Geology topics

Zachary C. Johnson

Publications and source records attributed to Zachary C. Johnson.

At least 19 recordsLinked to original sources

USGS2026

As above, so below? A framework for integrating long-term water quantity trends reveals divergent patterns in groundwater and low streamflow across the United States

Climate, land-use, and disturbance drive long-term global trends in groundwater levels and streamflow. At large scales, these trends are typically considered separately, despite the well-established concept that groundwater and surface water comprise a single resource. Joint trend assessment at national scales is challenging because it requires pairing and aggregating data from spatially disparate streamflow and groundwater monitoring sites for which no established framework exists. Here, we evaluate alternative approaches for integrating groundwater and streamflow data to enable joint trend analysis—a critical step toward understanding how water-budget components respond concurrently and interactively to environmental drivers. Mann–Kendall trends were computed for individual groundwater (annual mean depth) and streamflow (annual low of 7 d averages) sites across the U.S over 21- (2000–2020), 31- (1990–2020), and 41-year (1980–2020) periods. Regional Kendall trends were calculated using five spatially contiguous and noncontiguous regional classifications for aggregation based on subsurface (e.g. aquifer, geology) and surface (e.g. watershed, landscape) characteristics. Site-level results revealed contrasting trends, with tendencies toward increasing low flows (wetting) and increasing groundwater depths (drying). Agreement between streamflow and groundwater trends increased with regional aggregation and longer timeframes, though persistent skew toward streamflow wetting and groundwater drying remained. Results varied by region and trend period, with notable consistencies: unified drying in the West/Southwest and wetting in the Upper Midwest. Directional mismatches in long-term trends were prominent in the High Plains and Mississippi Alluvial Plain, whereas near-term mismatches were most evident in the Northwest. Aggregation by hydrologic landscape regions (HLR) yielded the greatest agreement between groundwater and streamflow trends. These findings indicate that coupled responses may represent combined influences of climate, relief, and geology, as captured by HLR, more strongly than geography or geology alone. Integrated water availability assessments may benefit from a multi-characteristic classification framework to treat groundwater and surface water as a unified resource.

Environmental Research: Water↗

USGS2026

Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020

The U.S. Geological Survey and the Washington State Department of Ecology (Ecology) have developed watershed models of seasonal load estimates of total nitrogen (TN) and total phosphorus (TP) discharging into the Washington State waters of the Salish Sea from 2005 through 2020. The modeling approach used was dynamic SPARROW (SPAtially Referenced Regressions On Watershed attributes), a statistical-physical watershed modeling technique, initially applied at large spatial scales to represent long-term average stream loads throughout a stream network, refined here to estimate seasonal TN and TP loads across watersheds. Upstream contributing sources included permitted treated wastewater facilities, crop fertilizer, animal feeding operations, septic systems, urban land and stormwater, atmospheric deposition (TN only), nitrogen fixation by Alnus rubra Bong. (red alder) trees (TN only), and background geologic material (TP only). Instream load magnitudes and their source compositions varied across watersheds, and even within each watershed, yet the largest loads typically occurred in the large rivers during winter and fall when streamflow was highest. Likewise, instream loads were typically lowest in summer during low streamflow, yet the relative instream aquatic decay was highest. The seasonal storage lag component of all nonpoint sources was estimated to contribute a quarter of the seasonal instream load during winter and fall high streamflow and sometimes half of the instream load during summer low streamflow. Simulated seasonal loads carried by streams to a few hundred river mouth marine discharge points ranged by several orders-of-magnitude for TN and TP due to the spatial and seasonal differences in hydrologic flows, magnitude and timing of contributing sources, and instream decay. The Snohomish and Skagit Rivers discharged the largest TN and TP loads, yet the Samish River was shown to have some of the highest TN and TP yields and concentrations. Additionally, a reference scenario estimate developed of the pre-industrial local and regional TN loads suggests that red alder tree density has increased in lower riparian areas and that treated wastewater is the dominant source in some watersheds that has led to increases in TN loading to marine waters.

British Columbia, Washington↗

USGS2025

Gaps in water quality modeling of hydrologic systems

This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.

