Barguna District, situated in the south-central coastal zone of Bangladesh, experiences periodic storm surges and coastal floods caused by cyclones, which lead to progressive salinity intrusion into agricultural land and freshwater sources. Although Barguna is consistently recognized as one of Bangladesh's most hazard-prone coastal districts, no systematic risk assessment has mapped the spatial distribution of flood-induced salinity intrusion at the local scale. This research addresses this gap by introducing a spatial multi-criteria approach that integrates remote sensing, geographic information systems (GIS), and the Analytical Hierarchy Process (AHP) to evaluate salinity intrusion risk across the district.
Risk is conceptualized through three components: hazard, vulnerability, and exposure, evaluated using sixteen spatial criteria spanning salinity level, storm surge height, sea-level change, elevation, slope, soil salinity, land use, population density, and embankment density. Thematic raster layers were developed for each criterion and weighted using AHP pairwise comparisons based on expert judgment. Component maps were generated using a weighted sum technique, and a final risk index was calculated by multiplying the three component scores. The index was categorized into five risk levels and validated through ROC-AUC analysis against a field-based salinity inventory.
The results are expected to yield a spatially explicit five-class risk map that identifies the most salinity-prone zones across Barguna District. Elevated risk is anticipated in the low-lying southern and south-eastern upazilas along the tidal river network, where low elevation, high storm-surge exposure, and proximity to rivers are the primary contributing factors. The more elevated inland northern areas are expected to fall within lower risk classes. The resulting risk information aims to inform targeted adaptation planning and salinity management policy in coastal Bangladesh. Furthermore, the proposed framework may be applicable to other coastal districts with similar geo-climatic conditions.