Geology topics

Gretchen P. Oelsner

Publications and source records attributed to Gretchen P. Oelsner.

12 recordsLinked to original sources

USGS2025

Disentangling geomorphic equifinality in sediment and hydrologic connectivity through the analyses of landscape drivers of hysteresis

Sources, transport mechanisms and pathways of fine sediment in river systems are dependent on a multitude of climatic, geomorphic and anthropogenic factors, resulting in geomorphic equifinality, in which it is difficult to parse how different landscape processes affect sediment transport across different spatiotemporal scales. The objectives of this study are to 1) provide a conceptual model to consider how differing spatial distributions and hydrologic timing of sediment sources, both upland and in-channel, can result in equifinal sediment transport outcomes, and 2) utilize analytical methods with widely available environmental datasets to infer sediment processes from stream gaging data. Hysteretic patterns of observed storm events were classified based on their direction and timing of peak sediment concentration, relative to streamflow, using records from 35 U.S. Geological Survey stream gages in the period between 2007 and 2023 within two different physiographic regions: the Mid-Atlantic Delaware River Basin (DRB) and the Midwestern Illinois River Basin (IRB). The DRB contains mixed forest, urban, suburban and agricultural watersheds over diverse topography, and the IRB is primarily an intensively managed agricultural watershed on flat terrain. We use principal component analysis and linear discriminant analysis to infer regional hydrologic relations with turbidity dynamics, and to identify the primary hydrologic and land surface characteristics most effective at distinguishing between hysteretic classes in each region. These analyses reveal underlying regional relations in storm event hydrodynamics and landscape characteristics that contribute to varying patterns in sediment dynamics. Incorporating these sediment dynamic relations with spatial distributions and hydrologic timing of sediment sources could help to improve process understanding and predictive capability of fine sediment transport in watersheds.

Delaware, Illinois, Indiana, New Jersey, New York,↗

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

Comparison of surrogate models to estimate pesticide concentrations at six U.S. Geological Survey National Water Quality Network sites during water years 2013–18

During water years 2013–18, the U.S. Geological Survey National Water-Quality Assessment Project sampled the National Water Quality Network for Rivers and Streams year-round and reported on 221 pesticides at 72 sites across the United States. Pesticides are difficult to measure, their concentrations often represent discrete snapshots in time, and capturing peak concentrations is expensive. Three types of regression models were developed to estimate concentrations for two selected pesticides at each of six National Water Quality Network for Rivers and Streams sites. The regression models used continuously measured streamflow and water-quality properties (differing combinations of pH, specific conductance, turbidity, and water temperature); discrete water-quality samples analyzed for atrazine, azoxystrobin, bentazon, bromacil, imidacloprid, simazine, and triclopyr; and time as an additional explanatory variable for seasonality. The modeling approaches included (1) a standard regression that included surrogates (differing combinations of pH, specific conductance, turbidity, and water temperature) and periodic functions (sine-cosine) of pesticide application use as predictor variables; (2) the seasonal wave with flow adjustment model that included a seasonal component and flow anomalies but excluded surrogates; and (3) the seasonal wave with flow adjustment model that included a seasonal component, flow anomalies, and surrogates. Models were evaluated using three measures of model performance: generalized coefficient of determination (generalized R 2 ), Akaike’s Information Criteria, and scale (the estimated standard deviation of the tobit regression error term). Because of low observation numbers, results from this study can be considered a pilot effort with the possibility that some models are overfit. In all cases, estimated pesticide concentrations modeled with base SEAWAVE-Q were better than the standard surrogate regression models; all 39 generalized R 2 values increased by 3–56 percent (median of 25 percent) when compared to the standard surrogate regression models, and all Akaike’s Information Criteria and scale values decreased. The addition of surrogate variables such as pH, specific conductance, turbidity, and water temperature to the base SEAWAVE-Q model to improve estimates of pesticide concentrations resulted in only modest improvements; generalized R 2 values increased by only 0–10 percent (median of 3 percent). In some instances, combinations of the surrogates produced more appreciative improvements in model results, but in those instances, we hypothesize that the surrogates correlated with some unknown measure that directly relates to pesticide transport.

Indiana, Kansas, Missouri, North Dakota, Oregon↗

USGS2020

Landscape drivers of dynamic change in water quality of US rivers

Water security is a top concern for social well-being and dramatic changes in the availability of freshwater have occurred as a result of human uses and landscape management. Elevated nutrient loading and perturbations to major ion composition have resulted from human activities and have degraded freshwater resources. This study addresses the emerging nature of stream water quality in the 21st century through analysis of concentrations and trends in a wide variety of constituents in streams and rivers of the U.S. Concentrations of fifteen separate water quality parameters including nutrients, major ions, sediment, and specific conductance were analyzed over the period 1982-2012 and a targeted trend analysis was performed from 1992-2012. Although environmental policy is geared toward addressing the long-standing problem of nutrient overenrichment, these efforts have had uneven success, with decreasing nutrient concentrations at urbanized sites and little to no change at agricultural sites. However, freshwaters are being salinized rapidly in all human-dominated land use types. Increasing salinity negatively affects biodiversity, mobilizes sediment-bound contaminants, and increases lead contamination of drinking water but the effects are poorly quantified. Therefore, while efforts to control nutrients are ongoing, rapid salinity increases are ushering in a new set of poorly-defined issues.

Environmental Science & Technology↗

USGS2019

Recent trends in nutrient and sediment loading to coastal areas of the conterminous U.S.: Insights and global context

Coastal areas in the U.S. and worldwide have experienced massive population and land use changes contributing to significant degradation of coastal ecosystems. Excess nutrient pollution causes coastal ecosystem degradation, and both regulatory and management efforts have targeted reducing nutrient and sediment loading to coastal rivers. Decadal trends in flow-normalized nutrient and sediment loads were determined for 95 monitoring locations on 88 U.S. coastal rivers, including tributaries of the Great Lakes, between 2002 and 2012 for nitrogen (N), phosphorus (P), and sediment. N and P loading from urban watersheds generally decreased between 2002 and 2012. In contrast, N and P trends in agricultural watersheds were variable indicating uneven progress in decreasing nutrient loading. Coherent decreases in N loading from agricultural watersheds occurred in the Lake Erie basin, but limited benefit is expected from these changes because P is the primary driver of degradation in the lake. Nutrient loading from undeveloped watersheds was low, but increased between 2002 and 2012, possibly indicating degradation of coastal watersheds with a lower intensity of anthropogenic influence. Regional differences in trends were evident, with stable nutrient loads from the Mississippi River to the Gulf of Mexico, but commonly decreasing N loads and increasing P loads in Chesapeake Bay. Compared to global rivers, coastal rivers of the conterminous U.S have somewhat lower TN yields and slightly higher TP yields, but similarities exist among land use, nutrient sources, and changes in nutrient loads. Despite widespread decreases in N loading in coastal watersheds, recent N:P ratios remained elevated compared to historic values in many areas. Additional progress in reducing N and P loading to U.S. coastal waters, particularly outside of urban areas, would benefit coastal ecosystems.

Science of the Total Environment↗

USGS2017

Water-quality trends in the nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results

Since passage of the Clean Water Act in 1972, Federal, State, and local governments have invested billions of dollars to reduce pollution entering rivers and streams. To understand the return on these investments and to effectively manage and protect the Nation’s water resources in the future, we need to know how and why water quality has been changing over time. As part of the National Water-Quality Assessment Project, of the U.S. Geological Survey’s National Water-Quality Program, data from the U.S. Geological Survey, along with multiple other Federal, State, Tribal, regional, and local agencies, have been used to support the most comprehensive assessment conducted to date of surface-water-quality trends in the United States. This report documents the methods used to determine trends in water quality and ecology because these methods are vital to ensuring the quality of the results. Specific objectives are to document (1) the data compilation and processing steps used to identify river and stream sites throughout the Nation suitable for water-quality, pesticide, and ecology trend analysis, (2) the statistical methods used to determine trends in target parameters, (3) considerations for water-quality, pesticide, and ecology data and streamflow data when modeling trends, (4) sensitivity analyses for selecting data and interpreting trend results with the Weighted Regressions on Time, Discharge, and Season method, and (5) the final trend results at each site. The scope of this study includes trends in water-quality concentrations and loads (nutrient, sediment, major ion, salinity, and carbon), pesticide concentrations and loads, and metrics for aquatic ecology (fish, invertebrates, and algae) for four time periods: (1) 1972–2012, (2) 1982–2012, (3) 1992–2012, and (4) 2002–12. In total, nearly 12,000 trends in concentration, load, and ecology metrics were evaluated in this study; there were 11,893 combinations of sites, parameters, and trend periods. The final trend results are presented with examples of how to interpret the results from each trend model. Interpretation of the trend results, such as causal analysis, is not included.