Water↗

USGS2025

Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020

The U.S. Geological Survey (USGS) and the Washington State Department of Ecology (Ecology) have developed watershed models of seasonal load estimates of total nitrogen (TN) and total phosphorus (TP) discharging into the Washington waters of the Salish Sea from 2005 through 2020. The modeling approach used was dynamic SPARROW (SPAtially Referenced Regressions On Watershed attributes), a statistical-physical watershed modeling technique, initially applied at large spatial scales to represent long-term average stream loads throughout a stream network, refined here to estimate seasonal TN and TP loads across watersheds to clarify upstream contributions from discernable point and nonpoint sources delivered to marine waters at surface water confluences along the shoreline and quantify when, where, and why they were high or low. Upstream contributing sources included permitted treated wastewater facilities, crop fertilizer, animal feeding operations, septic systems, urban land and stormwater, atmospheric deposition (TN only), nitrogen fixation by Red Alder Alnus rubra trees (TN only), and background geologic material (TP only). Instream load magnitudes and their source compositions varied widely across watersheds, and even within each watershed, yet the largest loads typically occurred in the large rivers during winter and fall when streamflow was highest. Likewise, instream loads were typically lowest in summer during low streamflow, yet the relative instream aquatic decay was highest. The seasonal storage lag component of those nonpoint sources was estimated to contribute a quarter of the seasonal instream load during winter and fall high streamflow and sometimes half of the instream load during summer low streamflow. A key aspect of Ecology’s current Puget Sound Nutrient Source Reduction Project is consideration of upstream watershed contributions of nutrients to their marine-water discharge points. Simulated seasonal loads carried by streams to 63 river mouth marine discharge points 9 ranged by several orders-of-magnitude for both TN and TP due to the spatial and seasonal differences in hydrologic flows, magnitude and timing of contributing sources, and in-stream decay. The Snohomish and Skagit Rivers discharged the largest TN and TP loads, yet the Samish River was shown to have some of the highest TN and TP yields and concentrations. Additionally, a reference scenario was developed to provide an estimate of the pre-industrial local and regional loads.

ESS Open Archive↗

USGS2025

Ranking river basins for stream temperature research and monitoring in the contiguous United States

There is a need to prioritize research and data collection in river basins by integrating information from environmental, ecological, and socioeconomic datasets to maintain acceptable water quality for human uses and ecosystem health. Multiple anthropogenic and natural stressors are responsible for driving changes in stream temperatures that can alter ecosystems and degrade water quality. These stressors are variable spatially and temporally, which can be challenging for prioritizing monitoring and research. In this study, an evaluation of variables related to stream temperature was performed for 163 candidate basins of the contiguous United States to highlight potential focal areas. Thirty variables were combined in six components: anthropogenic forcing, natural forcing, climate change, ecological sensitivity, socioeconomic sensitivity, and data availability. The components were incorporated into three themes: vulnerability of streams to thermal change, vulnerability of ecosystems, and vulnerability of communities. By evaluating each theme separately, patterns of vulnerability and potential resiliency were identified as well as consistency in ranks within the themes. For example, results of the national scale ranking indicated the Southern California Coastal basin (within California-Nevada region) was the highest-ranking priority in vulnerability of streams to thermal change and vulnerability of ecosystems. The analysis also identified vulnerable basins with gaps in monitoring. For example, the Missouri-Oahe basin (within the Northern High Plains region) was the highest-ranking priority for vulnerable communities with limitations in data availability. The ranking approach provides insight into basins that are resilient and are ideal candidates for monitoring and research.

Journal of Hydrology↗

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↗

USGS2024

Taking heat (downstream): Simulating groundwater and thermal equilibrium controls on annual paired air–water temperature signal transport in headwater streams

Headwater stream temperature often exhibits spatial variation at the kilometer-scale, but the relative importance of the underlying hydrogeological processes and riverine perturbations remains poorly understood. In this study, we investigated the relative importance of groundwater (GW) and other processes on downstream annual stream temperature signal characteristics using deterministic heat budget model (HFLUX) scenarios within an idealized stream reach representative of mountainous forested conditions. We summarized annual stream thermal regimes from the relationship of paired sinusoidal air and water temperature signals (amplitude ratio, phase lag, and mean ratio). Results showed that downstream changes in annual temperature depended on the thermal gradient between water and the hypothetical equilibrium temperature (where all heat fluxes sum to zero). GW inflow, riparian shading, and the boundary input signal were the most significant factors affecting downstream annual water temperature signals, while flow volume and channel dimensions impacted how quickly annual temperature signals changed. Effects of GW were dominated by advective rather than conductive heat exchange processes, but conduction played a larger role when GW input was more spatially diffuse. Our results indicated several mechanisms by which local processes may affect stream thermal resilience to disturbances and can help guide management of wildfire and climate change.

