Understanding the Influence of Hydrologic Parameter Uncertainty on Community Water Model Predictions: A Diagnostic Assessment through Extensive Ensemble Simulations

Land surface models (LSMs) play a crucial role in examining Earth's hydrological cycle and overseeing regional water resources. Despite their importance, there is a lack of a thorough exploration into the impact of parametric uncertainty on hydrological predictions across various regions and flow characteristics. To address this gap, we perform an extensive characterization of hydrologic parameter uncertainty in the Community Water Model (CWatM) across 481 basins spanning the Eurasian continent. In the presented datasets, we offer daily ensemble simulations covering a 30-year period from January 1981 to December 2010, employing 1,200 parameter sets. The dataset facilitates the identification of specific parametric uncertainties that have significant impacts on hydrological predictions.Land surface models (LSMs) play a crucial role in examining Earth's hydrological cycle and overseeing regional water resources. Despite their importance, there is a lack of a thorough exploration into the impact of parametric uncertainty on hydrological predictions across various regions and flow characteristics. To address this gap, we perform an extensive characterization of hydrologic parameter uncertainty in the Community Water Model (CWatM) across 481 basins spanning the Eurasian continent. In the presented datasets, we offer daily ensemble simulations covering a 30-year period from January 1981 to December 2010, employing 1,200 parameter sets. The dataset facilitates the identification of specific parametric uncertainties that have significant impacts on hydrological predictions.