Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling
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- Authors
- Gupta, H. V., Kling, H., Yilmaz, K. K., & Martinez, G. F.
- Affiliations
- University of Arizona (US)
- Corresponding author
- Kling, Harald
- Venue
- Journal of Hydrology
- Publisher
- Elsevier BV
- Published
- 2009-10
- Volume
- 377
- Issue
- 1-2
- Pages
- 80-91
- ISSN
- 0022-1694 (ISSN-L)
- OpenAlex
- W2138763184
- Cited by
- 6,758
- References
- 0
- Citations by year
- 2026: 922 · 2025: 864 · 2024: 910 · 2023: 869 · 2022: 912 · 2021: 738 · 2020: 416 · 2019: 279 · 2018: 231 · 2017: 181 · 2016: 136 · 2015: 93 · 2014: 65 · 2013: 49 · 2012: 35
- FWCI
- 30.32
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Journal of Hydrology (publishedVersion)
- NASA STI Repository (National Aeronautics and Space Administration) (submittedVersion)
- OpenMETU (Middle East Technical University) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Environmental Science › Water Science and Technology › Hydrology and Watershed Management Studies
- Physical Sciences › Environmental Science › Environmental Engineering › Hydrological Forecasting Using AI
- Physical Sciences › Environmental Science › Environmental Engineering › Soil Moisture and Remote Sensing
- Keywords
- mean squared error, Nash-Sutcliffe efficiency, hydrological model calibration, model evaluation, calibration problem, alternative performance measures
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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