Journal of Hydrology↗

USGS2023

Closing the gap between science and management of cold-water refuges in rivers and streams

Human activities and climate change threaten coldwater organisms in freshwater ecosystems by causing rivers and streams to warm, increasing the intensity and frequency of warm temperature events, and reducing thermal heterogeneity. Cold-water refuges are discrete patches of relatively cool water that are used by coldwater organisms for thermal relief and short-term survival. Globally, cohesive management approaches are needed that consider interlinked physical, biological, and social factors of cold-water refuges. We review current understanding of cold-water refuges, identify gaps between science and management, and evaluate policies aimed at protecting thermally sensitive species. Existing policies include designating cold-water habitats, restricting fishing during warm periods, and implementing threshold temperature standards or guidelines. However, these policies are rare and uncoordinated across spatial scales and often do not consider input from Indigenous peoples. We propose that cold-water refuges be managed as distinct operational landscape units, which provide a social and ecological context that is relevant at the watershed scale. These operational landscape units provide the foundation for an integrated framework that links science and management by (1) mapping and characterizing cold-water refuges to prioritize management and conservation actions, (2) leveraging existing and new policies, (3) improving coordination across jurisdictions, and (4) implementing adaptive management practices across scales. Our findings show that while there are many opportunities for scientific advancement, the current state of the sciences is sufficient to inform policy and management. Our proposed framework provides a path forward for managing and protecting cold-water refuges using existing and new policies to protect coldwater organisms in the face of global change.

Global Change Biology↗

USGS2023

Integrated water resources trend assessments: State of the science, challenges, and opportunities for advancement

Water is vital to human life and healthy ecosystems. Here we outline the current state of national-scale water resources trend assessments, identify key gaps, and suggest advancements to better address critical issues related to changes in water resources that may threaten human development or the environment. Questions like, “Do we have less suitable drinking water now than we had 20 years ago?” or “Are flood events more common now than they were in the past?” prompted improvements in data, trend estimation methods, and modeling frameworks to track changes in, and better understand how land use and climate influence four water resources domains: surface and groundwater quantity and quality. However, continued advancement in trend assessments to better address issues related to changes in water availability is needed. Areas of need include more timely and efficient delivery of water resources trend results and improved capacity to estimate trends at unmonitored locations. Additional integration pieces include increased understanding of groundwater–surface water interactions, incorporation of both quantity and quality trends into water availability estimates, and the refinement of trend metrics to account for the competing needs of society and ecological integrity. Coupled with improved driver attribution studies, these components will better inform current and future water resources management.

Journal of the American Water Resource Association↗

USGS2023

Paired Air and Stream Temperature Analysis (PASTA) to evaluate groundwater influence on streams

Groundwater is critical for maintaining stream baseflow and thermal stability; however, the influence of groundwater on streamflow has been difficult to evaluate at broad spatial scales. Techniques such as baseflow separation necessitate streamflow records and do not directly indicate whether groundwater inflow may be sourced from more dynamic shallow flowpaths. We present a web tool application PASTA (Paired Air and Stream Temperature Analysis; https://cuahsi.shinyapps.io/pasta/ ) that capitalizes on increased public stream temperature data availability and large-scale, gridded climate observations to provide new and efficient insights regarding relative groundwater influence on streams. PASTA analyzes paired air and stream water temperature signals to evaluate spatiotemporal patterns in stream thermal sensitivity and relative groundwater influence, including inference regarding the dominant source groundwater depth (shallow or deep (i.e., approximately >6 m depth)). The tool is linked to publicly available stream temperature datasets and accepts user-uploaded datasets. As local air temperature is not often monitored, PASTA pulls daily air temperature data from the comprehensive Daymet products when directly measured data are unavailable, allowing the repurposing of existing stream temperature data. After data are selected or uploaded, the tool (a) fits sinusoidal curves of daily stream and air temperatures by year (water or calendar) to indicate groundwater influence characteristics and (b) performs linear regressions for stream versus air temperatures to indicate stream thermal sensitivity. Results are exported in ASCII file format, creating an efficient and approachable analysis tool for the adoption of newly developed heat tracing analysis from stream reach to landscape scales.

