towards simplification of hydrologic modeling: identification of dominant processes

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ID: 134217
2016
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Abstract

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.

Reference Key
markstrom2016hydrologytowards Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;S. L. Markstrom;L. E. Hay;M. P. Clark
Journal materials research bulletin
Year 2016
DOI
10.5194/hess-20-4655-2016
URL
https://www.hydrol-earth-syst-sci.net/20/4655/2016/hess-20-4655-2016.pdf
Keywords
anthropology recreationenvironmental sciences sanitary engineeringgeography technologyenvironmental technology

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