3,4,5,7,8,9,1,9- 1KU Leuven, Department of Civil Engineering, Hydraulics and Geotechnics, Leuven, Belgium
- 2INES Ruhengeri, Department of Civil Engineering, Musanze, Rwanda
- 3Royal Museum for Central Africa, Department of Earth Sciences, Tervuren, Belgium
- 4Rwanda Institute for Conservation Agriculture (RICA), Department of Mechanization and Irrigation Enterprise, Bugesera, Rwanda
- 5Delft University of Technology, Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft, The Netherlands
- 6University of Rwanda, College of Agriculture, Forestry and Food Science, Musanze, Rwanda
- 7KU Leuven, Department of Earth and Environmental Sciences, Leuven, Belgium
- 8Ghent university, Department of Geography, Ghent, Belgium
- 9Royal Meteorological Institute of Belgium (KMI), Brussels, Belgium
Abstract
Rainfall-triggered landslides constitute a major natural hazard worldwide and are especially prevalent in mountainous regions experiencing intense rainfall. Despite substantial progress in the development of empirical hydrometeorological thresholds for landslide initiation, a central challenge remains the definition of spatially distributed thresholds that adequately represent both hydrological preconditioning, rainfall triggering and spatial variability in hillslope response. Existing regional approaches often rely on antecedent rainfall as a proxy for subsurface conditions or treat slope susceptibility as spatially homogeneous, thereby limiting their physical interpretability and operational robustness.
This study develops a susceptibility-informed hydro-meteorological threshold framework for rainfall-triggered landslides in Rwanda, a mountainous country of tropical Africa in an under-researched type of climate. The framework explicitly integrates rainfall triggering, hydrological preconditioning, and spatial variability in slope response within the cause–trigger concept. Rainfall forcing is derived from IMERG and downscaled from its native 0.1° (~10 km) spatial resolution to 1 km to better capture local-scale rainfall variability in complex terrain. Hydrological preconditioning is represented using a simple leaky-bucket water-balance model, providing spatially distributed proxy indicators of soil moisture and subsurface water storage that explicitly characterize antecedent wetness conditions relevant for slope stability.
Hydro-meteorological thresholds are formulated by combining rainfall intensity–duration and cumulative rainfall metrics with hydrological state indicators derived from the water-balance model. The threshold behavior is explicitly conditioned on an existing regional landslide susceptibility map, allowing identical hydro-meteorological forcing to produce different threshold responses depending on terrain predisposition. A landslide inventory comprising 82 documented events of exact known date of occurrence from 2000 to 2024 is used to analyze trigger–response relationships and to evaluate threshold behavior across susceptibility classes. Thresholds are explored using empirical and statistical techniques, including cumulative rainfall analysis, multi-dimensional trigger plots, and receiver operating characteristics (ROC)-based performance assessment.
Preliminary results show that observed landslides are strongly concentrated in moderate to high susceptibility classes, with frequency ratio (FR) values increasing from 0.24 in very low susceptibility areas to 4.1 in very high susceptibility areas. This supports conditioning hydro-meteorological thresholds on spatial predisposition, enabling more spatially differentiated and physically interpretable early warning thresholds.
Keywords: Rainfall-triggered landslides, Hydro-meteorological thresholds, Antecedent wetness, Landslide susceptibility
How to cite: Dusabimana, J. D., Dewitte, O., Uwihirwe, J., Bogaard, T., Bugenimana, E. D., Musemakweri, J., Vanmaercke, M., Van Weverberg, K., and Reinoso Rondinel, R.: Susceptibility-informed hydro-meteorological thresholds for rainfall-triggered landslides in Rwanda, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6632, https://doi.org/10.5194/egusphere-egu26-6632, 2026.
