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Title: Susceptibility to changes in coastal land dynamics in Bangladesh
Author: Ahmed, Asib
ISNI:       0000 0004 7654 7029
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2018
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Coastal areas of the world are physically dynamic in nature. The present study contributes new knowledge to studies on coastal land dynamics and land susceptibility to erosion. This study developed a raster GIS-based model namely, Land Susceptibility to Coastal Erosion (LSCE) to assess erosion susceptibility of coastal lands under hydro-climatic changes. The devised model was applied to the entire coastal area of Bangladesh. The model required the characterisation of the nature of land dynamics (i.e. erosion and accretion). The analysis showed a net gain of 237 km² of land over the past thirty years but, constant changes in land dynamics were observed in the area. The study then applied the LSCE model to measure the existing levels of land susceptibility of the coastal area to erosion. The validated model outputs were then used as a baseline for generating four possible scenarios of future land susceptibility to erosion in the coastal area. This allowed the model to ascertain the probable impacts of future hydro-climatic changes on land susceptibility to erosion in the area. Additionally, the study assessed seasonal variations of land susceptibility to erosion by using the same model. The model outputs showed that 276.33 km² of existing coastal lands classified as highly and very highly susceptible to erosion, would substantially increase in the future. Using a Fuzzy Cognitive Mapping (FCM) approach, the study elicited expert views to evaluate the model scenarios and to address uncertainties relevant to erosion susceptibility. This study could allow coastal managers and policymakers to develop effective measures in managing highly erosion susceptible coastal lands in the area.
Supervisor: Woulds, Clare ; Drake, Frances ; Nawaz, Rizwan Sponsor: University of Leeds
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available