Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change |
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| Authors: | Mo Li Ping Guo Vijay P Singh Jie Zhao |
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| Institution: | 1. Centre for Agricultural Water Research in China, China Agricultural University, Beijing, China;2. Department of Biological and Agricultural Engineering & Zachry Department of Civil Engineering, Texas A & M University, College Station, Texas;3. College of Water Sciences, Beijing Normal University, Beijing, China |
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| Abstract: | Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment. |
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| Keywords: | irrigation water allocation inexact two‐stage quadratic programming fuzzy mathematical programming uncertainty climate change |
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