Monte Carlo-Based Agricultural Water Management under Uncertainty: A Case Study of Shijin Irrigation District, China

IF 6 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
G. Yang, M. Li, P. Guo
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引用次数: 14

Abstract

Considering the multiple uncertainties in agricultural water resources management systems, this paper established an agricultural water optimal allocation model under uncertainty for Shijin irrigation district (ID). Uncertainties of four parameters, in- cluding precipitation, available groundwater, purchase prices of crops and crop cultivated area, were fully considered. Agricultural wa- ter allocation schemes were obtained based on the distribution characteristics simulation of the four parameters using Monte Carlo sim- ulation technique. In order to thoroughly analyze the results, the relationship between system benefits and water amounts was shown using 3D diagram. The optimized results show that total water use amount of 2016 ([217.460, 218.017] × 106 m3 for surface water irri- gation and [51.765, 66.266] × 106 m3 for groundwater irrigation) remains fairly static compared with the average level from 2003 to 2013, and irrigation water allocated to winter wheat is considerably larger than that to maize. The significant drop of the purchase price of maize has an apparent effect on water allocation. For winter wheat, surface water allocation of 2016 increases from 129.445 × 106 to 174.905 × 106 m3, and groundwater allocation increases from 24.511×106 m3 to 35.379 × 106 m3. For maize, surface water allocation of 2016 decreases from 88.329 × 106 to 42.846 × 106 m3, and groundwater allocation decreases from 34.733 × 106 to 23.865 × 106 m3. Water allocation amounts for the five subareas of Shijin ID are 54.326 × 106, 31.187 × 106, 51.899 × 106, 39.311 × 106, and 33.779 × 106 m3 respectively during the irrigation period of winter wheat, and are 16.693 × 106, 8.677 × 106, 16.151 × 106, 14.004×106, and 10.752 × 106 m3 during the irrigation period of maize. Moreover, cumulative probability distribution functions of surface water and ground- water allocation amounts for winter wheat and maize were obtained. Further, the linear relations between the difference in purchase price and the difference in water allocation of winter wheat and maize were obtained as well. These results will help decision makers learn detailed water distribution information and thus help make comprehensive irrigation schemes under uncertainty in future.
不确定性下基于蒙特卡罗的农业用水管理——以石锦灌区为例
考虑农业水资源管理系统存在的多重不确定性,以石津灌区为例,建立了不确定性条件下的农业用水优化配置模型。充分考虑了降水量、可利用地下水、作物收购价格和作物种植面积等4个参数的不确定性。利用蒙特卡罗模拟技术对这四个参数的分布特征进行模拟,得到农业用水分配方案。为了更深入地分析结果,采用三维图显示了系统效益与水量之间的关系。优化结果表明,与2003 - 2013年的平均水平相比,2016年的总耗水量(地表水灌溉[217.460,218.017]× 106 m3,地下水灌溉[51.765,66.266]× 106 m3)基本保持不变,冬小麦的灌溉分配水量明显大于玉米。玉米收购价的显著下降对水分配置有明显影响。冬小麦2016年地表水分配由129.445 ×106增加到174.905 ×106 m3,地下水分配由24.511×106 m3增加到35.379 ×106 m3。玉米地表水分配从2016年的88.329 × 106减少到42.846 × 106 m3,地下水分配从34.733 × 106减少到23.865 × 106 m3。冬小麦灌水期石津ID 5个分区的配水量分别为54.326 ×106、31.187 ×106、51.899 ×106、39.311 ×106、33.779 ×106 m3,玉米灌水期配水量分别为16.693 ×106、8.677 ×106、16.151 ×106、14.004×106、10.752 ×106 m3。此外,还得到了冬小麦和玉米地表水和地下水配水量的累积概率分布函数。此外,还得到了冬小麦和玉米的收购价格差异与水分分配差异之间的线性关系。这些结果将有助于决策者了解详细的水资源分布信息,从而有助于制定未来不确定条件下的综合灌溉方案。
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来源期刊
Journal of Environmental Informatics
Journal of Environmental Informatics ENVIRONMENTAL SCIENCES-
CiteScore
12.40
自引率
2.90%
发文量
7
审稿时长
24 months
期刊介绍: Journal of Environmental Informatics (JEI) is an international, peer-reviewed, and interdisciplinary publication designed to foster research innovation and discovery on basic science and information technology for addressing various environmental problems. The journal aims to motivate and enhance the integration of science and technology to help develop sustainable solutions that are consensus-oriented, risk-informed, scientifically-based and cost-effective. JEI serves researchers, educators and practitioners who are interested in theoretical and/or applied aspects of environmental science, regardless of disciplinary boundaries. The topics addressed by the journal include: - Planning of energy, environmental and ecological management systems - Simulation, optimization and Environmental decision support - Environmental geomatics - GIS, RS and other spatial information technologies - Informatics for environmental chemistry and biochemistry - Environmental applications of functional materials - Environmental phenomena at atomic, molecular and macromolecular scales - Modeling of chemical, biological and environmental processes - Modeling of biotechnological systems for enhanced pollution mitigation - Computer graphics and visualization for environmental decision support - Artificial intelligence and expert systems for environmental applications - Environmental statistics and risk analysis - Climate modeling, downscaling, impact assessment, and adaptation planning - Other areas of environmental systems science and information technology.
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