Coupled Adaptive Cycles of Shoreline Change and Households in Deltaic Bangladesh: Analysis of a 30-Year Shoreline Change Record and Recent Population Impacts
Coupled Adaptive Cycles of Shoreline Change and Households in Deltaic Bangladesh: Analysis of a 30-Year Shoreline Change Record and Recent Population Impacts
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DOI：
10.1080/24694452.2020.1799746
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发表时间：
2020-09
影响因子：
3.9
通讯作者：
T. Crawford;M. Rahman;M. G. Miah;Md. Rafiqul Islam;B. Paul;S. Curtis;Md Nazmul Islam
中科院分区：
文献类型：
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作者：
T. Crawford;M. Rahman;M. G. Miah;Md. Rafiqul Islam;B. Paul;S. Curtis;Md Nazmul Islam
本研究探讨了孟加拉三角洲地区海岸线变化的时空动态及其对人口的影响。由于季风降水，该地区是世界上最具活力的三角洲之一，它驱动着恒河-布拉马普特拉河-梅克纳河流域的巨大流量和沉积物量。从理论上讲，它借鉴了适应周期的概念，该概念将系统的过渡理论化为生长、保护、释放（崩溃）和重组的阶段，重点关注周期的释放（崩溃）阶段以及海岸线变化的自然系统与家庭行为的社会系统之间的耦合联系。我们使用陆地卫星图像来生成和描述下梅克纳河河口80公里长的海岸线变化的30年记录。住户调查数据反映了高侵蚀率分区域的人口影响和风险认知。结果表明，沿海岸线变化和种群影响具有明显的时空差异，且与适应周期相一致。北、中、南3个区域海岸线变化时空格局差异显著。大量家庭报告说，由于河岸侵蚀和高度的经验和对未来流离失所的担忧而流离失所。结果表明，对数十年的海岸线变化记录进行地理空间分析，并对住户调查数据进行分析，可以确定最容易受到河岸侵蚀的地区，从而为缓解和适应提供信息。这项工作为文献增加了耦合适应周期的实证证明。讨论了自适应循环框架的局限性和复杂性。
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.