DOI: 10.5194/hess-20-4655-2016
Scopus记录号: 2-s2.0-84997161451
论文题名: Towards simplification of hydrologic modeling: Identification of dominant processes
作者: Markstrom S ; L ; , Hay L ; E ; , Clark M ; P
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 11 起始页码: 4655
结束页码: 4671
语种: 英语
Scopus关键词: Runoff
; Soil moisture
; Calibration parameters
; Coefficient of variation
; Distributed parameter
; Fourier amplitude sensitivity tests
; Model-performance statistics
; Parameter sensitivities
; Parameter sensitivity analysis
; Performance statistics
; Sensitivity analysis
; amplitude
; calibration
; complexity
; hydrological modeling
; parameterization
; rainfall-runoff modeling
; sensitivity analysis
; United States
英文摘要: The Precipitation-Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many. © Author(s) 2016. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78683
Appears in Collections: 气候变化事实与影响
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作者单位: US Geological Survey, Denver Federal Center, P.O. Box 25046, MS 412, Denver, CO, United States; National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO, United States
Recommended Citation:
Markstrom S,L,, Hay L,et al. Towards simplification of hydrologic modeling: Identification of dominant processes[J]. Hydrology and Earth System Sciences,2016-01-01,20(11)