Separating Wet and Dry Years to Improve Calibration of SWAT in Barrett Watershed, Southern California

Xin Gao,Xingwei Chen,Trent Biggs,Huaxia Yao

doi:10.3390/w10030274

Abstract

Hydrological models often perform poorly in simulating dry years in regions with large inter-annual variability in rainfall. We calibrated the Soil and Water Assessment Tool (SWAT) model to dry and wet years separately, using the semi-arid Barrett watershed on the west coast of USA as an example. We used hydrological and meteorological data from 1980–2010 to calibrate the SWAT model parameters, compared the monthly runoff results simulated by SWAT using a traditional calibration for the entire runoff series with results using a calibration with the wet and dry year series, and analyzed differences in the most sensitive parameters between the wet and dry year series. The results showed that (1) the SWAT model calibrated to the entire runoff series produced significant differences in simulation efficiency between the wet years and dry years, with lower efficiency during the dry years; (2) the calibration with separate wet and dry years greatly enhanced the SWAT model’s simulation efficiency for both wet and dry years; (3) differences in hydrological conditions between wet and dry years were represented by changes in the values of the six most sensitive parameters, including baseflow recession rates, channel infiltration rates, Soil Conservation Service (SCS) curve number, soil evaporation, shallow aquifer flow, and soil water holding capacity. Future work can attempt to determine the physical processes that underlie these parameter changes and their impact on the hydrological response of the semi-arid watersheds.

Highlights

Distributed hydrologic models are effective tools for studying complex hydrological phenomena in watersheds under the influence of climate change and anthropogenic activities [1]
This study focused on the Barrett watershed, located in southwestern San Diego, California, on the west coast of the USA, simulated the monthly runoff based on a sensitivity analysis of the Soil Water Assessment Tool (SWAT) model parameters, analyzed the feasibility of dividing the data into wet and dry years for model calibration, and showed differences in the values of model parameters during wet and dry years, in order to improve the applicability of SWAT model to watersheds with different climates and watershed conditions
(3) Six main sensitive parameters of SWAT model (ALPHA_BF, CH_K2, CN2, ESCO, GWQMN, and SOL_AWC) were different between the wet and dry years, which indicated that the hydrological conditions or responses in this watershed were different between the wet and dry years

Summary

Introduction

Distributed hydrologic models are effective tools for studying complex hydrological phenomena in watersheds under the influence of climate change and anthropogenic activities [1]. Several studies [3,4] have shown differences in the simulation efficiency between the wet and dry seasons using the Soil Water Assessment Tool (SWAT) model, which is a typical and widely-used. Other hydrologic models show significant differences in simulation efficiency between wet and dry seasons [9,10]. One of the reasons for this is that some model assessment indices, such as the correlation coefficient (R2 ) and the Nash-Sutcliffe efficiency (NSE), better reflect the hydrological characteristics of wet periods, and the researcher cannot ensure that the simulations are acceptable in both wet and dry periods when the simulation of entire runoff series performs well [11]. At the Little River Experimental Watershed in Georgia, USA, the months were divided into a wet period (runoff coefficient > 0.1) and a dry period (runoff coefficient < 0.1); several parameters had different values during the wet and dry periods, including ALPHA_BF for baseflow, CH_K2 for channel routing, CN2 for curve number, ESCO for soil evaporation, and GWQMN for shallow aquifer flow [13]

Methods

Results

Conclusion