Implications of a Priori Parameters on Calibration in Conditions of Varying Terrain Characteristics: Case Study of the SAC-SMA Model in Eastern United States

Wafa Chouaib,Peter V Caldwell,Younes Alila

doi:10.3390/hydrology8020078

Abstract

This study seeks to advance the knowledge about the effect of a priori parameters on calibration using the Sacramento Soil Moisture accounting Model (SAC-SMA). We investigated the catchment characteristics where calibration is most affected by the limitations in the a priori parameters and we studied the effect on the modeled processes. The a priori parameters of SAC-SMA model parameters were determined from soil-derived physical expressions that make use of the soil’s physical properties. The study employed 63 catchments from the eastern United States (US). The model calibration employed the Shuffle-Complex algorithm (SCE-UA) and used the a priori parameters as default allowing for ±35% as a range of deviation. The model efficiency after calibration was sensitive to the catchment landscape properties, particularly the soil texture and topography. The highest efficiency was obtained in conditions of well-drained soils and flat topography where the saturation excess overland flow is predominant. Most of the catchments with smaller efficiency had poorly drained soils where mountainous and forested catchments of predominant subsurface stormflow had the lowest efficiency. The current regional study shows that improvements of SAC-SMA a priori parameters are crucial to foster their operational use for calibration and prediction at ungauged catchments.

Highlights

There has always been a need to understand the hydrological behavior of catchments at the regional scale because it drives the decisions of water resource planners and managers [1]
The need to evaluate Sacramento Soil Moisture accounting Model (SAC-SMA) a priori parameters and their effect on the calibration while gaining more advanced knowledge from conducting the analysis at a regional scale motivated the objective of this paper
The results suggested that soil physical properties obtained from the STATSGO soil map in conditions of poorly-drained soils require adjustments; those parameters responsible for simulating subsurface processes

Summary

Introduction

There has always been a need to understand the hydrological behavior of catchments at the regional scale because it drives the decisions of water resource planners and managers [1]. The regional evaluation of runoff processes and streamflow pattern provides some degree of predictability of the catchments’ behavior [2,3]. Streamflow analysis at a regional scale entails the use of hydrological modeling. The uncertainty due to model calibration and parameter estimation is among the challenges of hydrological modeling [4,5,6,7,8]. The technique of a priori parameter estimation was designed to facilitate the model parameterization and calibration [9]. The a priori parameters derive values directly from spatiotemporal data.

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Conclusion