Geology topics

Susan Wherry

Publications and source records attributed to Susan Wherry.

7 recordsLinked to original sources

USGS2026

Lost in translation: Reconciling different streamflow permanence data products

The objective of this study is to provide a framework to reconcile streamflow permanence products that provide information on whether a stream is perennial or nonperennial. Accurate classification of streams as perennial or nonperennial is important for a variety of land and water resource management decisions. However, resource managers are challenged with how to reconcile different streamflow permanence information to determine if it is sufficient to avoid field verification, which can be prohibitively costly and time consuming. The study evaluates two datasets for the Pacific Northwest Region, U.S., the National Hydrography Dataset Plus High Resolution (NHDPlus HR) hydrographic classification and the PRObability of Streamflow PERmanence (PROSPER) model output, which differ in structure, output type, and temporal and spatial resolution. The framework includes a two-level evaluation that involves assessing agreement between the two datasets and evaluating the reliability of the two datasets. Summarized at a regional scale, the two datasets agree for 68% of flowlines with higher agreement for nonperennial streams. PROSPER nonperennial stream classifications may be considered generally reliable in arid regions relative to other ecoregions within the Pacific Northwest study area but less reliable for high elevation mountain regions and larger streams and rivers. More than 75% of NHDPlusHR classifications may be considered reliable when evaluating reliability based on approximate climate conditions associated with the year that the NHDPlus HR classification was assigned. The decision procedure is reproducible, flexible to varying criteria of end user applications, and is intended to help provide cost saving opportunities for land managers by providing information for more strategic field verification of streamflow class determination based on available yet imperfect data sources.

California, Idaho, Montana, Nevada, Utah, Washingt↗

USGS2025

Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models

The report focuses on the screening of previously published concentration data associated with 12 elements of concern (aluminum, arsenic, cadmium, chromium, copper, iron, mercury, manganese, lead, selenium, uranium, and zinc) measured in stream surface waters of three hydrologic basins (Delaware River Basin, Illinois River Basin, and the Upper Colorado River Basin). The purpose of this analysis is to determine what subsets of the original dataset (containing more than 1,500,000 observations) may be most suitable for each of two types of modeling efforts. The first type of modeling envisions a machine learning approach to determine which geospatial attributes are most significant in describing the spatial distribution of elemental concentrations within a basin. The second type of modeling envisions a stepwise regression approach to develop multivariable models that can be used to determine high resolution time-series estimates of elemental concentrations or loads at discrete U.S. Geological Survey real-time stream surface water sites. These site-specific temporal models are based on continuous measurements of available discharge and (or) in situ sensor data (temperature, pH, turbidity, dissolved oxygen, specific conductance, and (or) fluorescent dissolved organic matter) as the explanatory variables. The data screening for both model types considered historical trends in analytical methods and detection quantitation limits, the extent of censored data, data density, and environmental relevance with respect to three U.S. Environmental Protection Agency water quality thresholds (drinking water guidelines, human health criteria, and aquatic life criteria). The result of this analysis was the production of a final list of potential models deemed suitable for further development based upon the data exclusion (or inclusion) scheme developed herein for each model type. In both cases, the final models included mostly the three crustal elements (iron, manganese, and aluminum) that are found at comparatively high concentrations in surface water, whereas most of the more pernicious elements were excluded from the final model lists owing to various data limitations. The one exception to this was arsenic, for which the existing data were sufficient at three U.S. Geological Survey real-time sites for potential further development of time-series models.

