Investigating the Feasibility of Using Satellite Rainfall for the Integrated Prediction of Flood and Landslide Hazards over Shaanxi Province in Northwest China

Rainfall-triggered flood and landslide hazards pose significant threats to human lives infrastructure worldwide. This study aims evaluate the applicability of three satellite rainfall data sets—namely, CMORPH, GPM, TRMM—for prediction using a coupled hydrological-slope stability model. The spatial distribution annual from sets was similar that gauge rainfall, with an increasing trend north south Shaanxi Province. average CMORPH lowest, while TRMM highest. modeled discharges forcing by generally matched observed at four hydrological stations for period 2010–2012, correlation coefficients 0.51, 0.61, 0.57 respectively. exceedance probabilities were close those observations, particularly when low. Moreover, results demonstrated could simulate events well; these simulations consistent information in inventory map. Furthermore, compared classical Intensity-Duration (ID) threshold method, physically based slope model presented higher global accuracy under all sets. GPM highest among (0.973 vs. 0.951 0.965 TRMM), indicating provides quality rainfall. These findings provide crucial basis application context prediction.