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Groundwater quality data in 15 GAMA study units: results from the 2006–10 Initial sampling and the 2009–13 resampling of wells, California GAMA Priority Basin Project

The Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) program was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). From May 2004 to March 2012, the GAMA-PBP collected samples from more than 2,300 wells in 35 study units across the State. Selected wells in each study unit were sampled again approximately 3 years after initial sampling as part of an assessment of temporal trends in water quality by the GAMA-PBP. This triennial (every 3 years) trend sampling of GAMA-PBP study units concluded in December 2013. Fifteen of the study units, initially sampled between January 2006 and June 2010 and sampled a second time between April 2009 and April 2013 to assess temporal trends, are the subject of this report. The initial sampling was designed to provide a spatially unbiased assessment of the quality of untreated groundwater used for public water supplies in the 15 study units. In these study units, 730 wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the areas assessed (grid wells, also called “status wells”). Approximately 3 years after the initial sampling, 93 of the previously sampled status wells (approximately 10 percent in each study unit) were randomly selected for trend sampling (“trend wells”). The 15 study units sampled for trends were distributed among 4 hydrogeologic provinces: Central Valley, Basin and Range, Desert, and Transverse and selected Peninsular Ranges. The total number of status wells sampled, along with those sampled again for trends, varied by study unit. In the Central Valley hydrogeologic province, the numbers of status wells and trend wells in each study unit were as follows: Kern County subbasin study unit—47 status wells, 5 trend wells Central Eastside San Joaquin Basin study unit—58 status wells, 6 trend wells Middle Sacramento Valley study unit—71 status wells, 8 trend wells Northern Sacramento Valley study unit—43 status wells, 4 trend wells Madera–Chowchilla study unit—30 status wells, 4 trend wells Western San Joaquin Valley study unit—39 status wells, 4 trend wells. The Basin and Range hydrogeologic province had only one study unit: Owens and Indian Wells Valleys study unit—53 status wells, 6 trend wells. In the Desert hydrogeologic province, the numbers of wells were as follows: Coachella Valley study unit—19 status wells 4 trend wells Colorado River study unit—20 status wells, 3 trend wells Antelope Valley study unit—56 status wells, 6 trend wells Mojave study unit—52 status wells, 7 trend wells Borrego Valley, Central Desert and Low-Use Basins of the Mojave and Sonoran Deserts study unit—49 status wells, 6 trend wells. In the Transverse and Selected Peninsular Ranges hydrogeologic province, the numbers of wells were as follows: Coastal Los Angeles Basin study unit—61 status wells, 8 trend wells Upper Santa Ana Watershed study unit—90 status wells, 16 trend wells Santa Clara River Valley study unit—42 status wells, 6 trend wells. The groundwater samples were analyzed for a number of synthetic organic constituents (volatile organic compounds, pesticides, and pesticide degradates), constituents of special interest (perchlorate, N -nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), and naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements). Naturally occurring isotopes (tritium, carbon-14, and stable isotopes of hydrogen and oxygen in water) also were measured to help identify processes affecting groundwater quality and the sources and ages of the sampled groundwater. More than 200 constituents and water-quality indicators were investigated. Quality-control samples (blanks, replicates, or samples for matrix spikes) were collected at 34 percent of the trend wells, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. On the basis of detections in laboratory and field blanks in samples from GAMA-PBP study units, including the study units presented here, some groundwater results were adjusted in this report. Differences between replicate samples were mostly within acceptable ranges, indicating acceptably low variability in analytical results. Median matrix-spike recoveries were within the acceptable range (70 to 130 percent) for 189 of the 224 compounds for which matrix spikes were analyzed (84 percent). This study did not attempt to evaluate the quality of water delivered to consumers. After withdrawal, groundwater used for drinking water typically is treated, disinfected, and blended with other waters to attain acceptable water quality. The benchmarks used in this report apply to treated water that is served to the consumer, not to untreated groundwater. To provide some context for the results, however, concentrations of constituents measured in these groundwater samples were compared with benchmarks established by the U.S. Environmental Protection Agency and California Department of Public Health. Comparisons between data collected for this study and benchmarks for drinking-water quality are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. Most constituents that were detected in groundwater samples from the trend wells were found at concentrations less than drinking-water benchmarks. Two volatile organic compounds (VOCs)—tetrachloroethene and trichloroethene—were detected in samples from one or more wells at concentrations greater than their health-based benchmarks, and three VOCs—chloroform, tetrachloroethene, and trichloroethene—were detected in at least 10 percent of the trend-well samples from the initial sampling period and the later trend sampling period. No pesticides were detected at concentrations near or greater than their health-based benchmarks. Three pesticide constituents—atrazine, deethylatrazine, and simazine—were detected in more than 10 percent of the trend-well samples in both sampling periods. Perchlorate, a constituent of special interest, was detected at a concentration greater than its health-based benchmark in samples from one trend well in the initial sampling and trend sampling periods, and in an additional trend well sample only in the trend sampling period. Most detections of nutrients, major and minor ions, and trace elements in samples from trend wells were less than health-based benchmarks in both sampling periods. Exceptions included nitrate, fluoride, arsenic, boron, molybdenum, strontium, and uranium; these were all detected at concentrations greater than their health-based benchmarks in at least one well sample in both sampling periods. Lead and vanadium were detected above their health-based benchmarks in one sample each collected in the initial sampling period only. The isotopic ratios of oxygen and hydrogen in water and the activities of tritium and carbon-14 generally changed little between sampling periods.

