A landslide susceptibility mapping study was performed using dynamic hillslope hydrology. The modified infinite slope stability model that directly includes vadose zone soil moisture(SM) was applied at Cleveland Corra...A landslide susceptibility mapping study was performed using dynamic hillslope hydrology. The modified infinite slope stability model that directly includes vadose zone soil moisture(SM) was applied at Cleveland Corral, California, US and Krishnabhir, Dhading, Nepal. The variable infiltration capacity(VIC-3L) model simulated vadose zone soil moisture and the wetness index hydrologic model simulated groundwater(GW). The GW model predictions had a 75% NASH-Sutcliffe efficiency when compared to California's in-situ GW measurements. The model performed best during the wet season. Using predicted GW and VIC-3L vadose zone SM, the developed landslide susceptibility maps showed very good agreement with mapped landslides at each study region. Previous quasi-dynamic model predictions of Nepal's hazardous areas during extreme rainfall events were enhanced to improve the spatial characterization and provide the timing of hazardous conditions.展开更多
基金NASA’s research funding through Earth System Science Fellowship, Grant No: NNG05GP66H, for this research
文摘A landslide susceptibility mapping study was performed using dynamic hillslope hydrology. The modified infinite slope stability model that directly includes vadose zone soil moisture(SM) was applied at Cleveland Corral, California, US and Krishnabhir, Dhading, Nepal. The variable infiltration capacity(VIC-3L) model simulated vadose zone soil moisture and the wetness index hydrologic model simulated groundwater(GW). The GW model predictions had a 75% NASH-Sutcliffe efficiency when compared to California's in-situ GW measurements. The model performed best during the wet season. Using predicted GW and VIC-3L vadose zone SM, the developed landslide susceptibility maps showed very good agreement with mapped landslides at each study region. Previous quasi-dynamic model predictions of Nepal's hazardous areas during extreme rainfall events were enhanced to improve the spatial characterization and provide the timing of hazardous conditions.
