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At least 1,153 records · Page 64Linked to original sources
USGS2017

Estimated dissolved-solids loads and trends at selected streams in and near the Uinta Basin, Utah, Water Years 1989–2013

The U.S. Geological Survey (USGS), in cooperation with the Colorado River Basin Salinity Control Forum, studied trends in dissolved-solids loads at selected sites in and near the Uinta Basin, Utah. The Uinta Basin study area includes the Duchesne River Basin and the Middle Green River Basin in Utah from below Flaming Gorge Reservoir to the town of Green River. Annual dissolved-solids loads for water years (WY) 1989 through 2013 were estimated for 16 gaging stations in the study area using streamflow and water-quality data from the USGS National Water Information System database. Eight gaging stations that monitored catchments with limited or no agricultural land use (natural subbasins) were used to assess loads from natural sources. Four gaging stations that monitored catchments with agricultural land in the Duchesne River Basin were used to assess loads from agricultural sources. Four other gaging stations were included in the dissolved-solids load and trend analysis to help assess the effects of agricultural areas that drain to the Green River in the Uinta Basin, but outside of the Duchesne River Basin. Estimated mean annual dissolved-solids loads for WY 1989–2013 ranged from 1,520 tons at Lake Fork River above Moon Lake, near Mountain Home, Utah (UT), to 1,760,000 tons at Green River near Green River, UT. The flow-normalized loads at gaging stations upstream of agricultural activities showed no trend or a relatively small change. The largest net change in modeled flow-normalized load was -352,000 tons (a 17.8-percent decrease) at Green River near Green River, UT. Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively. Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively. The flow-normalized dissolved-solids loads estimated at Duchesne River near Randlett, UT, and White River near Watson, UT, decreased by 68,000 and 55,300 tons, or 27.8 and 20.8 percent respectively, when comparing 1989 to 2013. The drainage basins for both rivers have undergone salinity-control projects since the early 1980s to reduce the dissolved-solids load entering the Colorado River. Approximately 19 percent of the net change in flow-normalized load at Green River at Green River, UT, is from changes in load modeled at Duchesne River near Randlett, UT, and 16 percent from changes in load modeled at White River near Watson, UT. The net change in flow-normalized load estimated at Green River near Greendale, UT, for WY 1989–2013 accounts for about 45 percent of the net change estimated at Green River at Green River, UT. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites in the Duchesne River Basin show that 75,400 tons or 44 percent of the load at the Duchesne River near Randlett, UT, gaging station was not accounted for at any of the upstream gages. Most of this unmonitored load is derived from tributary inflow, groundwater discharge, unconsumed irrigation water, and irrigation tail water. A mass balance of WY 1989–2013 flow-normalized loads estimated at sites in the Duchesne River Basin indicates that the flow-normalized load of unmonitored inflow to the Duchesne River between the Myton and Randlett gaging stations decreased by 38 percent. The total net decrease in flow-normalized load calculated for unmonitored inflow in the drainage basin accounts for 94 percent of the decrease in WY 1989–2013 flow-normalized load modeled at the Duchesne River near Randlett, UT, gaging station. Irrigation improvements in the drainage basin have likely contributed to the decrease in flow-normalized load. Reductions in dissolved-solids load estimated by the Natural Resources Conservation Service (NRCS) and the Bureau of Reclamation (Reclamation) from on- and off-farm improvements in the Uinta Basin totaled about 135,000 tons in 2013 (81,900 tons from on-farm improvements and 53,300 tons from off-farm improvements). The reduction in dissolved-solids load resulting from on- and off-farm improvements facilitated by the NRCS and Reclamation in the Price River Basin from 1989 to 2013 was estimated to be 64,800 tons. The amount of sprinkler-irrigated land mapped in the drainage area or subbasin area for a gaging station was used to estimate the reduction in load resulting from the conversion from flood to sprinkler irrigation. Sprinkler-irrigated land mapped in the Uinta Basin totaled 109,630 acres in 2012. Assuming conversion to wheel-line sprinklers, a reduction in dissolved-solids load in the Uinta Basin of 95,800 tons in 2012 was calculated using the sprinkler-irrigation acreage and a pre-salinity-control project dissolved-solids yield of 1.04 tons per acre. A reduction of 72,800 tons in dissolved-solids load from irrigation improvements was determined from sprinkler-irrigated lands in the Ashley Valley and Jensen, Pelican Lake, and Pleasant Valley areas (mapped in 2012); and in the Price River Basin (mapped in 2011). This decrease in dissolved-solids load is 8,800 tons more than the decrease in unmonitored flow-normalized dissolved-solids load (-64,000 tons) determined for the Green River between the Jensen and Green River gaging stations. The net WY 1989–2013 change in flow-normalized dissolved-solids load at the Duchesne River near Randlett, UT, and the Green River between the Jensen and Green River, UT, gaging stations determined from mass-balance calculations was compared to reported reductions in dissolved-solids load from on- and off-farm improvements and estimated reductions in load determined from mapped sprinkler-irrigated areas in the Duchesne River Basin and the area draining to the Green River between the Jensen and Green River gaging stations. The combined NRCS and Reclamation estimates of reduction in dissolved-solids load from on- and off-farm improvements in the study area (200,000 tons) is more than the reduction in load estimated using the acreage with sprinkler improvements (136,000 tons) or the mass-balance of flow-normalized load (132,000 tons).

Utah↗
USGS2018

Nutrient loads in the Lost River and Klamath River Basins, south-central Oregon and northern California, March 2012–March 2015

