Abstract
AbstractLarge-scale hydrological models describing the terrestrial water balance at continental and global scales are increasingly being used in earth system modeling and climate impact assessments. However, because of incomplete process understanding and limits of the forcing data, model simulations remain uncertain. To quantify this uncertainty a multimodel ensemble of nine large-scale hydrological models was compared to observed runoff from 426 small catchments in Europe. The ensemble was built within the framework of the European Union Water and Global Change (WATCH) project. The models were driven with the same atmospheric forcing data. Models were evaluated with respect to their ability to capture the interannual variability of spatially aggregated annual time series of five runoff percentiles—derived from daily time series—including annual low and high flows. Overall, the models capture the interannual variability of low, mean, and high flows well. However, errors in the mean and standard deviation, as well as differences in performance between the models, became increasingly pronounced for low runoff percentiles, reflecting the uncertainty associated with the representation of hydrological processes, such as the depletion of soil moisture stores. The large spread in model performance implies that any single model should be applied with caution as there is a great risk of biased conclusions. However, this large spread is contrasted by the good overall performance of the ensemble mean. It is concluded that the ensemble mean is a pragmatic and reliable estimator of spatially aggregated time series of annual low, mean, and high flows across Europe.
Highlights
Large-scale hydrological models have proved to be valuable tools for assessing fluctuations in terrestrial water stores and fluxes on continental and global scales (e.g., Dirmeyer 2011; Dirmeyer et al 2006; Milly et al 2005)
Observed and modeled daily runoff series were aggregated into time series of annual runoff percentiles at five different percentile levels
A good model performance with respect to interannual variability of all runoff percentiles is most likely related to the fact that the dynamics of annual runoff closely follow those of the atmospheric drivers
Summary
Large-scale hydrological models have proved to be valuable tools for assessing fluctuations in terrestrial water stores and fluxes on continental and global scales (e.g., Dirmeyer 2011; Dirmeyer et al 2006; Milly et al 2005). Examples are the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS) (Henderson-Sellers et al 1995), the Global Soil Wetness Project (GSWP) (Oki et al 1999; Dirmeyer et al 2006; Dirmeyer 2011), and the Water Model Intercomparison Project (WaterMIP) (Haddeland et al 2011). These studies conclude that there are large differences between the models, which may be caused by incomplete process understanding, different parameter estimates, and imperfect atmospheric forcing data
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