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Estimation of uncertainty in flood forecasts—A comparison of methods
HR Wallingford, Flood & Water Management Dept, Wallingford, Oxon, England.
HR Wallingford, Flood & Water Management Dept, Wallingford, Oxon, England.
HR Wallingford, Flood & Water Management Dept, Wallingford, Oxon, England.ORCID iD: 0000-0003-4550-1338
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England; Univ Reading, Dept Meteorol, Reading, Berks, England; CNDS, Ctr Nat Hazards & Disaster Sci, Uppsala, Sweden.ORCID iD: 0000-0002-1472-868x
2019 (English)In: Journal of Flood Risk Management, ISSN 1753-318X, E-ISSN 1753-318X, Vol. 12, no Supplement: 1, article id UNSP e12516Article in journal (Refereed) Published
Abstract [en]

The scientific literature has many methods for estimating uncertainty, however, there is a lack of information about the characteristics, merits, and limitations of the individual methods, particularly for making decisions in practice. This paper provides an overview of the different uncertainty methods for flood forecasting that are reported in literature, concentrating on two established approaches defined as the ensemble and the statistical approach. Owing to the variety of flood forecasting and warning systems in operation, the question "which uncertainty method is most suitable for which application" is difficult to answer readily. The paper aims to assist practitioners in understanding how to match an uncertainty quantification method to their particular application using two flood forecasting system case studies in Belgium and Canada. These two specific applications of uncertainty estimation from the literature are compared, illustrating statistical and ensemble methods, and indicating the information and output that these two types of methods offer. The advantages, disadvantages and application of the two different types of method are identified. Although there is no one "best" uncertainty method to fit all forecasting systems, this review helps to explain the current commonly used methods from the available literature for the non-specialist.

Place, publisher, year, edition, pages
2019. Vol. 12, no Supplement: 1, article id UNSP e12516
Keywords [en]
ensembles, flood forecasting, probabilistic, uncertainty
National Category
Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:uu:diva-395424DOI: 10.1111/jfr3.12516ISI: 000485980500003OAI: oai:DiVA.org:uu-395424DiVA, id: diva2:1365052
Available from: 2019-10-23 Created: 2019-10-23 Last updated: 2019-10-23Bibliographically approved

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