Assessment of Population Exposure to Urban Flood at the Building Scale

Flood vulnerability assessment of Thailand's flood-prone Pathum Thani province and vulnerability mitigation strategies

This research assesses the flood vulnerability of Thailand's flood-prone province of Pathum Thani using a comprehensive vulnerability assessment framework. The assessment framework incorporates three key components: exposure, sensitivity, and adaptive capacity, consisting of 10, 12 and 11 flood vulnerability indicators, respectively. The flood vulnerability components and the flood vulnerability indicators are statistically validated by confirmatory factor analysis to determine the factor loadings and reliability of the components and indicators. The flood vulnerability questionnaire corresponding to the flood vulnerability indicators is subsequently developed and applied to the flood-prone districts of the province. The results show that proximity to rivers (with an indicator score of 0.685), household debt levels (0.612), land use patterns (0.617), and the proportion of low-income households (0.621) significantly contribute to the flood exposure of the province (with an exposure index score of 0.531). Larger household size (with an indicator score of 0.901), disruptions in public utility services (0.747), and workplace absenteeism due to flooding (0.741) contribute to the province's higher flood sensitivity (with a sensitivity index score of 0.633). Drainage capacity of natural and man-made waterways (0.571) contributes to low to moderate levels of flood adaptive capacity. The flood vulnerability of seven administrative districts of Pathum Thani, as measured by the flood vulnerability index scores (0.454-0.608), range from moderate to high. Local authorities need to invest in flood warning and response systems, prioritize infrastructure development and encourage community engagement to reduce the flood vulnerability.

Urban growth modelling and social vulnerability assessment for a hazardous Kathmandu Valley

In our rapidly urbanizing world, many hazard-prone regions face significant challenges regarding risk-informed urban development. This study addresses this issue by investigating evolving spatial interactions between natural hazards, ever-increasing urban areas, and social vulnerability in Kathmandu Valley, Nepal. The methodology considers: (1) the characterization of flood hazard and liquefaction susceptibility using pre-existing global models; (2) the simulation of future urban built-up areas using the cellular-automata SLEUTH model; and (3) the assessment of social vulnerability, using a composite index tailored for the case-study area. Results show that built-up areas in Kathmandu Valley will increase to 352 km² by 2050, effectively doubling the equivalent 2018 figure. The most socially vulnerable villages will account for 29% of built-up areas in 2050, 11% more than current levels. Built-up areas in the 100-year and 1000-year return period floodplains will respectively increase from 38 km² and 49 km² today to 83 km² and 108 km² in 2050. Additionally, built-up areas in liquefaction-susceptible zones will expand by 13 km² to 47 km². This study illustrates how, where, and to which extent risks from natural hazards can evolve in socially vulnerable regions. Ultimately, it emphasizes an urgent need to implement effective policy measures for reducing tomorrow's natural-hazard risks.

Changes of Chinese Coastal Regions Induced by Land Reclamation as Revealed through TanDEM-X DEM and InSAR Analyses

Chinese coastal topography has changed significantly over the last two decades due to human actions such as the development of extensive land reclamation projects. Newly-reclaimed lands typically have low elevations (<10 m) and often experience severe ground subsidence. These conditions, combined with the more frequent occurrence of extreme sea-level events amplified by global climate change, lead to an increased risk of flooding of coastal regions. This work focuses on twelve Chinese coastal areas that underwent significant changes from 2000 to 2015 in their environments, correlated to relevant land reclamation projects. First, the ground changes between 2000 and 2015 were roughly computed by comparing the TanDEM-X and the Shuttle Radar Topography Mission (SRTM) digital elevation models of the investigated areas. These results indicate that six of the analyzed coastal zones have reclaimed more than 200 km2 of new lands from 2000 to 2015, with five of them in northern China. Second, we focused specifically on the city of Shanghai, and characterized the risk of flood in this area. To this purpose, two independent sets of synthetic aperture radar (SAR) data collected at the X- and C-band through the COSMO-SkyMed (CSK) and the European Copernicus Sentinel-1 (S-1) sensors were exploited. We assumed that the still extreme seawater depth is chi-square distributed, and estimated the probability of waves overtopping the coast. We also evaluated the impact on the territory of potential extreme flood events by counting the number of very-coherent objects (at most anthropic, such as buildings and public infrastructures) that could be seriously affected by a flood. To forecast possible inundation patterns, we used the LISFLOOD-FP hydrodynamic model. Assuming that an extreme event destroyed a given sector of the coastline, we finally computed the extent of the flooded areas and quantified its impact in terms of coherent structures potentially damaged by the inundation. Experimental results showed that two coastline segments located in the southern districts of Shanghai, where the seawalls height is lower, had the highest probability of wave overtopping and the most significant density of coherent objects potentially subjected to severe flood impacts.

A Geomorphic Approach for Identifying Flash Flood Potential Areas in the East Rapti River Basin of Nepal

Basin geomorphology is a complete system of landforms and topographic features that play a crucial role in the basin-scale flood risk evaluation. Nepal is a country characterized by several rivers and under the influence of frequent floods. Therefore, identifying flood risk areas is of paramount importance. The East Rapti River, a tributary of the Ganga River, is one of the flood-affected basins, where two major cities are located, making it crucial to assess and mitigate flood risk in this river basin. A morphometric calculation was made based on the Shuttle Radar Topographic Mission (SRTM) 30-m Digital Elevation Model (DEM) in the Geographic Information System (GIS) environment. The watershed, covering 3037.29 km2 of the area has 14 sub-basins (named as basin A up to N), where twenty morphometric parameters were used to identify flash flood potential sub-basins. The resulting flash flood potential maps were categorized into five classes ranging from very low to very high-risk. The result shows that the drainage density, topographic relief, and rainfall intensity have mainly contributed to flash floods in the study area. Hence, flood risk was analyzed pixel-wise based on slope, drainage density, and precipitation. Existing landcover types extracted from the potential risk area indicated that flash flood is more frequent along the major Tribhuvan Rajpath highway. The landcover data shows that human activities are highly concentrated along the west (Eastern part of Bharatpur) and the east (Hetauda) sections. The study concludes that the high human concentrated sub-basin “B” has been categorized as a high flood risk sub-basin; hence, a flood-resilient city planning should be prioritized in the basin.