Hydrologic regionalization of non-stationary intensity–duration–frequency relationships for Indian mainland

IF 1.5 Q4 WATER RESOURCES
Meera G. Mohan, Akhilesh Ar, A. S., Badarinadh S, Ajeesh Krishnan, Anand Rajan
{"title":"Hydrologic regionalization of non-stationary intensity–duration–frequency relationships for Indian mainland","authors":"Meera G. Mohan, Akhilesh Ar, A. S., Badarinadh S, Ajeesh Krishnan, Anand Rajan","doi":"10.2166/h2oj.2023.023","DOIUrl":null,"url":null,"abstract":"\n \n Intensity–duration–frequency (IDF) curve is one of the important hydrologic tools used for the design of hydraulic infrastructure. The static return period assumption of precipitation extremes is invalid in a changing climate environment, and the underestimation of rainfall intensity may lead to the failure of infrastructure in extreme events. This study first developed the non-stationary (NS) IDF curves for six selected locations in India based on sub-daily station data based on time-dependent estimates of five combinations of Generalized Extreme Value (GEV) distribution parameters. Then, in order to identify the critical regions of rainfall non-stationarity, the IDF curves were developed for 357 grid points over India using the daily gridded data for the period 1951–2016 at 1° × 1° resolution. The comparison of spatial patterns of rainfall intensity estimates under stationary and non-stationary showed that about 23% of grids showed an overestimation of NS rainfall over their stationary counterparts by at least 15%. About 32 grid locations which showed at least 15% overestimation of rainfall under an NS case displayed a significantly increasing rainfall trend. The majority of the grids with larger deviation of non-stationary rainfall estimates over stationary values are located in India's eastern regions and coastal belts.","PeriodicalId":36060,"journal":{"name":"H2Open Journal","volume":" ","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"H2Open Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/h2oj.2023.023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 1

Abstract

Intensity–duration–frequency (IDF) curve is one of the important hydrologic tools used for the design of hydraulic infrastructure. The static return period assumption of precipitation extremes is invalid in a changing climate environment, and the underestimation of rainfall intensity may lead to the failure of infrastructure in extreme events. This study first developed the non-stationary (NS) IDF curves for six selected locations in India based on sub-daily station data based on time-dependent estimates of five combinations of Generalized Extreme Value (GEV) distribution parameters. Then, in order to identify the critical regions of rainfall non-stationarity, the IDF curves were developed for 357 grid points over India using the daily gridded data for the period 1951–2016 at 1° × 1° resolution. The comparison of spatial patterns of rainfall intensity estimates under stationary and non-stationary showed that about 23% of grids showed an overestimation of NS rainfall over their stationary counterparts by at least 15%. About 32 grid locations which showed at least 15% overestimation of rainfall under an NS case displayed a significantly increasing rainfall trend. The majority of the grids with larger deviation of non-stationary rainfall estimates over stationary values are located in India's eastern regions and coastal belts.
印度大陆非平稳强度-持续时间-频率关系的水文区划
强度-持续-频率(IDF)曲线是水利基础设施设计的重要水文工具之一。极端降水静态回归期假设在气候变化环境下是不成立的,对降水强度的低估可能导致极端事件中基础设施的失效。该研究首先基于基于广义极值(GEV)分布参数的五种组合的随时间估计的次日站点数据,开发了印度六个选定地点的非平稳(NS) IDF曲线。然后,为了识别降雨非平稳性的关键区域,利用1951-2016年1°× 1°分辨率的日格点数据,对印度357个格点的IDF曲线进行了开发。对平稳和非平稳条件下降雨强度估算的空间格局的比较表明,约23%的网格对NS降雨量的估计比平稳条件下的估算至少高估了15%。约有32个格点在NS情景下高估了至少15%的降雨量,显示出明显的降雨量增加趋势。非平稳降水估计值相对于平稳值偏差较大的大多数网格位于印度东部地区和沿海地带。
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
H2Open Journal
H2Open Journal Environmental Science-Environmental Science (miscellaneous)
CiteScore
3.30
自引率
4.80%
发文量
47
审稿时长
24 weeks
×
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