Geology topics

Jason W. Kean

Publications and source records attributed to Jason W. Kean.

At least 19 recordsLinked to original sources

USGS2026

Regional models for postfire debris-flow likelihood and rainfall thresholds across the western United States

The U.S. Geological Survey (USGS) uses an empirical model developed with logistic regression (the ‘M1’ model) to rapidly assess debris-flow likelihood and to identify quantitative rainfall thresholds for debris flows after wildfire in the western United States. The M1 model was calibrated to a debris-flow inventory from southern California (United States) and has been applied throughout the western United States. Limited spatial coverage in the calibration dataset has motivated evaluation of M1 model accuracy outside the calibration region (e.g., the Sierra Nevada or the eastern Cascade Range, United States). Previous test cases showed that M1 overpredicts debris-flow likelihood and underpredicts rainfall thresholds for some locations (e.g., Arizona, northern California, Colorado, New Mexico, United States). We sought to improve the regional applicability of a debris-flow likelihood model by expanding the debris-flow inventory used for calibration, testing multiple potential models and generating an updated model framework. The updated inventory includes 3788 observations from 67 burned areas paired with short duration rainfall ratios. The updated model framework consists of a modified model structure and sets of coefficients calibrated separately to the entire updated inventory and to subsets of the inventory that intersect three Environmental Protection Agency (EPA) Level 2 ecoregions (Mediterranean California, Upper Gila Mountains and Western Cordillera). Comparisons of predictions from the updated models with observed rainfall and debris-flow activity show that the updated models outperform the M1 model by ~15%–60% and improve the uniformity of predictive performance across the western United States. The updated models also reduce false positive rates relative to M1 and generate rainfall thresholds that are better aligned with relative differences in regional climatology and debris-flow activity.

Arizona, California, Colorado, Idaho, Montana, Nev↗

USGS2026

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗

USGS2026

Characterizing changes in postfire debris-flow hazard as burned areas recover

Emergency assessments of postfire debris-flow hazards that are performed by the U.S. Geological Survey (USGS) provide estimates of debris-flow likelihood and rainfall triggering conditions that are used for evaluating and managing runoff-generated debris-flow hazards in recently burned areas throughout the western United States. Although the immediate postfire period, within roughly one year after fire, is typically the most susceptible to runoff-generated debris flows, the hazard evolves in time and space as the burned area recovers. The recovery trajectory a given burned area will take depends on local climate and weather and can be difficult to predict. Some burned areas recover quickly, whereas others experience debris flows for multiple years after fire. As a result, extending our ability to update debris-flow likelihood estimates and rainfall thresholds based on observed recovery of the burned area would be beneficial. We present a method for multi-year runoff-generated debris-flow hazard assessment that leverages the USGS “M1” debris-flow likelihood model and integrates updated, satellite-derived, normalized burn ratio data to estimate vegetation recovery. We predict recovery-aware rainfall thresholds and validate them against a multi-year debris-flow hazard prediction and could be adapted for use with other debris-flow models that incorporate burn severity data.

Arizona, California, Colorado, New Mexico, Washing↗

USGS2026

Channel morphology and large wood control postfire debris-flow erosion and deposition

Runoff-generated debris flows are a known response to wildfire, and accurately predicting the volume of these debris flows is important for estimating the magnitude of downstream hazards. Prior data collection efforts have focused on debris-flow volume measurements at catchment outlets, but few studies have considered how erosion and deposition modulate the volume of sediment arriving at catchment outlets. This study takes advantage of a high-resolution dataset to document the factors that control the total debris-flow volume reaching the catchment outlet during a fatal postfire debris flow. Using pre- and post-event airborne lidar, satellite imagery and field mapping, we found that a postfire debris flow in the Black Hollow catchment in northern Colorado eroded 136,000 ± 30,000 m 3 and redeposited 27,000 ± 7,500 m 3 in the main channel. Most of the in-channel deposition (52% by volume) occurred where a confined channel reach transitioned to an unconfined channel reach downstream, allowing the flow to widen and deposit material. Wood jams played multiple roles in the debris-flow dynamics, both nucleating deposition (25% of the deposit volume was stored behind wood jams) and exacerbating erosion (50% of the total erosion occurred downstream from a wood dam break). The remaining deposition occurred due to spatial changes in channel slope as well as deposition observed at newly formed channel bars. Using these data in this study, we identified topographic and vegetation metrics that can be used (pre-event) to anticipate where deposition may occur in channels prior to a debris flow.

