Wildfire can influence erosion regimes and alter sediment delivery to river systems, which can change the sediment size composition of rivers. Understanding how wildfire impacts streambed grain size distributions is essential in understanding broader wildfire impacts on aquatic habitat and downstream water resources. In Western Washington, Oregon, and Northern California, the Aquatic and Riparian Effectiveness Monitoring Program (AREMP) has been collecting ongoing monitoring data since 2002. Since the beginning of the monitoring program, approximately 37

Background High-severity burned areas can have lasting impacts on vegetation regeneration, carbon dynamics, hydrology, and erosion. Landscape models can predict erosion from burned areas using the differenced normalized burn ratio (dNBR), but so far post-fire erosion modelling has been limited to areas that already burned. Here, we developed and validated a predictive burn severity model that produces continuous dNBR predictions for recently unburned forest land in Utah. Results Vegetation productivity, elevation and canopy fuels were the most important predictor variables in the model, highlighting the strong control of fuels and vegetation on burn severity in Utah. Final model out-of-bag R2 was 67.1%, residuals showed a correlation coefficient of 0.89 and classification accuracy into three classes was 85%. We demonstrated that dNBR can be empirically modeled relative to fuels and topography and found burn severity was highest in productive vegetation and at relatively cooler sites. Conclusions We found that prediction accuracy was higher when fuel moisture was lower, suggesting drier weather conditions drive more consistent and predictable burn severity patterns across a range of burn severity, vegetation types and geographic locations. Moreover, burn severity predictions from this model can be used to inform hydro-erosion models and subsequent management actions aimed at reducing burn severity and post-wildfire erosion risks.

Post-fire debris flows represent one of the most erosive consequences associated with increasing wildfire severity and investigations into their downstream impacts have been limited. Recent advances have linked existing hydrogeomorphic models to predict potential impacts of post-fire erosion at watershed scales on downstream water resources. Here we address two key limitations in current models: (1) accurate predictions of post-fire debris flow volumes in the absence of triggering storm rainfall intensities and (2) understanding controls on grain sizes produced by post-fire debris flows. We compiled and analysed a novel dataset of depositional volumes and grain size distributions (GSDs) for 59 post-fire debris flows across the Intermountain West (IMW) collected via fieldwork and from the literature. We first evaluated the utility of existing models for post-fire debris flow volume prediction, which were largely developed for Southern California. We then constructed a new post-fire debris flow volume prediction model for the IMW using a combination of Random Forest modelling and regression analysis. We found topography and burn severity to be important variables, and that the percentage of pre-fire soil organic matter was an essential predictor variable. Our model was also capable of predicting debris flow volumes without data for the triggering storm, suggesting that rainfall may be more important as a presence/absence predictor, rather than a scaling variable. We also constructed the first models that predict the median, 16th percentile, and 84th percentile grain sizes, as well as boulder size, produced by post-fire debris flows. These models demonstrate consistent landscape controls on debris flow GSDs that are related to land cover, physical and chemical weathering, and hillslope sediment transport processes. This work advances our ability to predict how post-fire sediment pulses are transported through watersheds. Our models allow for improved pre- and post-fire risk assessments across diverse ranges of watersheds in the IMW.

Wildfires dramatically alter the hydraulics and root reinforcement of soil on forested hillslopes, which can promote the generation of debris flows. In the Pacific Northwest, post-fire shallow landsliding has been well documented and studied, but the potential role of runoff-initiated debris flows is not well understood and only one previous to 2018 had been documented in the region. On 20 June 2018, approximately 1 year after the Milli fire burned 24,000 acres, a runoff-initiated debris flow occurred on the flanks of Black Crater in the Oregon Cascade Range. The debris flow was initiated via dispersed rilling on > 30-degree slopes near the crater rim and traveled > 1.5 km downslope. We measured exceptionally low soil infiltration rates at the study site, likely due to high burn severity during the Milli fire. Based on nearby 5-min rain gage data, we quantified rainfall rates for the storm event that triggered the debris flow. Our results show that peak 15-min rainfall rates were 25.4 mmh−1, equaling or exceeding the measured infiltration rates at the study site, which had a geometric mean of ~ 24 mmh−1. Field mapping shows that high burn severity resulted in the initiation of the debris flow and that convergent and steep topography promoted the development of a debris flow at this site. As wildfires increase in frequency and intensity across the western USA, the Pacific Northwest could become more susceptible to runoff-initiated debris flows. Therefore, characterization of the conditions that resulted in this debris flow is crucial for understanding how runoff-initiated debris flows may shape terrain and impact hazards in the Pacific Northwest.