Towards simplification of hydrologic modeling: identification of dominant processes

Steven L Markstrom,Lauren E Hay,Martyn P Clark

doi:10.5194/hess-20-4655-2016

Abstract

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.

Highlights

It has long been recognized that distributed-parameter hydrology models (DPHMs) are complex because of the subtlety and diversity of the hydrologic cycle which they aim to simulate (Freeze and Harlan, 1969; Amorocho and Hart, 1964)
This illustrates the spatial variability in parameter sensitivity and the importance that choice of performance statistic can make in terms of evaluation of hydrologic response
The hydrologic response units (HRUs) are colored according to the parameter sensitivity, which is computed by summing the first-order sensitivity for all 35 parameters separately for each of the 8 output variables, each corresponding to their respective process. (These sums do not necessarily add up to 1)

Summary

Introduction

It has long been recognized that distributed-parameter hydrology models (DPHMs) are complex because of the subtlety and diversity of the hydrologic cycle which they aim to simulate (Freeze and Harlan, 1969; Amorocho and Hart, 1964). In this article, distributed parameters are defined as model inputs that remain constant through time, but can vary spatially across the landscape. Those who apply these models often have difficulty with understanding what these parameters are and how they are used in the model. Duan et al (2006) describes “a gap in our understanding of the links between model parameters and the land surface characteristics”. These unmeasured parameters, ostensibly tangible, are really empirical coefficients when it comes to application and calibration (Samaniego et al, 2010)

Methods

Results

Discussion

Conclusion