Colorado↗

USGS2026

Multi-site evaluation of a postfire debris-flow runout forecast method

Postfire debris flows pose a hazard to human life, property, and infrastructure when they travel from steep source areas to urbanized alluvial fans or other developed areas. Existing methods for rapid (<1 week) postfire debris-flow hazard assessment document the increase in the likelihood and size of debris flows as the magnitude of high-intensity rain necessary to initiate debris flows increases but do not indicate the extent of downstream debris-flow runout. Although many models for the simulation of debris-flow motion are available, there is no established approach for using these models to delineate locations susceptible to postfire debris-flow runout that (a) is feasible to use at the spatial scale of an entire fire; (b) is appropriate for runout onto unconfined areas; (c) reproduces observed relations between runout and rainfall intensity; and (d) characterizes inherent uncertainty in runout, even without spatiotemporally variable rainfall. We propose and evaluate a method for generating postfire debris-flow runout hazard maps that has all the above qualities. Selection of case studies prioritized events triggered by a range of rainfall intensities, locations within and outside of southern California, and observed runout onto unconfined topography. Qualitative and quantitative assessment of performance for four events indicate that simulation results broadly match observations albeit with some discrepancies at a scale larger than structure or land parcel level (approximately 20-m by 20-m). The method may be used to identify potentially hazardous areas immediately following a fire and to provide approximate runout forecasts when a storm is imminent.

Arizona, California↗

USGS2026

Helping California get ready for when the mud hits the fan

With frequent wildfires, powerful rainstorms, steep terrain, and dense population, California is particularly vulnerable to postfire hazards like flooding and debris flow. Major postfire flooding and debris-flow events can be more costly than the fire itself, causing dozens of fatalities and widespread damage (Chawner, 1934; Lancaster et al., 2021). Smaller events occur nearly every year in California and can locally damage structures and roads, affect water quality and storage, and result in injury or loss of life (e.g., Dow et al., 2024; Rodriguez, 2025; Swanson et al., 2024; Figure 1). To mitigate these threats, the U.S. Geological Survey (USGS) has developed tools to assist local, state, and federal agencies in rapidly assessing postfire debris-flow risk across California’s diverse geology and geography. This article summarizes that effort and describes ongoing work by the USGS and partners to advance these methods and help California better prepare for future wildfires.

Caliornia↗

USGS2026

Can a physics-based fire behavior model predict burn severity and post-fire debris flow hazard?

Post-wildfire flooding and debris flows pose a threat to ecosystems and infrastructure. As the frequency and size of severe wildfires increase, there is a growing need for predictive debris flow hazard modeling in unburned but fire-prone landscapes. However, no crosswalks have been established between physics-based models of fire behavior and the remotely sensed burn severity inputs needed for debris flow modeling. Here, we explore this connection by creating a large ensemble of fire behavior simulations using QUIC-Fire – a fast-running three-dimensional fire model – in basins across five major-disaster wildfires in California and Washington. We then conducted generalized linear mixed modeling (GLMM) and Random Forest modeling to identify QUIC-Fire outputs that best predicted remotely sensed burn severity. We found that the selected linear predictors exhibited weak and unintuitive relationships with soil burn severity and differenced Normalized Burn Ratio. Moreover, model evaluations of GLMMs and Random Forests showed they were poorly predictive of both metrics of remotely sensed burn severity. This suggests that there are barriers to integrating QUIC-Fire into a wildfire-hazards modeling framework, which could include mismatches in scale between fire models and remotely sensing, or simplifications of weather data and fire initiation. Further research is needed to establish connections between the fire physics outputs of QUIC-Fire and post-fire effects to vegetation and soils that are essential for evaluating debris flow hazard.

California, Washington↗

USGS2025

Landsliding follows signatures of wildfire history and vegetative regrowth in a steep coastal shrubland

Five years after the deadly and destructive 9 January 2018 Montecito debris flows (Santa Barbara County, California, USA), an atmospheric river storm on 9 January 2023 triggered widespread landsliding that affected many of the same drainages in the Santa Ynez Mountains. Using high-resolution aerial imagery, we identified >10,000 landslides over an ∼160 km 2 area. Most of the landslides were shallow (<1 m in depth) translational debris slides that initiated on steep (∼40°), south-facing hillslopes, with the highest incidence of landsliding in a sandstone-dominated bedrock unit. The landslides mobilized into debris flows and delivered substantial quantities of sediment downstream, which contributed to costly infrastructure impairments. We detected order-of-magnitude differences in landslide density across the study area that could not be attributed to variations in geomorphology (topographic aspect and slope), geology (bedrock type), or hydrology (seasonal antecedent rainfall, peak hourly storm rainfall intensity, total storm rainfall), which are usually considered relevant factors for shallow landsliding. Rather, we found that vegetation regrowth following wildfire was likely a relevant factor associated with the highly variable landslide densities. Hillslopes with less and different types of vegetation regrowth after fire appear to have been more susceptible to shallow landslides. We identify a possible vegetation control on postfire landsliding, which highlights an opportunity for hypothesis testing using more advanced techniques to track the evolution of vegetation cover and vegetation type in steep shrubland environments following wildfire.

