Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts
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 m...
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
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IOP Publishing
2018
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| Online Access: | https://eprints.nottingham.ac.uk/51860/ |
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| author | Zaherpour, Jamal Gosling, Simon N. Mount, Nick J. Müller Schmied, Hannes Veldkamp, Ted Dankers, Rutger Eisner, Stephanie Gerten, Dieter Gudmundsson, Lukas Haddeland, I. Hanasaki, Naota Kim, Hyungjun Leng, Guoyong Liu, Junguo Masaki, Yoshimitsu Oki, Taikan Pokhrel, Yadu Satoh, Yusuke Schewe, Jacob Wada, Yoshihide |
| author_facet | Zaherpour, Jamal Gosling, Simon N. Mount, Nick J. Müller Schmied, Hannes Veldkamp, Ted Dankers, Rutger Eisner, Stephanie Gerten, Dieter Gudmundsson, Lukas Haddeland, I. Hanasaki, Naota Kim, Hyungjun Leng, Guoyong Liu, Junguo Masaki, Yoshimitsu Oki, Taikan Pokhrel, Yadu Satoh, Yusuke Schewe, Jacob Wada, Yoshihide |
| author_sort | Zaherpour, Jamal |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T20:22:12Z |
| format | Article |
| id | nottingham-51860 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:22:12Z |
| publishDate | 2018 |
| publisher | IOP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-518602020-05-04T19:40:40Z https://eprints.nottingham.ac.uk/51860/ Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts Zaherpour, Jamal Gosling, Simon N. Mount, Nick J. Müller Schmied, Hannes Veldkamp, Ted Dankers, Rutger Eisner, Stephanie Gerten, Dieter Gudmundsson, Lukas Haddeland, I. Hanasaki, Naota Kim, Hyungjun Leng, Guoyong Liu, Junguo Masaki, Yoshimitsu Oki, Taikan Pokhrel, Yadu Satoh, Yusuke Schewe, Jacob Wada, Yoshihide 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. IOP Publishing 2018-06-12 Article PeerReviewed Zaherpour, Jamal, Gosling, Simon N., Mount, Nick J., Müller Schmied, Hannes, Veldkamp, Ted, Dankers, Rutger, Eisner, Stephanie, Gerten, Dieter, Gudmundsson, Lukas, Haddeland, I., Hanasaki, Naota, Kim, Hyungjun, Leng, Guoyong, Liu, Junguo, Masaki, Yoshimitsu, Oki, Taikan, Pokhrel, Yadu, Satoh, Yusuke, Schewe, Jacob and Wada, Yoshihide (2018) Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts. Environmental Research Letters, 13 (6). 065015. ISSN 1748-9326 global hydrological models land surface models human impacts extreme events model evaluation model validation http://iopscience.iop.org/article/10.1088/1748-9326/aac547 doi:10.1088/1748-9326/aac547 doi:10.1088/1748-9326/aac547 |
| spellingShingle | global hydrological models land surface models human impacts extreme events model evaluation model validation Zaherpour, Jamal Gosling, Simon N. Mount, Nick J. Müller Schmied, Hannes Veldkamp, Ted Dankers, Rutger Eisner, Stephanie Gerten, Dieter Gudmundsson, Lukas Haddeland, I. Hanasaki, Naota Kim, Hyungjun Leng, Guoyong Liu, Junguo Masaki, Yoshimitsu Oki, Taikan Pokhrel, Yadu Satoh, Yusuke Schewe, Jacob Wada, Yoshihide Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts |
| title | Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts |
| title_full | Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts |
| title_fullStr | Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts |
| title_full_unstemmed | Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts |
| title_short | Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts |
| title_sort | worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts |
| topic | global hydrological models land surface models human impacts extreme events model evaluation model validation |
| url | https://eprints.nottingham.ac.uk/51860/ https://eprints.nottingham.ac.uk/51860/ https://eprints.nottingham.ac.uk/51860/ |