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Water 2018, 10(8), 1031;

A Stochastic Optimization Model for Agricultural Irrigation Water Allocation Based on the Field Water Cycle

Department of Civil and Resource Engineering, Dalhousie University, Halifax, NS B3H 4R2, Canada
School of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin 150030, China
Key Laboratory of Effective Utilization of Agricultural Water Resources of Ministry of Agriculture, Northeast Agricultural University, Harbin 150030, China
Author to whom correspondence should be addressed.
Received: 28 June 2018 / Revised: 29 July 2018 / Accepted: 31 July 2018 / Published: 3 August 2018
(This article belongs to the Special Issue Data-Driven Methods for Agricultural Water Management)
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Agricultural water scarcity is a global problem and this reinforces the need for optimal allocation of irrigation water resources. However, decision makers are challenged by the complexity of fluctuating stream condition and irrigation quota as well as the dynamic changes of the field water cycle process, which make optimal allocation more complex. A two-stage chance-constrained programming model with random parameters in the left- and right-hand sides of constraints considering field water cycle process has been developed for agricultural irrigation water allocation. The model is capable of generating reasonable irrigation allocation strategies considering water transformation among crop evapotranspiration, precipitation, irrigation, soil water content, and deep percolation. Moreover, it can deal with randomness in both the right-hand side and the left-hand side of constraints to generate schemes under different flow levels and constraint-violation risk levels, which are informative for decision makers. The Yingke irrigation district in the middle reaches of the Heihe River basin, northwest China, was used to test the developed model. Tradeoffs among different crops in different time periods under different flow levels, and dynamic changes of soil moisture and deep percolation were analyzed. Scenarios with different violating probabilities were conducted to gain insight into the sensitivity of irrigation water allocation strategies on water supply and irrigation quota. The performed analysis indicated that the proposed model can efficiently optimize agricultural irrigation water for an irrigation district with water scarcity in a stochastic environment. View Full-Text
Keywords: agricultural irrigation water allocation; optimization model; field water cycle; randomness agricultural irrigation water allocation; optimization model; field water cycle; randomness

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Yan, Z.; Li, M. A Stochastic Optimization Model for Agricultural Irrigation Water Allocation Based on the Field Water Cycle. Water 2018, 10, 1031.

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