Evaluating Global Reanalysis Datasets as Input for Hydrological Modelling in the Sudano-Sahel Region

Abstract

This paper investigates the potential of using global reanalysis datasets as input for hydrological modelling in the data-scarce Sudano-Sahel region. To achieve this, we used two global atmospheric reanalyses (Climate Forecasting System Reanalysis and European Center for Medium-Range Weather Forecasts (ECMWF) ERA-Interim) datasets and one global meteorological forcing dataset WATCH Forcing Data methodology applied to ERA-Interim (WFDEI). These datasets were used to drive the Soil and Water Assessment Tool (SWAT) in the Logone catchment in the Lake Chad basin. Model performance indicators after calibration showed that, at daily and monthly time steps, only WFDEI produced Nash Sutcliff Efficiency (NSE) and Coefficient of Determination (R 2 ) values above 0.50. Despite a general underperformance compared to WFDEI, CFSR performed better than the ERA-Interim. Model uncertainty analysis after calibration showed that more than 60% of all daily and monthly observed streamflow values at all hydrometric stations were bracketed within the 95 percent prediction uncertainty (95PPU) range for all datasets. Results from this study also show significant differences in simulated actual evapotranspiration estimates from the datasets. Overall results showed that biased corrected WFDEI outperformed the two reanalysis datasets; meanwhile CFSR performed better than the ERA-Interim. We conclude that, in the absence of gauged hydro-meteorological data, WFDEI and CFSR could be used for hydrological modelling in data-scarce areas such as the Sudano-Sahel region.

Effect of single and multi-site calibration techniques on hydrological model performance, parameter estimation and predictive uncertainty: a case study in the Logone catchment, Lake Chad basin

“…Andersson et al (2015) used WFDEI as input to drive Hydrological Prediction of the Environment (HYPE) across different basins in Europe and Africa and concluded that, this dataset improved streamflow simulation compared to Watch Forcing Data (WFD) based on ERA-40. In a previous study Nkiaka et al (2017), compared the performance of CFSR, ERA-Interim and WFDEI for hydrological modelling in the Logone catchment and concluded that, WFDEI outperformed the other two datasets in simulating streamflow.…”

Spatial Downscaling of Satellite-Based Precipitation and Its Impact on Discharge Simulations in the Magdalena River Basin in Colombia

“…Previously, the hydrological model was calibrated with interpolated in situ precipitation data at 1 km resolution. Some previous studies calibrated the model for each precipitation dataset to evaluate the sensitivity of model parameters to precipitation (Andréassian et al, 2001;Nkiaka et al, 2017). In this study, model parameters are not optimized for each forcing aiming to avoid correcting precipitation errors through fine-tuning the hydrological processes representation in the model (sensitivity analysis).…”

“…), the hydrological model structure (Koren et al, 1999) and the considered spatial and time scales (Segond et al, 2007). Some studies stated that the impact of precipitation spatial resolution on discharge simulation was not significant (Gascon et al, 2015;Nkiaka et al, 2017). However, most studies (Andréassian et al, 2001;Smith et al, 2004;Schuurmans and Bierkens, 2006;Wagener et al, 2007;Arnaud et al, 2011;Fu et al, 2011;Zoccatelli et al, 2011;Emmanuel et al, 2012;Zhao et al, 2013;Lobligeois et al, 2014) showed that better model performances were obtained when representation of the spatial variability of precipitation was improved.…”

Science-policy interfaces

“…We recently investigated the science–policy interface as part of research into the impact of climate and hydrological changes on social and ecological vulnerability in the Lake Chad Basin (Nkiaka, Nawaz & Lovett, ,b, ,b). Our concern was that research often does not contribute to policy development that can solve societal problems, and there appears to be two parallel lines that do not intersect.…”