Abstract

Urban areas have increased vulnerability to pluvial flooding due to climate change and city urbanization. Pluvial flooding is a phenomenon that is caused by water accumulation at the surface due to extreme rainfall.  This phenomenon usually occurs in areas with sealed surfaces and dense urban structures, with low infiltration capabilities combined with defective drainage systems.  

Arvika, a town situated in the western Värmland, in Sweden, has a history with several flooding events and therefore desires a method to map flood-prone areas due to extreme rainfall.  The objective of this study is to develop a method in a geographic information system (GIS) to identify flood-prone areas in an urban environment, specific the town of Arvika. Furthermore, the method should be used to calculate the size of the flooded areas and identify which parts of the drainage system that are insufficient of handling the occurrence of an extreme rainfall event.

The method is based on overlay analysis of several raster data layers. A Digital Elevation Model (DEM) for delineation of the catchment areas of the city and a topographic wetness index was generated. Furthermore a simulation of the drainage system was used in order to create a friction-raster for the drainage system capability. A raster for the landuse and its infiltration capacity was constructed with known run-off coefficients. The created rasters were combined in an overlay in a multi-criteria analysis. Furthermore, to allow for identification of rain accumulation areas a low point mapping analyses was performed.

The result from the overlay analysis was classified into four categories (1-4) and visualized in maps. The maps show which areas that are likely to be flooded, Nygatan, Palmviksgatan/Järnvägsgatan and the harbor.  The sizes of the flood-prone areas differ, in category 4: 1 470 920 m²  were affected, in category 3: 381 904 m², in category 2: 53 884 m² and 1 172 m² in category 1. This corresponds to 46 %, 12 %, 2 % and 0.04 % affected area of the study-area. In order to identify defective drainage systems the amount of surface water drains within the flood-prone areas was calculated, showing 325 in category 4, 182 in category 3, 39 in category 2 and 2 in category 1.

The method developed in this study is rather coarse and based on several assumptions that must be further investigated and verified. Therefore, the result of flood-prone areas should not be seen as a “truth”. Further analysis, including additional parameters, should be included in the method in order to create a more reliable and accurate result.