California↗

Groundwater-quality data in the South Coast Range-Coastal study unit, 2008: Results from the California GAMA Program

Groundwater quality in the approximately 766-square-mile South Coast Range–Coastal (SCRC) study unit was investigated from May to December 2008, as part of the Priority Basins Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basins Project was developed in response to legislative mandates (Supplemental Report of the 1999 Budget Act 1999-00 Fiscal Year; and, the Groundwater Quality Monitoring Act of 2001 [Sections 10780-10782.3 of the California Water Code, Assembly Bill 599]) to assess and monitor the quality of groundwater in California, and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The SCRC study unit was the 25th study unit to be sampled as part of the GAMA Priority Basins Project. The SCRC study unit was designed to provide a spatially unbiased assessment of untreated groundwater quality in the primary aquifer systems and to facilitate statistically consistent comparisons of untreated groundwater quality throughout California. The primary aquifer systems (hereinafter referred to as primary aquifers) were defined as that part of the aquifer corresponding to the perforation interval of wells listed in the California Department of Public Health (CDPH) database for the SCRC study unit. The quality of groundwater in shallow or deep water-bearing zones may differ from the quality of groundwater in the primary aquifers; shallow groundwater may be more vulnerable to surficial contamination. In the SCRC study unit, groundwater samples were collected from 70 wells in two study areas (Basins and Uplands) in Santa Barbara and San Luis Obispo Counties. Fifty-five of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and 15 wells were selected to aid in evaluation of specific water-quality issues (understanding wells). In addition to the 70 wells sampled, 3 surface-water samples were collected in streams near 2 of the sampled wells in order to better comprehend the interaction between groundwater and surface water in the area. The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOC], pesticides and pesticide degradates, polar pesticides and metabolites, and pharmaceutical compounds), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-TCP), naturally occurring inorganic constituents (trace elements, nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], and alkalinity), and radioactive constituents (gross alpha and gross beta radioactivity). Naturally occurring isotopes (stable isotopes of hydrogen and oxygen in water, stable isotopes of nitrogen and oxygen in dissolved nitrate, stable isotopes of sulfur in dissolved sulfate, stable isotopes of carbon in dissolved inorganic carbon, activities of tritium, and carbon-14 abundance), and dissolved gases (including noble gases) also were measured to help identify the sources and ages of the sampled groundwater. In total, 298 constituents and field water-quality indicators were investigated. Three types of quality-control samples (blanks, replicates, and matrix-spikes) were collected at approximately 3 to 12 percent of the wells in the SCRC study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Differences between replicate samples generally were less than 10 percent relative and/or standard deviation, indicating acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 84 percent of the compounds. This study did not attempt to evaluate the quality of drinking water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and/or blended with other waters to maintain water quality. Regulatory thresholds apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-regulatory thresholds established for aesthetic concerns by CDPH. Comparisons between data collected for this study and thresholds for drinking water are for illustrative purposes only and are not indicative of compliance or noncompliance with those thresholds. Most organic and inorganic constituents that were detected in groundwater samples from the 55 grid wells in the SCRC study unit were detected at concentrations less than drinking-water thresholds. In addition, all detections of organic constituents in SCRC grid well samples were less than health-based thresholds. In total, VOCs were detected in 33 percent of the 55 grid wells sampled and pesticides and pesticide degradates were detected in 27 percent of grid wells sampled in the SCRC study unit. In the Basins study area, VOCs and pesticides and pesticide degradates were detected in approximately 33 percent of the 39 grid wells. In the Uplands study area, VOCs were detected in approximately 31 percent and pesticides and pesticide degradates were detected in approximately 13 percent of the 16 grid wells. Trace elements and minor ions were sampled for at 32 grid wells and nutrients at 33 grid wells in the SCRC study unit, and most detections were less than health-based thresholds. Exceptions in the Basins study area include one detection of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 µg/L and three detections of nitrite plus nitrate, as nitrogen (NO2-+NO3-) greater than the MCL-US of 10 mg/L. Exceptions in the Uplands study area include two detections of arsenic greater than the MCL-US and eight detections of molybdenum greater than the USEPA lifetime health advisory level (HAL-US) of 40 µg/L. All detections of major and minor ions and gross alpha and gross beta radioactivity from the SCRC grid wells were less than health-based thresholds. Results for trace elements, major ions, and TDS with non-enforceable thresholds set for aesthetic concerns from 16 Basins study area grid wells showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 µg/L were detected in grid wells. Manganese concentrations greater than the SMCL-CA of 50 µg/L were detected in six grid wells. Chloride concentrations greater than the recommended SMCL-CA threshold of 250 mg/L were detected in one grid well. Sulfate concentrations greater than the recommended SMCL-CA threshold of 250 mg/L were measured in 12 grid wells and 3 of these wells also were greater than the upper SMCL-CA threshold of 500 mg/L. TDS concentrations greater than the SMCL-CA recommended threshold of 500 mg/L were measured in 14 of the 16 Basins study area grid wells and concentrations in 5 of these wells also were greater than the SMCL-CA upper threshold of 1,000 mg/L. In the Uplands study area, iron concentrations greater than the SMCL-CA were detected in 2 of 16 grid wells and manganese concentrations greater than the SMCL-CA were detected in 3 grid wells. TDS and sulfate concentrations greater than the recommended SMCL-CA thresholds were detected in 11 and 2 grid wells, respectively, but none of these concentrations were greater than the SMCL-CA upper thresholds.

California↗

Structured decision-making workshop: Chronic wasting disease management in free-ranging cervids in Massachusetts

This document describes the results of a 2.5-day rapid decision prototype workshop that evaluated management activities for chronic wasting disease (CWD) in Massachusetts (MA) that were either proactive (i.e., actions taken prior to CWD arrival/detection) or reactive (i.e., actions taken after CWD arrival/detection). The workshop was led by members of the Wildlife Section of the MA Division of Fisheries and Wildlife (hereafter referred to as MassWildlife) and included a group of agency communications specialists and district managers. U. S. Geological Survey staff and a volunteer acted as decision facilitators and led the analysis of the decision. Chronic wasting disease is an always fatal neurological disease that has spread across much of North America and threatens the health of deer populations in locations where it occurs (reviewed by Escobar et al. 2020). CWD can spread into new areas via two general mechanisms: (1) natural spread (e.g., dispersal of CWD-infected male white-tailed deer [Odocoileus virginianus]), and (2) anthropogenic spread (e.g., CWD spread facilitated by human intervention; Leiss et al. 2017, Escobar et al. 2020). Once CWD arrives in a state, natural resources agencies spend eight times more on CWD than agencies with no known cases; to cover these new CWD-related management activities, the natural resources agencies are typically forced to reallocate money from existing conservation priorities (Chiavacci, 2022). As of May 2024, there were 34 U.S. states and five Canadian provinces that had detected CWD positive free-ranging and/or captive animals in the family Cervidae (collectively referred to as ‘cervid’ hereafter), and the number of new states/provinces that are detecting CWD for the first time continues to grow (U. S. Geological Survey, May 2024). As of February 2024, the closest CWD positive state to MA with CWD detected in free-ranging white-tailed deer is Pennsylvania. To date, there have been no detections of CWD in MA, but testing has been limited in MA since 2012. The growing number of CWD positive states suggests that there may be increasing risk of CWD entering and establishing in MA as the number of CWD cases increases across North America. According to a 2023 survey of hunters in MA conducted by MassWildlife, 68% of hunters were concerned about CWD entering MA, and 88% of respondents said that it was at least moderately important to keep CWD out of MA; these survey results indicate that most hunters may support CWD risk reduction actions (Martin Feehan, Massachusetts Division of Fisheries and Wildlife, oral communication, 12 Feb 2024). In addition, 23.1% of responding deer hunters in MA have hunted for cervids in CWD-positive states/provinces in the last five years (not including states/provinces that have been able to successfully eradicate CWD following a positive detection). Participants of the survey were also asked, “how many deer have you harvested that tested positive for CWD?”. A total of three respondents said that they had one deer test positive for CWD, which, when extended to the whole population of MA deer hunters, results in an estimated 32 CWD positive deer harvested in CWD-positive states and imported into MA in the last five years. When asked about how they transport harvested deer from out of state into MA, the three participants indicated either “already processed & packaged” or “not applicable.” Note, that in MA, it is a violation of regulation to import whole carcasses or high-risk parts (e.g., head, brain, spinal tissues, bones) of any member of the Cervidae family (wild or captive) from a state/province that has detected CWD; it is legal to bring in deboned meat, cleaned skull caps, hides without the head, or a fixed taxidermy mount (Massachusetts Division of Fisheries and Wildlife, 2024a). To date, testing for CWD has been limited in MA since 2012. However, the data collected from the 2023 MA hunter survey suggests that there is a real risk of CWD being imported by a MA resident who has hunted in a CWD positive state. Therefore, given the higher costs of CWD management post arrival, the potential natural spread of CWD from nearby states, and the risk of CWD introduction via humanmediated cervid movement, MassWildlife is motivated to take actions that minimize the risk of CWD introduction and spread in MA with the ultimate goal of managing thriving wildlife populations and maximizing hunter and general public satisfaction, which are both parts of the MassWildlife mission. A 2.5-day rapid prototyping structured decision making workshop was held with MassWildlife staff to develop a decision framework for CWD management in MA. During the workshop, we defined the context and extent of CWD management activities in MA. Next, we identified four fundamental objectives that help achieve the mission of MassWildlife and that address stakeholder concerns. The fundamental objectives included: (1) maximizing hunter satisfaction and participation, (2) maximizing public satisfaction (non-consumptive), (3) maximizing health and sustainability of cervids, and (4) maximizing the efficiency of CWD management. Then, we generated a list of five alternatives (i.e., strategies) that varied the intensity of proactive and reactive actions. The five strategies were: (1) minimal proactive and minimal reactive actions, (2) intermediate proactive and intermediate reactive actions, (3) intensive proactive and intermediate reactive actions, (4) minimal proactive and intensive reactive actions, and (5) intensive proactive and intensive reactive actions. Lastly, we estimated the performance of each strategy on the fundamental objectives and assessed the overall performance of strategies relative to one another. We did so by first estimating the consequences of each alternative strategy on fundamental objectives using expert elicitation, and then, we elicited objective weights from MassWildlife staff to incorporate the relative importance of different fundamental objectives. Given that it is unknown when CWD will arrive in MA, we evaluated the performance of alternative strategies against fundamental objectives given three distinct scenarios for time to arrival of CWD: introduction in 2.5, 7.5, or 10+ years. The preliminary results of the rapid prototype indicate that the performance of the CWD management strategies that we evaluated depends on when CWD first arrives in MA. If CWD were to arrive in 2.5 or 7.5 years from now (February, 2024), then the ‘minimal proactive and minimal reactive’ strategy performs the best on both the deer population and cost fundamental objectives (fundamental objectives 3 & 4), but the ‘intensive proactive and intensive reactive’ strategy performs best on both of the human dimensions fundamental objectives (fundamental objectives 1 & 2) as well as the minimize CWD prevalence objective (also related to fundamental objective 3). We also found that public trust is likely to remain high across all five alternative strategies if CWD arrives after year 10, but public trust decreases if CWD arrives in year 2.5 or 7.5. After incorporating objective weights, we found that in scenarios where CWD arrives in the near-term (in years 2.5 or 7.5), an intermediate strategy (e.g., ‘intermediate proactive and intermediate reactive’ or ‘intensive proactive and intermediate reactive’) performed best, and the ‘minimal proactive and intensive reactive’ strategy performed worst. Conversely, if CWD were to arrive after 10 years, then the ‘minimal proactive and minimal reactive’ and ‘minimal proactive and intensive reactive’ strategies performed best. Collectively, these results suggest that the decision on which alternative strategy to employ is sensitive to when CWD arrives in MA. Following the discussion of the preliminary results, we identified the following four next steps. First, we discussed how a more detailed communications plan is needed and would likely alter the performance estimates of the alternative strategies on fundamental objectives 1 & 2, which were hunter and public satisfaction, respectively. The development of the communication plan would likely be easier once the alternative actions have been identified along with the audience and message. Second, a surveillance plan could be a useful tool to inform CWD management. Surveillance for CWD was performed in MA annually from 2002 to 2012 (n = 4,356 wild white-tailed deer and moose [Alces alces] samples). Limited surveillance was conducted from 2013 to 2022; and in 2023, 242 wild samples were collected. It is not clear whether MA needs a robust or minimal surveillance plan (e.g., is a minimal surveillance plan enough to detect the pathogen at the threshold that would trigger action?), or what type of invasion event the surveillance plan should target (e.g., natural vs anthropogenic spread events). The use of decision trees and a formal risk assessment may help answer these questions. Third, some of the elicited estimates from experts during this rapid prototype could be replaced with empirical data. Lastly, given that the decision was sensitive to when CWD arrived in MA and a surveillance plan would rely on the mode of introduction, forecasting and predicting the CWD invasion front and/or the likelihood of different incursion events across MA would provide valuable insights.

