Geology topics

Trevor Fuess Partridge

Publications and source records attributed to Trevor Fuess Partridge.

7 recordsLinked to original sources

USGS2026

Inverse modeling for post-wildfire hydrologic process understanding over snow-dominated watersheds

Wildfire-induced changes to vegetation and soil properties can alter snowpack dynamics and hydrologic processes in ways that complicate predictions of post-wildfire water availability. To better understand these effects, we coupled the Parameter ESTimation in C++ (PEST++) software with the Weather Research & Forecasting Hydrologic model (WRF-Hydro) across three burned, snow-dominated watersheds in the western United States. We incorporated three burn-severity-based land cover categories into WRF-Hydro and used an iterative Ensemble Smoother (iES) within PEST++ to estimate model parameters controlling snow accumulation and melt, infiltration, and streamflow generation. This framework supported three complementary objectives: (1) assessing parameter sensitivities under pre- and post-wildfire conditions, (2) comparing pre- and post-wildfire parameter ensembles to identify wildfire-driven shifts in hydrologic processes, and (3) using counterfactual simulations to isolate the hydrologic response to wildfire from interannual climate variability. Our findings indicate that model parameter sensitivity varied by domain and shifted following wildfire. Maximum snow albedo and snow albedo decay were most influential in the higher-elevation East Troublesome domain, while the rain-snow partitioning temperature threshold dominated in the lower-elevation Chippy Creek and Las Conchas domains. Following wildfire, streamflow sensitivity shifted away from snowpack parameters toward soil hydraulic parameters, consistent with wildfire-driven reductions in evapotranspiration and increases in soil moisture. Incorporating wildfire effects led to complex changes in simulated snowpack accumulation and streamflow timing, generally leading to earlier snowmelt freshet initiation and cessation and reduced late season flows. Simulations were more sensitive to interannual climate variations than wildfire land cover changes. These results highlight both the potential and challenges of ensemble-based inverse modeling for understanding post-wildfire hydrologic change in snow-dominated watersheds.

Colorado, Montana, New Mexico↗

USGS2026

A review and synthesis of post-wildfire shifts in hydrologic processes and streamflow generation mechanisms

Critical water supply watersheds in the western United States (WUS) are impacted by wildfires, with potential negative effects on water quality and quantity. Scientific understanding is currently insufficient to deliver estimates of wildfire consequences for water quantity that are regionally accurate. Regional variability in the directionality and magnitude of post-wildfire shifts in streamflow generation fuels uncertainty in estimates of wildfire effects on water supply. In this work we provide a narrative review of wildfire effects on hydrologic processes and the resulting changes in streamflow generation mechanisms with a focus on the WUS, incorporating other global regions when pertinent. A conceptual model summary of wildfire effects on streamflow generation emphasizes: (1) precipitation seasonality, (2) synchrony of precipitation and potential evapotranspiration, (3) net shifts in interception, evaporation, and transpiration relative to total annual precipitation, (4) vegetation changes, including compensatory uptake and type conversion, (5) degree of overlap in rainfall rates and infiltration, (6) fire extent and severity, (7) burn scar positioning (e.g. in headwaters or proximal to watershed outlet), (8) scale-dependent groundwater leakage, (9) near-surface water storage reduction, and (10) soil to groundwater connectivity. Ongoing gaps and challenges include separating the influences of precipitation variability, water withdrawals, and post-fire land management; compound and overlapping disturbances; and lack of pre-fire data. Notable future opportunities include: harnessing ever-improving gridded and remotely sensed precipitation and fire-effects data; linking geophysical, isotopic tracer, and geochemical signatures to diagnose hydrologic changes; leveraging physically based and data-driven model advancements; and analyzing streamflow generation recovery trajectories across diverse watersheds.

western United States↗

USGS2025

A wavier polar jet stream contributed to the mid-20th century winter warming hole in the United States

Winter waves in the polar jet stream are associated with extreme cold outbreaks and can modulate longer-term winter temperature trends in the mid-latitudes. Recent research has highlighted a positive trend in jet stream waviness from 1990 to 2010, with a hypothesized connection to Arctic amplification of anthropogenic warming. However, an increase in jet stream waviness has also been hypothesized to contribute to the winter “warming hole” (WH) in eastern North America, a cooling phenomenon from 1958–1988, beginning several decades prior to the recent waviness trend. These potentially conflicting hypotheses highlight the uncertainty of long-term jet stream waviness variability prior to the satellite era (1979–present). Here we develop a new record of wintertime jet stream waviness spanning 1901–2023 based on self-organizing maps and nine different temperature and reanalysis data sets with the dual purpose of (a) understanding the historical variability of polar jet stream waviness in the eastern United States, and (b) quantifying the impact of jet stream waviness on WH-era surface temperatures. Our analysis reveals elevated jet stream waviness in the 1960s–1980s that surpassed modern waviness levels, and we find that jet stream waviness contributed to two-thirds of winter WH cooling beginning in 1958. These results are consistent with a strong connection between temperature trends in the eastern U.S. and jet stream troughing but indicate that additional mechanisms also contributed to the WH. Our analysis further highlights that recent increases in jet stream waviness are well within the range of early to mid-20th century variability, prior to the emergence of Arctic amplification.