California↗

USGS2025

Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows

In 2020, a wildfire burned across Glenwood Canyon in Colorado, USA. A history of postfire debris flows in the region and a hazard assessment for the burn area indicated that potentially life-threatening debris flows could be triggered by rainfall within months of a wildfire. As a result, four government agencies evaluated strategies to help mitigate hazards, including the loss of human life, that may be associated with debris-flow events. After the fire, 26 large debris flows occurred in the summer of 2021 and three sediment-laden flows occurred in the summer of 2023, but there were no major injuries or fatalities reported. We found that integrating hazard assessment/ forecasting, monitoring, and adaptation scenarios was a successful strategy for reducing postfire debris-flow risks to human life (including injuries and fatalities). Weather forecasts and estimates of debris-flow triggering rainfall thresholds, likelihood, and volume were used to anticipate the timing, location, and magnitude of debris-flow events. Rainfall monitoring and detailed recordkeeping of storms that triggered debris flows were used to validate and update debris-flow warning thresholds that varied with time following the wildfire. Although the governmental agencies working in this burn area had distinct and differing agency mandates, they were able to integrate information to reduce the risk of debris-flow events to human life.

Colorado↗

USGS2025

Rainfall thresholds for postfire debris-flow initiation vary with short-duration rainfall climatology

The size, frequency, and geographic scope of severe wildfires are expanding across the globe, including in the Western United States. Recently burned steeplands have an increased likelihood of debris flows, which pose hazards to downstream communities. The conditions for postfire debris-flow initiation are commonly expressed as rainfall intensity-duration thresholds, which can be estimated given sufficient observational history. However, the spread of wildfire across diverse climates poses a challenge for accurate threshold prediction in areas with limited observations. Studies of mass-movement processes in unburned areas indicate that thresholds vary with local climate, such that higher rainfall rates are required for initiation in climates characterized by frequent intense rainfall. Here, we use three independent methods to test whether initiation of postfire runoff-generated debris flows across the Western United States varies similarly with climate. Through the compilation of observed thresholds at various fires, analysis of the spatial density of observed debris flows, and quantification of feature importance at different spatial scales, we show that postfire debris-flow initiation thresholds vary systematically with short-duration rainfall-intensity climatology. The predictive power of climatological data sets that are readily available before a fire occurs offers a much-needed tool for hazard management in regions that are facing increased wildfire activity, have sparse observational history, and/or have limited resources for field-based hazard assessment. Furthermore, if the observed variation in thresholds reflects long-term adjustment of the landscape to local climate, rapid shifts in rainfall intensity related to climate change will likely induce spatially variable shifts in postfire debris-flow likelihood.

Arizona, California, Colorado, Nevada, New Mexico,↗

USGS2025

Assessment of western Oregon debris-flow hazards in burned and unburned environments

In the steep and mountainous environment of western Oregon, debris flows pose a considerable threat to property, infrastructure and life. Wildfire is commonly known to increase the susceptibility of steep slopes to debris flows, but the extent of this process in the western Cascades is not well understood. The US Geological Survey (USGS) currently estimates postfire debris-flow likelihood and triggering rainfall thresholds using a model calibrated to a southern California inventory of debris flows generated by excess runoff within the first year after fire. Because of a lack of available data, this model has not been tested in western Oregon, or in locations where postfire debris flows initiate via other mechanisms (e.g., shallow landslides or in-channel failures). Using repeat field observations and aerial imagery, we developed two new debris-flow inventories within and adjacent to the perimeters of five 2020 wildfires in western Oregon: Archie Creek, Holiday Farm, Beachie Creek, Lionshead and Riverside. The first inventory focuses on postfire debris flows (2020–2022); the second focuses on debris flows prior to fires (1995–2020). Our inventories of prefire and postfire debris flows were used to document initiation mechanisms in Oregon's western Cascades and to evaluate the effects of wildfire. We found that wildfire changed the distribution of debris-flow initiation mechanisms in the western Cascades. After the wildfires, annual rates of runoff-generated debris flows increased by 22% and the number of shallow landslide-initiated debris flows decreased by 17% relative to before the wildfires. Despite this shift, shallow landsliding was the dominant debris-flow initiation mechanism in both unburned and burned environments. We found the performance of the current USGS debris-flow likelihood model was degraded relative to other previously tested locations across the intermountain western United States. Our results highlight the need for improved postfire hazard assessment in western Oregon based on regional model calibration that is tuned to the dominant debris-flow initiation mechanisms.

