The effects of changing land use and flood hazard on poverty in coastal Bangladesh

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 appraisal 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 presentday 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.

Contrasting development trajectories for coastal Bangladesh to the end of century

“…They face severe multiple pressures, including reduced sediment supply due to upstream dams, subsiding land due to the embankment and/or groundwater withdrawal (Adnan et al 2019;Syvitski et al 2009), waterlogging, salinization (Bernier et al 2016), flooding, cyclones, climate change and sea-level rise (SLR). These chronic and acute processes directly influence the livelihood potential and the wellbeing of delta populations and vice versa (Adnan et al 2020). It is essential that delta development considers these processes and their interaction to minimize unintended and unexpected consequences.…”

Prediction Approaches for Smart Cultivation: A Comparative Study

“…Furthermore, the maximum temperature was quite decent, even though the minimum temperature for Mymensingh was upward compared to the other districts. Moreover, in the Mymensingh district, there are a huge number of noncalcareous dark grey floodplain soils, noncalcareous grey floodplain soils, deep red-brown terrace soils, shallow red-brown terrace soils, and acid basin clay soils [10]. Furthermore, we have found numerous soil textures in the Mymensingh area.…”

“…Hence, the objective of this research is to explore the possibilities of using a modern technology-driven prediction model to assist the farmers in efficiently selecting crops and maximizing the yield potentialities [10]. It is very important to explore alternatives to traditional agriculture systems so that the continuously increasing food demand of overly populated countries like Bangladesh can be addressed.…”

Examining the Effects of Land Use on Carbon Emissions: Evidence from Pearl River Delta

“…Land use is an important factor that affects carbon emissions [ 21 ]. To estimate the carbon emissions caused by land-use change, it is essential to first calculate the extent and character of land-use change [ 39 ]. We used land-cover data for six periods (1990, 1995, 2000, 2005, 2010, and 2015) with a resolution of 30 m, and included six first-grade land-use types in order to estimate the spatial and temporal dynamics of land use in the PRD.…”