Author
Mohammed Sarfaraz Gani Adnan
Paper Keyword
Land use change model,Flood risk,Poverty,Cellular automata,Markov Chain
Abstract
The construction of polders in the coastal region of Bangladesh has significantly modified the patterns of flooding, as well as leading to significant land use/land cover (hereinafter, LULC) changes. The impact of LULC change and flooding on poverty is complex and poorly understood. This study presents a spatiotemporal ap praisal of poverty in relation to LULC change and pluvial flood risk in the south western embanked area of Bangladesh. A combination of logistic regression (LR), cellular automata (CA), and Markov Chain models were utilised to predict future LULC based on historical data. Flood risk assessment was performed at present and for future LULC scenarios. A spatial regression model was developed, incorporating multiple parameters to estimate the wealth index (WI) for present-day and future scenarios. In the study area, agricultural lands reduced from 34% in 2005 to 8% in 2010, while aquaculture land cover increased from 17 % to 39 % during the same time. The rate of LULC change was relatively low between 2010 and 2019. Based on the recent trend, LULC was predicted for the year 2030. Flood risk was positively correlated with LULC and the expected annual damage (EAD) was estimated at $903 million in 2005, which is likely to increase to $2096 million by 2030, considering changes in LULC scenarios. The analysis further showed that the EAD and LULC change were negatively associated with the WI. Despite consistent national GDP growth in Bangladesh in recent years, the rate of increase of WI is likely to be low in the future because flood risk and patterns of LULC change have a negative effect on WI.