Massachusetts↗

Spatial and temporal variation of stream chemistry associated with contrasting geology and land-use patterns in the Chesapeake Bay watershed—Summary of results from Smith Creek, Virginia; Upper Chester River, Maryland; Conewago Creek, Pennsylvania; and Difficult Run, Virginia, 2010–2013

Despite widespread and ongoing implementation of conservation practices throughout the Chesapeake Bay watershed, water quality continues to be degraded by excess sediment and nutrient inputs. While the Chesapeake Bay Program has developed and maintains a large-scale and long-term monitoring network to detect improvements in water quality throughout the watershed, fewer resources have been allocated for monitoring smaller watersheds, even though water-quality improvements that may result from the implementation of conservation practices are likely to be first detected at smaller watershed scales. In 2010, the U.S. Geological Survey partnered with the U.S. Environmental Protection Agency and the U.S. Department of Agriculture to initiate water-quality monitoring in four selected small watersheds that were targeted for increased implementation of conservation practices. Smith Creek watershed is an agricultural watershed in the Shenandoah Valley of Virginia that is dominated by cattle and poultry production, and the Upper Chester River watershed is an agricultural watershed on the Eastern Shore of Maryland that is dominated by row-cropping activities. The Conewago Creek watershed is an agricultural watershed in southeastern Pennsylvania that is characterized by mixed agricultural activities. The fourth watershed, Difficult Run, is a suburban watershed in northern Virginia that is dominated by medium density residential development. The objective of this study was to investigate spatial and temporal variations in water chemistry and suspended sediment in these four relatively small watersheds that represent a range of land-use patterns and underlying geology to (1) characterize current water-quality conditions in these watersheds, and (2) identify the dominant sources, sinks, and transport processes in each watershed. The general study design involved two components. The first included intensive routine water-quality monitoring at an existing streamgage within each study area (including continuous water-quality monitoring as well as discrete water-quality sampling) to develop a detailed understanding of the temporal and hydrologic variability in stream chemistry and sediment transport in each watershed. The second component involved extensive water-quality monitoring at various sites throughout each watershed to develop a detailed understanding of spatial patterns. Both components were used to improve understanding of sources and transport processes affecting stream chemistry, including nutrients and suspended sediments, and their implications for detecting long-term trends related to best management practices. This report summarizes the results of monitoring that was performed from April 2010 through September 2013. Individual Small Watershed Summaries Summaries for each of the four small watersheds are presented below. Each watershed has a more descriptive and detailed section in the report, but these summaries may be particularly useful for some watershed managers and stakeholders desiring slightly less technical detail. Smith Creek Smith Creek is a 105.39-mi 2 watershed within the Shenandoah Valley that drains to the North Fork Shenandoah River. The long-term Smith Creek base-flow index is 72.3 percent, indicating that on average, approximately 72 percent of Smith Creek flow was base flow, which suggests that Smith Creek streamflow is dominated by groundwater discharge rather than stormwater runoff. A series of cluster and principal components analyses demonstrated that the majority of the variability in Smith Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed for turbidity, suspended sediments, total nitrogen, ammonium, orthophosphate, iron, total phosphorus, and the ratio of calcium to magnesium. Statistically significant inverse correlations with flow were observed for specific conductance, magnesium, δ 15 N of nitrate, pH, bicarbonate, calcium, and δ 18 O of nitrate. Of particular note, flow and nitrate were not statistically significantly correlated, likely because of the relatively complex concentration-discharge relationship observed in continuous and discrete datasets. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, turbidity, orthophosphate, total phosphorus, suspended-sediment concentration, and silica were higher during the warm season, but pH, dissolved oxygen, and sulfate were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loads in Smith Creek using the continuous water-quality monitors. The mean Smith Creek in-stream sediment load was approximately 6,900 tons per year, with nearly 90 percent of the sediment load over the 3-year study period contributed during the eight largest storm events during that period. The Smith Creek total phosphorus load was approximately 21,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods, although a substantial phosphorus load still occurs during base-flow conditions. The Smith Creek total nitrogen load was approximately 400,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions (as was the case for sediment and total phosphorus) and strongly affected by base-flow export