The U.S. Geological Survey and Bureau of Reclamation collected water-quality data from March 2012 to March 2015 at locations in the Lost River and Klamath River Basins, Oregon, in an effort to characterize water quality and compute a nutrient budget for the Bureau of Reclamation Klamath Reclamation Project. The study described in this report resulted in the following significant findings: Total phosphorus (TP), total nitrogen (TN), 5-day biochemical oxygen demand (BOD5), and 5-day carbonaceous biochemical oxygen demand (CBOD5) loads, calculated using the U.S. Geological Survey LOADEST software package at the upper and lower boundaries of the Klamath Reclamation Project, indicated higher loads at the upper boundary on the southern end of Upper Klamath Lake upstream of the Bureau of Reclamation A Canal diversion compared to the lower boundary on the Klamath River downstream of Keno Dam. Accounting for the diversion of loads down A Canal, BOD5 and CBOD5 loads decreased between these two sites during irrigation season, indicating that the Klamath Reclamation Project is not a large source of oxygen-demanding material and that much of the oxygen demand at study site FMT, the northern boundary of the study area, has been expressed by the time the same water passes through site KRK, the southern boundary of the study area. An evaluation of the nutrient balance along the Klamath River flowpath from sites FMT to KRK indicated that, during irrigation season in the 3 years of the study period (March 2012–March 2015), more loads of TP, TN, BOD5, and CBOD5 were being diverted from the Klamath River than were being added to the Klamath River from the combination of Klamath Straits Drain, regulated point sources along the Klamath River, and internal loading from the bottom sediments in the river. By contrast, during non-irrigation seasons, more loads were added to the Klamath River than were diverted through Ady and North Canals, and this difference primarily was due to additional loads to the river from the Lost River Diversion Channel. At the Lost River Diversion Channel, BOD5 loads were higher during irrigation season than non-irrigation season in all three study years owing to the high concentrations of oxygen-demanding cyanobacterial biomass from the seasonal blooms of Aphanizomenon flos-aquae in the Klamath River and Upper Klamath Lake. The difference between the two seasons was particularly large in years 2 and 3, when the low flows of these two drought years resulted in smaller nonirrigation period loads than in year 1. CBOD5 loads also were higher during irrigation season in years 2 and 3 than during non-irrigation season, indicating that the largest oxygen demand was coming from senescence of Aphanizomenon flos-aquae cells that are present in the Klamath River during the summer. However, during irrigation season in year 1, CBOD5 loads were lower than in the non-irrigation season, which may indicate that at times high concentrations of ammonia or cellular organic nitrogen leaving Upper Klamath Lake contribute a large nitrogenous oxygen demand as well. The smallest loads were computed for the farthest upstream sites in the Lost River Basin, suggesting that the upper Lost River Basin does not contribute substantial loads of TP, TN, BOD5, and CBOD5 to the Klamath Reclamation Project. Median concentrations of BOD5 and CBOD5 were lowest among the upper Lost River Basin sites and highest at site PPD (however, this comparison is based on only four samples collected at site PPD over the 3-year study). Median concentrations of BOD5 and CBOD5 also were elevated at sites KSDH (6.60 and 4.70 milligrams per liter [mg/L], respectively) and KSD97 (4.47 and 3.45 mg/L, respectively). The highest maximum BOD5 and CBOD5 concentrations were reported at the Lost River Diversion Channel (39.0 and 26.5 mg/L, respectively) when water was flowing from the Klamath River toward the Klamath Reclamation Project, and site FMT (25.0 and 23.9 mg/L, respectively), the study site at the southern end of Upper Klamath Lake. Carbonaceous oxygen demand, as represented by CBOD5, typically dominated the composition of the samples at all sites. The highest concentrations of dissolved organic carbon were present at sites KSDH (the headworks of Klamath Straits Drain) and KSD97 (Klamath Straits drain before it enters the Klamath River), and PPD (outlet of Tule Lake). Median concentrations of TN and TP at the upper Lost River Basin sites in years 1 and 2 were variable, but site MCRV showed a smaller range of values in those years compared to the other upper Lost River Basins sites, and an overall lower median concentration during irrigation seasons in years 1 and 2, suggesting that Gerber Reservoir does not contribute high concentrations of nutrients to the Lost River during irrigation season. Total Maximum Daily Load (TMDL) load allocations for TP and TN in Klamath Straits Drain were exceeded in all three study years. BOD5 load allocations were exceeded in years 1 and 2, but not year 3. TMDL load allocations for TP were exceeded in the Lost River Diversion Channel for all 3 years. Load allocations for TN were exceeded in year 1, but not in years 2 and 3. BOD5 loads were less than the TMDL load allocation for all three study years. The dearth of samples collected at the Klamath Straits Drain just downstream of the Lower Klamath National Wildlife Refuge did not allow for direct assessment of the Klamath Straits Drain acting as a nutrient source or sink. TP, TN, BOD5, and CBOD5 loads estimated during the study period likely were smaller than long-term average conditions because of persistent drought conditions in the Upper Klamath Basin. The study results, therefore, fail to characterize loads from the Klamath Reclamation Project to the Klamath River that could be present in typical years, and suggest the need for load assessments during average or aboveaverage streamflow years.

California, Oregon↗
USGS2018

Hydrology-driven chemical loads transported by the Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–17

The sediments in the Lower Duwamish Waterway Superfund site in Seattle, Washington, are contaminated with chemicals including metals such as arsenic, polychlorinated biphenyls (PCBs), carcinogenic polycyclic aromatic hydrocarbons (cPAHs), and dioxins/furans from decades of intense anthropogenic activities. The U.S. Geological Survey, in cooperation with the Washington State Department of Ecology, collected new data from 2013 to 2017 to estimate sediment and chemical loads transported by the Green/Duwamish River to the Lower Duwamish Waterway Superfund site (the final 8-kilometer reach of the river) in support of sediment remediation within the site. Chemical loads were calculated as the product of river suspended-sediment loads and suspended sediment-bound chemical concentrations measured at river kilometer 16.7. Using four different approaches, annual suspended sediment-bound chemical load estimates transported by the river to the Lower Duwamish Waterway were in the range of 1,120–1,470 kilograms arsenic, 2,810–8,200 grams (g) toxic equivalent cPAHs, 205–407 milligrams toxic equivalent dioxins/furans, and 340–1,180 g PCBs. Storm events contributed a disproportionately large amount of the load of anthropogenic organic compounds such as cPAHs (54 percent), dioxins/furans (44 percent), and PCBs (52 percent) as compared to overall time (17 percent). Chemical concentrations and load estimates often were underestimated using results from unfiltered water analysis only, especially in samples with high suspended-sediment concentrations and for hydrophobic organic chemicals such as cPAHs that prefer to sorb to particulates and are at low concentrations near or below the analytical limits of water methods. For metals and PCBs, the dissolved concentration was relatively low and consistent between sampling events, whereas the suspended sediment-bound chemical concentrations contributed most of the chemical concentration in the water column during periods of high river suspended-sediment concentrations. However, the dissolved fraction, on average, contributed more than one-third of the estimated total chemical load in the river system for arsenic and PCBs, even given the hydrophobic nature of the chemicals. These results suggest that the sum of the chemical concentrations measured on two separate fractions—the particulate fraction and the dissolved fraction—more fully represents the total chemical concentration as compared to analysis of an unfiltered water sample, especially in samples with high suspended-sediment concentrations. Most of the suspended-sediment load (97 percent) and sediment-bound chemical load (92–94 percent) occurred during the wet winter half of the year from October 15 to April 14. However, the highest sediment-bound chemical concentrations often occurred during short intense storms or “first flush” autumn runoff events during the dry summer half of the year from April 15 to October 14. Because of the highly variable and dynamic river system characteristics (including precipitation, discharge, sediment concentration, and tidal fluctuations), it is critical to characterize the occurrence, frequency, concentrations, and loads during extreme conditions (for example, when the river is affected by storm-derived runoff) rather than time-averaged conditions. These short extreme events have a high potential for acute effects on ecological and human health, and may have a great influence on the effectiveness of the sediment remediation activities that are underway in the Lower Duwamish Waterway.

