Development of an ice-jam flood forecasting modelling framework for freeze-up/winter breakup

IF 2.7 4区 环境科学与生态学 Q2 Environmental Science Hydrology Research Pub Date : 2023-04-13 DOI:10.2166/nh.2023.073
A. Das, S. Budhathoki, K. Lindenschmidt
{"title":"Development of an ice-jam flood forecasting modelling framework for freeze-up/winter breakup","authors":"A. Das, S. Budhathoki, K. Lindenschmidt","doi":"10.2166/nh.2023.073","DOIUrl":null,"url":null,"abstract":"\n River ice-jams can create severe flooding along many rivers in cold regions. While ice-jams often form during the spring breakup, the mid-winter breakup can cause ice-jamming and flooding. Although many studies have already been focused on forecasting spring ice-jam flooding, studies related to forecasting mid-winter breakup jamming and flooding severity are sparse. The main purpose of this research is to develop a stochastic framework to forecast the severity of mid-winter ice-jam flooding along the transborder (New Brunswick/Maine) Saint John River of North America. A combination of hydrological (MESH) and hydraulic model (RIVICE) simulations was applied to develop the stochastic framework. A mid-winter breakup along the river that occurred in 2018 has been hindcasted as a case study. The result shows that the modelling framework can capture the real-time ice-jam severity. The results of this research will help to improve the capacity of ice-jam flood management in cold regions.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2023-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrology Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.2166/nh.2023.073","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 2

Abstract

River ice-jams can create severe flooding along many rivers in cold regions. While ice-jams often form during the spring breakup, the mid-winter breakup can cause ice-jamming and flooding. Although many studies have already been focused on forecasting spring ice-jam flooding, studies related to forecasting mid-winter breakup jamming and flooding severity are sparse. The main purpose of this research is to develop a stochastic framework to forecast the severity of mid-winter ice-jam flooding along the transborder (New Brunswick/Maine) Saint John River of North America. A combination of hydrological (MESH) and hydraulic model (RIVICE) simulations was applied to develop the stochastic framework. A mid-winter breakup along the river that occurred in 2018 has been hindcasted as a case study. The result shows that the modelling framework can capture the real-time ice-jam severity. The results of this research will help to improve the capacity of ice-jam flood management in cold regions.
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
结冰/冬季破裂的冰塞洪水预测建模框架的开发
在寒冷地区,河流结冰堵塞会导致许多河流发生严重洪灾。虽然冰塞通常在春季破裂时形成,但隆冬破裂会导致冰塞和洪水。尽管许多研究已经集中在预测春季冰塞洪水上,但与预测冬季中期冰塞和洪水严重程度有关的研究却很少。本研究的主要目的是开发一个随机框架来预测北美跨界(新不伦瑞克/缅因州)圣约翰河冬季中期冰塞洪水的严重程度。将水文(MESH)和水力模型(RIVICE)模拟相结合来开发随机框架。2018年发生的一次冬季中期河流决裂已被推迟作为一项案例研究。结果表明,该建模框架能够实时捕捉冰塞的严重程度。研究结果将有助于提高寒冷地区冰塞洪水管理能力。
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
Hydrology Research
Hydrology Research Environmental Science-Water Science and Technology
CiteScore
5.30
自引率
7.40%
发文量
70
审稿时长
17 weeks
期刊介绍: Hydrology Research provides international coverage on all aspects of hydrology in its widest sense, and welcomes the submission of papers from across the subject. While emphasis is placed on studies of the hydrological cycle, the Journal also covers the physics and chemistry of water. Hydrology Research is intended to be a link between basic hydrological research and the practical application of scientific results within the broad field of water management.
期刊最新文献
Prediction of flash flood peak discharge in hilly areas with ungauged basins based on machine learning Effects of tributary inflows on unsteady flow hysteresis and hydrodynamics in the mainstream Drought mitigation operation of water conservancy projects under severe droughts Water quality level estimation using IoT sensors and probabilistic machine learning model Design storm parameterisation for urban drainage studies derived from regional rainfall datasets: A case study in the Spanish Mediterranean region
×
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