The impact of lake and reservoir parameterization on global streamflow simulation
| Autor: | Beatriz Revilla-Romero, Hylke E. Beck, Peter Burek, Feyera A. Hirpa, Peter Salamon, Zuzanna Zajac |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Hydrology
LISFLOOD geography geography.geographical_feature_category 0208 environmental biotechnology Flood forecasting Magnitude (mathematics) Forecast skill Context (language use) Parameterization 02 engineering and technology Research Papers 020801 environmental engineering Lakes Reservoirs Streamflow parasitic diseases Environmental science Global sensitivity and uncertainty analyses Hydrography Scale (map) Global streamflow Channel (geography) Water Science and Technology |
| Zdroj: | Journal of Hydrology |
| ISSN: | 1879-2707 0022-1694 |
| Popis: | Highlights • The effects of lakes and reservoirs on global daily streamflow are evaluated. • Reservoirs affect model performance substantially in the global domain. • Lakes’ effects on model performance are limited to few catchments. • Lakes and reservoirs reduce return levels discharge thresholds globally. • Reservoir parameters contribute to uncertainty of model performance metrics. Lakes and reservoirs affect the timing and magnitude of streamflow, and are therefore essential hydrological model components, especially in the context of global flood forecasting. However, the parameterization of lake and reservoir routines on a global scale is subject to considerable uncertainty due to lack of information on lake hydrographic characteristics and reservoir operating rules. In this study we estimated the effect of lakes and reservoirs on global daily streamflow simulations of a spatially-distributed LISFLOOD hydrological model. We applied state-of-the-art global sensitivity and uncertainty analyses for selected catchments to examine the effect of uncertain lake and reservoir parameterization on model performance. Streamflow observations from 390 catchments around the globe and multiple performance measures were used to assess model performance. Results indicate a considerable geographical variability in the lake and reservoir effects on the streamflow simulation. Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) metrics improved for 65% and 38% of catchments respectively, with median skill score values of 0.16 and 0.2 while scores deteriorated for 28% and 52% of the catchments, with median values −0.09 and −0.16, respectively. The effect of reservoirs on extreme high flows was substantial and widespread in the global domain, while the effect of lakes was spatially limited to a few catchments. As indicated by global sensitivity analysis, parameter uncertainty substantially affected uncertainty of model performance. Reservoir parameters often contributed to this uncertainty, although the effect varied widely among catchments. The effect of reservoir parameters on model performance diminished with distance downstream of reservoirs in favor of other parameters, notably groundwater-related parameters and channel Manning’s roughness coefficient. This study underscores the importance of accounting for lakes and, especially, reservoirs and using appropriate parameterization in large-scale hydrological simulations. |
| Databáze: | OpenAIRE |
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