Washington↗
USGS2019

Climate, streamflow, and lake-level trends in the Great Lakes Basin of the United States and Canada, water years 1960–2015

Water levels in the Great Lakes fluctuate substantially because of complex interactions among inputs (precipitation and streamflow), outputs (evaporation and outflow), and other factors. This report by the U.S. Geological Survey in cooperation with the Great Lakes Restoration Initiative was completed to describe trends in climate, streamflow, lake levels, and major water-budget components within the Great Lakes Basin for water years (WYs) 1960–2015 (study period). Resulting trends are applicable only to the study period and should not be considered indicative of longer-term trends. Analyses of climate trends used monthly data from the Parameter-elevation Regressions on Independent Slopes Model, which are available only for the United States. Trend tests were completed for annual and seasonal time series of monthly means for total precipitation, daily minimum air temperature ( T min ), and daily maximum air temperature ( T max ). Statistical significance for all time-trend tests (climate, streamflow, and lake levels) was determined using the Mann‑Kendall test for probability values less than or equal to 0.10. Trend analyses were completed without adjustments for serial correlation; however, a modified Mann-Kendall test was subsequently used to examine potential effects of short-term persistence in time-series data. Effects of short-term persistence were considered inconsequential for climate data and minor for streamflow data; however, the presence of short-term persistence in water-budget components had more substantial effects on trend analyses. Spatial distributions of trends in climatic data for WYs 1960–2015 for the U.S. part of the Great Lakes Basin (land only) indicate (1) generally ubiquitous upward trends in T min and (2) a sharp transition from neutral or downward trends in precipitation northwest of Lake Michigan to generally upward trends east of Lake Michigan. Trends in T max were not statistically significant. Analyses of annual climatic data aggregated for the U.S. land part of the Great Lakes Basin indicated statistically significant upward trends for precipitation and T min , and similar statistically significant trends existed for all the individual lake subbasins except Lake Superior. Of 103 U.S. Geological Survey streamgages analyzed for streamflow trends, 71 had significant annual trends (54 upward and 17 downward). Downward trends in annual streamflow are concentrated northwest of Lake Michigan (16 streamgages), and upward trends are concentrated east of Lake Michigan (53 streamgages). Of the 71 streamgages with significant annual trends, 70 had at least one season with a significant trend that matched the annual trend direction. Of 35 Environment and Climate Change Canada streamgages analyzed, 22 had significant upward trends in annual streamflow, and all but 1 of these 22 had at least one season with a significant upward trend. None of the Environment and Climate Change Canada streamgages had significant downward annual trends, and only one had a significant downward seasonal trend. Trends in lake levels and several major water-budget components affecting lake levels were analyzed for the study period. Significant downward trends in lake level and outflow for Lake Superior are driven primarily by low lake levels and outflows during WYs 1998–2014. A significant downward trend in runoff from the contributing drainage area also is indicated, which is consistent with numerous streamgages northwest of Lake Michigan with significant downward trends in annual streamflow. A significant upward trend in annual overlake evaporation also is indicated, which is consistent with the spatially distributed upward trends in annual T min . The sum of overlake precipitation and runoff from the contributing drainage area for each of the Great Lakes, less overlake evaporation, composes a variable called net basin supply (NBS). A significant downward trend in NBS is indicated for Lake Superior, which is consistent with significant trends for individual components of runoff (downward) and evaporation (upward) that contributed to a significant downward trend for lake outflow. Statistically significant upward trends in NBS for Lake Saint Clair and Lake Ontario offset the downward trend for Lake Superior and combine with nonsignificant upward trends in NBS for Lakes Michigan and Huron and Lake Erie to produce a neutral trend in NBS for the basin. A predictable pattern in monthly mean lake levels is noted for Lake Superior, with the minimum for each year usually during or near March and the maximum commonly during or near September or October. When an October lake level is in a period of substantial decline, potential for an ensuing short-term period of below-mean lake levels is enhanced. Downstream from Lake Superior, monthly lake levels have sawtooth patterns that somewhat resemble those for Lake Superior but with decreased predictability in timing. Similar to Lake Superior, Lakes Michigan and Huron, Lake Saint Clair, and Lake Erie all have a prolonged period of low lake levels around WYs 1998–2014; however, a significant downward trend is indicated only for Lakes Michigan and Huron. All these lakes also have a period of low lake levels before about WY 1968, when minimum lake levels were lower than during WYs 1998–2014. The significant downward trend of outflow from Lake Superior is carried downstream into Lakes Michigan and Huron; however, trends in outflow from the next three lakes downstream (Lakes Saint Clair, Erie, and Ontario) are offset by increased precipitation and runoff and are not significant.

Scientific Investigations Report↗
USGS2019

Groundwater/surface-water interactions along Ellerbe Creek in Durham, North Carolina, 2016–18

An assessment of groundwater/surface-water interactions along Ellerbe Creek, a major tributary to upper Falls Lake in Durham County, North Carolina, was conducted from July 2016 to March 2018 to determine if groundwater is a likely source of elevated nitrate input to the stream. Groundwater/surface-water interactions were characterized by synoptic streamflow measurements, groundwater-level monitoring, hydrograph-separation methods, and a continuous streambed temperature survey to aid in the collection and interpretation of water-quality data. A streamflow gain-loss survey identified gaining and losing reaches within the stream and found that surface-water inflow, including that from a treated wastewater outfall, provided much of the streamflow gain within the study reach. Through the use of two hydrograph-separation methods, base flow for the Ellerbe Creek study reach was estimated to be between 14.0 and 17.7 cubic feet per second during the study period, contributing up to 57 percent of mean streamflow, with the remaining contributions coming from surface runoff to the stream. The effluent discharge accounted for most of the estimated base-flow contribution to the stream below the North Durham Water Reclamation Facility outfall. Hydraulic gradients within the groundwater were determined to flow upward and toward the stream during base-flow conditions and reverse during storm events. Nitrate concentrations ranged from below the method detection level to 2.69 milligrams per liter, with the highest concentrations just downstream from the wastewater outfall. Bank seeps and groundwater samples had lower nitrate concentrations than surface-water samples, ranging from below the method detection level to 1.04 milligrams per liter, with the highest concentration at the piezometer within the stream. Results indicate that groundwater is not a large component of streamflow within Ellerbe Creek nor a major source of nitrate within the study reach.

North Carolina↗
USGS2019

A hydrogeomorphic classification of connectivity of large rivers of the Upper Midwest, United States

River connectivity is defined as the water-mediated exchange of matter, energy, and biota between different elements of the riverine landscape. Connectivity is an especially important concept in large-river corridors (channel plus floodplain ) because large rivers integrate fluxes of water, sediment, nutrients, contaminants, and other transported constituents emanating from large contributing drainage basins, and thereby contribute to the complexity of large-river ecosystems. Large rivers are also highly valued for socioeconomic goods and services, which has led to historical fragmentation, lack of connectivity, and contentiousness about best policies for managing large-river corridors. The classification is intended to serve as a template for understanding geographic variation in large rivers within the Midwest, to aid in designing scientific studies of large river ecological processes, and to match specific river-management and restoration objectives to specific river reaches. The focus of the classification is on measuring river connectivity from available hydrological and geomorphic data. We provide a multiscale assessment and classification for segments of 15 rivers that meet various criteria for largeness. All rivers are tributaries to the Mississippi River system. The 11,600 kilometers (km) that qualified as large were classified by major alterations (unimpounded, navigation pools, storage reservoir) and additionally assessed for their network continuity as a function of numbers and heights of dams. Among the 15 rivers, 55 percent of segment length was unimpounded, 30 percent was in navigation pools, and 15 percent was under storage reservoirs. Assessment of network longitudinal connectivity among river segments documented the contrast between river segments with low-head navigation dams (Upper Mississippi, Illinois, Ohio, Green, and Cumberland Rivers) and those segments with high-head dams (mostly in the Upper Missouri River). The longest unimpounded river pathways exist in the Lower Missouri River and connected tributaries where nearly 1,300 km of the Missouri River connect to an additional 1,800 km of the Middle and Lower Mississippi Rivers. At our finest scale, we present a statistically based, component classification based on 10-km segments. Cluster analysis of hydrologic variables from 66 streamflow-gaging stations yielded 5 clusters calculated from 5 ecohydrological metrics related to lateral connectivity with the floodplain. A separate cluster analysis of 5 geomorphologic variables associated with each of the 1,172 river segments also yielded 5 clusters. When the hydrologic variables were associated with corresponding segments, the cluster analysis yielded 8 hydrogeomorphic clusters that could be explained in terms of their contribution to floodplain connectivity. Although the clusters overlap considerably in principal component space, the resulting hydrogeomorphic classification leads to a physically reasonable distribution of classes. The resulting classification is intended to increase geographic awareness of the range of variation of connectivity potential among large rivers of the Upper Midwest, to increase understanding of the extent of alteration of these rivers, and potentially to serve as a template for stratifying study designs of large-river corridor ecological processes.

Colorado, Illinois, Indiana, Iowa, Kansas, Kentuck↗
USGS2020

Quality of pesticide data for groundwater analyzed for the National Water-Quality Assessment Project, 2013–18

The National Water-Quality Assessment (NAWQA) Project of the U.S. Geological Survey (USGS) submitted nearly 1,900 samples collected from groundwater sites across the United States in 2013–18 for analysis of 225 pesticide compounds (pesticides and pesticide degradates, hereafter referred to as “pesticides”) by USGS National Water Quality Laboratory schedule 2437 (S2437). For the associated NAWQA study of pesticide occurrence and concentration in groundwater, and for other studies using pesticide results determined by S2437, it is necessary to assess the ability of reported results to meet data-quality requirements that will allow study objectives to be achieved. This assessment of the quality of S2437 results reported in 2013–18 examined data from field and laboratory quality-control samples, along with third-party performance assessment samples, to estimate bias and variability and to identify their potential sources, with an emphasis on implications for the interpretation of pesticide data for groundwater. Results indicate that measurements produced by the S2437 method for most pesticides have bias and variability that would be considered acceptable for many interpretative studies, which could therefore use the results without qualification or censoring. However, the reported data for a subset of pesticides have the potential for unacceptable contamination bias, high or low recovery bias, or high variability as a consequence of method performance and (or) nonlaboratory factors that could preclude their use for certain common objectives or could necessitate adjustment or qualification to meet those objectives. Based on data for laboratory blanks, censoring of some detections for a subset of pesticides reported by the laboratory in environmental samples might be necessary or desirable to avoid an unacceptably high likelihood of a false-positive result caused by laboratory contamination. The 90-percent upper confidence limit for the 95th percentile of laboratory blank concentration equals or exceeds the minimum reported groundwater concentration in at least 1 water year for 28 pesticides. During at least 1 water year, this upper confidence limit exceeds the maximum laboratory detection limit for 17 pesticides and exceeds the maximum laboratory reporting limit for 3 pesticides (ametryn, atrazine, and diazinon). The level of contamination indicated by this upper confidence limit should not substantially affect the suitability of reported environmental concentrations for any compound for comparison with corresponding human-health benchmarks. Despite being subjected to the same laboratory processes as laboratory blanks, field blanks indicated little evidence of contamination bias. This observation could largely be the consequence of data-reporting practices, which utilize detections in laboratory blanks to censor results in associated field samples (including blanks and environmental samples) when relative concentrations indicate that a result could have a substantial contribution from laboratory contamination. Laboratory censoring appears likely to reduce the risk of false-positive results in environmental samples below the level that laboratory blank results alone would imply. Whereas data available for third-party blind blank samples analyzed in 2018 indicate that only propoxur had any false-positive results, data for pesticides that were not spiked into blind spike samples analyzed in 2013–18 indicate that the false-positive rates for 31 pesticides exceeded 1 percent when considering only detections reported at concentrations greater than the maximum detection limit. Although about half of these pesticides lack substantial supporting evidence of contamination bias based on laboratory blank or field blank detections, indicating that spiking issues or degradation of parent compounds within the spiked samples might be a contributing factor to some false-positive results, these results indicate the need to closely examine detections reported for some pesticides in environmental samples analyzed during a similar period for possible contributions from contamination bias. Data for blind spike samples that were spiked at concentrations above the maximum reporting limit indicate that false-negative rates for eight pesticides exceed 10 percent; substantial low bias could affect results reported for these pesticides in environmental samples analyzed during a similar period. Data for laboratory reagent spikes, which measure recovery of pesticides in blank water, show little evidence for unacceptable recovery bias for S2437 pesticides. However, field matrix spikes, which measure recovery of pesticides in environmental matrices, indicate that degradation and (or) matrix effects could result in moderate to substantial low bias for groundwater results for several pesticides. Low bias could cause some reported concentrations to be categorized as being below a benchmark when the actual concentration in groundwater is greater than the benchmark. Occurrence and concentrations in groundwater could be substantially underrepresented for six pesticides with benchmarks (1H-1,2,4-triazole, asulam, bifenthrin, cis-permethrin, fenbutatin oxide, and naled) that have median recoveries between zero and 50 percent in field matrix spikes. Two compounds (didealkylatrazine and 2-hydroxy-6-ethylamino-4-amino-s-triazine) have median recoveries near or greater than 150 percent in field matrix spikes, indicating a substantial high bias. Plots of data for all spike types show clear changes in the typical recovery with time for some pesticides, which would require further examination for evaluation of temporal trends in environmental concentrations. Data for laboratory reagent spikes indicate that nearly all S2437 pesticides have acceptable variability resulting from random measurement error. Only two compounds (fenbutatin oxide and naled) have F-pseudosigma values greater than 30 percent for recovery, which implies the potential for relatively high variability in reported concentrations and could affect comparison of concentrations to benchmarks and determination of whether concentrations for samples collected at separate locations or times are truly different with a specified level of confidence. Data for third-party blind spike samples show relatively high variability for a greater number of pesticides, although these results likely reflect the influence of degradation and (or) differences in the magnitude and variability of concentrations used for blind spikes relative to laboratory reagent spikes. Detailed analysis of variability using field replicate data is possible for only 12 pesticides on S2437; low variability in analyte detection and concentration is indicated for most of these pesticides in groundwater.

Scientific Investigations Report↗
USGS2021

Workflow for using unmanned aircraft systems and traditional geospatial data to delineate agricultural drainage tiles at edge-of-field sites

Managing nutrient and sediment runoff from fields that drain to the Great Lakes is key to mitigating harmful algal blooms. Implementation of best management practices on agricultural land is considered a critical step to improving water quality in these streams, however the effect of these best management practices is difficult to quantify. The purpose of this study was to use a suite of high-resolution imagery acquired with unmanned aircraft systems (including a combination of visible, multispectral, and thermal cameras) to better characterize edge-of-field (EOF) sites in Michigan and Wisconsin that are monitored in cooperation with the Great Lakes Restoration Initiative. This high-resolution imagery (2.5–12-centimeter ground resolution) was used to delineate artificial subsurface drainage (tile-drain) networks and surface water flow paths that indicate contributing areas (that is, all area that drains to a monitored point) at these EOF sites, providing better characterization of each study site. Contributing areas for these sites ranged from 2.86 to 5.07 hectares and, among the sites, tile drains were identified as those that followed soil properties and those that were more densely patterned networks. These surveys also indicated that the contributing area monitored at the EOF sites may cross field boundaries and is not always coincident with the area underlain by subsurface drainage.

Indiana, Michigan, Ohio, Wisconsin↗
USGS2021

Using microbial source tracking to identify fecal contamination sources in an embayment in Hempstead Harbor on Long Island, New York

The U.S. Geological Survey worked collaboratively with the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering Hempstead Harbor, an embayment on the northern shore of Nassau County, Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the harbor and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, surrounding land use, and additional water-quality data (including nutrient and stable isotopes of nitrate analyses) for the location where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment. Our analysis revealed an abundance of human and canine fecal contamination throughout the Hempstead Harbor landscape and that water from municipal separate storm sewer system conveyances was the most likely transport mechanism of this fecal contamination. Resuspension of bed sediment may contribute to fecal contamination in the harbor, but more targeted analyses are needed to support this finding. There was little evidence of groundwater-contributing fecal bacteria by direct discharge from the subsurface. A classification scheme was developed to convey the degree of fecal contamination to stakeholders and resource managers. Based on this classification scheme, the culvert at Glenwood Road and the outfall and the spillway at Skillman Street were identified as locations that contribute substantial fecal contamination to Hempstead Harbor.

New York↗
USGS2021

Factors affecting uncertainty of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data, 1985–2015—Evaluation of information sources, estimation methods, and data variability

The U.S. Geological Survey (USGS) Water-Use Program is responsible for compiling and disseminating the Nation's water-use data. Working in cooperation with local, State, and Federal agencies, the USGS has collected and published national water-use estimates every 5 years, beginning in 1950. These water-use data may vary because of actual changes in water use, because of changes in estimation methods, or because of errors. Comparison and interpretation of these data is difficult without first determining the factors that contribute to data variability. This report describes factors that may affect data quality and documents ways to investigate the variability of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data for the 1985–2015 compilations. The USGS produces national water-use estimates for various categories of water use for every county in the United States. Knowledge about the sources of data for county estimates is important because factors such as estimation methodology and reporting affect data uncertainty Determination of meaningful patterns and trends in the data are contingent on the use of consistent methodology throughout the period of interest. With the many ways that water-use data have been collected, assembled, and estimated, multiple factors likely contribute to data uncertainty, Data used to produce these estimates may be furnished from agencies that collect information from entities who report water use; gaps in reported data are typically estimated to achieve a comprehensive county estimate. For example, public supply and thermoelectric category data are based primarily on furnished site-specific data; whereas crop irrigation is often furnished or estimated at the county scale. Public supply deliveries for domestic use and self-supplied domestic withdrawals are most often estimated by USGS personnel using per capita use rate coefficients. Irrigation may be estimated using crop water requirements, application rates, or other soil water balance methods when furnished reported data are not available. Rates, percentages, medians, and interquartile ranges were used to investigate variability in the water-use data among States, regions, and years. The purposes of these evaluations were to (1) identify extreme values that may reflect changes in information sources, estimation methods, or errors; (2) indicate areas of variable or consistent values that are unexpected; and (3) indicate areas where values change because of local climate or other factors. Where factors are identified that contribute to data variability, such as a change in methodology, additional work could determine uncertainty because of these factors. These evaluations identified the availability of information that is needed to address data limitations. Factors such as estimation methodology affect data quality. Some updates to method codes assigned in 2015 and assignment of method codes to earlier compilation datasets for all categories would provide much needed metadata for users of the data. Improvements in data documentation describing sources of information and estimation methods and additional metadata information from agencies and entities that furnish water-use data, would enable a more complete understanding and depiction of water-use patterns and trends. Additional metadata are needed for users of the data to better understand the water-use data and interpret changes in water use across the United States and with time.

