Landslides in the US and around the world constitute a serious hazard that causes substantial human and financial loss. In the US alone, the estimated loss averages 25 to 50 deaths and approximately $1 billion to $3 billion per year (NRC, 2004). As a result of a Congressional directive, a National Landslide Hazards Strategy, coordinated by the USGS, has been established which calls for focused activities, ranging from basic research to improved policy measures. The future GPM products offer a tremendous opportunity to: (a) advance our understanding of rainfall-induced landslide hazards, (b) develop and test predictive models that incorporate uncertainty and risk, and (c) deploy effective operational forecasting and warning systems over large areas. Specifically, the goal of the proposed research is to evaluate the potential of the GPM products to advance fundamental understanding and enhance our operational ability to predict rainfall-induced landslides. The specific objectives are: (1) develop quantitative understanding of the statistical multiscale properties of space-time rainfall in complex terrain; (2) develop and test multiscale/multisensor merging techniques and a space-time downscaling model to disaggregate rainfall from the GPM scale of 4 km, 3 hrs to scales commensurate with those needed for landslide prediction (~0.1-0.5km; ~0.5-1.0 hrs); (3) build, based on accepted slope stability and hillslope hydrology theories, a process based model for predicting shallow landslides, acknowledging the uncertainty in the rainfall products and in model parameters; and (4) apply the model in an operation context and for enhancing our understanding of the factors that control the spatio-temporal pattern of landslides. The proposed research aims to bridge the TRMM/GPM remote sensing community with the hydro-geomorphology, earth-surface hazards communities for the purpose of improved prediction of rainfall-induced hazards using GPM precipitation products in mountainous regions. Although this proposal does not directly address flood prediction, the proposed physical-statistical downscaling model for orographic precipitation will contribute to the wider use of GPM products for hydrologic applications.
