Comparison of Various Stochastic Approaches for Irrigation Scheduling Using Seasonal Climate Forecasts
Publication: Journal of Water Resources Planning and Management
Volume 144, Issue 7
Abstract
This paper presents a modeling framework for real-time decision support for irrigation scheduling using probabilistic seasonal weather forecasts which are incorporated into a simulation-optimization framework. The simulation of the field processes is performed by the Soil Water Atmosphere Plant (SWAP) model, whereas the optimization is performed by three different stochastic programming methods: implicit approach, explicit single-stage approach and explicit two-stage approach. To evaluate the benefit of the probabilistic forecasts, the irrigation schedules from the different stochastic methods are compared with the best benchmark of perfect forecasts as well as with the real field and the Agriculture Extension Service of Israel schedules. The analysis is performed on a real case study of irrigated chickpeas field in Kibbutz Hazorea, Northern Israel. The results show that incorporating stochastic weather forecasts could lead to substantial improvements compared with current irrigation practices.
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Acknowledgments
This research was made possible by the financial support of the Israeli Water Authority Research Fund. The authors thank Dr. Anna Brook for providing the field measurements.
References
Bastiaanssen, W. G., R. G. Allen, P. Droogers, G. D’Urso, and P. Steduto. 2007. “Twenty-five years modeling irrigated and drained soils: State of the art.” Agric. Water Manage. 92 (3): 111–125. https://doi.org/10.1016/j.agwat.2007.05.013.
Bergez, J. E., J. M. Deumier, B. Lacroix, P. Leroy, and D. Wallach. 2002. “Improving irrigation schedules by using a biophysical and a decisional model.” Eur. J. Agron. 16 (2): 123–135. https://doi.org/10.1016/S1161-0301(01)00124-1.
Birge, J. R., and F. Louveaux. 2011. Introduction to stochastic programming. New York: Springer Science & Business Media.
Cai, X., M. I. Hejazi, and D. Wang. 2010. “Value of probabilistic weather forecasts: Assessment by real-time optimization of irrigation scheduling.” J. Water Resour. Plann. Manage. 137 (5): 391–403. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000126.
Chen, J., F. P. Brissette, and R. Leconte. 2012. “WeaGETS—A Matlab-based daily scale weather generator for generating precipitation and temperature.” Procedia Environ. Sci. 13: 2222–2235. https://doi.org/10.1016/j.proenv.2012.01.211.
Crawley, P., and G. Dandy. 1993. “Optimal operation of multiple reservoir system.” J. Water Resour. Plann. Manage. 119 (1), 1–17. https://doi.org/10.1061/(ASCE)0733-9496(1993)119:1(1).
Dupačová, J., G. Consigli, and S. W. Wallace. 2000. “Scenarios for multistage stochastic programs.” Ann. Oper. Res. 100 (1–4), 25–53.
Eitzinger, J., M. Trnka, J. Hösch, Z. Žalud, and M. Dubrovský. 2004. “Comparison of CERES, WOFOST and SWAP models in simulating soil water content during growing season under different soil conditions.” Ecol. Modell. 171 (3): 223–246. https://doi.org/10.1016/j.ecolmodel.2003.08.012.
Grakis, A., and J. T. Ritchie. 1998. “Simulation of atrazine leaching in relation to water-table management using the CERES model.” J. Environ. Manage. 52 (3): 241–258. https://doi.org/10.1006/jema.1997.0172.
Hashemi, F., and W. Decker. 1969. “Using climatic information and weather forecast for decisions in economizing irrigation water.” Agric. Meteorol. 6 (4): 245–257. https://doi.org/10.1016/0002-1571(69)90052-1.
Hejazi, M. I., X. Cai, X. Yuan, X. Z. Liang, and P. Kumar. 2013. “Incorporating reanalysis-based short-term forecasts from a regional climate model in an irrigation scheduling optimization problem.” J. Water Resour. Plann. Manage. 140 (5): 699–713. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000365.
Housh, M., A. Ostfeld, and U. Shamir. 2013. “Limited multi-stage stochastic programming for managing water supply systems.” Environ. Modell. Software 41: 53–64. https://doi.org/10.1016/j.envsoft.2012.11.006.