Scientific Investigations Report↗

USGS2017

Challenges with secondary use of multi-source water-quality data in the United States

Combining water-quality data from multiple sources can help counterbalance diminishing resources for stream monitoring in the United States and lead to important regional and national insights that would not otherwise be possible. Individual monitoring organizations understand their own data very well, but issues can arise when their data are combined with data from other organizations that have used different methods for reporting the same common metadata elements. Such use of multi-source data is termed “secondary use”—the use of data beyond the original intent determined by the organization that collected the data. In this study, we surveyed more than 25 million nutrient records collected by 488 organizations in the United States since 1899 to identify major inconsistencies in metadata elements that limit the secondary use of multi-source data. Nearly 14.5 million of these records had missing or ambiguous information for one or more key metadata elements, including (in decreasing order of records affected) sample fraction, chemical form, parameter name, units of measurement, precise numerical value, and remark codes. As a result, metadata harmonization to make secondary use of these multi-source data will be time consuming, expensive, and inexact. Different data users may make different assumptions about the same ambiguous data, potentially resulting in different conclusions about important environmental issues. The value of these ambiguous data is estimated at \$US12 billion, a substantial collective investment by water-resource organizations in the United States. By comparison, the value of unambiguous data is estimated at \$US8.2 billion. The ambiguous data could be preserved for uses beyond the original intent by developing and implementing standardized metadata practices for future and legacy water-quality data throughout the United States.

Water Research↗

USGS2016

Groundwater hydrology and estimation of horizontal groundwater flux from the Rio Grande at selected locations in Albuquerque, New Mexico, 2009–10

