Evaluating the Potential of GloFAS-ERA5 River Discharge Reanalysis Data for Calibrating the SWAT Model in the Grande San Miguel River Basin (El Salvador)

Javier Senent-Aparicio,Patricia Jimeno-Sáez,Adrián López-Ballesteros,Julio Pérez-Sánchez,Pablo Blanco-Gómez

doi:10.3390/rs13163299

Abstract

Hydrological modelling requires accurate climate data with high spatial-temporal resolution, which is often unavailable in certain parts of the world—such as Central America. Numerous studies have previously demonstrated that in hydrological modelling, global weather reanalysis data provides a viable alternative to observed data. However, calibrating and validating models requires the use of observed discharge data, which is also frequently unavailable. Recent, global-scale applications have been developed based on weather data from reanalysis; these applications allow streamflows with satisfactory resolution to be obtained. An example is the Global Flood Awareness System (GloFAS), which uses the fifth generation of reanalysis data produced by the European Centre for Medium-Range Weather Forecasts (ERA5) as input. It provides discharge data from 1979 to the present with a resolution of 0.1°. This study assesses the potential of GloFAS for calibrating hydrological models in ungauged basins. For this purpose, the quality of data from ERA5 and from the Climate Hazards Group InfraRed Precipitation and Temperature with Station as well as the Climate Forecast System Reanalysis (CFSR) was analysed. The focus was on flow simulation using the Soil and Water Assessment Tool (SWAT) model. The models were calibrated using GloFAS discharge data. Our results indicate that all the reanalysis datasets displayed an acceptable fit with the observed precipitation and temperature data. The correlation coefficient (CC) between the reanalysis data and the observed data indicates a strong relationship at the monthly level all of the analysed stations (CC > 0.80). The Kling–Gupta Efficiency (KGE) also showed the acceptable performance of the calibrated SWAT models (KGE > 0.74). We concluded that GloFAS data has substantial potential for calibrating hydrological models that estimate the monthly streamflow in ungauged watersheds. This approach can aid water resource management.

Highlights

Using monthly flow data provided by the Ministry of Environment and Natural Resources in El Salvador for the period 2005–2010, we explored the potential of the GLoFAS-ERA5 river discharge reanalysis dataset for calibrating hydrological models in ungauged watersheds
Precipitation data was collected from the reanalysis data grid cells closest to the available weather stations; days with no observed data were omitted from the comparative analysis
These results demonstrate that when the ERA5 reanalysis data show an adequate fit, Global Flood Awareness System (GloFAS) discharge data could potentially be used to simulate the hydrological processes of ungauged catchments at the monthly scale

Summary

Introduction

Hydrological models are commonly used to understand changes in hydrological processes due to changes in the climatic or the land use [1,2]. Such changes in land use and climatic conditions are especially important in Central America. Climate change can strongly affect the hydrological cycle by altering the timing and intensity of rainfall, recharge and runoff. This change has intensified the mid-summer drought characteristic of Central America’s weather [4]

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