通过最大化用水和经济效益管理水稻种植中的地表水流分配

Water Supply Pub Date : 2023-11-30 DOI:10.2166/ws.2023.307
Zhenghui Chen
{"title":"通过最大化用水和经济效益管理水稻种植中的地表水流分配","authors":"Zhenghui Chen","doi":"10.2166/ws.2023.307","DOIUrl":null,"url":null,"abstract":"The multi-objective genetic algorithm was used as a decision variable to estimate the water required for irrigation in each of the growth stages. Agricultural costs and product sales prices in the agricultural year 2017–2023 in Luoyang Plain and its surrounding areas were collected for this purpose. Optimal irrigation strategies according to different water price scenarios were considered to calculate water use efficiency and net profit. In the conditions of optimal distribution, the amount of allocated water was 7,809, 2,928, 3,904, and 1,789 m3/ha for the stages of vegetative growth, flowering, crop formation, and ripening by the proposed model. On the other hand, it is necessary to reduce water stress in the periods of clustering and seed filling to increase crop yield and net income, as well as to achieve the desired irrigation schedule. Effective rainfall, especially in the ripening stage of the crop, can be considered to determine the optimal volume of water harvesting from the river. In addition, the results showed that by reducing the amount of available water, the water model allocated to leaf greening and tillering stages decreases.","PeriodicalId":23725,"journal":{"name":"Water Supply","volume":"106 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Management of surface flow allocation in rice cultivation by maximization of water use and economic efficiency\",\"authors\":\"Zhenghui Chen\",\"doi\":\"10.2166/ws.2023.307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The multi-objective genetic algorithm was used as a decision variable to estimate the water required for irrigation in each of the growth stages. Agricultural costs and product sales prices in the agricultural year 2017–2023 in Luoyang Plain and its surrounding areas were collected for this purpose. Optimal irrigation strategies according to different water price scenarios were considered to calculate water use efficiency and net profit. In the conditions of optimal distribution, the amount of allocated water was 7,809, 2,928, 3,904, and 1,789 m3/ha for the stages of vegetative growth, flowering, crop formation, and ripening by the proposed model. On the other hand, it is necessary to reduce water stress in the periods of clustering and seed filling to increase crop yield and net income, as well as to achieve the desired irrigation schedule. Effective rainfall, especially in the ripening stage of the crop, can be considered to determine the optimal volume of water harvesting from the river. In addition, the results showed that by reducing the amount of available water, the water model allocated to leaf greening and tillering stages decreases.\",\"PeriodicalId\":23725,\"journal\":{\"name\":\"Water Supply\",\"volume\":\"106 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Supply\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/ws.2023.307\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Supply","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/ws.2023.307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

采用多目标遗传算法作为决策变量,估算各生长阶段的灌溉需水量。为此收集了洛阳平原及其周边地区 2017-2023 农业年度的农业成本和产品销售价格。考虑了不同水价情景下的最优灌溉策略,以计算用水效率和净利润。在最优配水条件下,根据所提出的模型,作物的无性生长期、开花期、作物形成期和成熟期的配水量分别为 7809、2928、3904 和 1789 立方米/公顷。另一方面,为了提高作物产量和净收入,以及实现理想的灌溉计划,有必要减少结球期和籽粒灌浆期的水分胁迫。有效降雨量,尤其是作物成熟期的有效降雨量,可用于确定从河流获取的最佳水量。此外,研究结果表明,通过减少可用水量,分配给绿叶期和分蘖期的水量模式会减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Management of surface flow allocation in rice cultivation by maximization of water use and economic efficiency
The multi-objective genetic algorithm was used as a decision variable to estimate the water required for irrigation in each of the growth stages. Agricultural costs and product sales prices in the agricultural year 2017–2023 in Luoyang Plain and its surrounding areas were collected for this purpose. Optimal irrigation strategies according to different water price scenarios were considered to calculate water use efficiency and net profit. In the conditions of optimal distribution, the amount of allocated water was 7,809, 2,928, 3,904, and 1,789 m3/ha for the stages of vegetative growth, flowering, crop formation, and ripening by the proposed model. On the other hand, it is necessary to reduce water stress in the periods of clustering and seed filling to increase crop yield and net income, as well as to achieve the desired irrigation schedule. Effective rainfall, especially in the ripening stage of the crop, can be considered to determine the optimal volume of water harvesting from the river. In addition, the results showed that by reducing the amount of available water, the water model allocated to leaf greening and tillering stages decreases.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信