Scientific Investigations Report↗
USGS2021

Evaluation of hydrologic simulation models for fields with subsurface drainage to mitigated wetlands in Barnes, Dickey, and Sargent Counties, North Dakota

Proper identification of wetlands, along with a better understanding of the hydrology of mitigated wetlands, is needed to assist with conservation efforts aimed at maintaining the productivity and ecological function (wetland mitigation) of agricultural lands. The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, completed a study to evaluate two models for simulating hydrologic conditions in fields with subsurface drainage to mitigated wetlands at several sites in North Dakota. These two models were evaluated as possible tools for water resource managers to use for designing wetland mitigation projects in the area in the future. The Soil-Plant-Atmosphere-Water (SPAW) model simulates the daily hydrologic water budgets of agricultural landscapes by two linked routines, one for farm fields (field hydrology) and one for impoundments such as wetlands and ponds (pond model). The DRAINMOD model was used in conjunction with the SPAW model because although the SPAW model can be used to simulate the hydrology of small drainage basins containing wetlands, the SPAW model does not contain routines to simulate drainage, either subsurface drainage or surface (drainage ditches), that can directly affect the wetland hydrology. The wetlands in the study areas in this report are all downstream from and adjacent to drained agricultural fields. SPAW and DRAINMOD models were developed and calibrated at three study areas (study areas B, D, and S) to evaluate how the models simulated field-scale hydrologic characteristics and the water balance in wetlands from January 1, 2003, through December 31, 2018. The SPAW model developed for study area B included five modeled fields in the field hydrology portion of SPAW that contributed inflow to one wetland simulated in the pond model portion of SPAW. Simulated wetland water depths were most similar to water depths measured at site BWET1, with an absolute mean error of 0.10 foot and a root mean square error of 0.14 foot. Site BWET2 had slightly larger errors, with an absolute mean error of 0.22 foot and a root mean square error of 0.28 foot. Simulated water depths were similar to the pattern of measured water depths at BWET1 and BWET2 from about mid-April 2018 through about mid-September 2018, but overpredicted water depths in the fall from about mid-September 2018 through about mid-October 2018. The SPAW model developed for study area D included six modeled fields in the field hydrology portion of SPAW that contributed inflow to five wetlands connected in series in the pond model portion of SPAW. Simulated water depths compared relatively well to water depths in the five wetlands, with the absolute mean error ranging from 0.17 foot (DWET1) to 0.39 foot (DWET2), and the root mean square error ranging from 0.28 foot (DWET1) to 0.56 foot (DWET5). The SPAW model developed for study area S included one modeled field in the field hydrology portion of SPAW that contributed inflow to one wetland in the pond model portion of SPAW. Among the SPAW models developed for the three study areas, the model for study area S had the best comparison between simulated and measured water depths, with an absolute mean error of 0.06 foot and a root mean square error of 0.10 foot. DRAINMOD models were developed and calibrated at the three study areas and provided inflow from subsurface drainage discharge to the SPAW models for simulating water levels in wetlands in the study areas. The calibrated DRAINMOD model for study area B showed the variability of hydrologic processes in the modeled field throughout the wide range of hydrologic conditions from January 1, 2003, through December 31, 2018. In general, the discharge through the modeled subsurface drainage system was in the spring and early summer (April through June) most years, with little to no discharge later in the year. Although the subsurface drainage system in study area D was the most complex among the three study areas and was simplified into a uniform system within DRAINMOD, simulated water table depths at study area D correlated better to measured water table depths compared to results from the model applications at the other two study areas. Simulated water table depths had an absolute mean error of 0.30 foot and root mean square error of 0.37 foot at site DGW1 and an absolute mean error of 0.29 foot and a root mean square error of 0.34 foot at site DGW2. Although the subsurface drainage system in study area S was the simplest and the modeled field was the smallest among the three study areas, simulated water table depths at study area S did not correlate as well to measured water table depths compared to results from the model applications at the other two study areas. The SPAW and DRAINMOD model applications at the three study areas in southeast North Dakota adequately simulated the hydrologic processes for fields with subsurface drainage that are connected to adjacent wetlands. However, more measured data would be needed to fully evaluate the models throughout the range of possible climatic conditions.

North Dakota↗
USGS2022

Using microbial source tracking to identify contamination sources in Port Jefferson Harbor, Setauket Harbor, and Conscience Bay on Long Island, New York

The U.S. Geological Survey worked in cooperation with the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering Port Jefferson Harbor, Setauket Harbor, and Conscience Bay, an embayment complex on the northern shore of Suffolk County, Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the harbor and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, and surrounding land use where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment. Our analysis revealed that the most substantial source of fecal contamination to the Port Jefferson Harbor complex was discharge from sites draining ponds and wetlands, particularly during the summer months. Fecal coliform bacteria at sites where ponds and wetlands drain are increased by stormwater runoff, which is another substantial source of fecal contamination. Human markers, likely originating from the outfall of the Port Jefferson sewage treatment plant, were found at least once in every sample collected within Port Jefferson Harbor; however, fecal coliform concentrations were low, indicating that the sewage treatment plant is not a likely source of fecal contamination to the embayment. Canine markers detected in Conscience Bay were associated with high fecal coliform, particularly in wet summer samples. Waterfowl markers were most often detected in source water for Port Jefferson Harbor, but in Conscience Bay, waterfowl was frequently detected within the bay itself. Resuspension of bed sediment may contribute to fecal contamination in the harbor, but more targeted analyses are needed to support this finding. There was little evidence of groundwater-contributing fecal bacteria by direct discharge from the subsurface. A classification scheme was developed to convey the degree of fecal contamination to stakeholders and resource managers. Based on this classification scheme, the Culvert North of State Route 25A, Culvert North of Shore Road, Old Mill Creek Culvert, and Mill Pond Culvert to Conscience Bay sites were identified as locations that contribute substantial fecal contamination to the Port Jefferson Harbor complex.

New York↗
USGS2023

Nutrient and suspended-sediment concentrations, flux, and yields in the Galena River, Illinois, 2019–21

Two stations on the Galena River in Illinois were monitored for nitrogen, phosphorus, and suspended sediment from 2019 to 2021 to determine physiochemical properties and constituent concentrations, flux, and yields. This information could aide in the management and understanding of the Galena River and the contributions from the intervening 58-square-mile study area watershed. Constituent concentrations were characteristic for contemporary midwestern agricultural watersheds and did not display any notable high or low values. Concentrations of nitrogen were generally higher at the upstream station, whereas concentrations of phosphorus and suspended sediment were generally higher at the downstream station. Decreases in nutrient concentrations were observed at both stations during the study period, but there was no appreciable pattern in suspended-sediment concentrations. Constituent fluxes, particularly nitrogen, were higher at the downstream station, whereas fluxes of phosphorus and suspended sediment were higher at the upstream station during several high-flow events, indicating substantial contribution of particulate material upstream from the study area and potential sequestration within the study area reach of the Galena River. For all constituents, yields were typically higher at the upstream station during periods of increased streamflow and lower at the upstream station during periods of reduced streamflow. These data indicate that the constituent contributions are greater from within the study area than from the watershed upstream from the study area during periods of normal to low streamflow.

