Li Chenyang, Yu Weiming, Chen Zhengrui, Cao Mengke, Guo Tingting. Two-stage interval parameters water resources model considering ecology and application in irrigation district[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(21): 105-114. DOI: 10.11975/j.issn.1002-6819.2017.21.013
    Citation: Li Chenyang, Yu Weiming, Chen Zhengrui, Cao Mengke, Guo Tingting. Two-stage interval parameters water resources model considering ecology and application in irrigation district[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(21): 105-114. DOI: 10.11975/j.issn.1002-6819.2017.21.013

    Two-stage interval parameters water resources model considering ecology and application in irrigation district

    • Abstract: Rapid economic development and expanded utilization of natural resources have caused shortage of water resources, environmental pollution and ecological deterioration and the others. The current water resources allocation rarely is related with ecology. In this study, a two-stage interval parameters water resources optimal model considering ecology was established. The agricultural water resources was allocated by considering crop water allocation, ecological water requirement, water quality pollution compensation, water uncertainty and economic benefits. In the model, the nitrogen and phosphorus concentrations were considered to represent the effect of water quality. The output was given in an interval form. Then, the model was applied to Jiansanjiang region for its reliability test. The Jiansanjiang included 15 farms, covering an area of 67.42 hm2. The water resources were rich here with surface water storage of 520 million cubic meter and underground water storage of 1483 million cubic meter in 2011. The inflow amount was 400-450 mm in 2002, 2008 and 2011, 500 mm above in 2009, 2012 and 2013, and 450-500 mm for the other years. Thus, the inflow was assumed to be low, middle and high levels. The probability of these 3 levels was assumed to be 20%, 60% and 20%, respectively. According to the local statistics, the irrigation amount per unit area was 6 561, 1 305 and 1 443 m3/hm2, respectively for rice, maize and soybean. The target water in advance and water demand of crops for rice were far higher than those for maize and soybean. The absorbance from the groundwater was higher than that from the surface water. The penalty coefficient of maize was the highest among the 3 crops. The surface water for nitrogen dilution and phosphorus dilution was between 1 823.58 million cubic meter and 15 207.80 million cubic meter and the ground water for dilution was between 576.23 and 3 126.10 million cubic meter. The total compensation cost was highest in the low flow level and lowest in the high flow level. The decision variable was 0 for the surface water in rice, 1 for the ground water in rice, 0.92 for the surface water in maize, 0.89 for the ground water in maize, 1 for the ground water in soybean and 0.66 for the ground water in soybean. For the rice, the optimal allocation target of water was 594.61 million cubic meter for the surface water. The optimal water allocation for rice was 516.49 million cubic meter when the inflow level was low. The optimal ground water allocation was between 1 035.09 million cubic meter and 1 224.38 million cubic meter in rice, between 2.02 million cubic meter and 2.92 million cubic meter in maize, between 6.27 million cubic meter and 6.80 million cubic meter in soybean. The optimal surface water allocation was between 516.49 million cubic meter and 536.49 million cubic meter in rice, 1.47 million cubic meter in maize and 2.39 million cubic meter in soybean. The optimized income based on the optimal model was between 7 561.78 and 7 691.06 million yuan, between 345.80 million yuan and 498.05 million yuan in maize, and between 70.89 million yuan and 112.42 million yuan in soybean. Compared to the original income of 7 366.65 million yuan, 301.14 million yuan and 105.69 million yuan, the income after optimization was high. The model provides a reasonable decision-making interval for the decision-makers and provides a technique support for of the rational agricultural water resources allocation.
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