Urban infrastructure inundation risk from permanent sea-level rise scenarios in London (UK), Bangkok (Thailand) and Mumbai (India): A comparative analysis
Abstract: Due to anthropogenically created climate change, global cities are facing inundation by rising sea levels. This study aimed to fill knowledge gaps in understanding the exposure of urban infrastructure such as roads, railways, buildings and parks to sea-level rise (SLR) scenarios, and how this would affect local populations. Three economic hubs, namely London (United Kingdom), Bangkok (Thailand) and Mumbai (India) were chosen for comparison due to their coastal locations and regionally concentrated asset wealth with dense populations and economic influence regionally. The data sources for this research study included three digital elevation models (DEMs); two traditionally used globally available datasets from the Japanese Aerospace Exploration Agency and United States Geological Survey (1 arc-second spatial resolution), and a recently released elevation model by ClimateCentral (3 arc-second spatial resolution). Vector data for the urban infrastructural layers was sourced from navigational supplier HERE, while raster population data was sourced from WorldPop (3 arc-second spatial resolution). A modified bathtub-fill modelling method approach was then applied within GIS applications to model landward-creeping SLR (high-risk: 1 metre, medium-risk: 3 metres and low-risk: 5 metres) using the three DEMs, resulting in the extraction of the total lengths, areas and counts of the infrastructural layers and populations that intersected these flooded areas. Risk index maps were built for the cities' districts to understand where the greatest risks lie, while hypotheses for the inter-relationship between the cities and their infrastructure were tested using non-parametric Kruskal-Wallis independent tests. From this method, the results showed that in a 1m (high-risk) scenario, Mumbai is consistently the most vulnerable city with between 6-10% of the city's area (particularly the central business district) showing flooding. Bangkok is at lower risk at 4-6% inundation of the city's area (in lower density suburbs), while approximately 2% of London's area (mainly in industrial riverside locations) is at risk. In the medium- and low-risk scenarios, Bangkok is the most vulnerable with 16-51% and 57-92% of its area showing flooding respectively. A 1m SLR shows greatest threat to Mumbai's functionality as a city as all infrastructural elements and up to 24% of the local population will be impacted on a day-to-day basis. On the other hand, a 3 and 5 metre SLR would impact up to 52% and 96% of Bangkok's population respectively. Although this study gives a geographic indication of the SLR impact on these three cities, budgetary and network constraints precluded the sourcing of high-resolution elevation model data from ClimateCentral as well as locally sourced flood defence structure and hydrological input data. Accuracy within the findings in future studies would increase from inputs such as LiDAR elevation data, socio-economic asset values for the cities' urban infrastructure and multi-criteria hydrological information. In this way, researchers and municipalities would be better informed on the vulnerability to their cities, and use this to build resilience and mitigative efforts against SLR over the coming decades.
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