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Abstract. This study evaluates the ability of different griddedrainfall datasets to plausibly represent the spatio-temporal patterns ofmultiple hydrological processes (i.e. streamflow, actual evaporation, soilmoisture and terrestrial water storage) for large-scale hydrologicalmodelling in the predominantly semi-arid Volta River basin (VRB) in WestAfrica. Seventeen precipitation products based essentially ongauge-corrected satellite data (TAMSAT, CHIRPS, ARC, RFE, MSWEP, GSMaP,PERSIANN-CDR, CMORPH-CRT, TRMM 3B42 and TRMM 3B42RT) and on reanalysis (ERA5,PGF, EWEMBI, WFDEI-GPCC, WFDEI-CRU, MERRA-2 and JRA-55) are compared asinput for the fully distributed mesoscale Hydrologic Model (mHM). To assessthe model sensitivity to meteorological forcing during rainfall partitioninginto evaporation and runoff, six different temperature reanalysis datasetsare used in combination with the precipitation datasets, which results inevaluating 102 combinations of rainfall–temperature input data. The model isrecalibrated for each of the 102 input combinations, and the model responsesare evaluated by using in situ streamflow data and satellite remote-sensingdatasets from GLEAM evaporation, ESA CCI soil moisture and GRACEterrestrial water storage. A bias-insensitive metric is used to assess theimpact of meteorological forcing on the simulation of the spatial patternsof hydrological processes. The results of the process-based evaluation showthat the rainfall datasets have contrasting performances across the fourclimatic zones present in the VRB. The top three best-performing rainfalldatasets are TAMSAT, CHIRPS and PERSIANN-CDR for streamflow; ARC, RFE andCMORPH-CRT for terrestrial water storage; MERRA-2, EWEMBI/WFDEI-GPCC andPGF for the temporal dynamics of soil moisture; MSWEP, TAMSAT and ARC forthe spatial patterns of soil moisture; ARC, RFE and GSMaP-std for thetemporal dynamics of actual evaporation; and MSWEP, TAMSAT and MERRA-2 for thespatial patterns of actual evaporation. No single rainfall or temperaturedataset consistently ranks first in reproducing the spatio-temporalvariability of all hydrological processes. A dataset that is best inreproducing the temporal dynamics is not necessarily the best for thespatial patterns. In addition, the results suggest that there is moreuncertainty in representing the spatial patterns of hydrological processesthan their temporal dynamics. Finally, some region-tailored datasetsoutperform the global datasets, thereby stressing the necessity andimportance of regional evaluation studies for satellite and reanalysismeteorological datasets, which are increasingly becoming an alternative toin situ measurements in data-scarce regions.

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa