The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
HydroTest: A web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts
Open accessAbstract
This paper presents details of an open access web site that can be used by hydrologists and other scientists to evaluate time series models. There is at present a general lack of consistency in the way in which hydrological models are assessed that handicaps the comparison of reported studies and hinders the development of superior models. The HydroTest web site provides a wide range of objective metrics and consistent tests of model performance to assess forecasting skill. This resource is designed to promote future transparency and consistency between reported models and includes an open forum that is intended to encourage further discussion and debate on the topic of hydrological performance evaluation metrics. It is envisaged that the provision of such facilities will lead to the creation of superior forecasting metrics and the development of international benchmark time series datasets.
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Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
A leisurely look at the bootstrap, the jackknife, and cross-validation
Efron, B., & Gong, G. (1983) · The American Statistician · doi:10.1080/00031305.1983.10483087 · Cited by 3,229
Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods
EFRON, B. (1981) · Biometrika · doi:10.1093/biomet/68.3.589 · Cited by 1,399
Cited by
Characterising performance of environmental models
Bennett, N. D., Croke, B. F. W., Guariso, G., Guillaume, J. H. A., Hamilton, S. H., Jakeman, A. J., Marsili-Libelli, S., Newham, L. T. H., Norton, J. P., Perrin, C., et al. (2013) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2012.09.011 · Cited by 1,536
Ritter, A., & Muñoz-Carpena, R. (2013) · Journal of Hydrology · doi:10.1016/j.jhydrol.2012.12.004 · Cited by 991
Maier, H. R., Jain, A., Dandy, G. C., & Sudheer, K. P. (2010) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2010.02.003 · Cited by 871
Tyralis, H., Papacharalampous, G., & Langousis, A. (2019) · Water · doi:10.3390/w11050910 · Cited by 771
Applications of hybrid wavelet–Artificial Intelligence models in hydrology: A review
Nourani, V., Hosseini Baghanam, A., Adamowski, J., & Kisi, O. (2014) · Journal of Hydrology · doi:10.1016/j.jhydrol.2014.03.057 · Cited by 730
Metadata
- Authors
- Dawson, C. W., Abrahart, R. J., & See, L. M.
- Venue
- Environmental Modelling & Software
- Publisher
- Elsevier BV
- Published
- 2007-07
- Volume
- 22
- Issue
- 7
- Pages
- 1034-1052
- ISSN
- 1364-8152 (ISSN-L)
- OpenAlex
- W2065902166
- Cited by
- 504
- References
- 3
- FWCI
- 8.80
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.