The Albuquerque area of New Mexico has two principal sources of water: (1) groundwater from the Santa Fe Group aquifer system, and (2) surface water from the Rio Grande. From 1960 to 2002, pumping from the Santa Fe Group aquifer system caused groundwater levels to decline more than 120 feet while water-level declines along the Rio Grande in Albuquerque were generally less than 40 feet. These differences in water-level declines in the Albuquerque area have resulted in a great deal of interest in quantifying the river-aquifer interaction associated with the Rio Grande. In 2003, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, acting as fiscal agent for the Middle Rio Grande Endangered Species Collaborative Program, and the U.S. Army Corps of Engineers, began a study to characterize the hydrogeology of the Rio Grande inner valley alluvial aquifer in the Albuquerque area of New Mexico. The study provides hydrologic data in order to enhance the understanding of rates of water leakage from the Rio Grande to the alluvial aquifer, groundwater flow through the aquifer, and discharge of water from the aquifer to riverside drains. The study area extends about 20 miles along the Rio Grande in the Albuquerque area. Piezometers and surface-water gages were installed in paired transects at eight locations. Nested piezometers, completed at various depths in the alluvial aquifer, and surface-water gages, installed in the Rio Grande and riverside drains, were instrumented with pressure transducers. Water-level and water-temperature data were collected from 2009 to 2010. Water levels from the piezometers indicated that groundwater movement was usually away from the river towards the riverside drains. Annual mean horizontal groundwater gradients in the inner valley alluvial aquifer ranged from 0.0024 (I-25 East) to 0.0144 (Pajarito East). The median hydraulic conductivity values of the inner valley alluvial aquifer, determined from slug tests, ranged from 30 feet per day (ft/d) (Montaño) to 120 ft/d (Central) for paired transects, with a median hydraulic conductivity for all transects of 50 ft/d. Daily mean groundwater fluxes from the river through the inner valley alluvial aquifer computed using Darcy’s Law and the slug test results ranged from about 0.01 ft/d (Montaño West) to between 1.0 and 2.0 ft/d (Central East). Median annual groundwater fluxes from the river through the inner valley alluvial aquifer determined using the Suzuki-Stallman method was greatest at Alameda East (0.50 ft/d) and lowest at Alameda West (0.25 ft/d). The results from both methods agreed reasonably well. Seepage investigations conducted by measuring discharge in the east and west riverside drains provided information for computing changes in flow within the drains and for evaluating results from Darcy’s Law and Suzuki-Stallman method flux calculations. Discharge measured in the east riverside drain between the Barelas Bridge and the I-25 bridge indicated that the flow in the east riverside drain increased by an average of 56.5 cubic feet per day per linear foot (ft 3 /d/ft) of drain. Discharge measured in the west riverside drain between the Central bridge and the I-25 bridge indicated that flow increased between west drain miles 0 and 4, an average of 53.8 ft 3 /d/ft of drain, and that flow increased between west drain miles 7 and 10, an average of 44.9 ft 3 /d/ft of drain. In comparison to the seepage measurement results, the groundwater fluxes from the river through the inner valley alluvial aquifer calculated from Darcy’s Law (q slug ) and by the Suzuki-Stallman method (q heat ) would account for 20–36 percent or 53–95 percent, respectively, of the total flow in the east riverside drain and 22–31 percent or 19–26 percent, respectively, of the total flow in the west drain. These results indicate that the drains likely also receive water from outside the inner valley. The spatial variability of horizontal hydraulic gradients and groundwater fluxes can be primarily attributed to variability in the distances between the river and riverside drains throughout the study area and geologic heterogeneities in the alluvial aquifer. Temporal variability in the water levels, which control the horizontal hydraulic gradients and fluxes between the Rio Grande and the riverside drains, can be primarily attributed to seasonal fluctuations in river stage and irrigation practices.

New Mexico↗

USGS2015

Assessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development — Why existing national data sets cannot tell us what we would like to know

Heightened concern regarding the potential effects of unconventional oil and gas development on regional water quality has emerged, but the few studies on this topic are limited in geographic scope. Here we evaluate the potential utility of national and publicly available water-quality data sets for addressing questions regarding unconventional oil and gas development. We used existing U.S. Geological Survey and U.S. Environmental Protection Agency data sets to increase understanding of the spatial distribution of unconventional oil and gas development in the U.S. and broadly assess surface water quality trends in these areas. Based on sample size limitations, we were able to estimate trends in specific conductance (SC) and chloride (Cl − ) from 1970 to 2010 in 16% ( n = 155) of the watersheds with unconventional oil and gas resources. We assessed these trends relative to spatiotemporal distributions of hydraulically fractured wells. Results from this limited analysis suggest no consistent and widespread trends in surface water quality for SC and Cl − in areas with increasing unconventional oil and gas development and highlight limitations of existing national databases for addressing questions regarding unconventional oil and gas development and water quality.

