How well do the multi-satellite and atmospheric reanalysis products perform in hydrological modelling

Abstract

Multi-satellite, gauge-based and atmospheric reanalysis precipitation and temperature datasets with increasing spatiotemporal resolution are proliferating in recent decades. Their estimation accuracy has been evaluated in several areas, but their applications in global hydrological monitoring and modelling have been poorly understood so far. Here, we focus on the performance of the recently released Multi-Source Weighted-Ensemble Precipitation, version 2 (MSWEP V2) and the atmospheric reanalysis ERA5 temperature in modelling daily river discharge over 10,596 global catchments. Four lumped models including XAJ, GR4J, HMETS, and HBV are employed to take different model conceptual schemes into consideration. Moreover, different streamflow conditions including the peak timing and volumes of both high and low flows are evaluated to reveal further dynamics. The results show that: (a) the MSWEP V2 and ERA5 combination yields satisfactory performance in global streamflow simulation with at least one candidate model exhibiting Kling-Gupta efficiency (KGE) > 0.5 at both calibration and validation periods for each catchment; (b) better simulation skills are achieved in temperate, cold, polar, and tropical Köppen-Geiger climate zones, whereas the arid zone has poorer performance; (c) the XAJ, GR4J, and HMETS models with different degree of realisms have their own merits in simulating both daily mean flow and wet flow conditions but perform less satisfactorily in low flow conditions, while the HBV exhibits consistently poor performance in various flow conditions over most catchments. Our findings highlight the importance of selecting appropriate hydrological models by considering both climatic and geophysical conditions and targeting streamflow metrics, and suggest the potential of using multi-satellite and atmospheric reanalysis datasets as observed alternatives for quasi-global hydrological modelling.