Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watersheds
We introduce a new diagnosis tool that is well suited to analyzing simulation results over large samples of watersheds. It consists of a modification of the classical Taylor diagram to simultaneously visualize several error components (based on bias, standard deviation or squared errors) that are co...
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| Format: | Article |
| Language: | English |
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Académie des sciences
2023-01-01
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| Series: | Comptes Rendus. Géoscience |
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| Online Access: | https://comptes-rendus.academie-sciences.fr/geoscience/articles/10.5802/crgeos.189/ |
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| author | Mathevet, Thibault Le Moine, Nicolas Andréassian, Vazken Gupta, Hoshin Oudin, Ludovic |
| author_facet | Mathevet, Thibault Le Moine, Nicolas Andréassian, Vazken Gupta, Hoshin Oudin, Ludovic |
| author_sort | Mathevet, Thibault |
| collection | DOAJ |
| description | We introduce a new diagnosis tool that is well suited to analyzing simulation results over large samples of watersheds. It consists of a modification of the classical Taylor diagram to simultaneously visualize several error components (based on bias, standard deviation or squared errors) that are commonly used in efficiency criteria (such as the Nash–Sutcliffe efficiency (NSE) or the Kling–Gupta efficiency (KGE)) to evaluate hydrological model performance. We propose a methodological framework that explicitly links the graphical and numerical evaluation approaches, and show how they can be usefully combined to visually interpret numerical experiments conducted on large datasets. The approach is illustrated using results obtained by testing two rainfall-runoff models on a sample of 2050 watersheds from 8 countries and calibrated with two alternative objective functions (NSE and KGE). The assessment tool clearly highlights well-documented problems related to the use of the NSE for the calibration of rainfall-runoff models, which arise due to interactions between the ratio of simulated to observed standard deviations and the correlation coefficient. We also illustrate the negative impacts of classical mathematical transformations (square root) applied to streamflow when employing NSE and KGE as metrics for model calibration. |
| format | Article |
| id | doaj-art-bdaf26f29ebd4a88aef6ef0ba705e8af |
| institution | Kabale University |
| issn | 1778-7025 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Académie des sciences |
| record_format | Article |
| series | Comptes Rendus. Géoscience |
| spelling | doaj-art-bdaf26f29ebd4a88aef6ef0ba705e8af2025-02-07T10:40:14ZengAcadémie des sciencesComptes Rendus. Géoscience1778-70252023-01-01355S111714110.5802/crgeos.18910.5802/crgeos.189Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watershedsMathevet, Thibault0https://orcid.org/0000-0002-4142-4454Le Moine, Nicolas1https://orcid.org/0000-0002-5848-2300Andréassian, Vazken2https://orcid.org/0000-0001-7124-9303Gupta, Hoshin3https://orcid.org/0000-0001-9855-2839Oudin, Ludovic4https://orcid.org/0000-0002-3712-0933EDF, 4 allée du Lac de Tignes, 73290 La Motte Servolex, France; Visiting research scholar at Hydrology and Atmospheric Sciences, University of Arizona, in 2014Sorbonne Université, CNRS, EPHE, UMR 7619 METIS, Case 105, 4 place Jussieu, 75005 Paris, FranceUniversité Paris-Saclay, INRAE, UR HYCAR, 1 Rue Pierre-Gilles de Gennes, 92160 Antony, FranceDepartment of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USASorbonne Université, CNRS, EPHE, UMR 7619 METIS, Case 105, 4 place Jussieu, 75005 Paris, FranceWe introduce a new diagnosis tool that is well suited to analyzing simulation results over large samples of watersheds. It consists of a modification of the classical Taylor diagram to simultaneously visualize several error components (based on bias, standard deviation or squared errors) that are commonly used in efficiency criteria (such as the Nash–Sutcliffe efficiency (NSE) or the Kling–Gupta efficiency (KGE)) to evaluate hydrological model performance. We propose a methodological framework that explicitly links the graphical and numerical evaluation approaches, and show how they can be usefully combined to visually interpret numerical experiments conducted on large datasets. The approach is illustrated using results obtained by testing two rainfall-runoff models on a sample of 2050 watersheds from 8 countries and calibrated with two alternative objective functions (NSE and KGE). The assessment tool clearly highlights well-documented problems related to the use of the NSE for the calibration of rainfall-runoff models, which arise due to interactions between the ratio of simulated to observed standard deviations and the correlation coefficient. We also illustrate the negative impacts of classical mathematical transformations (square root) applied to streamflow when employing NSE and KGE as metrics for model calibration.https://comptes-rendus.academie-sciences.fr/geoscience/articles/10.5802/crgeos.189/Hydrological modelingLarge-sample hydrologyTaylor diagramDiagnosticsKling–Gupta efficiencyNash–Sutcliffe efficiency |
| spellingShingle | Mathevet, Thibault Le Moine, Nicolas Andréassian, Vazken Gupta, Hoshin Oudin, Ludovic Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watersheds Comptes Rendus. Géoscience Hydrological modeling Large-sample hydrology Taylor diagram Diagnostics Kling–Gupta efficiency Nash–Sutcliffe efficiency |
| title | Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watersheds |
| title_full | Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watersheds |
| title_fullStr | Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watersheds |
| title_full_unstemmed | Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watersheds |
| title_short | Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watersheds |
| title_sort | multi objective assessment of hydrological model performances using nash sutcliffe and kling gupta efficiencies on a worldwide large sample of watersheds |
| topic | Hydrological modeling Large-sample hydrology Taylor diagram Diagnostics Kling–Gupta efficiency Nash–Sutcliffe efficiency |
| url | https://comptes-rendus.academie-sciences.fr/geoscience/articles/10.5802/crgeos.189/ |
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