Water Resources Research↗

USGS2022

Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams

In mountain headwater streams, the quality and resilience of summer cold-water habitat is generally regulated by stream discharge, longitudinal stream channel connectivity and groundwater exchange. These critical hydrologic processes are thought to be influenced by the stream corridor bedrock contact depth (sediment thickness), a parameter often inferred from sparse hillslope borehole information, piezometer refusal and remotely sensed data. To investigate how local bedrock depth might control summer stream temperature and channel disconnection (dewatering) patterns, we measured stream corridor bedrock depth by collecting and interpreting 191 passive seismic datasets along eight headwater streams in Shenandoah National Park (Virginia, USA). In addition, we used multi-year stream temperature and streamflow records to calculate several baseflow-related metrics along and among the study streams. Finally, comprehensive visual surveys of stream channel dewatering were conducted in 2016, 2019 and 2021 during summer low flow conditions (124 total km of stream length). We found that measured bedrock depths along the study streams were not well-characterized by soils maps or an existing global-scale geologic dataset where the latter overpredicted measured depths by 12.2 m (mean) or approximately four times the average bedrock depth of 2.9 m. Half of the eight study stream corridors had an average bedrock depth of less than 2 m. Of the eight study streams, Staunton River had the deepest average bedrock depth (3.4 m), the coldest summer temperature profiles and substantially higher summer baseflow indices compared to the other study steams. Staunton River also exhibited paired air and water annual temperature signals suggesting deeper groundwater influence, and the stream channel did not dewater in lower sections during any baseflow survey. In contrast, Paine Run and Piney River did show pronounced, patchy channel dewatering, with Paine Run having dozens of discrete dry channel sections ranging from 1 to greater than 300 m in length. Stream dewatering patterns were apparently influenced by a combination of discrete deep bedrock (20+ m) features and more subtle sediment thickness variation (1–4 m) depending on local stream valley hydrogeology. In combination, these unique datasets show the first large-scale empirical support for existing conceptual models of headwater stream disconnection based on spatially variable underflow capacity and shallow groundwater supply.

Virginia↗

USGS2022

Puget Sound Spatially Referenced Regression on Watershed Attributes (SPARROW)

The United States Geological Survey (USGS) and the Washington State Department of Ecology (Ecology) are collaborating on the development of refined, seasonal load estimates of total nitrogen and total phosphorus within watersheds draining to Washington waters of the Salish Sea for the period 2005-2020. The modeling approach for this work is based on SPARROW (Spatially Referenced Regression on Watershed Attributes), a watershed modeling technique developed by the USGS. SPARROW is typically used to estimate stream loads throughout a stream network. The estimated loads will be used within the context of the Puget Sound Nutrient Source Reduction Project to evaluate the influence of watershed contributions of nutrients throughout the stream network and to marine waters. This quality assurance project plan (QAPP) contains details about the technical approach, observational data, spatial and temporal source data, limitations, and quality assurance procedures that will be employed to develop the SPARROW models so that they can be used to inform additional actions to address excess nutrients.

Washington↗

USGS2021

Continental-scale analysis of shallow and deep groundwater contributions to streams

Groundwater discharge generates streamflow and influences stream thermal regimes. However, the water quality and thermal buffering capacity of groundwater depends on the aquifer source-depth. Here, we pair multi-year air and stream temperature signals to categorize 1729 sites across the continental United States as having major dam influence, shallow or deep groundwater signatures, or lack of pronounced groundwater (atmospheric) signatures. Approximately 40% of non-dam stream sites have substantial groundwater contributions as indicated by characteristic paired air and stream temperature signal metrics. Streams with shallow groundwater signatures account for half of all groundwater signature sites and show reduced baseflow and a higher proportion of warming trends compared to sites with deep groundwater signatures. These findings align with theory that shallow groundwater is more vulnerable to temperature increase and depletion. Streams with atmospheric signatures tend to drain watersheds with low slope and greater human disturbance, indicating reduced stream-groundwater connectivity in populated valley settings.

Nature Communications↗

USGS2021

Heed the data gap: Guidelines for using incomplete datasets in annual stream temperature analyses

