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Identification of Flood Reactivity Regions via the Functional Clustering of Hydrographs
Univ Zurich, Dept Geog, Zurich, Switzerland;Univ Grenoble Alpes, CNRS, IRD, Grenoble INP,IGE, Grenoble, France.
Univ Zurich, Dept Geog, Zurich, Switzerland;Belop Gmbh, Sarnen, Switzerland.ORCID iD: 0000-0002-1214-8657
Univ Zurich, Dept Math, Zurich, Switzerland;Univ Zurich, Dept Computat Sci, Zurich, Switzerland.ORCID iD: 0000-0002-6319-2332
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Zurich, Dept Geog, Zurich, Switzerland.ORCID iD: 0000-0002-6314-2124
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2018 (English)In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 54, no 3, p. 1852-1867Article in journal (Refereed) Published
Abstract [en]

Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establish these regions is very flexible and has the potential to be extended to other geographical regions or toward the use in climate impact studies.

Place, publisher, year, edition, pages
2018. Vol. 54, no 3, p. 1852-1867
Keywords [en]
clustering, functional data analysis, hydrograph shapes, homogeneous regions, regionalization
National Category
Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:uu:diva-354257DOI: 10.1002/2017WR021650ISI: 000430364900025OAI: oai:DiVA.org:uu-354257DiVA, id: diva2:1228767
Available from: 2018-06-28 Created: 2018-06-28 Last updated: 2018-06-28Bibliographically approved

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Seibert, Jan

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