Oregon↗

USGS2025

Landslide-channel feedbacks amplify channel widening during floods

Channel widening is a major hazard during floods, particularly in confined mountainous catchments. However, channel widening during floods is not well understood and not always explained by hydraulic variables alone. Floods in mountainous regions often coincide with landslides triggered by heavy rainfall, yet landslide-channel interactions during a flood event are not well known or documented. Here we demonstrate with an example from the Great Colorado Flood in 2013, a 1000 year precipitation event, how landslide-channel feedbacks can substantially amplify channel widening and flood risk. We use a combination of DEM differencing, field analysis, and multiphase flow modeling to document landslide-channel interaction during the flood event in which sediment delivered by landslides temporarily dammed the channel before failing and generating substantial channel widening. We propose that such landslide-flood interactions will become increasingly important to account for in flood hazard assessment as flooding and landsliding both increase with extreme rainfall under climate change.

Colorado↗

USGS2024

Postfire sediment mobilization and its downstream implications across California, 1984 – 2021

Fire facilitates erosion through changes in vegetation and soil, with major postfire erosion commonly occurring even with moderate rainfall. As climate warms, the western United States (U.S.) is experiencing an intensifying fire regime and increasing frequency of extreme rain. We evaluated whether these hydroclimatic changes are evident in patterns of postfire erosion by modeling hillslope erosion following all wildfires larger than 100 km 2 in California from 1984 to 2021. Our results show that annual statewide postfire hillslope erosion has increased significantly over time. To supplement the hillslope erosion modeling, we compiled modeled and measured postfire debris-flow volumes. We find that, in northern California, more than 50% of fires triggering the top 20 values of sediment mass and sediment yield occurred in the most recent decade (between 2011 and 2021). In southern California, the postfire sediment budget was dominated by debris flows, which showed no temporal trend. Our analysis reveals that 57% of postfire sediment erosion statewide occurred upstream of reservoirs, indicating potential impacts to reservoir storage capacity and thus increased risk to water-resource security with ongoing climate change.

California↗

USGS2024

A robust quantitative method to distinguish runoff-generated debris flows from floods

Debris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post-event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric ( Q* ) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross-section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow-type observations.

Geophysical Research Letters↗

USGS2024

Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA

As wildfire increases in the western United States, so do postfire debris-flow hazards. The U.S. Geological Survey (USGS) has developed two separate models to estimate (1) rainfall intensity thresholds for postfire debris-flow initiation and (2) debris-flow volumes. However, the information necessary to test the accuracy of these models is seldom available. Here, we studied how well these models performed over a 2-year period in the 2020 Grizzly Creek Fire burn perimeter in Glenwood Canyon, Colorado, USA, through the development of a debris-flow response inventory. The study area had the advantage of a network of 11 rain gauges for rainfall intensity measurements and repeat lidar data for volume estimates. Our observations showed that 89 % of observed debris flows in the first year postfire were triggered by rainfall rates higher than the fire-wide rainfall threshold produced by the current USGS operational model (M1). No debris flows were observed in the second year postfire, despite eight rainstorms with intensities higher than the modeled rainfall threshold. We found that the operational model for debris-flow initiation rainfall thresholds works well in this region during the first year but may be too conservative in year 2 due to vegetation recovery and sediment depletion. However, rainfall thresholds in the second year can be improved by using updated remote sensing imagery to recalculate the debris-flow initiation likelihood with the M1 model. The current volume model overestimates for this region by a median value of 4.4 times. However, the offset between the model estimates and observations is approximately linear, and the volumes from the Grizzly Creek debris flows had a similar magnitude to historic postfire debris flows in the region. Consequently, the current volume model could be adjusted with a regional correction factor.

Colorado↗

USGS2024

Rainfall intensification amplifies exposure of American Southwest to conditions that trigger postfire debris flows

Short-duration, high-intensity rainfall can initiate deadly and destructive debris flows after wildfire. Methods to estimate the conditions that can trigger debris flows exist and guidance to determine how often those thresholds will be exceeded under the present climate are available. However, the limited spatiotemporal resolution of climate models has hampered efforts to characterize how rainfall intensification driven by global warming may affect debris-flow hazards. We use novel, dynamically downscaled (3.75-km), convection-permitting simulations of short-duration (15-min) rainfall to evaluate threshold exceedance for late 21st-century climate scenarios in the American Southwest. We observe significant increases in the frequency and magnitude of exceedances for regions dominated by cool- and warm-season rainfall. We also observe an increased frequency of exceedance in regions where postfire debris flows have not been documented, and communities are unaccustomed to the hazard. Our findings can inform planning efforts to increase resiliency to debris flows under a changing climate.