Colorado, Delaware, Illinois, Indiana, Maryland, N↗

USGS2024

Predicting redox conditions in groundwater at a national scale using random forest classification

Redox conditions in groundwater may markedly affect the fate and transport of nutrients, volatile organic compounds, and trace metals, with significant implications for human health. While many local assessments of redox conditions have been made, the spatial variability of redox reaction rates makes the determination of redox conditions at regional or national scales problematic. In this study, redox conditions in groundwater were predicted for the contiguous United States using random forest classification by relating measured water quality data from over 30,000 wells to natural and anthropogenic factors. The model correctly predicted the oxic/suboxic classification for 78 and 79% of the samples in the out-of-bag and hold-out data sets, respectively. Variables describing geology, hydrology, soil properties, and hydrologic position were among the most important factors affecting the likelihood of oxic conditions in groundwater. Important model variables tended to relate to aquifer recharge, groundwater travel time, or prevalence of electron donors, which are key drivers of redox conditions in groundwater. Partial dependence plots suggested that the likelihood of oxic conditions in groundwater decreased sharply as streams were approached and gradually as the depth below the water table increased. The probability of oxic groundwater increased as base flow index values increased, likely due to the prevalence of well-drained soils and geologic materials in high base flow index areas. The likelihood of oxic conditions increased as topographic wetness index (TWI) values decreased. High topographic wetness index values occur in areas with a propensity for standing water and overland flow, conditions that limit the delivery of dissolved oxygen to groundwater by recharge; higher TWI values also tend to occur in discharge areas, which may contain groundwater with long travel times. A second model was developed to predict the probability of elevated manganese (Mn) concentrations in groundwater (i.e., ≥50 μg/L). The Mn model relied on many of the same variables as the oxic/suboxic model and may be used to identify areas where Mn-reducing conditions occur and where there is an increased risk to domestic water supplies due to high Mn concentrations. Model predictions of redox conditions in groundwater produced in this study may help identify regions of the country with elevated groundwater vulnerability and stream vulnerability to groundwater-derived contaminants.

contiguous United States↗

USGS2024

Examining the effect of physicochemical and meteorological variables on water quality indicators of harmful algal blooms in a shallow hypereutrophic lake using machine learning techniques

Two independent machine learning techniques, boosted regression trees and artificial neural networks, were used to examine the physicochemical and meteorological variables that affect the seasonal growth and decline of harmful algal blooms (HABs) in a shallow, hypereutrophic lake in southern Oregon. High temporal resolution data collected at four monitoring locations were aggregated into daily timesteps to create two response variables: (1) daily maximum pH (pH max ), representing HAB growth, and (2) daily minimum dissolved oxygen (DO min ), representing HAB decline. Predictors included meteorological and physical data, estimates of external phosphorus loading, and previous-year average nutrient concentrations, and excluded HAB biomass and internal phosphorus loading. The predictors that captured seasonal changes in both pH max and DO min were temperature, inflows, lake-surface elevation, and external phosphorus loading, while short-term changes were captured by measures of stratification, temperature, and wind speed. The pH max models had similar fits with leave-one-year-out cross-validation (LOYO-CV) R 2 values of 0.2–0.43 (median = 0.40). The DO min models for the deeper locations had LOYO-CV R 2 values of 0.27–0.43 compared to 0.1–0.25 for the shallower locations. Model performance was affected by variability due to patchiness of HABs, measurement uncertainty, and advection.

Water↗

USGS2023

Future climate-induced changes in mixing and deep oxygen content of a caldera lake with hydrothermal heat and salt inputs

Vertical profiles of temperature, salinity and dissolved oxygen in Crater Lake, a caldera lake in the Oregon Cascade Range that receives hydrothermal inputs of heat and salt, were simulated with a 1-dimensional model. Twelve Global Circulation Models and two Representative Concentration Pathways (RCPs) were used to develop boundary conditions from 1950 to 2099. The model simulated the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. All models predicted a reduction in the frequency of deep ventilation events, from an ensemble median frequency of 5.4 winters decade−1 during 1950–2005 to 4.3 (RCP4.5) or 2.5 (RCP8.5) winters decade−1 during 2045–2099. Favorable conditions for thermobaric instability-induced mixing currently occur infrequently and will become rare in the future. The salinity gradient resulting from hydrothermal inputs presents an additional barrier to thermobaric instability that will continue through 2099. A redistribution of salt to the deep lake may prevent ventilation all the way to the bottom in the future. Hypolimnetic dissolved oxygen percent saturation remained above 75% within the 21st century, consistent with oligotrophy and very small oxygen demands. The rate of change in all variables accelerated approaching 2099, coincident with elimination of winter reverse stratification. Historically, about half of the hydrothermal heat added to Crater Lake has been vented to the atmosphere. In the RCP8.5 scenario, the hydrothermal heat will cease to be vented to the atmosphere by the end of the 21st century, and then the temperature of the deep waters will increase rapidly.

