Impervious surface mapping using satellite data and runoff modeling in Amersfoort, NL

An increase of urban flash flood issues has been observed throughout the world in recent years. It has led to enormous losses and people were killed. The increase of urban flash flooding is mainly due to more intensive rain events and more ground surfaces converted into impervious surfaces. Although the runoff mechanism and process have been widely studied, the runoff modeling on the basis of impervious surface mapping is still a new aspect to the study of urban flooding. The main objective of this study is to evaluate various approaches for impervious surface mapping on the basis of satellite images, and evaluating the hydrological impact of impervious surface expansion in Amersfoort by a runoff model. The study area is located at Amersfoort, which is the second largest city in Utrecht Province in the Netherlands. A fast urbanization process took place over the last 30 years. In addition, Amersfoort is a high risk area of urban (flash) flooding because it is located next to an elevated hill in the south-west. The regression modeling method and the Normalized Linear Spectral Mixing Analysis (NLSMA) methods were applied to Landsat images. Accuracy assessment of these two methods showed that impervious areas mapped by NLSMA had a higher accuracy. The Decision Tree Classification (DTC) method was applied to FORMOSAT-2 image. An overall accuracy of 92% was achieved by the error matrix. Uncertainties, advantages and constraints for these three methods were compared and discussed. The runoff responses were evaluated by linking the impervious surfaces maps to a straightforward rainfall-runoff model. A number of one-hour rainfall events with various intensities were worked out and the results showed that the Amersfoort railway station is the most vulnerable place o runoff in case of an intensive rainfall event. The investigated area can bear a one-hour rainfall with a return time of less than two years. Risk maps of buildings for every scenario were worked out. Risk maps are very important for city managers as they can guide them to distribute the limited relief resources efficiently