Section Water Resources, Department of Water Management, Faculty of
Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
Department of Irrigation and Drainage, School of Agricultural
Engineering, College of Agriculture Animal Sciences and Veterinary Medicine,
University of Rwanda, P.O. Box 210, Musanze, Rwanda
Alessia Riveros
Section Water Resources, Department of Water Management, Faculty of
Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
Deltares, P.O. Box 177, 2600 MH Delft, the Netherlands
Hellen Wanjala
Planet Labs, PBC, Wilhelminastraat 43A, 2011 VK Haarlem, the
Netherlands
Jaap Schellekens
Planet Labs, PBC, Wilhelminastraat 43A, 2011 VK Haarlem, the
Netherlands
Frederiek Sperna Weiland
Deltares, P.O. Box 177, 2600 MH Delft, the Netherlands
Section Water Resources, Department of Water Management, Faculty of
Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
Section Water Resources, Department of Water Management, Faculty of
Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
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This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
This study compared gauge-based and satellite-based precipitation products. Similarly,...
