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 Journal of Environmental Informatics Pub Date : 2020-09-15 DOI:10.3808/JEI.202000441
G. Yang, M. Li, P. Guo
{"title":"Monte Carlo-Based Agricultural Water Management under Uncertainty: A Case Study of Shijin Irrigation District, China","authors":"G. Yang, M. Li, P. Guo","doi":"10.3808/JEI.202000441","DOIUrl":null,"url":null,"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.","PeriodicalId":54840,"journal":{"name":"Journal of Environmental Informatics","volume":null,"pages":null},"PeriodicalIF":6.0000,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Informatics","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3808/JEI.202000441","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Modelling Soil δ13C across the Tibetan Plateau Using Deep-Learning Impact of Carbon Emissions and Advance Payment on Optimal Decisions for Perishable Products via Parametric Approach of Interval Prediction of the Breeding and Wintering Ranges of Pomacea canaliculata in China Using Ensemble Models Decentralized Algae Removal Technologies for Lake Diefenbaker Irrigation Canals: A Review Real-Time LNG Buses Emissions Prediction Based on a Temporal Fusion Trans-Formers Model
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1