Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R. (1998). “Large area hydrologic modeling and assessment. Part I: Model development.” J. Am. Water Resour. Assoc., 34(1), 73–89.
Burt, O. R., Baker, M., and Helmers, G. A. (2002). “Statistical estimation of streamflow depletion from irrigation wells.” Water Resour. Res., 38(12), 32-1–32-13.
Cai, X., McKinney, D. C., and Lasdon, L. S. (2002). “A framework for sustainability analysis in water resources management and application to the Syr Darya basin.” Water Resour. Res., 38(6), 21-1–21-14.
Cai, X., and Rosegrant, M. W. (2004). “Irrigation technology choices under hydrologic uncertainty: A case study from Maipo River basin, Chile.” Water Resour. Res., 40(4), W04103.
Cai, X., Wang, D., and Laurent, R. (2009). “Impact of climate change on crop yield: A case study of rainfed corn in central Illinois.” J. Appl. Meteorol. Climatol., 48(9), 1868–1881.
Challinor, A. J., Wheeler, T. R., Craufurd, P. Q., and Slingo, J. M. (2005). “Simulation of the impact of high temperature stress on annual crop yields.” Agric. For. Meteorol., 135(1–4), 180–189.
Chang, C.-C., and Lin, C.-J. (2011). “LIBSVM: A library for support vector machines.” ACM Trans. Intell. Syst. Technol., 2(3), 1–27.
Ciais, P., et al. (2005). “Europe-wide reduction in primary productivity caused by the heat and drought in 2003.” Nature, 437(7058), 529–533.
Drucker, H., Burges, C. J. C., Kaufman, L., Smola, A., and Vapnik, V. (1997). Support vector regression machines, MIT Press, Cambridge, MA.
Dudhia, J., Gill, D., Manning, K., Wang, W., Bruyere, C., Kelly, S., and Lackey, K. (2005). “PSU/NCAR mesoscale modeling system tutorial class notes and user’s guide: MM5 modeling system version.” National Center for Atmospheric Research, Boulder, CO.
Ehret, U., Zehe, E., Wulfmeyer, V., Warrach-Sagi, K., and Liebert, J. (2012). “HESS opinions: ‘Should we apply bias correction to global and regional climate model data?’.” Hydrol. Earth Syst. Sci., 16(9), 3391–3404.
Gitau, M., Veith, T. L., and Gburek, W. (2004). “Farm-level optimization of BMP placement for cost-effective pollution reduction.” Trans. ASAE, 47(6), 1923–1931.
Haimes, Y. Y., Lasdon, L. S., and Wismer, D. A. (1971). “On a bicriterion formulation of the problems of integrated system identification and system optimization.” IEEE Trans. Syst. Man Cybern., 1(3), 296–297.
Hill, H. S. J., et al. (2004). “Implications of seasonal climate forecasts on world wheat trade: A stochastic, dynamic analysis.” Can. J. Agr. Econ., 52(3), 289–312.
Hong, W.-C., and Pai, P.-F. (2007). “Potential assessment of the support vector regression technique in rainfall forecasting.” Water Resour. Manage., 21(2), 495–513.
Huang, W.-C., and Yuan, L.-C. (2004). “A drought early warning system on real-time multireservoir operations.” Water Resources Research, 40(6), W06401.
IPCC (Intergovernmental Panel on Climate Change). (2012). “Managing the risks of extreme events and disasters to advance climate change adaptation: Special report of the Intergovernmental Panel on Climate Change.” Cambridge University Press, Cambridge, U.K.
IPCC (Intergovernmental Panel on Climate Change). (2014). “Climate change 2014: Impacts, adaptation, and vulnerability. Part A: Global and sectoral aspects. Working group II contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change.” C. B. Field, et al., eds., Cambridge University Press, Cambridge, U.K.
Kaini, P., Artita, K., and Nicklow, J. (2012). “Optimizing structural best management practices using SWAT and genetic algorithm to improve water quality goals.” Water Resour. Manage., 26(7), 1827–1845.
Liang, X.-Z., Kunkel, K. E., Meehl, G. A., Jones, R. G., and Wang, J. X. L. (2008). “Regional climate models downscaling analysis of general circulation models present climate biases propagation into future change projections.” Geophys. Res. Lett., 35(8), L08709.
Liang, X.-Z., Li, L., Kunkel, K. E., Ting, M., and Wang, J. X. L. (2004). “Regional climate model simulation of U.S. precipitation during 1982–2002. Part I: Annual cycle.” J. Clim., 17(18), 3510–3529.
Liang, X.-Z., Pan, J., Zhu, J., Kunkel, K. E., Wang, J. X. L., and Dai, A. (2006). “Regional climate model downscaling of the U.S. summer climate and future change.” J. Geophys. Res. Atmos., 111(D10), D10108.
Logar, I., and Bergh, J. J. M. (2013). “Methods to assess costs of drought damages and policies for drought mitigation and adaptation: Review and recommendations.” Water Resour. Manage., 27(6), 1707–1720.
Mallya, G., Zhao, L., Song, X., Niyogi, D., and Govindaraju, R. (2013). “2012 midwest drought in the United States.” J. Hydrol. Eng., 737–745.
Matlab [Computer software]. Natick, MA, Mathworks.
McGuire, V. L. (2009). “Water-level changes in the High Plains aquifer, predevelopment to 2007, 2005–06, and 2006–07.”, USGS, Reston, VA.
Milly, P. C. D., et al. (2008). “Stationarity is dead: Whither water management?” Science, 319(5863), 573–574.
Mishra, A. K., and Singh, V. P. (2010). “A review of drought concepts.” J. Hydrol., 391(1–2), 202–216.
