TITLE:
Geospatial Assessment of Flood Susceptibility in the Nong Peung Wetland, Central Laos
AUTHORS:
Vongphet Sihapanya, Chittana Phompila, Xinping Wen, Kethsa Nongthavongduangsi, Metmany Soukhavong, Phomsanh Chantharangsone, Rajendra P. Shrestha
KEYWORDS:
Flood Susceptibility, Land Use Change, Hazard Assessment, Remote Sensing/GIS, Wetland Hydrology, Central Laos
JOURNAL NAME:
Advances in Remote Sensing,
Vol.14 No.4,
December
12,
2025
ABSTRACT: Inundation events within the Nong Peung wetland of Pakxan district, Laos, represent a growing environmental and societal challenge, a threat compounded by the interplay of accelerated land use transformations, ongoing deforestation, and the broader impacts of climate change. This study presents the first systematic, geospatial assessment of flood susceptibility for this critical region, filling a significant void in local hazard analysis. We applied an integrated model utilizing a Geographic Information System (GIS) coupled with a Multi-Criteria Decision-Making (MCDM) approach, using the Analytical Hierarchy Process (AHP) for the systematic weighting of causative factors. The analysis incorporated nine determinative variables: elevation, slope, annual rainfall, proximity to river channels, drainage density, Topographic Wetness Index (TWI), land use/land cover, soil composition, and the Normalized Difference Vegetation Index (NDVI). The resultant susceptibility model stratifies the landscape into five classes, identifying 13.80% of the area as “very high risk” and 20.06% as “high risk.” Cumulatively, our model indicates that more than half (61.42%) of the wetland exhibits moderate to very high susceptibility to flooding. Areas of acute risk are concentrated in the northern and southern portions of the wetland, a spatial pattern directly attributable to a convergence of low elevation, gentle slopes, concentrated rainfall, high drainage density, and predominant agricultural land use. Validation against historical flood records confirms a strong predictive agreement, substantiating the reliability of the AHP-GIS framework for this application. The high-resolution susceptibility map produced by this research offers a foundational, evidence-based tool for enhancing disaster risk reduction strategies and guiding sustainable development in the Pakxan district.