Human impact parameterizations in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study
| Autor: | Simon N. Gosling, Yusuke Satoh, Dieter Gerten, H. de Moel, H. Müller Schmied, Felix T. Portmann, Philip J. Ward, Jeroen C. J. H. Aerts, Yoshihide Wada, Yadu Pokhrel, Fang Zhao, Yoshimitsu Masaki, Xingcai Liu, Ted Veldkamp, Jamal Zaherpour |
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| Přispěvatelé: | Water and Climate Risk |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
human impact
010504 meteorology & atmospheric sciences 0208 environmental biotechnology 02 engineering and technology 01 natural sciences Model validation multi-model validation hydrological extremes global hydrological modeling fresh water resources 0105 earth and related environmental sciences General Environmental Science Renewable Energy Sustainability and the Environment Discharge Public Health Environmental and Occupational Health SDG 10 - Reduced Inequalities Performance results 6. Clean water 020801 environmental engineering Catchment hydrology 13. Climate action Climatology Environmental science Performance indicator |
| Zdroj: | Environmental Research Letters, 13(5):055008, 1-16. IOP Publishing Ltd. Environmental research letters, 13(5):055008 Veldkamp, T I E, Zhao, F, Ward, P J, De Moel, H, Aerts, J C J H, Schmied, H M, Portmann, F T, Masaki, Y, Pokhrel, Y, Liu, X, Satoh, Y, Gerten, D, Gosling, S N, Zaherpour, J & Wada, Y 2018, ' Human impact parameterizations in global hydrological models improve estimates of monthly discharges and hydrological extremes : A multi-model validation study ', Environmental Research Letters, vol. 13, no. 5, 055008, pp. 1-16 . https://doi.org/10.1088/1748-9326/aab96f |
| ISSN: | 1748-9326 |
| DOI: | 10.1088/1748-9326/aab96f |
| Popis: | Human activity has a profound influence on river discharges, hydrological extremes and water-related hazards. In this study, we compare the results of five state-of-the-art global hydrological models (GHMs) with observations to examine the role of human impact parameterizations (HIP) in the simulation of mean, high- and low-flows. The analysis is performed for 471 gauging stations across the globe for the period 1971-2010. We find that the inclusion of HIP improves the performance of the GHMs, both in managed and near-natural catchments. For near-natural catchments, the improvement in performance results from improvements in incoming discharges from upstream managed catchments. This finding is robust across the GHMs, although the level of improvement and the reasons for it vary greatly. The inclusion of HIP leads to a significant decrease in the bias of the long-term mean monthly discharge in 36%-73% of the studied catchments, and an improvement in the modeled hydrological variability in 31%-74% of the studied catchments. Including HIP in the GHMs also leads to an improvement in the simulation of hydrological extremes, compared to when HIP is excluded. Whilst the inclusion of HIP leads to decreases in the simulated high-flows, it can lead to either increases or decreases in the low-flows. This is due to the relative importance of the timing of return flows and reservoir operations as well as their associated uncertainties. Even with the inclusion of HIP, we find that the model performance is still not optimal. This highlights the need for further research linking human management and hydrological domains, especially in those areas in which human impacts are dominant. The large variation in performance between GHMs, regions and performance indicators, calls for a careful selection of GHMs, model components and evaluation metrics in future model applications. |
| Databáze: | OpenAIRE |
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