Stream temperature data are useful for deciphering watershed processes important for aquatic ecosystems. Accurately extracting signal trends from stream temperature is essential for predicting responses of environmental and ecological indicators to change. Missing data periods are common for various reasons, and pose a challenge for scientists using temperature signal analysis to support stream research and ecological management objectives. However, the sensitivity of estimated temperature signal patterns to missing data has not been thoroughly evaluated, despite the potentially large impact on interpretation. In this study, we explored the effects of simulated missing daily data on the characterization of annual water temperature signals measured at headwater sites in the Pacific Northwest and Mid-Atlantic regions of the USA. For each site, we used linear regressions of sine-waves fitted to complete (365-d) and partial (7–357 consecutive missing data points) annual datasets of daily mean water temperature and computed three thermal parameters (mean, phase, and amplitude), which together can indicate thermally and ecologically influential watershed processes (e.g., depth and magnitude of groundwater discharge). Expected values (derived from complete datasets) ranged from 7.0 to 12.6 °C, 205 to 254 d, and 1.9 to 9.5 °C for annual mean, phase, and amplitude, respectively. While annual phase and amplitude could be accurately estimated (i.e., within 95–99% confidence intervals of expected values) with up to approximately two months of consecutively missing data, annual mean temperature required more complete datasets. We found that datasets with less than seven weeks of consecutively missing data enabled estimation of all annual signal parameters with reasonable accuracy (>75% probability of being within the 95–99% confidence intervals of expected values). Imputation of missing data expanded this range to approximately 20 weeks, with the greatest improvements in parameter estimation between 9 and 27 weeks of imputed missing data. However, caution should be exercised when applying this technique. For example, imputation improved the accuracy of parameter estimation for most sites, but accuracy decreased for some sites exhibiting strong groundwater influence. The timing of consecutive missing data points within a year had inconsistent effects on annual thermal parameter estimates among regions, years, and individual parameters. Utilizing sites with more than approximately seven consecutive weeks of missing data or 20 weeks of imputed data increases the probability of mischaracterization of annual stream thermal regimes. Understanding this limitation is vital for identifying the potential of streams to serve as climate refugia for ecological indicator species and effective future management of stream systems.

Ecological Indicators↗

USGS2020

Paired air-water annual temperature patterns reveal hydrogeological controls on stream thermal regimes at watershed to continental scales

Despite decades of research into air and stream temperature dynamics, paired air-water annual temperature signals have been underutilized to characterize watershed processes. Annual stream temperature dynamics are useful in classifying fundamental thermal regimes and can enhance process-based interpretation of stream temperature controls, including deep and shallow groundwater discharge, when paired with air signals. In this study, we investigated multi-scale variability in annual paired air-water temperature patterns using sine-wave linear regressions of multi-year daily temperature data from streams of various sizes. A total of 311 sites from two spatially intensive regional datasets (Shenandoah National Park and Olympic Experimental State Forest) and a spatially extensive national dataset spanning the contiguous United States (U.S. Geological Survey gages) were evaluated. We calculated three annual air-water thermal metrics (mean ratio, phase lag, and amplitude ratio) to deduce the influence of groundwater and other watershed processes on stream thermal regimes at multiple spatial scales. Site-specific values of the three annual air-water thermal metrics ranged from 0.69 to 5.29 (mean ratio), −9 to 40 days (phase lag), and 0.29 to 1.12 (amplitude ratio). Regional patterns in the annual thermal metrics revealed persistent yet spatially variable influences of shallow groundwater discharge and high levels of thermal variability within watersheds, indicating the importance of local hydrogeological controls on stream temperature. Furthermore, annual thermal metric patterns from the regional datasets were generally concordant with the national dataset suggesting the utility of these annual thermal metrics for analysis at multiple scales. Analysis of the national dataset showed that previously defined thermal regimes based on water temperature alone could be further refined using air-water metrics and these metrics were related to physiographic watershed characteristics such as contributing area, elevation, and slope. This research demonstrates the importance of spatial scale and heterogeneity for inferring hydrological process in streams and provides guidance for the interpretation of annual air-water temperature metrics that can be efficiently applied to the growing database of multi-year temperature records. Results from this research can aid in the prediction of future thermal habitat suitability for coldwater-adapted species at ecologically and management-relevant spatial scales with readily available data.

