Rainfall Thresholds for Geological Disasters in Rainfall Data-Scarce Mountainous ： A Case Study of Mao County

Objectives Rainfall-induced geological disasters often result in significant human and property losses, and rainfall thresholds can effectively reduce the hazards of geological disasters. However, limited rainfall data in mountainous areas lead to low accuracy of rainfall thresholds. Establishing rainfall thresholds in mountainous areas with scarce data is an unresolved problem.

Methods We downscale global precipitation measurement (GPM) data to the resolution of 1 km and verify its validity with ground station rainfall. By combining disaster data, we extract rainfall events and obtain critical thresholds for different types of disasters and different precisions in Mao County based on the frequency method. Furthermore, we also analyze the evolution of the threshold curves over the years following the earthquake.

Results Rainfall-induced landslides in Mao Country area are primarily controlled by long-duration weak rainfall, while debris flows are dominated by short-duration intense rainfall. Assuming cumulative rainfall is E and rainfall duration is D, the critical threshold equations are: $E=\mathrm{4.17}{D}^{\mathrm{0.18}}$ (8<D<868) and $E=\mathrm{3.93}{D}^{\mathrm{0.24}}$ (10<D<441). The rainfall threshold after downscaling is lower than the unscaled threshold, and the critical threshold equation can be expressed as: $E=\mathrm{4.09}{D}^{\mathrm{0.19}}$ (8<D<868) and $E=\mathrm{3.96}{D}^{\mathrm{0.21}}$ (4<D<736). The rainfall events that triggered geological disasters in Mao County after the earthquake have shift from long-duration weak rainfall to short-duration intense rainfall control, and rainfall thresholds show an increasing trend over time.

Conclusions Downscaling can effectively enhance the spatial resolution of rainfall products and improve their ability to capture rainfall events. The critical thresholds established by downscaled data can serve as the minimum indicators for disaster monitoring and early warning in Mao County.