Large Uncertainties in Runoff Estimations of GLDAS Versions 2.0 and 2.1 in China

Abstract

Gauge observed runoff can reflect influences of both natural hydrological cycle and human intervention. The Global Land Data Assimilation System (GLDAS) 2.0 and 2.1 provide abundant runoff which are useful for water resources assessment in ungauged/poorly gauged regions. However, GLDAS2.0 and GLDAS2.1 runoff have only been validated and inter-compared in very limited regions. In this study, they are evaluated and inter-compared utilizing gauge observation in 11 large river basins in China. Results show their runoff have large uncertainties: absolute values of relative bias (|RB|) being above 39% and Nash-Sutcliffe efficiency lower than 0.15 on average, but GLDAS2.1 is better. Both of them have large uncertainty in the Tibetan Plateau:|RB|are higher than 40%. The gap between GLDAS runoff and observations could attribute to both GLDAS system uncertainty and the fact that GLDAS does not consider human intervention. Therefore, cautions should be taken when using them in coupled human-natural systems.