Continental United States↗

USGS2018

Shallow bedrock limits groundwater seepage-based headwater climate refugia

Groundwater/surface-water exchanges in streams are inexorably linked to adjacent aquifer dynamics. As surface-water temperatures continue to increase with climate warming, refugia created by groundwater connectivity is expected to enable cold water fish species to survive. The shallow alluvial aquifers that source groundwater seepage to headwater streams, however, may also be sensitive to seasonal and long-term air temperature dynamics. Depth to bedrock can directly influence shallow aquifer flow and thermal sensitivity, but is typically ill-defined along the stream corridor in steep mountain catchments. We employ rapid, cost-effective passive seismic measurements to evaluate the variable thickness of the shallow colluvial and alluvial aquifer sediments along a headwater stream supporting cold water-dependent brook trout ( Salvelinus fontinalis ) in Shenandoah National Park, VA, USA. Using a mean depth to bedrock of 2.6 m, numerical models predicted strong sensitivity of shallow aquifer temperature to the downward propagation of surface heat. The annual temperature dynamics (annual signal amplitude attenuation and phase shift) of potential seepage sourced from the shallow modeled aquifer were compared to several years of paired observed stream and air temperature records. Annual stream water temperature patterns were found to lag local air temperature by ∼8–19 d along the stream corridor, indicating that thermal exchange between the stream and shallow groundwater is spatially variable. Locations with greater annual signal phase lag were also associated with locally increased amplitude attenuation, further suggestion of year-round buffering of channel water temperature by groundwater seepage. Numerical models of shallow groundwater temperature that incorporate regional expected climate warming trends indicate that the summer cooling capacity of this groundwater seepage will be reduced over time, and lower-elevation stream sections may no longer serve as larger-scale climate refugia for cold water fish species, even with strong groundwater discharge.

Limnologica - Ecology and Management of Inland Wat↗

USGS2018

Inferring watershed hydraulics and cold-water habitat persistence using multi-year air and stream temperature signals

Streams strongly influenced by groundwater discharge may serve as “climate refugia” for sensitive species in regions of increasingly marginal thermal conditions. The main goal of this study is to develop paired air and stream water annual temperature signal analysis techniques to elucidate the relative groundwater contribution to stream water and the effective groundwater flowpath depth. Groundwater discharge to streams attenuates surface water temperature signals, and this attenuation can be diagnostic of groundwater gaining systems. Additionally, discharge from shallow groundwater flowpaths can theoretically transfer lagged annual temperature signals from aquifer to stream water. Here we explore this concept using multi-year temperature records from 120 stream sites located across 18 mountain watersheds of Shenandoah National Park, VA, USA and a coastal watershed in Massachusetts, USA. Both areas constitute important cold-water habitat for native brook trout ( Salvelinus fontinalis ). Observed annual temperature signals indicate a dominance of shallow groundwater discharge to streams in the National Park, in contrast to the coastal watershed that has strong, apparently deeper, groundwater influence. The average phase lag from air to stream signals in Shenandoah National Park is 11 d; however, extended lags of approximately 1 month were observed in a subset of streams. In contrast, the coastal stream has pronounced attenuation of annual temperature signals without notable phase lag. To better understand these observed differences in signal characteristics, analytical and numerical models are used to quantify mixing of the annual temperature signals of surface and groundwater. Simulations using a total heat budget numerical model indicate groundwater-induced annual temperature signal phase lags are likely to show greater downstream propagation than the related signal amplitude attenuation. The measurement of multi-seasonal paired air and water temperatures offers great promise toward understanding catchment processes and informing current cold-water habitat management at ecologically-relevant scales.

Virginia↗

USGS2017

Landform features and seasonal precipitation predict shallow groundwater influence on temperature in headwater streams

Headwater stream responses to climate change will depend in part on groundwater‐surface water exchanges. We used linear modeling techniques to partition likely effects of shallow groundwater seepage and air temperature on stream temperatures for 79 sites in nine focal watersheds using hourly air and water temperature measurements collected during summer months from 2012 to 2015 in Shenandoah National Park, Virginia, USA. Shallow groundwater effects exhibited more variation within watersheds than between them, indicating the importance of reach‐scale assessments and the limited capacity to extrapolate upstream groundwater influences from downstream measurements. Boosted regression tree (BRT) models revealed intricate interactions among geomorphological landform features (stream slope, elevation, network length, contributing area, and channel confinement) and seasonal precipitation patterns (winter, spring, and summer months) that together were robust predictors of spatial and temporal variation in groundwater influence on stream temperatures. The final BRT model performed well for training data and cross‐validated samples (correlation = 0.984 and 0.760, respectively). Geomorphological and precipitation predictors of groundwater influence varied in their importance between watersheds, suggesting differences in spatial and temporal controls of recharge dynamics and the depth of the groundwater source. We demonstrate an application of the final BRT model to predict groundwater effects from landform and precipitation covariates at 1075 new sites distributed at 100 m increments within focal watersheds. Our study provides a framework to estimate effects of groundwater seepage on stream temperature in unsampled locations. We discuss applications for climate change research to account for groundwater‐surface water interactions when projecting future thermal thresholds for stream biota.

Virginia↗