Illinois↗
USGS2024

Nitrogen load estimates from six nonpoint sources on Long Island, New York, from 1900 to 2019

Estimates of nitrogen loading from nonpoint sources on Long Island, New York, at or just below the land surface, are essential for assessing the current and future effects of nitrogen on the island’s drinking water and fresh and marine surface receiving waters. Annual estimates of nitrogen loading for the 120 years from 1900 to 2019 for major nonpoint nitrogen sources—septic systems, residential fertilizer, agricultural fertilizer, livestock waste, pet waste, and atmospheric deposition—were made by using a geographic information system to analyze, visualize, and process data sources, and format output data. This analysis provided spatial and temporal estimates of nitrogen loading derived from each nonpoint source at a 500- by 500-foot gridded resolution and represents the total mass of nitrogen applied on, or just below, the land surface annually from 1900 to 2019. These mass estimates are considered unattenuated as they do not reflect the various mechanisms of nitrogen loss, such as plant uptake, overland runoff, and chemical transformations in the soil and unsaturated zones that likely reduce the amount of nitrogen that reaches the water table. Island-wide and countywide summaries of the estimated nitrogen loading were analyzed to describe the long-term average nitrogen totals and the contributions from the six nonpoint sources. The island-wide average annual nitrogen load from 1900 to 2019 was 14.92 million kilograms (Mkg) nitrogen, which represents the aggregate of individual contributions from septic systems (4.15 Mkg), residential fertilizer (3.28 Mkg), agricultural fertilizer (3.19 Mkg), livestock waste (1.22 Mkg), pet waste (0.98 Mkg), and atmospheric deposition (2.10 Mkg). The island-wide average annual nitrogen load, normalized by area, was 4,100 kilograms nitrogen per square kilometer (kg N/km 2 ), which represents the aggregate of individual contributions from septic systems (1,100 kg N/km 2 ), residential fertilizer (910 kg N/km 2 ), agricultural fertilizer (880 kg N/km 2 ), livestock waste (340 kg N/km 2 ), pet waste (270 kg N/km 2 ), and atmospheric deposition (580 kg N/km 2 ).

New York↗
USGS2025

Evaluating drought risk of the Red River of the North Basin using historical and stochastic streamflow upstream from Emerson, Manitoba

Drought and its effect on streamflow are important to understand because of the potential to adversely affect water supply, agricultural production, and ecological conditions. The Red River of the North Basin in north-central United States and central Canada is susceptible to dry conditions. During an extended drought, streamflow conditions in the Red River of the North may become inadequate to support existing water supply needs in the basin for agriculture, industry, human use, and aquatic life. To understand potential future low-streamflow conditions in the Red River of the North Basin, the U.S. Geological Survey, in cooperation with the International Joint Commission, North Dakota Department of Water Resources, Red River Joint Water Resource District, and Red River Watershed Management Board, developed a water-balance model of the Red River of the North Basin upstream from Emerson, Manitoba, Canada, and coupled the model with stochastic weather inputs to simulate possible future low-streamflow conditions. Historical changes in low-streamflow conditions were characterized across the Red River of the North Basin using multiple change-point analysis for 12 streamgages. Across these stations, significant change-point years in 1943 and 1994 marked increases in the magnitude of low-streamflow conditions. During 1920–2015, conversion of primary land (not affected by human use) to agricultural and secondary land was followed by a conversion from smalls grains to corn and soybeans as the dominant crop type. From land-use analysis, 1940–2000 was determined to have relatively stable land use and therefore was used as the calibration period for the water-balance model. A deterministic water-balance model was developed for the Red River of the North Basin upstream from Emerson, Manitoba. The water-balance model was calibrated with data from 37 U.S. Geological Survey streamgages for 1940–2000 and verified using data for 2001–15. The calibrated water-balance model simulated streamflow distributions that mirrored the seasonal patterns of the observed mean monthly streamflow and the standard deviation of the monthly streamflow data, especially during the fall and winter months when streamflow was lowest. For the verification period, during the low-streamflow months of December through January, the difference between simulated and observed data was similar to the calibration comparison and successfully reproduced seasonal trends in the distribution of streamflow, even when using weather data that were outside the calibration period. To determine the future risk of low-streamflow conditions in the Red River of the North Basin, a block-bootstrap method was used to generate multiple possible future climates. These stochastically generated weather time series were then input to a water-balance model to simulate a distribution of possible streamflows. Three sets of experiments were performed, with each experiment containing a set of scenarios. The first set of experiments from the stochastic streamflow model were designed to investigate how changes in reservoir management would affect the distribution of low streamflow. Relative to scenario 1 (present-day [2023] reservoir operation), scenario 2 (no reservoir operation) shifted the low-streamflow frequency curves downward, reducing the annual minimum monthly streamflow for the Emerson subbasin. Subbasins were defined by the contributing area upstream from a selected streamgage station. Relative to scenario 1, scenario 3 (regulated streamflow with an increased reservoir capacity of 10 percent) shifted the low-streamflow frequency curves upward for the Emerson subbasin. The magnitude of this upward shift, caused by increased reservoir capacity, was lower than the magnitude of the shift caused by the absence of the reservoirs, which indicates that the streamflow was most affected when the reservoirs were first constructed. The second set of experiments from the stochastic streamflow model included two scenarios that were performed to better understand how the Red River of the North Basin responds to long periods of low or high precipitation. The results indicate that the model consistently overestimated streamflow, but the relative change between a wet and dry climate state of simulated streamflow distribution reasonably matched the relative change of historical streamflow. Across the subbasins, the model was most accurate for low-streamflow conditions associated with nonexceedance probabilities between 20 and 40 percent. The third set of experiments from the stochastic streamflow model were done to investigate low-streamflow response across the basin to several drought events. Low-end streamflow was reduced when the basin was exposed to a drought, and the magnitude of the reduction increased with longer or more intense droughts. Compared to the low-intensity drought scenarios, the range of percent reductions (as indicated by the interquartile range) was larger for the high-intensity drought scenarios for all subbasins, and the subbasins of Grand Forks and Emerson had a smaller range of reductions compared to the other three subbasins. The larger drainage area—combined with the large contribution of the Red Lake River and several other Minnesota tributaries that generally experience wetter climate conditions—upstream from the Emerson and Grand Forks subbasins may contribute to the smaller range in reductions under the high intensity scenarios. Comparison of the percent reduction in low-end streamflow among subbasins also indicated that the effects of drought duration and intensity could be cumulative. Combining factors of time and intensity produced a larger reduction in streamflow than when each effect was isolated. The array of drought scenarios can be used to determine how a subbasin would respond to multiple possible future conditions. Based on climate predictions, the drought scenario that best matches a future anticipated drought scenario can be used to estimate a low streamflow response for a given subbasin.

