Abstract
Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF) are compared with the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.
Highlights
Rainfall-induced landslides are widespread phenomena that cause casualties and extensive damages every year
Differently from the other literature papers, we focus on the evaluation of the possible use of satellite rainfall products for the forecast of rainfall-induced landslides, introducing specific analyses
This study focuses on the analysis and comparison of TMPA and VRF data in Italy, where the climate variability is large and where landslides and other instability processes are frequent
Summary
Rainfall-induced landslides are widespread phenomena that cause casualties and extensive damages every year. Forecasting the occurrence of the rainfall-induced landslide is challenging due to the nature of these hazards and the information required to assess the triggering phenomena. Rainfall-induced landslides predominately occur within steep topography where intense or prolonged rainfall increases pore water pressures and decreases soil cohesion in the subsurface, causing the driving forces to overcome resisting forces on a hill slope and activate a landslide [3]. Approaches to analyze rainfall-induced landslide triggering include: (i) empirical approaches focus on the determination of rainfall thresholds [4,5,6,7]; and (ii) deterministic approaches use a physically-based modelling schema that generally couples an infiltration model to an instability model to estimate slope stability/instability conditions [8,9,10].
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