Arizona, California, Nevada, New Mexico, Utah↗

USGS2024

Evaluation of debris-flow building damage forecasts

Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building damage forecasts for the 9 January 2018 Montecito postfire debris-flow runout event, in which over 500 buildings were damaged. We constructed forecasts using either peak debris-flow depth or momentum flux as the hazard intensity measure and applied each approach using three debris-flow runout models (RAMMS, FLO-2D, and D-Claw). Generated forecasts were based on averaging multiple simulations that sampled a range of debris-flow volume and mobility, reflecting typical sources and magnitude of pre-event uncertainty. We found that only forecasts made with momentum flux and the D-Claw model could correctly predict the observed number of damaged buildings and the spatial patterns of building damage. However, the best forecast only predicted 50 % of the observed damaged buildings correctly and had coherent spatial patterns of incorrectly predicted building damage (i.e., false positives and false negatives). These results indicate that forecasts made at the building level reliably reflect the spatial pattern of damage but do not support interpretation at the individual building level. We found the event size strongly influences the number of damaged buildings and the spatial pattern of debris-flow depth and velocity. Consequently, future research on the link between precipitation and the volume of sediment mobilized may have the greatest effect on reducing uncertainty in building damage forecasts. Finally, because we found that both depth and velocity are needed to predict building damage, comparing debris-flow models against spatially distributed observations of building damage is a more stringent test for model fidelity than comparison against the extent of debris-flow runout.

Natural Hazards and Earth System Sciences↗

USGS2024

Post-wildfire debris flows

Post-wildfire debris flows pose severe hazards to communities and infrastructure near and within recently burned mountainous terrain. Intense heat of wildfires changes the runoff characteristics of a watershed by combusting the vegetative canopy, litter, and duff, introducing ash into the soil and creating water repellant soils. Following wildfire, rainfall on bare ground is less able to infiltrate into the fire-altered soils and overland flow is less impeded by vegetation. Rainfall runoff in recently burned areas can erode hillslopes owing to the removal of soil binding organic matter near the soil surface by fire. In channels, loose, dry-ravel deposits composed of sand and gravel are readily entrained by concentrated runoff in channels. Entrainment of soil on hillslopes and in channels bulks up the sediment concentration of the rainfall runoff to generate debris flows capable of transporting boulders and large woody debris. Post-wildfire debris flows can be triggered by rainfall conditions that would typically produce little runoff during unburned conditions. The primary rainfall trigger for post-wildfire debris flows is high intensity rainfall during short duration convective rainstorms or periods of high rainfall intensity embedded within a long-duration frontal storm. Numerous observations of debris flows triggered by storms lasting less than an hour following periods of little to no rainfall indicate that antecedent rainfall is not a requirement for initiation of post-wildfire debris flows. Post-wildfire debris-flow hazard assessment entails estimating probability and magnitude of debris flows in the burned area, estimating debris-flow runout and intensity, and defining rainfall intensity-duration thresholds for debris-flow initiation. In the United States, probability and magnitude is estimated using empirically derived models largely based on data collected in southern California. The models provide maps to identify watersheds and drainage paths where post-wildfire hazards are most pronounced. Rainfall intensity-duration thresholds can be incorporated into flood hazard forecasting tools. Currently, work is underway to identify how to best implement debris-flow runout models in burned areas with efficiency and accuracy. Post-wildfire debris flows have been a long-recognized process in the Transverse Ranges of southern California; however, climate change is driving more frequent wildfires to burn more mountainous terrain throughout the western United States and worldwide. As a result, post-wildfire debris flows are becoming a more common threat in areas where they were once infrequent. As the threat of post-wildfire debris flow expands into new areas, evaluating the hazard becomes challenging because the degree to which wildfire increases debris-flow susceptibility varies from region to region. This chapter summarizes the knowledge to date for evaluating post-wildfire debris-flow susceptibility and hazard assessment. We summarize the characteristics of wildfire burn severity, topography, underlying soil and geology, and rainfall conditions that contribute to making a watershed most likely to produce post-wildfire debris flows. Methods for hazard assessment in the United States and other countries are summarized. We highlight knowledge gaps for how post-wildfire debris-flow susceptibility varies throughout the western United States and worldwide and identify research needs to improve hazard assessment methods in different geographies.

Book chapter↗