AGU Advances↗

USGS2025

Disparate groundwater responses to wildfire

Post-wildfire investigations of groundwater response reveal a range of outcomes, varying from substantial increases to notable decreases in recharge and baseflow, with some studies indicating negligible or short-lived effects. This review assesses these varied responses within five critical categories: climate, vegetation, hydrogeology, fire characteristics, and the cryosphere, examining both short-term (within 2 years) and intermediate (2–10 years post-fire) effects. Despite considerable variability, some consistent patterns emerge. For instance, in hydroclimatic settings where water input and evaporative demand cycles are out of sync, post-wildfire groundwater responses tend to be positive (i.e., increased flux or storage), whereas under low fire severity conditions or in vegetation types that quickly recover, groundwater responses tend to be negative (i.e., decreased flux or storage). We synthesize relevant findings into a compendium of testable hypotheses aimed at explaining the spatiotemporal variability in observed post-wildfire groundwater responses. A recurring theme is the critical influence of the pre-wildfire groundwater regime on expected response and recovery. We identify opportunities for specific improvements in post-wildfire monitoring and modeling that would further advance capabilities to predict groundwater response. A key area for further research is understanding how wildfire effects on snow dynamics and other cryospheric processes translate to changes in groundwater.

WIREs Water↗

USGS2025

A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities

As wildfires increasingly affect water-supply watersheds, the demand for models to predict water-quality responses is increasing. This work reviews and synthesizes existing post-wildfire applications of water-quality models in the context of geographic and ecohydrological distribution, hydrologic and water-quality response process representation, model parameterization, model and input data scales, model calibration data availability, as well as calibration and performance evaluation approaches. Emphasis is placed on models that simulate water-quality output, rather than sediment and erosional response as the primary focus. Here, identified gaps and opportunities to advance the post-wildfire application of water-quality models include: 1. applying models in under-represented geographic and ecohydrologic regions, 2. simulating multiple streamflow generation mechanisms, including groundwater, with an emphasis on shifting dominant flow pathways as the landscape recovers following wildfire, 3. adding studies that include the simulation of metals, 4. incorporating more biogeochemical and in-stream processes to model applications, 5. applying finer spatial and temporal resolution of precipitation data input as well as finer spatial resolution hydrologic response units, 6. implementing fully distributed grid or element models or finer resolution response units to capture burn severity heterogeneity, 7. collecting enhanced water-quality data for model calibration and validation, 8. conducting model-intercomparison studies, and 9. developing model parameter value guidance in post-wildfire applications. These identified gaps and opportunities may assist users in deciding on key processes and approaches to consider in modeling post-wildfire water-quality conditions.

Science of the Total Environment↗

USGS2024

Opportunities and challenges for precipitation forcing data in post-wildfire hydrologic modeling applications

The frequency and extent of wildfires have increased in recent decades with immediate and cascading effects on water availability in many regions of the world. Precipitation is used as primary input to hydrologic models and is a critical driver of post-wildfire hydrologic hazards including debris flows, flash floods, water-quality effects, and reservoir sedimentation. These models are valuable tools for understanding the hydrologic response to wildfire but require accurate precipitation data at suitable spatial and temporal resolutions. Wildfires often occur in data-sparse, headwater catchments in complex terrain, and post-wildfire hydrologic effects are particularly sensitive to high-intensity, short-duration precipitation events, which are highly variable and difficult to measure or estimate. Therefore, the assessment and prediction of wildfire-induced changes to watershed hydrology, including the associated effects on ecosystems and communities, are complicated by uncertainty in precipitation data. When direct measurements of precipitation are not available, datasets of indirect measurements or estimates are often used. Choosing the most appropriate precipitation dataset can be difficult as different datasets have unique trade-offs in terms of spatial and temporal accuracy, resolution, and completeness. Here, we outline the challenges and opportunities associated with different precipitation datasets as they apply to post-wildfire hydrologic models and modeling objectives. We highlight the need for expanded precipitation gage deployment in wildfire-prone areas and discuss potential opportunities for future research and the integration of precipitation data from disparate sources into a common hydrologic modeling framework.

WIREs Water↗

USGS2023

Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation

Wildfire is a growing concern as climate shifts. The hydrologic effects of wildfire, which include elevated hazards and changes in water quantity and quality, are increasingly assessed using numerical models. Post-wildfire application of physically based distributed models provides unique insight into the underlying processes that affect water resources after wildfire. This work reviews and synthesizes post-wildfire applications of physically based distributed models by examining the scales and geographic/ecohydrologic distribution of model applications, hydrologic response process representation, model parameterization, and model performance metrics. Highlighted gaps and opportunities for advancing physically based distributed hydrologic response modeling after wildfire include the following: (a) applying models in under-represented geographic (S. America, Africa, Asia) and ecohydrologic regions (arid or dry subhumid climates), (b) incorporating all four major streamflow generation mechanisms (infiltration excess, saturation excess, subsurface storm flow, and groundwater flow), (c) representing integrated vadose zone and saturated zone processes to better capture subsurface streamflow generation, (d) building new remotely sensed model parameterization methods for precipitation interception, infiltration, and overland flow that account for burn severity and recovery, (e) incorporating distributed state variables (e.g., soil moisture, groundwater levels) in model performance assessment, (f) designing model intercomparison studies, including field datasets specifically for post-wildfire model development and validation, (g) linking mechanistic vegetation regrowth models with hydrologic models to improve simulation of process shifts as ecosystems recover, and (h) creating a new community modeling framework to integrate modeling advances across the wildfire science community.

Earth's Future↗