Oregon↗

USGS2020

Factors affecting nitrate concentrations in stream base flow

Elevated nitrogen concentrations in streams and rivers in the Chesapeake Bay watershed have adversely affected the ecosystem health of the bay. Much of this nitrogen is derived as nitrate from groundwater that discharges to streams as base flow. In this study, boosted regression trees (BRTs) were used to relate nitrate concentrations in base flow ( n = 156) to explanatory variables describing nitrogen sources, geology, and soil and catchment characteristics. From these relations, a BRT model was developed to predict base flow nitrate concentrations in streams throughout the Chesapeake Bay watershed. The highest base flow nitrate concentrations were associated with intensive agricultural land use, carbonate geology, and sparse riparian canopy, which suggested that reduced nitrogen inputs, particularly over carbonate terrane, are critical for limiting nitrate concentrations. The lowest nitrate concentrations in the BRT model were associated with extensive riparian canopy, high levels of organic carbon in soils, and suboxic conditions at shallow depths, which suggested that denitrification in the subsurface, particularly in the riparian zone, is limiting base flow nitrate concentrations. Nitrate transport from aquifers to streams can take decades to occur, resulting in decades-long lag times between the time when a land-use activity is implemented and when its effects are fully observed in streams. Predictive models of base flow nitrate concentrations in streams will help identify which portions of a watershed are likely to have large fractions of total stream nitrogen load derived from pathways with significant lag times.

Delaware, Maryland, New York, North Carolina, Penn↗

USGS2016

Comparison of mercury mass loading in streams to atmospheric deposition in watersheds of Western North America: Evidence for non-atmospheric mercury sources

Annual stream loads of mercury (Hg) and inputs of wet and dry atmospheric Hg deposition to the landscape were investigated in watersheds of the Western United States and the Canadian-Alaskan Arctic. Mercury concentration and discharge data from flow gauging stations were used to compute annual mass loads with regression models. Measured wet and modeled dry deposition were compared to annual stream loads to compute ratios of Hg stream load to total Hg atmospheric deposition. Watershed land uses or cover included mining, undeveloped, urbanized, and mixed. Of 27 watersheds that were investigated, 15 had some degree of mining, either of Hg or precious metals (gold or silver), where Hg was used in the amalgamation process. Stream loads in excess of annual Hg atmospheric deposition (ratio > 1) were observed in watersheds containing Hg mines and in relatively small and medium-sized watersheds with gold or silver mines, however, larger watersheds containing gold or silver mines, some of which also contain large dams that trap sediment, were sometimes associated with lower load ratios (< 0.2). In the non-Arctic regions, watersheds with natural vegetation tended to have low ratios of stream load to Hg deposition (< 0.1), whereas urbanized areas had higher ratios (0.34–1.0) because of impervious surfaces. This indicated that, in ecosystems with natural vegetation, Hg is retained in the soil and may be transported subsequently to streams as a result of erosion or in association with dissolved organic carbon. Arctic watersheds (Mackenzie and Yukon Rivers) had a relatively elevated ratio of stream load to atmospheric deposition (0.27 and 0.74), possibly because of melting glaciers or permafrost releasing previously stored Hg to the streams. Overall, our research highlights the important role of watershed characteristics in determining whether a landscape is a net source of Hg or a net sink of atmospheric Hg.

Science of the Total Environment↗