Nakicenovic, N., and Swart, R. (2000). “Special report on emission scenarios: A special report of working group III of the Intergovernmental Panel on Climate Change.” Cambridge University Press, Cambridge, U.K.
Neitsch, S., Arnold, J., Kiniry, J., Williams, J., and King, K. (2002). “Soil and water assessment tool theoretical documentation, version 2000.”, Texas Water Resources Institute, College Station, TX.
Pachauri, R., and Reisinger, A. (2007). “Climate change 2007: Synthesis report. Contribution of working groups I, II and III to the fourth assessment report of the Intergovernmental Panel on Climate Change.” Cambridge University Press, Cambridge, U.K.
Perritt, R., and Masucci, M. (1997). Human environmental interchange: Managing the effects of recent droughts in the southeastern U.S., Harcourt Brace/Saunders, Philadelphia.
Phillips, D. L., Hardin, P. D., Benson, V. W., and Baglio, J. V. (1993). “Nonpoint source pollution impacts of alternative agricultural management practices in Illinois: A simulation study.” J. Soil Water Conserv., 48(5), 449–457.
Pope, V. D., Gallani, M. L., Rowntree, P. R., and Stratton, R. A. (2000). “The impact of new physical parameterizations in the Hadley Centre climate model: HadAM3.” Clim. Dyn., 16(2–3), 123–146.
Queipo, N. V., et al. (2005). “Surrogate-based analysis and optimization.” Prog. Aerosp. Sci., 41(1), 1–28.
Ray, P., Kirshen, P., and Watkins, D. (2012). “Staged climate change adaptation planning for water supply in Amman, Jordan.” J. Water Resour. Plann. Manage., 403–411.
Ross, T., and Lott, N. (2003). “A climatology of 1980–2003 extreme weather and climate events.”, NOAA/NESDIS, National Climatic Data Center, Asheville, NC.
Smola, A., and Schölkopf, B. (2004). “A tutorial on support vector regression.” Stat. Comput., 14(3), 199–222.
Strzepek, K., Yohe, G., Neumann, J., and Boehlert, B. (2010). “Characterizing changes in drought risk for the United States from climate change.” Environ. Res. Lett., 5(4), 044012.
Teutschbein, C., and Seibert, J. (2012). “Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods.” J. Hydrol., 456–457, 12–29.
Wang, D., Hejazi, M., Cai, X., and Valocchi, A. J. (2011). “Climate change impact on meteorological, agricultural, and hydrological drought in central Illinois.” Water Resour. Res., 47(9), W09527.
Washington, W. M., et al. (2000). “Parallel climate model (PCM) control and transient simulations.” Clim. Dyn., 16(10–11), 755–774.
Watkins, D. W., Jr., McKinney, D. C., Lasdon, L. S., Nielsen, S. S., and Martin, Q. W. (2000). “A scenario-based stochastic programming model for water supplies from the Highland Lakes.” Int. Trans. Oper. Res., 7(3), 211–230.
Werick, W. J., and Whipple, W., Jr. (1994). “National study of water management during drought: Managing water for drought.” U.S. Army Corps of Engineers, Water Resources Support Center, Institute for Water Resources, Alexandria, VA.
Wilby, R. L. (2010). “Evaluating climate model outputs for hydrological applications.” Hydrol. Sci. J., 55(7), 1090–1093.
Wilhite, D. A. (2002). “Combating drought through preparedness.” Nat. Resour. Forum, 26(4), 275–285.
Wilhite, D. A., Hayes, M. J., Knutson, C., and Smith, K. H. (2000). “Planning for drought: Moving from crisis to risk management.” J. Am. Water Resour. Assoc., 36(4), 697–710.
Woodhouse, C. A., and Overpeck, J. T. (1998). “2000 years of drought variability in the central United States.” Bull. Am. Meteorol. Soc., 79(12), 2693–2714.
Wossink, G., and Osmond, D. (2002). “Farm economics to support the design of cost-effective best management practice (BMP) programs to improve water quality: Nitrogen control in the Neuse River basin, North Carolina.” J. Soil Water Conserv., 57(4), 213–220.
Yohe, G., Andronova, N., and Schlesinger, M. (2004). “To hedge or not against an uncertain climate future?” Science, 306(5695), 416–417.
Yu, C., MacEachren, A. M., Peuquet, D. J., and Yarnal, B. (2009). “Integrating scientific modeling and supporting dynamic hazard management with a GeoAgent-based representation of human-environment interactions: A drought example in central Pennsylvania, USA.” Environ. Model. Softw., 24(12), 1501–1512.
Yu, P. S., Chen, S. T., and Chang, I. F. (2006). “Support vector regression for real-time flood stage forecasting.” J. Hydrol., 328(3), 704–716.
Zeng, R. (2012). “Infrastructure planning for drought mitigation under climate change.” M.S. thesis, Univ. of Illinois at Urbana-Champaign, IL.
Zeng, R., and Cai, X. (2014). “Analyzing streamflow changes: Irrigation-enhanced interaction between aquifer and streamflow in the Republican River basin.” Hydrol. Earth Syst. Sci., 18(2), 493–502.
Zhang, X., Srinivasan, R., and Van Liew, M. (2009). “Approximating SWAT model using artificial neural network and support vector machine.” J. Am. Water Resour. Assoc., 45(2), 460–474.
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Journal of Water Resources Planning and Management
Volume 141 • Issue 9 • September 2015
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© 2015 American Society of Civil Engineers.
History
Received: Jun 4, 2014
Accepted: Dec 3, 2014
Published online: Jan 19, 2015
Discussion open until: Jun 19, 2015
Published in print: Sep 1, 2015
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