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This data release contains two debris-flow inventories summarizing observations from burned and unburned areas in the western Cascade Range of Oregon (OR). The burned inventory focuses on debris flows that occurred during the first two years after the 2020 Archie Creek, Holiday Farm, Beachie Creek/Lionshead, and Riverside fires (OR_field_observations.csv). The unburned inventory (1995-2022) focuses on debris flows in the same areas (excluding the Riverside Fire). The inventories are derived from field observations (OR_field_observations.csv) and aerial imagery (OR_imagery_observations.csv). They include mapped debris-flow initiation locations, descriptions of the inferred initiation process, other notable site characteristics, and rainfall data. Locations of debris flows observed after wildfires are also linked to USGS postfire debris-flow hazard assessments (USGS, 2022; Staley and others, 2017; Thomas and others 2023). Rainfall characteristics for each debris flow in the inventory are derived from the closest rainfall gage to an observed debris flow (gage_locations.csv). Peak rainfall rates during the known time window of debris-flow initiation are reported for durations of 15 minutes, 30 minutes, 60 minutes, 12 hours, 24 hours, 36 hours, and 48 hours. More detailed explanations of the headers for each of these csv files can be found within the README_csvname.txt file. References: Landslide Hazards Program. (n.d.). Emergency assessment of post-fire debris-flow hazards. U.S. Geological Survey. https://landslides.usgs.gov/hazards/postfire_debrisflow Staley, D. M., Negri, J. A., Kean, J. W., Laber, J. L., Tillery, A. C., and Youberg, A. M., 2017, Prediction of spatially explicit rainfall intensity–duration thresholds for post-fire debris-flow generation in the western United States. Geomorphology, 278, 149–162. https://doi.org/10.1016/j.geomorph.2016.10.019 Thomas, M. A., Kean, J. W., McCoy, S. W., Lindsay, D. N., Kostelnik, J., Cavagnaro, D. B., Rengers, F. K., East, A. E., Schwartz, J. Y., Smith, D. P., and Collins, B. D., 2023, Postfire hydrologic response along the Central California (USA) coast: insights for the emergency assessment of postfire debris-flow hazards. Landslides, 20, 2421-2436. https://doi.org/10.1007/s10346-023-02106-7 

Debris flows pose persistent hazards and shape high‐relief landscapes in diverse physiographic settings, but predicting the spatiotemporal occurrence of debris flows in postglacial topography remains challenging. To evaluate the debris flow process in high‐relief postglacial terrain, we conducted a geomorphic investigation to characterize geologic, glacial, volcanic, and land use contributions to landslide initiation across Southeast Alaska. To evaluate controls on landslide (esp. debris flow) occurrence in Sitka, we used field observation, geomorphic mapping, landslide characteristics as documented in the Tongass National Forest inventory, and a novel application of the shallow landslide model SHALSTAB to postglacial terrain. A complex geomorphic history of glaciation and volcanic activity provides a template for spatially heterogeneous landslide occurrence. Landslide density across the region is highly variable, but debris flow density is high on south‐ or southeast‐facing hillslopes where volcanic tephra soils are present and/or where timber harvest has occurred since 1900. High landslide density along the western coast of Baranof and Kruzof islands coincides with deposition of glacial sediment and thick tephra and exposure to extreme rainfall from atmospheric rivers on south‐facing aspects but the relative contributions of these controls are unclear. Timber harvest has also been identified as an important control on landslide occurrence in the region. Focusing on a subset of geo‐referenced landslides near Sitka, we used the SHALSTAB shallow landslide initiation model, which has been frequently applied in non‐glacial terrain, to identify areas of high landslide potential in steep, convergent terrain. In a validation against mapped landslide polygons, the model significantly outperformed random guessing, with area under the curve (AUC) = 0.709 on a performance classification curve of true positives vs. false positives. This successful application of SHALSTAB demonstrates practical utility for hazards analysis in postglacial landscapes to mitigate risk to people and infrastructure.