干旱区生态环境知识资源中心(Arid): Multiparameter Regression Modeling for Improving Quality of Measured Rainfall and Runoff Data in Densely Instrumented Watersheds

Arid

DOI	10.1061/(ASCE)HE.1943-5584.0001825
	Multiparameter Regression Modeling for Improving Quality of Measured Rainfall and Runoff Data in Densely Instrumented Watersheds
	Bitew, Menberu Meles 1; Goodrich, David C.1; Demaria, Eleonora 1; Heilman, Philip 1; Nichols, Mary 1; Levick, Lainie 2; Unkrich, Carl L.1; Kautz, Mark 1
通讯作者	Bitew, Menberu Meles
来源期刊	JOURNAL OF HYDROLOGIC ENGINEERING
ISSN	1084-0699
EISSN	1943-5584
出版年	2019
卷号	24 期号:10
英文摘要	The Walnut Gulch Experimental Watershed is a semi-arid experimental watershed and long-term agro-ecosystem research (LTAR) site managed by the USDA-Agricultural Research Services (ARS) Southwest Watershed Research Center for which high-resolution, long-term hydroclimatic data are available across its 149-km2 drainage area. Quality control and quality assurance of the massive data set are a major challenge. We present the analysis of 50 years of data sets to develop a strategy to identify errors and inconsistencies in historical rainfall and runoff databases. A multiple regression model was developed to relate rainfall, watershed properties, and the antecedent conditions to runoff characteristics in 12 subwatersheds ranging in area from 0.002-94 km2. A regression model was developed based on 18 predictor variables, which produced predicted runoff with correlation coefficients ranging from 0.4-0.94 and Nash efficiency coefficients up to 0.76. The model predicted 92% of runoff events and 86% of no-runoff events. The modeling approach is a complement to existing quality assurance and quality control (QAQC) procedures and provides a specific method for ensuring that rainfall and runoff data in the USDA-ARS Walnut Gulch Experimental Watershed database are consistent and contain minimal error. The model has the potential for making runoff predictions in similar hydroclimatic environments with available high-resolution observations.
英文关键词	Walnut gulch Rainfall-runoff Multiparameter regression model Quality assurance and quality control (QAQC) Database Uncertainty Semiarid
类型	Article
语种	英语
国家	USA
收录类别	SCI-E
WOS记录号	WOS:000481578800006
WOS关键词	WALNUT GULCH ; SOIL-MOISTURE ; NETWORK ; CATCHMENT ; SCALE ; OBSERVATORIES ; BASIN ; FLOW
WOS类目	Engineering, Civil ; Environmental Sciences ; Water Resources
WOS研究方向	Engineering ; Environmental Sciences & Ecology ; Water Resources
来源机构	University of Arizona
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/217116
作者单位	1.USDA ARS, Southwestern Watershed Res Ctr, Tucson, AZ 85719 USA; 2.Univ Arizona, Sch Nat Resources & Environm, Tucson, AZ 85721 USA
推荐引用方式 GB/T 7714	Bitew, Menberu Meles,Goodrich, David C.,Demaria, Eleonora,et al. Multiparameter Regression Modeling for Improving Quality of Measured Rainfall and Runoff Data in Densely Instrumented Watersheds[J]. University of Arizona,2019,24(10).
APA	Bitew, Menberu Meles.,Goodrich, David C..,Demaria, Eleonora.,Heilman, Philip.,Nichols, Mary.,...&Kautz, Mark.(2019).Multiparameter Regression Modeling for Improving Quality of Measured Rainfall and Runoff Data in Densely Instrumented Watersheds.JOURNAL OF HYDROLOGIC ENGINEERING,24(10).
MLA	Bitew, Menberu Meles,et al."Multiparameter Regression Modeling for Improving Quality of Measured Rainfall and Runoff Data in Densely Instrumented Watersheds".JOURNAL OF HYDROLOGIC ENGINEERING 24.10(2019).