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. Up-to-date monitoring on the distribution of flood hazards in cities is necessary and valuable for urban planning. This research combines two common urban flooding approaches, namely hydraulic and GIS models, in a case study of London, Ontario, Canada. 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. We used a binary logistic regression model to integrate the hydraulic concept in a 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. 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. Furthermore, the impervious surface percentage is an important input in the hydraulic model. 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.
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This work was supported by both the NSERC Engage Grant awarded to Dr. Jinfei Wang with industry support from Esri Canada Limited and the NSERC Discovery Grant awarded to Dr. Jinfei Wang. This research used a free university license for the PCSWMM software. Funding was provided by NESRC Discovery (Grant No. RGPIN-2016-04741).
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Feng, B., Wang, J., Zhang, Y. et al. Urban flood hazard mapping using a hydraulic–GIS combined model. Nat Hazards (2020). https://doi.org/10.1007/s11069-019-03850-7
- Flood hazard map
- Hydraulic model
- GIS model