Abstract
Global and continental scale hydrological reanalysis datasets receive growing attention due to their increasing number of applications, ranging from water resources management, climate change studies, water related hazards and policy support. Until recently, their use was mostly limited to qualitative assessments, due to their coarse spatial and temporal resolution, large uncertainty and bias in the model output, and limited extent of the dataset in space and time. This research reports on the setup of a gridded hydrological model with quasi-global coverage, able to reproduce a seamless 39-year streamflow simulation in all world’s medium to large river basins. The model was calibrated at 1226 river sections with a total drainage area of 51 million km2 within 66 countries, using ECMWF’s latest atmospheric reanalysis ERA5. A performance assessment revealed large improvements in reproducing past discharge observations, in comparison to the calibration used in the current operational setup of the hydrological model as part of the Copernicus – Global Flood Awareness System (GloFAS, www.globalfloods.eu), with median scores of Kling-Gupta Efficiency KGE = 0.67 and correlation r = 0.8. The simulation bias was also dramatically reduced and narrowed around zero, with more than 60% of stations showing percent bias within ±20%. Pronounced regional differences in the simulation results remain, pointing out the need for detailed investigation of the hydrological processes in specific regions, including parts of Africa and South Asia. In addition, observed discharges with high data quality is key to achieving skillful model output. The new calibrated model will become part of the operational runs of GloFAS in the next system release foreseen for Spring 2020, together with a near real time extension of the streamflow reanalysis.
Highlights
Knowledge of the hydrological states and their variability in space and time on our planet is key information for a variety of disciplines, including water resources, natural hazards, biodiversity, and energy production
In this work we report on the development of a semi-automated calibration procedure of a large scale hydrological model that underpins the Global Flood Awareness System (GloFAS, www.globalfloods.eu, see Alfieri et al, 2013; Hirpa et al, 2018), to improve the simulated output discharge by tuning a set of model parameters
Such model differs from the operational GloFAS setup, which is based on a combination of the Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (HTESSEL, Balsamo et al, 2011), ECMWF’s land surface scheme, and a simplified version of Lisflood to simulate the groundwater processes and the river routing
Summary
Knowledge of the hydrological states and their variability in space and time on our planet is key information for a variety of disciplines, including water resources, natural hazards, biodiversity, and energy production. Coordinated multi-model initiatives such as the WaterMIP (Haddeland et al, 2011) and the Earth2Observe (Schellekens et al, 2017) projects aimed to characterize the variability of the simulated runoff in large rivers using ensembles of global hydrological simulations produced at the common grid resolution of 0.5°. Both projects acknowledged the added value of an ensemble of simulations, results showed large discrepancies due to different concepts and parameterization in modeling the runoff generation (Schellekens et al, 2017) and the lack of a common protocol to calibrate and validate the participating models
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