Integrated Rainfall Estimation Using Rain Gauges and Weather Radar: Implications for Rainfall-Induced Landslides

Highlights: What are the main findings? The integration of radar and rain gauge data significantly improves the quality of spatial rainfall representation compared to using rain gauges alone, even in rela-tively small and densely instrumented areas. Radar data calibrated with rain gauges provides a more accurate estimate of landslide-triggering rainfall. What is the implication of the main finding? Improved rainfall estimates based on the combined use of radar and rain gauges, enhance landslide risk assessment and the reconstruction of cumulative rainfall that triggers landslide events. The integrated approach of radar and rain gauge data generally supports a better understanding of hydrological and geomorphological processes and a more effec-tive management of flood and landslide risk, providing more realistic inputs for hydrological modeling and early warning systems. The availability of reliable and spatially distributed rainfall data is a key element flood and landslide risk assessment, both for forecasting and post-event analysis. In this context, this study evaluates the contribution of radar-based rainfall estimates to enhancing the spatial accuracy of precipitation fields with respect to those derived from rain gauge networks alone. The analysis was conducted over a ~100 km2 area in the Liguria Region, north-western Italy, characterized by a dense rain gauge network, with an average density of one gauge per 10 km2, and covers seven years of hourly rainfall observations. Radar-derived rainfall fields, available at a 1 × 1 km2 spatial resolution, were locally corrected across the study area by interpolating gauge-based local correction factors through an Inverse Distance Weighting (IDW) scheme. The corrected radar fields were then assessed through Leave-P-Out Cross-Validation and rainfall-intensity-based classification, also simulating scenarios with progressively reduced gauge density. The results demonstrate that radar-corrected estimates systematically provide a more accurate spatial representation of rainfall, especially for high-intensity events and in capturing the actual magnitude of local rainfall peaks, even in areas covered by a dense rain gauge network. Regarding the implications for rainfall-induced landslide hazard assessment, the analysis of 56 landslides from the ITALICA (Italian Rainfall-Induced Landslides Catalogue) database showed that including radar information can lead to significant differences in the estimation of rainfall thresholds for landslide initiation compared with gauge-only data.