Coupled Adaptive Cycles of Shoreline Change and Households in Deltaic Bangladesh: Analysis of a 30-Year Shoreline Change Record and Recent Population Impacts

Thomas W. Crawford, Munshi Khaledur Rahman, Md. Giashuddin Miah, Md. Rafiqul Islam, Bimal Kanti Paul, Scott Curtis and Md. Sariful Islam

Annals of the American Association of Geographers, 2021, vol. 111, issue 4, 1002-1024

Abstract: This research investigates the spatiotemporal dynamics of shoreline change and associated population impacts in deltaic Bangladesh. This region is among the world’s most dynamic deltas due to monsoon precipitation that drives tremendous discharge and sediment volumes from the Ganges–Brahmaputra–Meghna drainage basin. Theoretically, it draws on the concept of adaptive cycles that theorizes systems transitioning through phases of growth, conservation, release (collapse), and reorganization, with a focus on the cycle’s release (collapse) phase and coupled linkages between the natural system of shoreline change and social system of household behavior. We use Landsat imagery to produce and describe a thirty-year record of shoreline change for an 80-km stretch of the Lower Meghna estuary. Household survey data characterized population impacts and risk perception for a subregion with high erosion rates. Results identified significant space–time differences and patterns of shoreline change and population impacts consistent with the adaptive cycle. North, central, and south regions exhibited statistically significant differences in space–time patterns of shoreline change. Substantial numbers of households reported displacement due to riverbank erosion and high levels of experience and worry about future displacement. Results demonstrate how geospatial analysis of a multidecade record of shoreline change along with analysis of household survey data can identify regions most vulnerable to riverbank erosion with implications to inform mitigation and adaptation. This work adds empirical demonstration of coupled adaptive cycles to the literature. Limitations and complexities of the adaptive cycle framework are discussed.

Date: 2021
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DOI: 10.1080/24694452.2020.1799746

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