of nitrogen from the basin. Extensive water-quality monitoring throughout the Smith Creek watershed revealed how the complex geology and hydrology interacted to result in variable water chemistry. During relatively dry and low base-flow periods, much of the discharge in Smith Creek was contributed by a single dominant spring—Lacey Spring. During wetter base-flow periods, the flows in Smith Creek were largely generated by a mixture of headwater springs and forested mountain tributaries with very different geochemical composition. The headwater springs generally issued from limestone bedrock and were characterized as having relatively high nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The undeveloped, high-gradient, forested mountain sites were generally characterized by low ionic strength waters with low nutrient concentrations. Nitrate isotope data from the limestone springs generally were consistent with manure-derived nitrogen sources (such as cattle and poultry), although the possibility of other mixed sources cannot be excluded. Nitrate isotope data from the undeveloped, high-gradient forested mountain sites were more consistent with nitrogen from undisturbed soils, atmospheric deposition, or nitrogen fixation. Regardless of the nitrogen source, oxygen isotope data indicate that the nitrate was largely a result of nitrification. Land-use data indicate that manure sources of nitrogen dominated watershed nitrogen inputs. Phosphorus sources were less well studied. The presence of a single point-source discharge near the town of New Market contributed the majority of the phosphorus to Smith Creek under base-flow conditions, but nonpoint sources of phosphorus dominated the loading to Smith Creek during stormflow periods. Implementation of conservation practices increased in the Smith Creek watershed during the study period, and even though a broad range of practice types was implemented, the most common practices included stream fencing (for cattle exclusion), the development of nutrient management plans, conservation crop rotation, and the planting of cover crops. While the implementation of these conservation practices is encouraging, results indicate small increases in nitrate concentrations at the streamgage over the last 29 years, concurrent with small decreases in nitrate fluxes. It will likely be years before the cumulative effect of these practices can be detected in the Smith Creek water quality, and the magnitude of the effect of these conservation practices detected in Smith Creek will depend largely on whether nutrient loading (of manure and commercial fertilizer) is reduced over time. Upper Chester River The Upper Chester River watershed includes the 36-square-mile (mi 2 ) watershed area around several nontidal tributaries that drain into the tidal Chester River. The streamgage is on Chesterville Branch, the largest nontidal tributary (approximately 6.12 mi 2 ) and is the site for continuous water-quality monitoring for this project. The base-flow index at Chesterville Branch is about 72 percent and indicates that, as in most of the Coastal Plain, groundwater is the greatest contributor to streamflow. As such, more than 90 percent of the nitrogen in the stream is in the form of nitrate from groundwater. Continuous and discrete data collected at Chesterville Branch show the effects of streamflow and season on water quality. Significantly positive correlations with flow were observed for ammonium, dissolved and total phosphorus, sediment, and turbidity as runoff carried these constituents from the land surface into Chesterville Branch. Other constituents that increased significantly with flow include potassium, sulfate, iron, and manganese, which are likely contributed from near-stream areas and ponds with high organic-matter content. Total nitrogen, pH, and specific conductance, along with chemical constituents associated with groundwater inputs including nitrate, calcium, ratio of calcium to magnesium, silica, bicarbonate, and sodium, were negatively correlated with flow because concentrations of these constituents were diluted by runoff. Seasonal differences in water chemistry, which are most likely related to increased biologic effects on the uptake and release of chemicals in the stream and near-stream areas, also were observed. Water temperature, orthophosphate, δ 15 N of nitrate, bicarbonate, sodium, and the ratio of sodium to chloride were higher during the warm season, and dissolved oxygen, total nitrogen, nitrate, magnesium, sulfate, and manganese were higher during the cool season. Surrogate-regression models developed by using continuous water-quality data showed that the annual sediment load for the 2013 water year was about 2,600 tons, with more than 90 percent of this sediment contributed during two storms. The total phosphorus load in 2013 was about 13,000 pounds with more than 90 percent contributed during the same two storms as sediment. The load of total nitrogen, 140,000 pounds, accumulated steadily throughout the 2013 water year as nitrate in groundwater continuously discharged into the stream. The same two large storms that contributed 90 percent of the suspended-sediment and total phosphorus load only contributed about 20 percent of the annual total nitrogen load. Extensive water-quality monitoring of stream base flow throughout the Upper Chester River watershed identified how differences in