Monte Carlo approach for modelling uncertainty in hydraulic flood routing in ephemeral streams in arid regions

IF 5.7 3区 环境科学与生态学 Q1 WATER RESOURCES
Applied Water Science Pub Date : 2026-09-22 Epub Date: 2026-09-25 DOI:10.1007/s13201-026-02970-3
Fahad Alzahrani, Abdulaziz Alqaraway, Abdullah Alodah, Amro Elfeki
{"title":"Monte Carlo approach for modelling uncertainty in hydraulic flood routing in ephemeral streams in arid regions","authors":"Fahad Alzahrani,&nbsp;Abdulaziz Alqaraway,&nbsp;Abdullah Alodah,&nbsp;Amro Elfeki","doi":"10.1007/s13201-026-02970-3","DOIUrl":null,"url":null,"abstract":"<div><p>Flood routing in ephemeral streams of arid regions is characterized by high uncertainty due to limited data, variable transmission losses, and the transient nature of flow events. To address these challenges, this study introduces a newly developed convection–decay-based flood routing model that captures both the translation of the flood wave and the attenuation of peak discharge and volume caused by channel transmission losses. The model simulates hydrograph evolution in response to uncertain hydraulic conditions typical of arid environments. The model is applied to the Yiba Basin in western Saudi Arabia, a highly arid and data-scarce watershed where steep upstream slopes, permeable alluvial channels, and substantial infiltration losses strongly influence flood-wave propagation. The analysis uses observed inflow and outflow hydrographs from four hydrometric stations and 22 historical storm events. Uncertainty in flood-wave travel time and peak decay is incorporated using a Monte Carlo simulation framework. One thousand realizations are generated by randomly sampling the lag time between stations (<i>K</i>) and the decay factor (<i>λ</i>) from their fitted probability distributions to produce an ensemble of plausible outflow hydrographs while reflecting the natural variability in ephemeral channels. The resulting ensemble of simulated outflow hydrographs falls within a 90% confidence interval in most of the events. Flood peaks and volumes lie extremely close to the 1-to-1 line, indicating a highly successful and robust model for future predictions (r = 0.72 and RMSE = 30.9 m<sup>3</sup>/s for peak flows, and r = 0.73 and RMSE = 11.9 MCM for runoff volume). The probabilistic framework enables a more realistic and risk-informed understanding of flood behavior, supporting sustainable flood management in data-scarce arid regions. This approach offers a practical and adaptable tool for resilient infrastructure design and disaster preparedness under uncertain hydrologic conditions.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 10","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02970-3.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Water Science","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s13201-026-02970-3","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/9/25 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 0

Abstract

Flood routing in ephemeral streams of arid regions is characterized by high uncertainty due to limited data, variable transmission losses, and the transient nature of flow events. To address these challenges, this study introduces a newly developed convection–decay-based flood routing model that captures both the translation of the flood wave and the attenuation of peak discharge and volume caused by channel transmission losses. The model simulates hydrograph evolution in response to uncertain hydraulic conditions typical of arid environments. The model is applied to the Yiba Basin in western Saudi Arabia, a highly arid and data-scarce watershed where steep upstream slopes, permeable alluvial channels, and substantial infiltration losses strongly influence flood-wave propagation. The analysis uses observed inflow and outflow hydrographs from four hydrometric stations and 22 historical storm events. Uncertainty in flood-wave travel time and peak decay is incorporated using a Monte Carlo simulation framework. One thousand realizations are generated by randomly sampling the lag time between stations (K) and the decay factor (λ) from their fitted probability distributions to produce an ensemble of plausible outflow hydrographs while reflecting the natural variability in ephemeral channels. The resulting ensemble of simulated outflow hydrographs falls within a 90% confidence interval in most of the events. Flood peaks and volumes lie extremely close to the 1-to-1 line, indicating a highly successful and robust model for future predictions (r = 0.72 and RMSE = 30.9 m3/s for peak flows, and r = 0.73 and RMSE = 11.9 MCM for runoff volume). The probabilistic framework enables a more realistic and risk-informed understanding of flood behavior, supporting sustainable flood management in data-scarce arid regions. This approach offers a practical and adaptable tool for resilient infrastructure design and disaster preparedness under uncertain hydrologic conditions.

用蒙特卡罗方法模拟干旱地区短暂河流中水力洪水路径的不确定性
由于有限的数据、可变的传输损失和流动事件的瞬态性质,干旱地区短暂河流的洪水路径具有很高的不确定性。为了解决这些挑战,本研究引入了一种新开发的基于对流衰减的洪水路由模型,该模型既可以捕获洪水波的平移,也可以捕获由通道传输损失引起的峰值流量和体积的衰减。该模型模拟了水文曲线的演变,以响应干旱环境中典型的不确定水力条件。该模型应用于沙特阿拉伯西部的伊巴盆地,这是一个高度干旱和数据稀缺的流域,上游陡峭的斜坡,渗透性冲积河道和大量的入渗损失强烈影响洪水波的传播。该分析使用了四个水文站和22个历史风暴事件观测到的流入和流出的水文曲线。利用蒙特卡罗模拟框架,将洪水波传播时间和峰值衰减的不确定性结合起来。通过随机采样站点之间的滞后时间(K)和衰减因子(λ),从它们的拟合概率分布中产生一个貌似合理的流出水流图集合,同时反映了短暂通道的自然变异性,从而产生了1000个实现。在大多数事件中,模拟流出水流的综合结果落在90%的置信区间内。洪峰和洪量非常接近1对1线,表明该模型对未来的预测非常成功和稳健(洪峰流量r = 0.72, RMSE = 30.9 m3/s,径流量r = 0.73, RMSE = 11.9 MCM)。概率框架使人们能够更现实地了解洪水行为和风险,支持数据稀缺干旱地区的可持续洪水管理。该方法为不确定水文条件下的弹性基础设施设计和备灾提供了实用且适应性强的工具。
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
Applied Water Science
Applied Water Science WATER RESOURCES-
CiteScore
9.90
自引率
3.60%
发文量
268
审稿时长
13 weeks
期刊介绍:
×
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:604180095
Book学术官方微信
小红书