![]() ![]() ![]() Water Sci Technol 52(5):265–273īrunner GW (1995) HEC-RAS river analysis system. Hydrol Process 28(13):4067–4077Īshley RM, Balmforth DJ, Saul AJ, Blanskby JD (2005) Flooding in the future–predicting climate change, risks and responses in urban areas. ![]() This research experimented different impervious surface percentages as input to the hydraulic model and found that a spatially variable impervious surface percentage achieves better agreement with hydraulic modelling than that of uniform (25% and 42%) impervious surface percentages.Īlfieri L, Salamon P, Bianchi A, Neal J, Bates P, Feyen L (2014) Advances in pan-European flood hazard mapping. Furthermore, the impervious surface percentage is an important input in the hydraulic model. ![]() Such a strategy serves as a promising prototype for addressing similar geographical modelling issues, where the time-consuming physical model can be potentially replaced by a simplified GIS model. The multi-criteria GIS model built by binary logistic regression was able to simulate the results from the hydraulic model with good consistency. We used a binary logistic regression model to integrate the hydraulic concept in a GIS model. The hydraulic–GIS combined model employs the hydraulic concept in a simplified GIS frame, hence avoiding heavy computation in the hydraulic model and arbitrary coefficients in a GIS model. This research combines two common urban flooding approaches, namely hydraulic and GIS models, in a case study of London, Ontario, Canada. Up-to-date monitoring on the distribution of flood hazards in cities is necessary and valuable for urban planning. Urban flooding is a reoccurring disaster, and its frequency and intensity are likely to increase in the future due to the increasing frequency of storm events. ![]()
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