Jamal, A. 2016. “Utilizing probabilistic weather forecasting for optimal irrigation scheduling.” Master dissertation. Technion–Israel Institute of Technology.
Joodavi, A., M. Zare, and M. Mahootchi. 2015. “Development and application of a stochastic optimization model for groundwater management: crop pattern and conjunctive use consideration.” Stochastic Environ. Res. Risk Assess. 29 (6): 1637–1648. https://doi.org/10.1007/s00477-015-1049-x.
Labadie, J. W. 2004. “Optimal operation of multi-reservoir systems: State-of-the-art review.” J. Water Resour. Plann. Manage. 130 (2): 93–111. https://doi.org/10.1061/(ASCE)0733-9496(2004)130:2(93).
Ma, Y., S. Feng, Z. Huo, and X. Song. 2011. “Application of the SWAP model to simulate the field water cycle under deficit irrigation in Beijing, China.” Math. Comput. Modell. 54 (3): 1044–1052. https://doi.org/10.1016/j.mcm.2010.11.034.
Pleban, S., D. F. Heermann, J. W. Labadie, and H. R. Duke. 1984. “Real time irrigation scheduling via ‘Reaching’ dynamic programming.” Water Resour. Res. 20 (7): 887–895. https://doi.org/10.1029/WR020i007p00887.
Raghuwanshi, N. S., and W. W. Wallender. 1998. “Optimal furrow irrigation scheduling under heterogeneous conditions.” Agric. Syst. 58 (1): 39–55. https://doi.org/10.1016/S0308-521X(98)00030-4.
Shad, M. Y., and G. C. Pug. 2014. “Stochastic vs. deterministic programming in water management: The value of flexibility.” Ann. Oper. Res. 223 (1): 309–328. https://doi.org/10.1007/s10479-013-1455-8.
Singh, R., J. C. Van Dam, and R. A. Feddes. 2006. “Water productivity analysis of irrigated crops in Sirsa district, India.” Agric. Water Manage. 82 (3): 253–278. https://doi.org/10.1016/j.agwat.2005.07.027.
Supit, I., A. A. Hooijer, and C. A. Van Diepen. 1994. System description of the WOFOST 6.0 crop simulation model implemented in CGMS. Luxembourg: Office for Official Publications of the EC.
Tukimat, N. N. A., S. Harun, and S. Shahid. 2017. “Modeling irrigation water demand in a tropical paddy cultivated area in the context of climate change.” J. Water Resour. Plann. Manage. 143 (7): 05017003. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000753.
Van Dam, J. C., J. Huygen, J. G. Wesseling, R. A. Feddes, P. Kabat, P. E. V. Van Walsum, P. Groenendijk, and C. A. Van Diepen. 1997. Theory of SWAP version 2.0, 167. Wageningen, Netherlands: DLO Winand Staring Centre.
Vazifedoust, M., J. C. Van Dam, R. A. Feddes, and M. Feizi. 2008. “Increasing water productivity of irrigated crops under limited water supply at field scale.” Agric. Water Manage. 95 (2): 89–102. https://doi.org/10.1016/j.agwat.2007.09.007.
Wang, D., and X. Cai. 2009. “Irrigation scheduling: The role of weather forecasting and farmers’ behavior.” J. Water Resour. Plann. Manage. 135 (5): 364–372. https://doi.org/10.1061/(ASCE)0733-9496(2009)135:5(364).
Wilks, D. S., and D. W. Wolfe. 1998. “Optimal use and economic value of weather forecasts for lettuce irrigation in a humid climate.” Agric. For. Meteorol. 89 (2), 115–129. https://doi.org/10.1016/S0168-1923(97)00066-X.
Xu, B., S. E. Boyce, Y. Zhang, Q. Liu, L. Guo, and P. A. Zhong. 2016. “Stochastic programming with a joint chance constraint model for reservoir refill operation considering flood risk.” J. Water Resour. Plann. Manage. 89 (2): 04016067. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000715.
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Published In
Journal of Water Resources Planning and Management
Volume 144 • Issue 7 • July 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: May 30, 2017
Accepted: Jan 17, 2018
Published online: Apr 30, 2018
Published in print: Jul 1, 2018
Discussion open until: Sep 30, 2018
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