Geology topics

Jaime Kostelnik

Publications and source records attributed to Jaime Kostelnik.

11 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

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

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↗

USGS2025

Improved prediction of postfire debris flows through rainfall anomaly maps

Predicting where runoff-generated debris flows might occur during rainfall on steep, recently burned terrain is challenging. Studies of mass-movement processes in unburned areas indicate that event locations are well-predicted by rainfall anomaly, R* , in which peak observed rainfall is normalized by local rainfall climatology. Here, we use remote and field methods to map debris flows triggered within the 2020 Dolan Fire burn area in coastal California, demonstrate that a short-duration R* metric predicts debris-flow occurrence more effectively than absolute peak intensity or longer-duration rainfall metrics, and show that incorporating an R* criterion into an existing debris-flow likelihood model can reduce false positive predictions and improve accuracy. We test R * at three other climatically distinct fires in California, demonstrating its utility for mapping likely debris-flow locations in different climates. We also consider how R* can benefit postfire debris-flow prediction given recent increases in climatological variability within individual burn perimeters.

Callifornia↗

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↗

USGS2024

Before the fire: Predicting burn severity and potential post-fire debris-flow hazards to Colorado River Cutthroat Trout (Oncorhynchus clarkii pleuriticus) conservation populations

Background Colorado River Cutthroat Trout (CRCT; Oncorhynchus clarkii pleuriticus ) conservation populations may be at risk from wildfire and post-fire debris flows hazards. Aim To predict burn severity and potential post-fire debris flow hazard classifications to CRCT conservation populations before wildfires occur. Methods We used remote sensing, spatial analyses, and machine learning to model 28 wildfire incidents (2016–2020) and spatially predict burn severity from pre-wildfire environmental factors to evaluate the likelihood (%) and volume (m 3 ) hazard classification of post-fire debris flow. Key results Burn severity was best predicted by fuels, followed by topography, physical ecosystem conditions, and weather (mean adjusted R 2 = 0.54). Predictions of high or moderate burn severity covered 1.1 (15% of study area) and 1.5 (19% of study area) million ha, respectively, and varied by watershed. Combined high or moderate debris flow hazard classification included 80% of stream reaches with conservation populations and 97% of conservation population point nodes. Conclusions Predicted burn severity and potential post-fire debris flow indicated moderate to high hazard for CRCT conservation populations native to the Green and Yampa rivers of the Upper Colorado River Basin. Implications Future management actions can incorporate predicted burn severity and potential post-fire debris flow to mitigate impacts to CRCT and other at-risk resource values before a wildfire occurs.

Colorado, Utah, Wyoming↗

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

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↗

USGS2023

The spatial distribution of debris flows in relation to observed rainfall anomalies: Insights from the Dolan Fire, California

A range of hydrologic responses can be observed in steep, recently burned terrain, which makes predicting the spatial distribution of large debris flows challenging. Studies from rainfall-induced landslides in unburned areas show evidence of hydroclimatic tuning of landslide triggering, such that the spatial distribution of events is best predicted by the observed rainfall anomaly relative to climatic norms rather than by absolute rainfall. In this paper, we test whether the spatial distribution of debris flows in response to rainfall can be similarly predicted by rainfall anomaly. The 520 km 2 Dolan Fire burn scar in Monterey County, California, USA, spans a sharp hydroclimatic gradient and experienced a widespread storm in January 2021 that triggered floods and debris flows, providing a natural experiment in which to test this hypothesis. In this study, we use remote and field methods to map debris-flow response and examine its spatial heterogeneity. Together with rainfall data, our mapping reveals that the observed anomalies in peak 15-min rainfall intensity (I 15 ) relative to the intensity of the 1-yr return interval storm predict debris-flow occurrence better than the absolute peak I 15 . Our findings indicate that debris-flow processes and threshold rainfall required for debris-flow initiation may be tuned to local hydroclimate.

California↗

USGS2023

Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards

The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across multiple burn areas. We used this inventory to evaluate the predictive performance of the US Geological Survey M1 likelihood model, a tool that presently underlies the emergency assessment of postfire debris-flow hazards in the western USA. To test model performance, we used the threat score skill statistic and found that the rainfall thresholds estimated by the M1 model for the Central California coast performed similarly to training (Southern California) and testing (Intermountain West) data associated with the original model calibration. Model performance decreased when differentiating between “minor” and “major” postfire hydrologic response types, which weigh effects on human life and infrastructure. Our results underscore that the problem of false positives is a major challenge for developing accurate rainfall thresholds for the occurrence of postfire debris flows. As wildfire activity increases throughout the western USA, so too will the demand for the assessment of postfire debris-flow hazards. We conclude that additional collection of field-verified inventories of postfire hydrologic response will be critical to prioritize which model variables may be suitable candidates for regional calibration or replacement.

California↗