2015
DOI: 10.1016/j.jhydrol.2015.08.061
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Significant uncertainty in global scale hydrological modeling from precipitation data errors

Abstract: Keywords:Global hydrological modeling Forcing uncertainty Model calibration Parameter uncertainty s u m m a r yIn the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on largescale hydrologic modeling and analyze the effect of parameter and rainfall data uncertain… Show more

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Cited by 59 publications
(29 citation statements)
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“…Second, this calibration strategy and resulted parameters are inevitably forcing-dependent, because the calibrated parameters can compensate forcing biases and model structure problems (Blöschl et al, 2007;Bock et al, 2016;Elsner et al, 2014;Merz et al, 2011;Weiland et al, 2015). This would reduce the skill of the model in replicating results outside of calibration conditions and increase the potential for equifinality of parameter sets and higher model uncertainty.…”
Section: Advantages and Disadvantages Of The Calibration Strategymentioning
confidence: 99%
“…Second, this calibration strategy and resulted parameters are inevitably forcing-dependent, because the calibrated parameters can compensate forcing biases and model structure problems (Blöschl et al, 2007;Bock et al, 2016;Elsner et al, 2014;Merz et al, 2011;Weiland et al, 2015). This would reduce the skill of the model in replicating results outside of calibration conditions and increase the potential for equifinality of parameter sets and higher model uncertainty.…”
Section: Advantages and Disadvantages Of The Calibration Strategymentioning
confidence: 99%
“…Inaccuracies in runoff estimation from GHMs and LSMs may be first attributed to the uncertainty in global satellite precipitation products (Tian and PetersLidard, 2010;Sperna Weiland et al, 2015), but several studies have shown considerable differences between model outputs even when using the same meteorological forcing, given the lack of knowledge about runoff generation processes and 30 deficiencies in parameter estimation (e.g., Haddeland et al, 2011;Gudmundsson et al, 2012;Zhou et al, 2012;Beck et al, 2017a). In particular, calibration has been found to have the largest impact on storage fluxes, evapotranspiration and Hydrol.…”
Section: Introductionmentioning
confidence: 99%
“…In this study we used simulated flows instead of measured flows to provide a spatially consistent picture that is not impeded by the heterogeneity of observed flow data. As a global hydrologic model, PCR-GLOBWB requires a wealth of input data to characterize global or continental variation in, amongst others, land-use, soil type, elevation, climatic conditions and groundwater table depths [57]. All these datasets are accompanied by a high degree of uncertainty, which compromises the performance of global hydrologic models [58].…”
Section: Resultsmentioning
confidence: 99%