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Empirical models to estimate the probability of occurrence and volume of postwildfi re debris fl ows can be quickly implemented in a geographic information system (GIS) to generate debris-fl ow hazard maps either before or immediately following wildfi res. Models that can be used to calculate the probability of debris-fl ow production from individual drainage basins in response to a given storm were developed using logistic regression analyses of a database from 388 basins located in 15 burned areas located throughout the U.S. Intermountain West. The models describe debris-fl ow probability as a function of readily obtained measures of areal burned extent, soil properties, basin morphology, and rainfall from short-duration and lowrecurrence-interval convective rainstorms. A model for estimating the volume of material that may issue from a basin mouth in response to a given storm was developed using multiple linear regression analysis of a database from 56 basins burned by eight fi res. This model describes debris-fl ow volume as a function of the basin gradient, aerial burned extent, and storm rainfall. Applications of a probability model and the volume model for hazard assessments are illustrated using information from the 2003 Hot Creek fi re in central Idaho. The predictive strength of the approach in this setting is evaluated using information on the response of this fi re to a localized thunderstorm in August 2003. The mapping approach presented here identifi es those basins that are most prone to the largest debris-fl ow events and thus provides information necessary to prioritize areas for postfi re erosion mitigation, warnings, and prefi re management efforts throughout the Intermountain West.

We model the rainfall-induced initiation of shallow landslides over a broad region using a deterministic approach, the Transient Rainfall Infiltration and Grid-based Slope-stability (TRIGRS) model that couples an infinite-slope stability analysis with a one-dimensional analytical solution for transient pore pressure response to rainfall infiltration. This model permits the evaluation of regional shallow landslide susceptibility in a Geographic Information System framework, and we use it to analyze susceptibility to shallow landslides in an area in the eastern Umbria Region of central Italy. As shown on a landslide inventory map produced by the Italian National Research Council, the area has been affected in the past by shallow landslides, many of which have transformed into debris flows. Input data for the TRIGRS model include time-varying rainfall, topographic slope, colluvial thickness, initial water table depth, and material strength and hydraulic properties. Because of a paucity of input data, we focus on parametric analyses to calibrate and test the model and show the effect of variation in material properties and initial water table conditions on the distribution of simulated instability in the study area in response to realistic rainfall. Comparing the results with the shallow landslide inventory map, we find more than 80% agreement between predicted shallow landslide susceptibility and the inventory, despite the paucity of input data.

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