Sensitivity analysis of hydrological model parameters based on improved Morris method with the double-Latin hypercube sampling

IF 2.7 4区 环境科学与生态学 Q2 Environmental Science Hydrology Research Pub Date : 2023-01-20 DOI:10.2166/nh.2023.109
Delong Li, Q. Ju, Peng Jiang, Ping Huang, Xiaohua Xu, Qin Wang, Z. Hao, Yueguan Zhang
{"title":"Sensitivity analysis of hydrological model parameters based on improved Morris method with the double-Latin hypercube sampling","authors":"Delong Li, Q. Ju, Peng Jiang, Ping Huang, Xiaohua Xu, Qin Wang, Z. Hao, Yueguan Zhang","doi":"10.2166/nh.2023.109","DOIUrl":null,"url":null,"abstract":"\n Sensitivity analysis of hydrological model parameters is a crucial step in the calibration process of hydrological simulation. In this paper, the improved Morris method with the double-Latin hypercube sampling is proposed for global sensitivity analysis of 10 parameters of the Xin'anjiang model. In addition, the local sensitivity is analyzed based on the rate validation of the model parameters. In general, the results show those parameters about evaporation coefficient in the deep layer (C), free water storage capacity (SM), impervious area as a percentage of total watershed area (IMP), free water storage capacity curve index (EX), groundwater outflow coefficient (KG) and subsurface runoff abatement factor (KKG) are all less than 0.01, insensitive parameters; the parameters about evaporation conversion factor (K) and square times of the storage capacity curve(B) are in the range of [0.01, 0.1], less sensitive parameters; the parameter about flow out coefficient in soil (KSS) is in the range of [0.1, 0.2], a low-sensitivity parameter; the parameter abatement coefficient of mid-soil flow (KKSS) is greater than 1, a high-sensitivity parameter; the improved Morris method better reflects the existence of interactions between parameters. This research result provides a new technical approach for the sensitivity analysis of hydrological model parameters.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrology Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.2166/nh.2023.109","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: 1

Abstract

Sensitivity analysis of hydrological model parameters is a crucial step in the calibration process of hydrological simulation. In this paper, the improved Morris method with the double-Latin hypercube sampling is proposed for global sensitivity analysis of 10 parameters of the Xin'anjiang model. In addition, the local sensitivity is analyzed based on the rate validation of the model parameters. In general, the results show those parameters about evaporation coefficient in the deep layer (C), free water storage capacity (SM), impervious area as a percentage of total watershed area (IMP), free water storage capacity curve index (EX), groundwater outflow coefficient (KG) and subsurface runoff abatement factor (KKG) are all less than 0.01, insensitive parameters; the parameters about evaporation conversion factor (K) and square times of the storage capacity curve(B) are in the range of [0.01, 0.1], less sensitive parameters; the parameter about flow out coefficient in soil (KSS) is in the range of [0.1, 0.2], a low-sensitivity parameter; the parameter abatement coefficient of mid-soil flow (KKSS) is greater than 1, a high-sensitivity parameter; the improved Morris method better reflects the existence of interactions between parameters. This research result provides a new technical approach for the sensitivity analysis of hydrological model parameters.
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
基于改进Morris法的双拉丁超立方采样水文模型参数敏感性分析
水文模型参数的灵敏度分析是水文模拟定标过程中的关键环节。本文针对新安江模型10个参数的全局灵敏度分析,提出了双拉丁超立方体采样的Morris改进方法。此外,基于模型参数的速率验证,对局部灵敏度进行了分析。结果表明,深层蒸发系数(C)、自由蓄水量(SM)、不透水面积占流域总面积的百分比(IMP)、自由储水量曲线指数(EX)、地下水流出系数(KG)和地表径流消减因子(KKG)等参数均小于0.01,是不敏感的参数;关于蒸发转换因子(K)和存储容量曲线(B)的平方倍的参数在[0.01,0.1]的范围内,是不太敏感的参数;土壤流出系数(KSS)参数在[0.1,0.2]范围内,是一个低灵敏度参数;中层土壤流参数消减系数大于1,为高灵敏度参数;改进的Morris方法更好地反映了参数之间相互作用的存在。该研究成果为水文模型参数的敏感性分析提供了一种新的技术途径。
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