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Landslide-triggering rainfall thresholds are often subject to both false negatives (landslides where none are expected) and false positives (no landslides despite thresholds being exceeded). Debris flows and shallow landslides impact communities and infrastructures worldwide. Refinement of the relation between rainfall intensity and landslide occurrence would help remove the imprecise nature of this tool moving forward. Continuous 6-hour gridded precipitation data from over a five-year interval 900 km2, combined with a complete, time-constrained, landslide data base over the same period, are used to derive relations for the probability of shallow landslides with rainfall intensity measured over 6-hour, 12-hour, or 24-hour durations. Previously published and widely used thresholds are quantified in terms of landslide probability per unit area and demonstrate, for different sized study areas, the likelihood that at least one landslide will be initiated at different intensities and durations. Probabilistic distribution of landslides for a given study area and rainfall intensity can be easily derived using the binomial method from these relations.

Debris flow hazard and risk assessments are critical tools in mitigating and planning for these events. Existing debris flow hazard assessments can provide a rapid view of the likelihood of debris flows in recently burned watersheds and along stream segments within the watershed. Furthermore, debris flow volumes can be predicted for these watersheds and along the stream segments. Advances in modeling and remote-sensing data can add further value to the rapid assessments. Here, modeled debris flow volumes and a more detailed understanding of rainfall conditions highlight a need to reconcile debris flow probabilities and volumes using local conditions. Modeled debris flow volumes are consistently lower than even the lowest predicted volumes from empirical models used in the debris flow hazard assessments. Watershed probability and volume relations also over predict based on our probabilities derived from rainfall intensity from Multi-Radar/Multi-Sensor System 1-hr data. Probability and volume measures need to be further considered as the conservative measures of the rapid assessments have implication for risk analyses required for planning and management decisions, and ultimately for design and cost of mitigation to manage risk.

Often linear infrastructure, including rail, highways, and pipelines, span large geographic areas intersecting a variety of terrain, predisposing infrastructure to a higher likelihood of geohazard interaction. Debris flow models can be particularly advantageous in remote hazard and risk mapping along linear infrastructure as runout from susceptible slopes may extend considerable distance downslope to a receptor. In this sentiment, a method is developed using an agent-based model, DebrisFlow Predictor, in combination with geographic information software (GIS), to produce regional debris flow hazard and risk profiles along widespread corridors. Thousands of debris flows upslope of a receptor(s) are simulated in the model environment (i.e., model scenarios). Outputs of the modelled scenarios provide probabilistic spatial attributes of debris flow runout and depth across a digital elevation model at a 5m resolution. The outputs of multiple scenarios are mosaiced and corrected to in-situ temporal and spatial debris flow initiation conditions in GIS. The corrected scenario outputs provide a comprehensive hazard profile along the infrastructure alignment, that in turn can facilitate quantified vulnerability and risk calculations. Thousands of modelled debris flows throughout several physiographic regions of Canada and the United States of America, calibrated to local conditions, provide substantive support for a novel methodology to identify key hazard and risk locations to major linear infrastructure.