Item talk:Q55341
From geokb
{
"USGS Publications Warehouse": { "schema": { "@context": "https://schema.org", "@type": "CreativeWork", "additionalType": "USGS Numbered Series", "name": "Hydrology, water-quality, and watershed characteristics in 15 watersheds in Gwinnett County, Georgia, water years 2002\u201320", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "sir20235035", "url": "https://pubs.usgs.gov/publication/sir20235035" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70242838 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.3133/sir20235035", "url": "https://doi.org/10.3133/sir20235035" }, { "@type": "PropertyValue", "propertyID": "ISSN", "value": "2328-0328; 2328-031X" }, { "@type": "PropertyValue", "propertyID": "ISBN", "value": "978-1-4113-4517-1" } ], "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Scientific Investigations Report" } ], "datePublished": "2023", "dateModified": "2023-05-30", "abstract": "The U.S. Geological Survey, in cooperation with Gwinnett County Department of Water Resources, established the Long-Term Trend Monitoring program in 1996 to monitor and analyze the hydrologic and water-quality conditions in Gwinnett County, Georgia. Gwinnett County is a suburban to urban area northeast of the city of Atlanta in north-central Georgia. The monitoring program currently consists of 15 watersheds ranging in size from 1.3 to about 161 square miles. This report synthesizes watershed characteristics and hydrologic and water-quality monitoring data collected for water years (WYs) 2002\u201320.The 15 study watersheds were characterized for land-surface elevations, average land-surface slopes, septic densities, sanitary sewer densities, and detention pond areas. Temporal patterns in watershed characteristics were determined for land cover (2001\u201319), percent imperviousness (2000\u201320), population density (2000\u201320), and building density (1950\u20132022). In 2001, most of the watersheds had at least 45 percent of their land cover composed of developed land cover groups, and by 2019, at least 59 percent of each watershed was developed. Land cover changes occurred most rapidly between 2004 and 2008 at most watersheds. Percent imperviousness in the study watersheds varied substantially and ranged from 14.75 to 55.13 percent in 2019.Precipitation and runoff were quantified at all study watersheds for WYs 2002\u201320, and the hydrologic cycle was evaluated both annually and seasonally. Several 1-year or longer droughts occurred during this period. Study area precipitation averaged 51.5 inches per year and runoff averaged 22.5 inches per year. Variations in annual runoff were largely determined by annual precipitation but were also dependent upon watershed storage. Runoff varied seasonally because of high evapotranspiration rates in the summer and changes in base flow associated with seasonal changes in watershed storage. Fifty-one percent of runoff in the study area occurred as base flow. Watersheds with higher imperviousness had higher stormflows because of increased surface runoff and lower base flows because of reduced infiltration that recharges watershed storage.Turbidity, water temperature, and specific conductance were continuously measured at each study site. These constituents varied seasonally, diurnally, and with streamflow. A minimum of two base-flow and six stormflow samples were collected per year at each watershed and were analyzed for 21 water-quality constituents (water temperature, laboratory specific conductance, pH, and turbidity, biochemical and chemical oxygen demand, suspended sediments, nutrients, base cations, trace metals, and total dissolved solids). Concentrations of most particulate constituents were approximately one-half or more orders of magnitude higher in stormflow samples than in base-flow samples. Total copper and zinc stormflow concentrations exceeded the national recommended aquatic life criteria for acute conditions to varying degrees.Annual loads and yields were estimated for 12 constituents (which include suspended sediments, nutrients, base cations, trace metals, and total dissolved solids) using a surrogate regression model approach and the Beale load estimator. Loads were typically higher for years with higher runoff. The proportional range of annual loads for total suspended solids, suspended-sediment concentrations, total phosphorus, and total lead, however, were 3.2 to 4.8 times larger than for annual runoff. Higher-than-expected annual sediment loads occurred in the years that also had some of the highest peak flows during the period, indicating that large storms are responsible for much of the sediment transport. Large development projects in proximity to streams also were related to years with high sediment loads. Yields from the Crooked Creek and North Fork Peachtree Creek watersheds were typically among the highest for 8 of the 12 constituents. These watersheds had the two highest amounts of developed medium plus high intensity land cover and the two highest percentages of imperviousness. Moderate to strong correlations were identified between seven of the constituent yields and the percentage of developed medium and high intensity land cover groups. Temporal trends in concentrations and loads were identified for 140 of the 300 possible watershed-time period-constituent combinations. There were substantially more negative than positive temporal trends identified during WYs 2003\u201310, whereas the number of negative and positive temporal trends were similar during WYs 2010\u201320. Measures of sediment transport had the most negative temporal trends. A few watersheds had consistent trends across several constituents; however, these trends did not appear to be associated with temporal changes in development or imperviousness.This study provides a thorough assessment of watershed characteristics, hydrology, and water-quality conditions and trends for the 15 study watersheds and can be used to identify possible factors that affect runoff and water quality and determine changes in water-quality conditions. Watershed managers can use these data and analyses to inform management decisions regarding the designated uses of streams, minimization of flooding, protection of aquatic habitats, and optimization of the effectiveness of best management practices.", "description": "Report: xii, 106 p; Data release; Dataset", "publisher": { "@type": "Organization", "name": "U.S. Geological Survey" }, "author": [ { "@type": "Person", "name": "Aulenbach, Brent T. btaulenb@usgs.gov", "givenName": "Brent T.", "familyName": "Aulenbach", "email": "btaulenb@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0003-2863-1288", "url": "https://orcid.org/0000-0003-2863-1288" }, "affiliation": [ { "@type": "Organization", "name": "South Atlantic Water Science Center", "url": "https://www.usgs.gov/centers/sawsc" }, { "@type": "Organization", "name": "Georgia Water Science Center", "url": "https://www.usgs.gov/centers/sawsc" } ] }, { "@type": "Person", "name": "Henley, Joshua C. jhenley@usgs.gov", "givenName": "Joshua C.", "familyName": "Henley", "email": "jhenley@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-9893-229X", "url": "https://orcid.org/0000-0002-9893-229X" }, "affiliation": [ { "@type": "Organization", "name": "South Atlantic Water Science Center", "url": "https://www.usgs.gov/centers/sawsc" } ] }, { "@type": "Person", "name": "Hopkins, Kristina G. khopkins@usgs.gov", "givenName": "Kristina G.", "familyName": "Hopkins", "email": "khopkins@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0003-1699-9384", "url": "https://orcid.org/0000-0003-1699-9384" }, "affiliation": [ { "@type": "Organization", "name": "Eastern Geographic Science Center", "url": "https://www.usgs.gov/centers/pwrc" }, { "@type": "Organization", "name": "South Atlantic Water Science Center", "url": "https://www.usgs.gov/centers/sawsc" } ] } ], "funder": [ { "@type": "Organization", "name": 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