热带地区单变量与多变量洪水频率分析:采用两类水文模型

IF 1.5 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES Clean-soil Air Water Pub Date : 2024-04-11 DOI:10.1002/clen.202300351
Proloy Deb, Pragnaditya Malakar, Pradip Kumar Bora, Swatantra Kumar Dubey
{"title":"热带地区单变量与多变量洪水频率分析:采用两类水文模型","authors":"Proloy Deb, Pragnaditya Malakar, Pradip Kumar Bora, Swatantra Kumar Dubey","doi":"10.1002/clen.202300351","DOIUrl":null,"url":null,"abstract":"Flood frequency analysis is critical in flood planning and management and hydraulic structures design. While univariate flood frequency analysis (using the peak flow) is still widely employed in developing countries, how does it compare to the robust copula‐based bivariate flood frequency analysis remains unknown. Moreover, there is also a decade‐long critical question whether less data requiring hydrological models can be an alternate to the data‐intensive models in flood prediction, especially in a developing tropical country like India? To answer these questions, this study aims in comparing two types of hydrological models (IHACRES, a less data requiring model, and VIC‐3L, a data‐intensive model) in simulating the peak flows, following which the simulated peak flows are used in a detailed comparison of the univariate and bivariate flood frequency analysis. The results indicate that the data‐intensive fully distributed hydrological model performs poorly relative to the conceptually lumped IHACRES model at the study catchment in simulating the peak flows. Moreover, both univariate and copula‐based bivariate flood frequency analyses show similar peak flows for a given return period at the study catchment. Given that bivariate flood frequency analysis accounts for both peak flow and flood volume, it is recommended over the univariate flood frequency analysis since the results are widely applicable for flood planning and hydraulic structure designing the developing countries.","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"57 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Univariate versus multivariate flood frequency analysis in tropical region: Employing two classes of hydrological models\",\"authors\":\"Proloy Deb, Pragnaditya Malakar, Pradip Kumar Bora, Swatantra Kumar Dubey\",\"doi\":\"10.1002/clen.202300351\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Flood frequency analysis is critical in flood planning and management and hydraulic structures design. While univariate flood frequency analysis (using the peak flow) is still widely employed in developing countries, how does it compare to the robust copula‐based bivariate flood frequency analysis remains unknown. Moreover, there is also a decade‐long critical question whether less data requiring hydrological models can be an alternate to the data‐intensive models in flood prediction, especially in a developing tropical country like India? To answer these questions, this study aims in comparing two types of hydrological models (IHACRES, a less data requiring model, and VIC‐3L, a data‐intensive model) in simulating the peak flows, following which the simulated peak flows are used in a detailed comparison of the univariate and bivariate flood frequency analysis. The results indicate that the data‐intensive fully distributed hydrological model performs poorly relative to the conceptually lumped IHACRES model at the study catchment in simulating the peak flows. Moreover, both univariate and copula‐based bivariate flood frequency analyses show similar peak flows for a given return period at the study catchment. Given that bivariate flood frequency analysis accounts for both peak flow and flood volume, it is recommended over the univariate flood frequency analysis since the results are widely applicable for flood planning and hydraulic structure designing the developing countries.\",\"PeriodicalId\":10306,\"journal\":{\"name\":\"Clean-soil Air Water\",\"volume\":\"57 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clean-soil Air Water\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1002/clen.202300351\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clean-soil Air Water","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1002/clen.202300351","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

洪水频率分析对于洪水规划和管理以及水力结构设计至关重要。虽然单变量洪水频率分析(使用峰值流量)在发展中国家仍被广泛使用,但它与基于协整的稳健双变量洪水频率分析相比如何,仍是一个未知数。此外,还有一个长达十年之久的关键问题:对数据要求较低的水文模型能否替代数据密集型模型进行洪水预测,尤其是在印度这样的热带发展中国家?为了回答这些问题,本研究旨在比较两种水文模型(数据要求较低的 IHACRES 模型和数据密集型模型 VIC-3L)在模拟峰值流量方面的优劣,然后利用模拟的峰值流量对单变量和双变量洪水频率分析进行详细比较。结果表明,在研究集水区,数据密集型全分布式水文模型在模拟洪峰流量方面的表现要差于概念上的块状 IHACRES 模型。此外,单变量洪水频率分析和基于协方差的双变量洪水频率分析均显示,在研究流域的给定回归期内,洪峰流量相似。鉴于双变量洪水频率分析同时考虑了洪峰流量和洪水量,因此建议采用双变量洪水频率分析,而不是单变量洪水频率分析,因为其结果可广泛应用于发展中国家的洪水规划和水力结构设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Univariate versus multivariate flood frequency analysis in tropical region: Employing two classes of hydrological models
Flood frequency analysis is critical in flood planning and management and hydraulic structures design. While univariate flood frequency analysis (using the peak flow) is still widely employed in developing countries, how does it compare to the robust copula‐based bivariate flood frequency analysis remains unknown. Moreover, there is also a decade‐long critical question whether less data requiring hydrological models can be an alternate to the data‐intensive models in flood prediction, especially in a developing tropical country like India? To answer these questions, this study aims in comparing two types of hydrological models (IHACRES, a less data requiring model, and VIC‐3L, a data‐intensive model) in simulating the peak flows, following which the simulated peak flows are used in a detailed comparison of the univariate and bivariate flood frequency analysis. The results indicate that the data‐intensive fully distributed hydrological model performs poorly relative to the conceptually lumped IHACRES model at the study catchment in simulating the peak flows. Moreover, both univariate and copula‐based bivariate flood frequency analyses show similar peak flows for a given return period at the study catchment. Given that bivariate flood frequency analysis accounts for both peak flow and flood volume, it is recommended over the univariate flood frequency analysis since the results are widely applicable for flood planning and hydraulic structure designing the developing countries.
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
Clean-soil Air Water
Clean-soil Air Water 环境科学-海洋与淡水生物学
CiteScore
2.80
自引率
5.90%
发文量
88
审稿时长
3.6 months
期刊介绍: CLEAN covers all aspects of Sustainability and Environmental Safety. The journal focuses on organ/human--environment interactions giving interdisciplinary insights on a broad range of topics including air pollution, waste management, the water cycle, and environmental conservation. With a 2019 Journal Impact Factor of 1.603 (Journal Citation Reports (Clarivate Analytics, 2020), the journal publishes an attractive mixture of peer-reviewed scientific reviews, research papers, and short communications. Papers dealing with environmental sustainability issues from such fields as agriculture, biological sciences, energy, food sciences, geography, geology, meteorology, nutrition, soil and water sciences, etc., are welcome.
期刊最新文献
Issue Information: Clean Soil Air Water. 11/2024 Effect of Intercropping Soybean on the Diversity of the Rhizosphere Soil Arbuscular Mycorrhizal Fungi Communities in Wheat Field Short-Term Benefits of Tillage and Agronomic Biofortification for Soybean–Wheat Cropping in Central India Issue Information: Clean Soil Air Water. 10/2024 Geochemical Interaction and Bioavailability of Zinc in Soil Under Long-Term Integrated Nutrient Management in Pearl Millet–Wheat System
×
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