Flood Risk Assessment in Urban Catchments Using Multiple Regression Analysis
Publication: Journal of Water Resources Planning and Management
Volume 144, Issue 2
Abstract
Flood assessment in urban catchments is usually addressed through the combination of geographic information systems (GISs) and stormwater models. However, the coupled use of these tools involves a level of detail in terms of hydrological modeling that can be beyond the scope of overall flood management planning strategies. This research consists of the development of a methodology based on multiple regression analysis (MRA) to assess flood risk in urban catchments according to their morphologic characteristics and the geometrical and topological arrangement of the drainage networks into which they flow. Stormwater models were replaced by a combination of multiple linear regression (MLR), multiple nonlinear regression (MNLR), and multiple binary logistic regression (MBLR), which enabled identifying influential parameters in the maximum runoff rates generated in urban catchments, modeling the magnitude of peak flows across them, and estimating flood risk in the nodes of sewer networks, respectively. The results obtained through a real urban catchment located in Espoo, Finland, demonstrated the usefulness of the proposed methodology to provide an accurate replication of flood occurrence in urban catchments due to intense storm events favored by climate change, information that can be used to plan and design preventative drainage strategies.
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Acknowledgments
This paper was possible thanks to the research projects SUPRIS-SUReS (Ref. BIA2015-65240-C2-1-R MINECO/FEDER, UE) and SUPRIS-SUPeI (Ref. BIA2015-65240-C2-2-R MINECO/FEDER, UE), financed by the Spanish Ministry of Economy and Competitiveness with funds from the State General Budget (PGE) and the European Regional Development Fund (ERDF). The authors wish to express their gratitude to all the entities that provided the data necessary to develop this research: Helsinki Region Environmental Services Authority HSY, Map Service of Espoo, National Land Survey of Finland, Geological Survey of Finland, EURO-CORDEX, and European Climate Assessment & Dataset.
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Journal of Water Resources Planning and Management
Volume 144 • Issue 2 • February 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: May 30, 2017
Accepted: Jul 25, 2017
Published online: Nov 22, 2017
Published in print: Feb 1, 2018
Discussion open until: Apr 22, 2018
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