Abstract
AbstractA major challenge in flood mapping using multi‐criteria decision analysis (MCDA) is the selection of the flood risk factors and the estimation of their relative importance. A novel MCDA method through the integration of two state‐of‐the‐art MCDA methods based on catastrophe and entropy theory is proposed for mapping flood risk in the Peninsular Malaysia, an area very susceptible to flooding events, is presented. A literature review was undertaken which identified the various socioeconomic, physical and environmental factors which can influence flood vulnerability and risk. A set of variables was selected using an importance index which was developed based on a questionnaire survey. Population density, percentage of vulnerable people, household income, local economy, percentage of foreign nationals, elevation and forest cover were all deemed highly relevant in mapping flood risk and determining the zones of maximum vulnerability. Spatial integration of factors using the proposed MCDA revealed that coastal regions are highly vulnerable to floods when compared to inland locations. Flood risk maps indicate that the northeastern coastal region of Malaysia is at greatest risk of flooding. The prediction capability of the integrated method was found to be 0.93, which suggests good accuracy of the proposed method in flood risk mapping.
Highlights
Extreme rainfall-driven events such as flood or droughts have increased in severity and frequency in many regions as a result (Nashwan et al, 2019a, Sediqi et al, 2019)
4.1 Identification of flood vulnerability factors A large number of factors related to flood vulnerability in Peninsular Malaysia have been documented in various studies (Elsheikh et al, 2015, Alias et al, 2019, Dano et al, 2019)
A data-driven multi-criteria decision analysis (MCDA) approach through the integration of both catastrophe and entropy theories is proposed in this work which can provide an unbiased assessment of flood risk distribution in Peninsular Malaysia
Summary
Extreme rainfall-driven events such as flood or droughts have increased in severity and frequency in many regions as a result (Nashwan et al, 2019a, Sediqi et al, 2019). To ameliorate the risks associated with flooding events on the development of a region, it is important to define the spatial distribution of at-risk locations, in the context of ongoing climate change (Pour et al, 2020, Santos and Reis, 2018). Recent studies have reported the adverse consequences on the societies and economies of tropical regions arising from the increasing frequency and severity of weather extremes (Noor et al, 2019, Noor et al, 2018, Shahid et al, 2016, Sa’adi et al, 2017, Wong et al, 2018). As a result of these type of events, the development of flood management processes has been proposed to mitigate the negative impacts on people and the economy (Salarpour et al, 2013)
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