land use and hydrogeology affected water chemistry. In parts of the watershed with well-drained soil and thick sandy aquifer sediments, concentrations of nitrate and other chemicals associated with fertilizer and lime application increased in streams as agricultural land use increased. More than 90 percent of the nitrogen in streams from these areas was in the form of nitrate, and concentrations ranged from about 5 milligrams per liter (mg/L) to 8 mg/L as nitrogen in the two largest tributaries. Stream nitrate concentrations were about 1 mg/L as nitrogen where soils were more poorly drained, the surficial aquifer sediments were thinner, and forests and wetlands were more widespread than agriculture. Nitrate isotope data were consistent with inorganic fertilizers ± atmospheric deposition and N 2 fixation as sources of nitrogen, and with nitrification as the dominant nitrate-forming process. Nitrate reduction was indicated by elevated δ 15 N and δ 18 O values in some samples from streams draining watersheds with poorly drained soils. An analysis of land-use data and SPARROW modeling input data attributed almost 90 percent of the nitrogen sources in the Upper Chester River watershed to inorganic fertilizer and fixation of atmospheric nitrogen by legumes, which is in agreement with the isotopic characteristics of nitrate in this watershed. Local sources of manure are limited in this area. Total phosphorus concentrations during base flow ranged from below detection to about 0.2 mg/L. Stream phosphorus concentrations during base flow were generally lower than those measured during storms because most phosphorus transport likely occurs as phosphorus attached to sediment particles during runoff. Because manure is not widely used in this area, the major source of phosphorus is likely fertilizer. The implementation of conservation practices in the Upper Chester River watershed increased substantially during the study period, with a total implementation of 1,194 U.S. Department of Agriculture-compliant practices. The most frequently used practices were oriented towards nutrient and sediment control, including cover crops, nutrient management planning, conservation crop rotation, conservation tillage, and irrigation management. The current Chesapeake Bay model for this area predicts that implementation of best management practices should result in a 13-percent decrease in overall delivery of nitrogen to the Upper Chester River. Because most nitrogen travels through the groundwater system for years to decades before being discharged to streams, the time period of monitoring was not sufficient to see the effects of these practices on water quality. The magnitude of the effect that may eventually be detected will depend on the degree to which nitrate leaching into the groundwater system is reduced over time. Loadings of phosphorus and sediment are primarily transported during large runoff events and are difficult to control and analyze for trends because of their timing and episodic nature. Conewago Creek Conewago Creek has two primary monitoring locations—one near the middle of the 47-mi 2 watershed and the other near the outlet just upstream of the Susquehanna River. The base-flow index was 47.3 percent for 2012–2013, indicating that on average, approximately 53 percent of the streamflow in Conewago Creek exited the watershed as surface flow, which suggests that the stormwater runoff was somewhat greater than groundwater discharge (base flow). A series of cluster and principal components analyses demonstrated that the majority of the variability in the Conewago Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed at both monitoring sites for ammonium, total phosphorus, orthophosphate, iron, and manganese; additionally, at the upstream monitoring station, total nitrogen demonstrated a statistically significant positive correlation with flow. Statistically significant inverse correlations with flow were observed at both sites for water temperature, specific conductance (at the downstream site only), sulfate, chloride, calcium, and magnesium. Statistically significant seasonal patterns were observed for several water-quality constituents. Water temperature, phosphorus (upstream site only), and orthophosphate were higher during the warm season, and nitrate and total nitrogen (upstream site only) were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient load in Conewago Creek by using the continuous water-quality monitors and water-quality samples. Conewago Creek sediment load was approximately 9,900 tons in 2012 and approximately 18,900 tons in 2013, with nearly 80 percent of the sediment load in 2013 contributed by the three largest storm events. Annual total nitrogen loads could not be estimated due to poor model performance. The addition of continued monitoring or a continuously recording nitrate sensor could improve estimates of total nitrogen loads. During 2012 and 2013, phosphorus loads in Conewago Creek were approximately 50,000 pounds in each year. Combining data from one high-flow synoptic sampling with the data from routine sampling revealed how the geology and hydrology interact to result in variable water chemistry throughout the Conewago Creek watershed. The areas above the upstream gage in the headwaters are generally underlain by forested non-carbonate bedrock and are characterized by relatively low nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The