Coastal Flooding Risk Assessment Using a GIS-Based Spatial Multi-Criteria Decision Analysis Approach

Abstract

Coastal areas are expected to be at a higher risk of flooding when climate change-induced sea-level rise (SLR) is combined with episodic rises in sea level. Flood susceptibility mapping (FSM), mostly based on statistical and machine learning methods, has been widely employed to mitigate flood risk; however, they neglect exposure and vulnerability assessment as the key components of flood risk. Flood risk assessment is often conducted by quantitative methods (e.g., probabilistic). Such assessment uses analytical and empirical techniques to construct the physical vulnerability curves of elements at risk, but the role of people’s capacity, depending on social vulnerability, remains limited. To address this gap, this study developed a semiquantitative method, based on the spatial multi-criteria decision analysis (SMCDA). The model combines two representative concentration pathway (RCP) scenarios: RCP 2.6 and RCP 8.5, and factors triggering coastal flooding in Bandar Abbas, Iran. It also employs an analytical hierarchy process (AHP) model to weight indicators of hazard, exposure, and social vulnerability components. Under the most extreme flooding scenario, 14.8% of flooded areas were identified as high and very high risk, mostly located in eastern, western, and partly in the middle of the City. The results of this study can be employed by decision-makers to apply appropriate risk reduction strategies in high-risk flooding zones.

GIS-Based Urban Flood Resilience Assessment Using Urban Flood Resilience Model: A Case Study of Peshawar City, Khyber Pakhtunkhwa, Pakistan

“…Moreover, the high risk of urban floods in Peshawar city could be attributed to rapid urbanization, high population growth, degraded environment, lack of advanced early warning mechanism, low public awareness, and lack of adaptive capacity. Similar findings were reported by previous studies related to vulnerability assessment [38,39,44], which found that proper early warning system, high preparedness level, good economic status, better employment, multiple sources of income, and social networks or participation of people in intra community activities play a significant role in enhancing capacities of the local communities to cope effectively with floods.…”

“…The presence of enough coping capacity in the above-mentioned parts highlights the strong economic status, organized institutional setup and high literacy/awareness level. Similar findings were reported by various studies related to vulnerability assessment [38,39,44,68], which found that proper early warning system, high preparedness level, good income status, better employment, multiple sources of income, and social networks or participation of people in intra community activities play a significant role in enhancing capacities of the communities to cope effectively with floods.…”

“…Globally, floods causing a large number of deaths and damages to property [2]. The degree of hazard varies with the severity of flooding and is affected by flood behavior (extent, depth, velocity, isolation, rate of rising of floodwaters, and duration), topography, and emergency management [44]. In this study, we measure flood hazards with six subfactors, which are discussed below.…”

Tidal Flood Risk on Salt Farming: Evaluation of Post Events in the Northern Part of Java Using a Parametric Approach

“…Hazard assessment has been conducted in many different areas including coastal regions, with a pronounced focus on hydrometeorology hazards such as cyclones, storm surges, and flooding. Flood hazard measurement aims to identify the flood pattern utilizing relevant parameters such as inundation depth [36][37][38], flood duration [38][39][40], and even timing of flooding [41][42][43]. This information can be extracted through hydraulic models with different scenarios [44] or based on past recorded events [45,46].…”

Application of AHP and GIS for Determination of Suitable Wireless Sensor Network Zones for Oceanographic Monitoring in the South Caribbean Sea Upwelling Zone

“…Because the System has a trivial solution, (1) must be a singular matrix. Being (3) an equation of degree n, called the characteristic equation of M, which is equal to 0 if λ is replaced by M, producing a matrix equation, where the roots are the characteristic values that were obtained from the priority vector, from of the solution of the corresponding systems of equations [42], [43].…”