Simulation of flood inundation in urban areas longer important, given the magnitude of potential loss and disruption associated with non-river based, urban flooding. The complexity of the urban environment and lack of high-resolution topographic and hydrologic data compromise the development and implementation of models. Low impact development (LID) is technical know-how on a collection of sustainable practices that mimic natural hydrological functions including infiltration, evapotranspiration or use of surface runoff. Several studies have been carried out to discuss the impact of urbanization scenarios in reducing the urban flood risk in watershed scale in Sri Lanka. Yet, there is a gap remains in simulating the effectiveness of LID-based planning practices to reduce flood risk with the complex built form scenarios. In such a situation, this study attempts to make a significant contribution to simulate the variations of flood regulation functions under different high-intensive urban development scenarios, particularly focusing on the urban metropolitan regions. The analyses were carried out utilizing SWMM (Storm Water Management Model) which is open-source flood inundation simulation approach with the help of GIS in a more qualitative manner. The simulation results indicate that expanding built form scenarios increase the flood venerability for city functions, increasing inundation duration and LID scenarios able to reduce the surface runoff to reduce flood vulnerability at a significant level. The simulation results had been verified with the real ground situation (mean percentage change < 15.5%) which able to capture the thresholds of built form variation, as well as dynamic land uses and infrastructure supply which can be used as a tool for future planning practices and decision-making.
Community resilience assessments and minimizing the anticipated disruptions to vulnerable communities, is a broad topic in disaster studies. In common practice, most of the indicator-based resilience assessment studies rely on statistical aggregation methods of tabular data collected for macro administrative units, as it is readily available in most of the countries. However, this method confronts severe drawbacks in converting such data into micro-scale geospatial units. To address those issues, this study proposes to utilize the Dasymetric Mapping Technique in the geospatial population resilience assessments, as it is capable of identifying the micro level impact to the population distribution as a pixel representation. In order to geospatially demonstrate the population exposure, the study has selected three major flooding events occurred in Colombo, Sri Lanka. The results revealed a great applicability of the proposed method as a statistical approach which estimates the exposed population by over 90% accuracy. Therefore, the proposed method is recommended to be utilized as an efficient tool of community resilience assessment as it is highly accurate in downscaling the spatial distribution of population data.
This study presents a methodology to assess transport network resilience to urban flooding. The proposed methodology is developed based on the centrality measures and graph theory. The study utilises Open-Source GIS tools to compute betweenness and closeness centrality values. The case study was carried out in Greater Colombo -Sri Lanka, with reference to three significant urban flooding events in 2010, 2016, and 2017. The study assessed the resilience of road network in terms of topological impacts and accessibility changes.The results revealed three key findings. First, over 60% of road network revealed a significant change in its topological structural coherence during each flooding event. This was particularly pronounced in vehicular movements relative to pedestrian movements. Second, the study revealed a redundant depreciation of the transport accessibility as it shifted from city centre to peripheral areas creating temporary accessibility hotpots in the periphery. Third, a significant drawback of the resilience of road network was identified in terms of the deviation from the shortest path, increasing the travel time and trip length. In overall, the study concluded that the proposed methodology can be utilised as a planning and designing tool to assess road network`s resilience devising precautionary measures to mitigate disaster risk.
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