Geophysical Analysis Of Flood Susceptibility In Nyabarongo Lower Catchment, Rwanda

Emile Niragire, Aboubakar Gasirabo

Abstract


Floods have increasingly been observed as a recurring phenomenon and increasingly hazardous in the Nyabarongo Lower Catchment, Rwanda, which is characterized by fast-changing land use/land cover (LULC) together with topography and hydrology, all determining whether floods will occur or not. The current study sought to determine the impact of LULC changes in shaping flood susceptibility in the Nyabarongo Lower Catchment using Geographic Information Systems (GIS), Remote Sensing (RS) and the Analytical Hierarchy Process (AHP) under the Multi-Criteria Decision Analysis (MCDA) framework. Multitemporal Landsat images for the years 1990, 2000, 2010, 2020 and 2025 were classified into six LULC categories and were validated using stratified random sampling techniques that resulted in an overall average accuracy of 86.0% and Kappa coefficient of 0.83. There were ten factors considered during the evaluation of flood susceptibility in the study area and these include distance to river, topographic wetness index (TWI), elevation, slope, rainfall, drainage density, LULC, curvature, aspect and distance to road. Forest cover decreased by 68.4% from 1,099,311 ha in 1990 to 347,762 ha in 2025, wetlands by 91.1% while cropland increased by 180.3% and built-up land by 596%. FSI generated maps identified five susceptibility classes: very low (19.65%), low (27.79%), moderate (28.95%), high (14.92%) and very high (8.69%). 23.61% (approx. 71,188 ha) of the catchment area was found highly to very highly susceptible to flooding mostly along low-lying floodplains and riparian corridors. Spatial overlay analysis established a positive relationship between forest and wetland loss and the increase in the high susceptibility class with 67.2% of the remaining wetlands and waterbodies falling within high and very high susceptibility areas and more than 65% of new built-up area expansion between 2010 and 2020 falling within the moderate-to-very-high susceptibility class. The results illustrate the importance of anthropogenic land transformation over terrain alone as a major cause of increased flood risk in the catchment, and highlight the potential benefits of the application of multi-temporal LULC and GIS-AHP modeling in the evidence-based conservation of wetlands, river buffers and land use planning in Rwanda and similar East African catchments.

Keywords


Analytic Hierarchy Process; Flood susceptibility; GIS; LULC; Multi-Criteria Decision Analysis

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References


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DOI: http://dx.doi.org/10.52155/ijpsat.v59.1.8469

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