Water Resources Research↗

USGS2015

Summary of urban stormwater quality in Albuquerque, New Mexico, 2003-12

Urban stormwater in the Albuquerque metropolitan area was sampled by the U.S. Geological Survey in cooperation with the City of Albuquerque, the Albuquerque Metropolitan Arroyo Flood Control Authority, the New Mexico Department of Transportation, and the University of New Mexico. Stormwater was sampled from a network of monitoring stations from 2003 to 2012 by following regulatory requirements for the National Pollutant Discharge Elimination System stormwater permit. During this period, stormwater was sampled in the Albuquerque metropolitan area at outfalls from nine drainage basins with residential, industrial, commercial, agricultural, and undeveloped land uses. Stormwater samples were analyzed for selected physical and chemical characteristics, nutrients, major ions, metals, organic compounds, and bacteria. General quality of stormwater samples, as measured by dissolved solids, nutrient (with the exception of phosphorus), major ion, and dissolved metal concentrations, was similar to that in samples from the Rio Grande. Of the nearly 200 organic compounds that were analyzed for this study, less than one-third (58 constituents) were positively identified at or above the analytical detection limit in stormwater. Concentrations for volatile organic compounds, semivolatile organic compounds, polychlorinated biphenyls, and pesticides were generally low in the stormwater samples. Fifteen of the 16 polycyclic aromatic hydrocarbons listed on the U.S. Environmental Protection Agency Priority Chemicals list were detected in at least one stormwater sample from each outfall. Maximum concentrations for some polycyclic aromatic hydrocarbons in stormwater did exceed a water-quality criterion. Median concentrations for Escherichia coli ( E. coli ) bacteria in the stormwater samples, including those from the background location (Embudo Arroyo), were above the New Mexico water-quality standard. Concentrations for E. coli in stormwater often exceeded the water-quality criterion. The stormwater quality in Albuquerque was compared with that of six other Western U.S. cities (Phoenix, Arizona; Tucson, Arizona; Las Vegas, Nevada; Denver, Colorado; Salt Lake City, Utah; and Boise, Idaho) for selected constituents. In general, water-quality data for stormwater samples from these six other Western U.S. cities were similar to water-quality data for the stormwater samples from the Albuquerque outfalls. Median concentrations for suspended solids, total phosphorus, and bacteria ( E. coli and fecal coliform) in stormwater samples from the Albuquerque outfalls, as a whole, were higher than those in samples from the other Western U.S. cities except for Las Vegas.

New Mexico↗

USGS2014

Simulated and measured water levels and estimated water-level changes in the Albuquerque area, central New Mexico, 1950-2012

The City of Albuquerque, the major population center in New Mexico, underwent a more than fivefold population increase between 1950 and 2010. Before 2009, groundwater was the primary source of the City of Albuquerque’s municipal water supply, but since that time, the city has diverted water through the San Juan-Chama Drinking Water Project to augment municipal water supplies. Consequently, there is interest in understanding how groundwater levels changed in response to groundwater pumping, surface-water diversions, and conservation measures. To give a more detailed history of water-level changes from 1950 through 2012, the U.S. Geological Survey, in cooperation with the Albuquerque Bernalillo County Water Utility Authority, created maps showing water-level contours and changes by contouring water-table elevations and production-zone hydraulic heads that were simulated with a recently updated regional-scale transient groundwater-flow model at 10-year intervals from 1950 to 2000 and again for 2008. Both the water-table elevations and production-zone hydraulic heads declined over time with the largest change occurring between 1970 and 1980, which was a period of rapid population growth and groundwater use. Declines in the water-table elevations and production-zone hydraulic heads are focused around major pumping centers and are largest in the production zone. Hydrographs from nine production-zone piezometers in the modeled area indicated varying responses to the increased use of surface-water diversions during 2009–12, with responses related to the locations of the wells within the study area and their proximity to pumping centers and the Rio Grande.

New Mexico↗

USGS2012

Water quality studied in areas of unconventional oil and gas development, including areas where hydraulic fracturing techniques are used, in the United States

Domestic oil and gas production and clean water are critical for economic growth, public health, and national security of the United States. As domestic oil and gas production increases in new areas and old fields are enhanced, there is increasing public concern about the effects of energy production on surface-water and groundwater quality. To a great extent, this concern arises from the improved hydraulic fracturing techniques being used today, including horizontal drilling, for producing unconventional oil and gas in low-permeability formations. The U.S. Geological Survey (USGS) John Wesley Powell Center for Analysis and Synthesis is hosting an interdisciplinary working group of USGS scientists to conduct a temporal and spatial analysis of surface-water and groundwater quality in areas of unconventional oil and gas development. The analysis uses existing national and regional datasets to describe water quality, evaluate water-quality changes over time where there are sufficient data, and evaluate spatial and temporal data gaps.

Fact Sheet↗