Performance evaluation of CFSR, MERRA-2 and TRMM3B42 data sets in simulating river discharge of data-scarce tropical catchments: a case study of Manafwa, Uganda

Abstract

Data scarcity has been a huge problem in modelling catchments especially in the tropical region. Satellite data and different statistical methods are being used to improve the quality of conventional meteorological data. However, their potential needs to be further investigated. This paper evaluates the performance of three datasets in simulating discharge of River Manafwa, Uganda. Two reanalysis datasets were selected for studying both rainfall and temperature, whereas a satellite algorithm was selected for studying rainfall alone. MERRA-2 data and CFSR were chosen as the reanalysis datasets whereas TRMM3B42 data were used as the satellite product in this study. The SWAT model was used to evaluate the performance of these datasets. The model performance indicators indicated that, at daily time steps, all the three datasets produced values of Nash-Sutcliffe Efficiency (NSE<0.4), coefficient of determination (R2<0.4) and Percent Bias +25%. Despite a general underperformance compared to MERRA-2, CFSR performed better than TRMM. On applying generated bias corrections for precipitation and temperature climate data, overall results showed that the bias-corrected data outperformed the original data. We conclude that, in the absence of gauged hydro-meteorological data, bias-corrected MERRA-2, CFSR and TRMM data could be used for simulating river discharge in data-scarce areas.