Manitoba, Minnesota, North Dakota↗
USGS2026

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

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

British Columbia, Washington↗
USGS2026

Variability of discharge, nutrients, and Escherichia coli from tile drains in a small agricultural stream, a synoptic study in the School Branch watershed, Hendricks County, Indiana

The U.S. Geological Survey, in cooperation with the Indiana Department of Environmental Management, sampled a 1-mile stream reach of School Branch in Hendricks County, Indiana. Sampling consisted of 24 tile drain sites and surface-water sites both upstream and downstream from the tile drains. This study intended to (1) assess the variability of discharge, nutrients, and Escherichia coli ( E. coli ) among tiles within a stream reach in variable conditions; (2) define how the tiles affect the stream hydrology and water quality; and (3) determine potential management implications. Samples were collected on three dates—round 1 on June 12, 2018, after fertilizer was applied; round 2 on September 11, 2018, in fall harvest conditions; and round 3 on April 16, 2019, before fertilizer was applied—to encompass differing precipitation events, multiple seasons, and field conditions. Sites were sampled for water-quality parameters, dissolved and total nutrients (ammonia, nitrate plus nitrite, total nitrogen, orthophosphate, and total phosphorus), E. coli , and instantaneous discharge. Instantaneous nutrient loads were calculated from tiles and at the upstream and downstream surface-water sites. Nutrient concentrations and instantaneous loads varied depending on the tile and the sampling date. Tiles contributed between 26.5 and 66.0 percent of increased discharge between the surface-water sites. Tiles contributed between 34.7 and 87.4 percent and between 19.7 and 65.9 percent of the increased total nitrogen and phosphorus loads, respectively, for the downstream site relative to the upstream site. Most of the total nitrogen and total phosphorus from the tiles was in the dissolved forms (nitrate plus nitrite and orthophosphate). Surface-water samples had a nitrate plus nitrite to total nitrogen ratio of 71 to 93 percent, with an average of 82 percent; tile samples ranged from 44 to nearly 100 percent, with an average of 91 percent dissolved nitrogen. Surface-water samples had an orthophosphate to total phosphorus ratio of 30 to 65 percent, with an average of 53 percent; tile samples ranged from 32 to nearly 100 percent, with an average of 85 percent dissolved phosphorus. E. coli was detected in all but 5.79 percent of tile and surface-water samples. The E. coli results indicated the possibility of human or animal fecal contamination by way of septic systems leaking or directly linked to the tiles draining into the study area. Consequently, five microbial source tracking samples were collected from the upstream and downstream surface-water sites between August 3, 2021, and May 18, 2022. Human, canine, ruminant, and avian sources of fecal contamination were evaluated. The microbial source tracking samples indicated that human-specific sources are likely consistently contributing to elevated fecal contamination. Differences in discharge, nutrient concentrations, nutrient loads, and E. coli concentrations show that many factors affect how tiles alter the hydrology and water quality of receiving waters. The timing and severity of precipitation events, season, and the antecedent conditions of the field or watershed before sampling can affect the results. Tiles with the largest discharge rate had the most potential effect on the water quality and quantity of the stream. Targeting high-flowing tiles may affect efforts to improve overall water quality.

Indiana↗
USGS2026

Arsenic and isotope concentrations in the lower Platte River valley of eastern Nebraska, early 1970s to 2023

The City of Lincoln, Nebraska, has been monitoring concentrations of arsenic in their source water and evaluating their options for treatment and removal since at least 2002. In 2022, the City of Lincoln, Nebr., with funding assistance from the Nebraska Water Sustainability Fund, began cooperating with the U.S. Geological Survey to examine arsenic concentrations in surface water and groundwater in the lower Platte River valley and the area around City of Lincoln Water System (LWS) well field. Arsenic data collected from the Platte River since 1974 were examined using the “weighted regression on time, discharge, and season” model, which compared the streamflow (also referred to as “discharge”), time of year, and season to estimate concentrations of arsenic. Annual mean arsenic concentrations modeled for more than 49 years at the Platte River at Louisville, Nebr., U.S. Geological Survey streamgage (station 06805500), indicated a significant increasing trend. Arsenic concentrations in the Platte River were seasonal, with the highest concentrations being observed during mid- to late summer. When seasonal patterns and streamflow were combined with arsenic concentrations in the Platte River during low streamflow conditions, groundwater contributions, which can have higher arsenic concentrations, make up a larger portion of the streamflow. Arsenic samples were collected from upstream rivers in 2022 and 2023 and were paired to analyze the arsenic contributions at the U.S. Geological Survey streamgage on the Platte River near Ashland, Nebr. (station 06801000), near the City of Lincoln well field. The arsenic concentrations from the streamgage on the Platte River near Ashland, Nebr., location, were higher than the U.S. Geological Survey streamgage on the Elkhorn River at Waterloo, Nebr. (station 06800500), and significantly lower than at the U.S. Geological Survey streamgage on the Platte River near Leshara, Nebr.(station 06796500), indicating that the Platte River usually contributes a higher concentration of arsenic than does the Elkhorn River as they join near Ashland, Nebr. During 1991–2023, six groundwater monitoring wells were analyzed to identify trends in arsenic concentrations. Two of the six wells had a positive trend during the 33-year period. One monitoring well did not reveal a long-term trend during this period but showed a trend during 2019–23, correlating to a period when the island in the middle of the Platte River was connected to the east bank of the river when manganese reducing conditions were present and groundwater levels were declining in the well. Across all wells the oxidation and reduction (redox) condition during the time of sampling was assessed. Mixed anoxic and (or) oxic redox condition was the most common redox process and the highest sampled arsenic concentrations in monitoring wells were observed in anoxic conditions driven by manganese reduction. Groundwater arsenic concentrations had seasonal variation around the City of Lincoln well field, with higher arsenic concentrations tending to be further south in comparison to samples collected further north. Isotope samples were collected and analyzed in surface water and groundwater around the LWS well field. The samples indicate that the proportion of surface water present in the LWS production wells can be higher in the spring and lower in the summer. With higher arsenic concentrations observed in the stream water during the summer period, the LWS source water can be affected by these elevated arsenic concentrations even though the proportion of surface water is lower.

Nebraska↗