Navigating Urban Flood Risk: Assessment, Modelling, and Management

Published by on November 19, 2023

In the face of evolving climate dynamics, urban flooding is emerging as a major concern that calls for urgent action and demands prioritization in research initiatives. Since 1980, over 4588 flood disasters have occurred in 172 countries, causing the loss of over 250,000 people’s lives (Dąbrowska, et al., 2023). In nature, fluctuations in water levels are natural occurrences as part of Earth’s hydrological cycle as a result of various events, such as increased precipitation, river discharge, snowmelt, or glacial lake outbursts (Okazawa, et al., 2011). However, when considered in the context of urbanized environments, the effects of flooding are often exacerbated by anthropogenic activities. As a result, parts of the urbanized world, such as the July 2020 rainstorms in the Henan Province of China, have begun experiencing severe consequences of urban flooding, resulting in threats to human health and property. Therefore, it is necessary to consider the role of urbanization in exacerbating disasters driven by climate change.

To contextualize the term, flood risk is defined as the possibility of the degree of damage from a flood event (Okazawa, et al., 2011). Hazard level is dependent on factors such as flood depth, velocity, and duration. Urbanization typically increases many cities’ risks of flooding due to infrastructure that cannot facilitate proper water drainage. To illustrate, consider the amount of impermeable surfaces and modifications of flow paths, both of which are processes that greatly increase the chances of flooding in urban watersheds (Bertilsson, et al., 2019). Although flood risk varies depending on the state of urbanization of a city and natural hydrologic networks, there are various indices that can be applied to assess the level of impact of a flood event. One such index refers to the Disaster Risk Index (DRI), developed by the United Nations Environment Programme, through regression analyses of past floods, droughts, earthquakes, and tropical cyclones (Mosquera-Machado and Dilley, 2009) (Figure 1).

Figure 1: The logarithmic regression equation used to analyze past flood events, which revealed that highly exposed and poorer populations are susceptible to greater flood casualties. It also showed that high-population density countries were more vulnerable than low-population density countries (United Nations Environment Programme, 2004) (Adapted from Mosquera-Machado and Dilley, 2009).

Current flood disaster management is primarily reactive and focuses on emergency response after a disaster event has taken place. While these protocols are necessary, greater emphasis on proactive management can increase efficacy and reduce loss of life and property (Tingsanchali, 2012). Flood forecasting is one major aspect of proactive flood management, produced in relation to precipitation-driven hydrological models (Chen, et al., 2015). Although flood modelling has been under development for decades, producing models such as the Personnel Computer Storm Water Management Model (PCSWMM) and the Illinois Urban Drainage Area Simulator (ILLUDAS), the field’s primary focus has been on underground water movement (Figure 2). Current literature neglects surface runoff, which in urban environments is often the main driver for flood events (NASEM, 2019; Prokešová, Horáčková and Snopková, 2022). 

Figure 2: Real-world applications of the PCSWMM model in flood forecasting for the Don River Watershed in Toronto, Ontario. A variety of technologies were used in the development of detailed high-resolution rainfall, including the PCSWMM real-time model, NEXRAD radar data, and Google Maps. Ultimately, weather radar products from the National Oceanic and Atmospheric Administration (NOAA) were used in conjunction with the SWMM5 model to produce inflow hydrographs for radar rainfall scenarios in the Don River Watershed (Randall et al., 2014).

Compared to underground flood events, in which drainage and pipe networks support water flow, surface runoff does not have a fixed path or direction. To understand these events, shallow-water equations (SWEs) can be used to stimulate their process. SWEs utilize hydrodynamic calculations to create numerical models of urban surface runoff. Simply put, SWEs represent the water current in a flood zone as a 2D field, assuming that water depth is more ‘shallow’ compared to other dimensions in the area (Luo, et al., 2022). This type of modelling is applicable as surface runoff is typically low in elevation, in comparison to other physical structures of an urban region. 

Although this field is still developing, there are limitations of SWE, challenged by poor representation of urban terrain and processing of shallow water in irregular beds (Guo, Guan and Yu, 2021). As climate dynamics intensify, there is ultimately a pressing demand for modelling urban surface floods to produce simulations and weather forecasting at higher accuracy rates.

References

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Chen, Y., Zhou, H., Zhang, H., Du, G. and Zhou, J., 2015. Urban flood risk warning under rapid urbanization. Environmental Research, 139, pp.3–10. https://doi.org/10.1016/j.envres.2015.02.028.

Dąbrowska, J., Menéndez Orellana, A.E., Kilian, W., Moryl, A., Cielecka, N., Michałowska, K., Policht-Latawiec, A., Michalski, A., Bednarek, A. and Włóka, A., 2023. Between flood and drought: How cities are facing water surplus and scarcity. Journal of Environmental Management, 345, p.118557. https://doi.org/10.1016/j.jenvman.2023.118557.

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Luo, P., Luo, M., Li, F., Qi, X., Huo, A., Wang, Z., He, B., Takara, K., Nover, D. and Wang, Y., 2022. Urban flood numerical simulation: Research, methods and future perspectives. Environmental Modelling & Software, 156, p.105478. https://doi.org/10.1016/j.envsoft.2022.105478.

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National Academies of Sciences, Engineering, and Medicine (NASEM), 2019. Trends Affecting Urban Flooding. In: Framing the Challenge of Urban Flooding in the United States. Washington, DC: The National Academies Press. doi: https://doi.org/10.17226/25381.

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