more developed, agricultural areas below the upstream site were generally characterized by higher ionic strength waters with higher nutrient and metal concentrations. An analysis of land-use data and SPAtially Referenced Regressions On Watershed (SPARROW) modeling data indicates that manure sources of nitrogen dominate the input of nitrogen to the watershed. Implementation of conservation practices increased in the Conewago Creek watershed during the study period, and while a broad range of practice types were implemented, the most common practices included residue and tillage management, cover crops, nutrient management, terracing, and stream fencing (for animal exclusion or bank restoration). While the implementation of these conservation practices is encouraging, the cumulative effects of these practices probably will not be detected in Conewago Creek water quality for several years. The magnitude of the effects of these conservation practices on water quality in Conewago Creek will depend largely on the extent to which nutrient loading (septic, manure, and commercial fertilizer) and sediment-producing activities are reduced over time. Difficult Run The Difficult Run watershed is a 57.82-mi 2 watershed that drains to the Potomac River. The long-term Difficult Run base-flow index (from 1936 to 2010) was 57.9, indicating that approximately 58 percent of streamflow exited the watershed as base flow and 42 percent as stormflow; however, with continued development and urbanization of the watershed, the base-flow index has decreased to 50 percent during the last 20 years. This base-flow index was less than those of the other watersheds evaluated in this study, likely because the Difficult Run watershed largely is underlain by crystalline piedmont metamorphic rocks and has a greater proportion of impervious urban land cover. A series of cluster and principal components analyses indicated that most of the variability in Difficult Run water quality could be attributed to hydrologic variability and seasonality. Statistically significant positive correlations with flow were observed for turbidity, dissolved oxygen, suspended sediments, ammonium, orthophosphate, iron, and total phosphorus. Statistically significant inverse correlations with flow were observed for water temperature, pH, specific conductance, bicarbonate, calcium, magnesium, nitrate, δ 15 N of nitrate, and silica. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, ammonium, orthophosphate, and δ 15 N of nitrate were higher during the warm season, and dissolved oxygen, nitrate, and manganese were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loading rates. The Difficult Run sediment load was approximately 8,000 tons per year, with greater than 95 percent of the sediment load in the 2013 water year contributed by the seven largest storm events. The total phosphorus load in Difficult Run was approximately 14,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods. The total nitrogen load in Difficult Run is estimated to have been approximately 140,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions than that of phosphorus and strongly affected by base-flow export of nitrogen from the basin. Extensive water-quality monitoring throughout the Difficult Run watershed revealed relatively uniform generation of flow per unit of watershed area, as well as spatial variation in water quality that is strongly related to land-use activities. Elevated nitrate concentrations were observed in a subset of monitoring sites that are inversely correlated with population density and positively correlated to the septic system density within each subwatershed. The majority of the elevated nitrate concentrations for these sites are hypothesized to be caused by nitrate leaching from septic systems, more so than homeowner fertilizer usage among these subwatersheds that have lower population densities than other parts of the watershed. Nitrate isotope data, temporal patterns in the water-quality data, mass-balance computations, and a separate land-use analysis all generally indicate that leachate from septic systems was the likely source of the elevated nitrate. Another group of water-quality sites have relatively low nitrogen concentrations, are located in areas that are served by city sewer lines, and have experienced stream restoration activities. A final group of sites drained the areas with the highest imperviousness and had strongly elevated specific conductance, chloride, and sodium, which were likely caused by a combination of road salting and other anthropogenic sources draining these urbanized areas in the watershed. A fourth group of sites represents a mixture of water sources and had water quality similar to that at the Difficult Run streamgage. Analysis of the nitrate isotope data generally indicates a broad range of composition indicative of mixed natural and anthropogenic nitrogen sources. Implementation of conservation practices increased in the Difficult Run watershed during the study period, and while a broad range of practice types was implemented, the most common practices included stream restoration. While the implementation of these conservation practices is encouraging, the cumulative effect of these practices probably will not be detected in Difficult Run water quality for several years.

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