Landslides and vegetation fragmentation drive hydro-sedimentary hazards and urban flooding in Uvira
Abstract
Across the mountainous regions of the East African Rift, interactions between human activities and extreme rainfall events can intensify urban hydro-geomorphological hazards. Yet, observation remains challenging, as remote sensing in humid tropical terrains can be constrained by e.g., persistent cloud cover and dense canopy. This study focused on Uvira (Democratic Republic of the Congo), a city built on narrow alluvial fans along Lake Tanganyika’s northwestern shores, where recent rainfall events (2020-2021) culminated in severe floods. We examined the upstream-downstream sediment cascade to clarify the processes driving flood genesis. We applied an integrated approach combining extensive field observation campaigns, morpho-dimensional classification of 225 erosive events, Sentinel-2 imagery processed via Google Earth Engine, and statistical workflow. Results revealed a predominance of landslides (44.40%) and sheet erosion (38.20%), largely influenced by steep gradients between 900 and 1700 m. Statistical analysis (χ2 = 35.42; p > 0.05) showed no significant link between land-cover class and slope failures, suggesting that fragmented vegetation cover, likely linked to unplanned urbanization, may drive localized infiltration and slope instability. Hazards appeared controlled by dual rainfall regimes: seasonal accumulation (800-1000 mm) followed by short, intense pulses (e.g., 114 mm in 6 h). These conditions generated rapid hydro-sedimentary responses, with 3-4 m riverbed aggradation at the Kavimvira and Mulongwe River’s outlets, severely affecting downstream residential areas. Conversely, the Kalimabenge River carried a smaller sediment load, likely reflecting upstream reforestation. This work advances understanding of sediment connectivity and vegetation fragmentation in tropical rift environments. It highlights the need to move beyond curative dredging toward integrated watershed management, eco-protective measures, and participatory monitoring. Given the scarcity of hydrometeorological data in Uvira, these findings provide a baseline for land-use planning and risk reduction.