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Environmental and Engineering Geoscience; May 2008; v. 14; no. 2; p. 61-80; DOI: 10.2113/gseegeosci.14.2.61
© 2008 Association of Engineering Geologists
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Classification of Flood Retention Basins: The Kaiserstuhl Case Study

MIKLAS SCHOLZ1

1 Institute for Infrastructure and Environment, School of Engineering and Electronics, The University of Edinburgh, William Rankine Building, Mayfield Road, The King's Buildings, Edinburgh EH9 3JL, Scotland, United Kingdom

The aim of this paper is to describe a conceptual classification model for Sustainable Flood Retention Basins (SFRB) used to control runoff in temperate climates. The author has defined a SFRB as an aesthetically pleasing (from the general publics' point of view) retention basin, predominantly used for flood protection and adhering to sustainable drainage and best management practices. The classification model concept was developed on the basis of an example database of 147 SFRB in Baden-Württemberg (Germany). The data were of high quality because the researchers had detailed local knowledge of the case study area. The model quality was improved on the basis of a more detailed case study of The Kaiserstuhl, a region (no clearly defined boundaries) with a very high density of flood retention basins (one SFRB per 2 km2; 51 sites in total). The model is based on an agglomerative cluster analysis and is intended to be used by landscape planners, environmental engineers, and environmental scientists to adequately classify the following different types of SFRB with the purpose of improving communication among stakeholders: Hydraulic Flood Retention Basin, Traditional Flood Retention Basin, Sustainable Flood Retention Wetland, Aesthetic Flood Retention Wetland, Integrated Flood Retention Wetland, and Natural Flood Retention Wetland. Despite the limited regional variation in flood retention basin characteristics within The Kaiserstuhl, the classification model example had an accuracy of 60 percent. A scoring template for the classification of future SFRB was devised on the basis of researcher experience, and this was optimized with a genetic algorithm.

Key Words: Classification System • Cluster Analysis • The Kaiserstuhl • Self-Organizing Map • Sustainable Flood Retention Basin • Rural and Urban Runoff







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