Advances in using mathematical optimization to manage floods with assessment of possible benefits using a case study

Nesa Ilich, Ashoke Basistha
{"title":"Advances in using mathematical optimization to manage floods with assessment of possible benefits using a case study","authors":"Nesa Ilich, Ashoke Basistha","doi":"10.2166/hydro.2023.247","DOIUrl":null,"url":null,"abstract":"This paper presents the benefits of using mathematical optimization for reservoir operation based on the assumed availability of short-term runoff forecasts. The novelty is the inclusion of the SSARR hydrological routing as optimization constraints in multiple time step optimization, where the routing coefficients are adjusted dynamically as functions of the channel flows. The paper shows significant reduction to downstream peak flows in flood-prone areas even with a forecast horizon of only 2 days, and it also includes the results of testing the effects of different lengths of forecasting horizons on model results. The case study is conducted on the Damodar River Basin in the Indian State of West Bengal, where basin development started in the 1950s, with flood protection of the downstream river valley as the highest management priority, in addition to water supply and hydro power. The solution methodology and the model results presented in this paper pave the way for eventual introduction to automated management of reservoir outflows that could revolutionize water resources industry in much the same way that auto-pilot and driverless cars are revolutionizing the transportation industry, assuming that runoff forecasting capabilities continue to improve.","PeriodicalId":507813,"journal":{"name":"Journal of Hydroinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydroinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/hydro.2023.247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper presents the benefits of using mathematical optimization for reservoir operation based on the assumed availability of short-term runoff forecasts. The novelty is the inclusion of the SSARR hydrological routing as optimization constraints in multiple time step optimization, where the routing coefficients are adjusted dynamically as functions of the channel flows. The paper shows significant reduction to downstream peak flows in flood-prone areas even with a forecast horizon of only 2 days, and it also includes the results of testing the effects of different lengths of forecasting horizons on model results. The case study is conducted on the Damodar River Basin in the Indian State of West Bengal, where basin development started in the 1950s, with flood protection of the downstream river valley as the highest management priority, in addition to water supply and hydro power. The solution methodology and the model results presented in this paper pave the way for eventual introduction to automated management of reservoir outflows that could revolutionize water resources industry in much the same way that auto-pilot and driverless cars are revolutionizing the transportation industry, assuming that runoff forecasting capabilities continue to improve.
利用数学优化管理洪水的进展,以及利用案例研究评估可能的效益
本文介绍了在假定可获得短期径流预报的基础上利用数学优化进行水库运行的好处。新颖之处在于将 SSARR 水文路由作为优化约束条件纳入多时步优化,其中路由系数作为渠道流量的函数进行动态调整。论文显示,即使预报期只有 2 天,洪水易发区的下游峰值流量也会明显减少,论文还包括测试不同预报期长度对模型结果影响的结果。案例研究的对象是印度西孟加拉邦的达莫达尔河流域,该流域的开发始于 20 世纪 50 年代,除供水和水力发电外,下游河谷的防洪保护也是管理的重中之重。本文介绍的解决方法和模型结果为最终引入水库出流的自动化管理铺平了道路,假定径流预报能力不断提高,这可能会像自动驾驶和无人驾驶汽车彻底改变交通运输业一样,彻底改变水利行业。
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 求助全文
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