Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts
| Autor: | Dieter Gerten, Guoyong Leng, Nick J. Mount, Hyungjun Kim, Simon N. Gosling, Ted Veldkamp, Yadu Pokhrel, Ingjerd Haddeland, Yusuke Satoh, Naota Hanasaki, Junguo Liu, Jacob Schewe, Jamal Zaherpour, Lukas Gudmundsson, Taikan Oki, Stephanie Eisner, Hannes Müller Schmied, Yoshihide Wada, Yoshimitsu Masaki, Rutger Dankers |
|---|---|
| Přispěvatelé: | Water and Climate Risk |
| Rok vydání: | 2018 |
| Předmět: |
extreme events
model evaluation model validation 010504 meteorology & atmospheric sciences global hydrological models 0208 environmental biotechnology Magnitude (mathematics) 02 engineering and technology land surface models human impacts 01 natural sciences Water scarcity Time series 0105 earth and related environmental sciences General Environmental Science Flood myth Renewable Energy Sustainability and the Environment Public Health Environmental and Occupational Health Replicate 6. Clean water 020801 environmental engineering 13. Climate action Climatology Environmental science Metric (unit) Surface runoff Scale (map) SDG 6 - Clean Water and Sanitation |
| Zdroj: | Environmental Research Letters, 13 (6) Environmental research letters, 13(6):065015 Environmental Research Letters 13 (2018) 6 Zaherpour, J, Gosling, S N, Mount, N, Schmied, H M, Veldkamp, T I E, Dankers, R, Eisner, S, Gerten, D, Gudmundsson, L, Haddeland, I, Hanasaki, N, Kim, H, Leng, G, Liu, J, Masaki, Y, Oki, T, Pokhrel, Y, Satoh, Y, Schewe, J & Wada, Y 2018, ' Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts ', Environmental Research Letters, vol. 13, no. 6, 065015, pp. 1-18 . https://doi.org/10.1088/1748-9326/aac547 Environmental Research Letters, 13(6) Environmental Research Letters, 13(6):065015, 1-18. IOP Publishing Ltd. |
| ISSN: | 1748-9318 1748-9326 |
| DOI: | 10.1088/1748-9326/aac547 |
| Popis: | Global-scale hydrological models are routinely used to assess water scarcity, flood hazards and droughts worldwide. Recent efforts to incorporate anthropogenic activities in these models have enabled more realistic comparisons with observations. Here we evaluate simulations from an ensemble of six models participating in the second phase of the Inter-Sectoral Impact Model Inter-comparison Project (ISIMIP2a). We simulate observed monthly runoff in 40 catchments, spatially distributed across 8 global hydrobelts. The performance of each model and the ensemble mean is examined with respect to their ability to replicate observed mean and extreme runoff under human-influenced conditions. Application of a novel integrated evaluation metric to quantify the models’ ability to simulate timeseries of monthly runoff suggests that the models generally perform better in the wetter equatorial and northern hydrobelts than in drier southern hydrobelts. When model outputs are temporally aggregated to assess mean annual and extreme runoff, the models perform better. Nevertheless, we find a general trend in the majority of models towards the overestimation of mean annual runoff and all indicators of upper and lower extreme runoff. There are particular challenges associated with reproducing both the timing and magnitude of seasonal cycles; the models struggle to capture the timing of the seasonal cycle, particularly in northern hydrobelts, while in southern hydrobelts the models struggle to reproduce the magnitude of the seasonal cycle. It is noteworthy that over all hydrological indicators, the ensemble mean fails to perform better than any individual model – a finding that challenges the commonly held perception that model ensemble estimates deliver superior performance over individual models. The study highlights the need for continued model development and improvement. It also suggests that caution should be taken when summarising the simulations from a model ensemble based upon its mean output. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|