A step towards unravelling dynamics and connectivity of slow-moving landslides in changing tropical landscapes

Human activities transform Earth's ecosystems and landscapes at unprecedented rates and scales. Land use changes are particularly drastic in economically developing countries of the tropics, where major demographic and economic shifts are driving unparalleled rates of agricultural expansion, deforestation and urbanisation. These changes to the environment are increasing the incidence of geo-hydrological hazards such as landslides. Dramatic increase in the occurrence of shallow, high-velocity landslides has been comprehensively demonstrated on recently deforested and/or urbanised steep slopes. Yet, our understanding of how such constraints – typical for the tropics – interact and affect larger (often > 0.2 km²), slow-moving (mm year−1 to 100 m year−1), deep-seated (> 5 m) landslides (SML) remains very limited. Often manifesting as long-term, persistent slope failures, these SML can nevertheless permanently affect the livelihood of local communities in mountain regions. Their connectivity to river networks also places them as a dominant geomorphic process in mountain landscapes: they shape the morphology of hillslopes and can exert very strong controls on river sediment budgets, regional erosion rates, channel network evolution and flooding patterns. Nevertheless, estimations of landslide mobilisation rates over sufficient spatiotemporal scales are very scarce, especially in tropical environments. As a result, the potential interactions between rivers and landslide dynamics remain poorly constrained while being key for our understanding of landscape evolution, sediment budgets and geo-hydrological hazards.

Untangling the intricate influences of climate, lithology, tectonics and man-made environmental changes on the activity of SML will require a large and robust dataset across diverse landscape conditions. Here, we aim to present and discuss our strategy is to quantify SML spatio-temporal patterns over the western branch of the East African Rift System (wEARS), a > 1000 km north-south region exemplary of many tropical mountain areas, i.e., affected by large-scale land use changes and disproportionately high landslide impacts – as well as largely overlooked in landslide research. Synergies between different space-borne remote sensing tools (combined use of optical and radar imagery, historical aerial photographs, etc.), which proved effective in our recent work in the region, will be exploited to gather a large dataset on the activity of SML across diverse time scales, landscapes and climatic conditions in the wEARS. Overall, this work aims at moving forward our understanding of a key geomorphic process in severely under-researched types of environments subject to rapid changes. This is not only essential for a better hazard assessment, but also for comprehending how (human-induced and/or natural) environmental changes affect these landscapes and the sediment dynamics.