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A Modified SCS-CN Method Incorporating Storm Duration and Antecedent Soil Moisture Estimation for Runoff Prediction
Shi, Wenhai1,2; Huang, Mingbin1,2; Gongadze, Kate5; Wu, Lianhai5; Huang, MB (reprint author), Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi Provinc, Peoples R China.; Huang, MB (reprint author), MWR, Yangling 712100, Shaanxi Provinc, Peoples R China.; Huang, MB (reprint author), Northwest A&F Univ, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi Provinc, Peoples R China.
SubtypeArticle
2017
Source PublicationWATER RESOURCES MANAGEMENT
ISSN0920-4741
description.correspondentemailhmingbin@yahoo.com
Volume31Issue:5Pages:1713-1727
AbstractIn one of the widely used methods to estimate surface runoff -Soil Conservation Service Curve Number (SCS-CN), the antecedent moisture condition (AMC) is categorized into three AMC levels causing irrational abrupt jumps in estimated runoff. A few improved SCS-CN methods have been developed to overcome several in-built inconsistencies in the soil moisture accounting (SMA) procedure that lies behind the SCS-CN method. However, these methods still inherit the structural inconsistency in the SMA procedure. In this study, a modified SCS-CN method was proposed based on the revised SMA procedure incorporating storm duration and a physical formulation for estimating antecedent soil moisture (V0). The proposed formulation for V-0 estimation has shown a high degree of applicability in simulating the temporal pattern of soil moisture in the experimental plot. The modified method was calibrated and validated using a dataset of 189 storm-runoff events from two experimental watersheds in the Chinese Loess Plateau. The results indicated that the proposed method, which boosted the model efficiencies to 88% in both calibration and validation cases, performed better than the original SCS-CN and the Singh et al. (2015) method, a modified SCS-CN method based on SMA. The proposed method was then applied to a third watershed using the tabulated CN value and the parameters of the minimum infiltration rate (f(c)) and coefficient (beta) derived for the first two watersheds. The root mean square error between the measured and predicted runoff values was improved from 6 mm to 1 mm. Moreover, the parameter sensitivity analysis indicated that the potential maximum retention (S) parameter is the most sensitive, followed by f(c). It can be concluded that the modified SCS-CN method, may predict surface runoff more accurately in the Chinese Loess Plateau.
KeywordSoilmoisture Accounting Soil Conservation Service Curve Number Method Loess Plateau Watershed
Subject AreaEngineering ; Water Resources
DOI10.1007/s11269-017-1610-0
URL查看原文
Indexed BySCI
Publication PlaceDORDRECHT
Language英语
WOS IDWOS:000398042800018
PublisherSPRINGER
Funding OrganizationNSFC; NERC Newton Fund through the China-UK [41571130082, NE/N007433/1] ; NSFC; NERC Newton Fund through the China-UK [41571130082, NE/N007433/1]
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.iswc.ac.cn/handle/361005/8025
Collection水保所科研产出--SCI_2017--SCI
Corresponding AuthorHuang, MB (reprint author), Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi Provinc, Peoples R China.; Huang, MB (reprint author), MWR, Yangling 712100, Shaanxi Provinc, Peoples R China.; Huang, MB (reprint author), Northwest A&F Univ, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi Provinc, Peoples R China.
Affiliation1.Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi Provinc, Peoples R China
2.MWR, Yangling 712100, Shaanxi Provinc, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Northwest A&F Univ, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi Provinc, Peoples R China
5.Rothamsted Res, Okehampton EX20 2SB, Devon, England
Recommended Citation
GB/T 7714
Shi, Wenhai,Huang, Mingbin,Gongadze, Kate,et al. A Modified SCS-CN Method Incorporating Storm Duration and Antecedent Soil Moisture Estimation for Runoff Prediction[J]. WATER RESOURCES MANAGEMENT,2017,31(5):1713-1727.
APA Shi, Wenhai.,Huang, Mingbin.,Gongadze, Kate.,Wu, Lianhai.,Huang, MB .,...&Huang, MB .(2017).A Modified SCS-CN Method Incorporating Storm Duration and Antecedent Soil Moisture Estimation for Runoff Prediction.WATER RESOURCES MANAGEMENT,31(5),1713-1727.
MLA Shi, Wenhai,et al."A Modified SCS-CN Method Incorporating Storm Duration and Antecedent Soil Moisture Estimation for Runoff Prediction".WATER RESOURCES MANAGEMENT 31.5(2017):1713-1727.
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