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USGS2003

Probability of detecting elevated concentrations of nitrate in ground water in a six-county area of south-central Idaho

A probability map constructed for this study identified several areas in a six-county region of south-central Idaho with high probabilities of detecting elevated concentrations (greater than 2 milligrams per liter) of nitrate. An increasing proportion of Idaho’s ground water being used for drinking water and large increases in the inputs of nitrogen to ground water in Cassia, Gooding, Jerome, Lincoln, Minidoka, and Twin Falls Counties have prompted concerns about the quality of the resource. The probability map was constructed to assist regulatory and resource agencies in managing land use and protecting water resources. To construct the probability map, hydrogeologic and anthropogenic data were integrated with ground-water quality data in a geographic information system. The resulting data set contained land use, geology, precipitation, soil characteristics, depth to ground water, nitrogen input, and ground-water velocity information for each of the 1,365 samples collected from 1991 to 2001. Logistic regression analysis was used to determine the most statistically significant variables related to the detection of elevated nitrate concentrations. The resulting multivariate probability model showed that ground-water velocity, nitrogen input, precipitation, soil drainage, land use, and depth to ground water were significantly correlated with elevated nitrate concentrations. A subset of the water-quality data set was used to verify these results. Linear regression of the percentage of predicted probabilities of elevated nitrate concentrations and the actual percentage of elevated nitrate concentrations with the model data set and the verification data set both showed good correlations: r-squared values were 0.96 and 0.97, respectively. Statistical comparisons of both data sets showed that ground-water samples containing elevated nitrate concentrations had significantly higher probabilities of detection (p < 0.001) than samples without elevated nitrate concentrations. On the basis of these results, a map identifying the probability of detecting elevated nitrate concentrations was constructed. High-probability areas on the map coincided with regions of agricultural land use and high nitrogen input, except in southern Gooding County and western Jerome County. In these areas, high ground-water velocities representing a predominance of regional ground water resulted in a low probability of detecting elevated nitrate concentrations. Areas of poor prediction tended to be congregated along the transition zone between high and low ground-water velocities in Jerome and Gooding Counties, indicating a mix of regional and recently recharged ground water.

Idaho↗

USGS2003

Simulation of streamflow and water quality in the Christina River subbasin and overview of simulations in other subbasins of the Christina River Basin, Pennsylvania, Maryland, and Delaware, 1994-98

The Christina River Basin drains 565 square miles (mi 2 ) in Pennsylvania and Delaware and includes the major subbasins of Brandywine Creek, Red Clay Creek, White Clay Creek, and Christina River. The Christina River subbasin (exclusive of the Brandywine, Red Clay, and White Clay Creek subbasins) drains an area of 76 mi 2 . Streams in the Christina River Basin are used for recreation, drinking water supply, and support of aquatic life. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the stream. A multi-agency water-quality management strategy included a modeling component to evaluate the effects of point- and nonpoint-source contributions of nutrients and suspended sediment on stream water quality. To assist in nonpoint-source evaluation, four independent models, one for each of the four main subbasins of the Christina River Basin, were developed and calibrated using the model code Hydrological Simulation Program–Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in small subbasins predominantly covered by one land use following a nonpoint- source monitoring plan. Under this plan, stormflow and base-flow samples were collected during 1998 at two sites in the Christina River subbasin and nine sites elsewhere in the Christina River Basin. The HSPF model for the Christina River subbasin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into nine reaches draining areas that ranged from 3.8 to 21.9 mi 2 . Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the Christina River subbasin are residential, urban, forested, agricultural, and open. The hydrologic component of the model was run at an hourly time step and calibrated using streamflow data from two U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Daily precipitation data from one National Oceanic and Atmospheric Administration (NOAA) meteorologic station and hourly data from one NOAA meteorologic station were used for model input. The difference between observed and simulated streamflow volume ranged from -2.3 to 5.3 percent for a 10-month portion of the calibration period at the two calibration sites. Annual differences between observed and simulated streamflow generally were greater than the overall error for the 4-year period. For example, at Christina River at Coochs Bridge, near the bottom of the free-flowing part of the subbasin (drainage area of 21 mi 2 ), annual differences between observed and simulated streamflow ranged from -6.9 to 6.5 percent and the overall error for the 4-year period was -1.1 percent. Calibration errors for 36 storm periods at the three calibration sites for total volume, low-flow recession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were within the recommended criteria of 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the rainfall data. The water-quality component of the model was calibrated using nonpoint-source monitoring data collected at two USGS streamflow-measurement stations and other water-quality monitoring data. The period of record for water-quality monitoring was variable at the stations, with a start date ranging from October 1994 to January 1998 and an end date of October 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspended-sediment concentrations, although suspended-solids data may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulaion. Comparison of observed to simulated loads for up to six storms in 1998 at the two nonpoint-source monitoring sites (Little Mill Creek near Newport and Christina River at Coochs Bridge, Del.) indicate that simulation error is commonly as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved nutrients than for particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria; much larger errors are possible for individual events. Assessment of the water-quality calibration under stormﬂow conditions is limited by the relatively small amount of available water-quality data in the subbasin. Users of the Christina River subbasin HSPF model and HSPF models for other subbasins in the Christina River Basin should be aware of model limitations and consider the following if the model is used for predictive purposes: streamﬂow-duration curves suggest the model simulates streamﬂow reasonably well when measured over a broad range of conditions and time although streamﬂow and the corresponding water quality for individual storm events may not be well simulated; streamﬂow-duration curves for the simulation period compare well with duration curves for the 8-year period ending in 2001 at Christina River at Coochs Bridge, Del., and include all but the extreme high-ﬂow and low-ﬂow events; and calibration for water quality was based on limited data, with the result of increasing uncertainty in the water-quality simulation.

Water-Resources Investigations Report↗

USGS2007

Simulation of Intra- or transboundary surface-water-rights hierarchies using the farm process for MODFLOW-2000

Water-rights driven surface-water allocations for irrigated agriculture can be simulated using the farm process for MODFLOW-2000. This paper describes and develops a model, which simulates routed surface-water deliveries to farms limited by streamflow, equal-appropriation allotments, or a ranked prior-appropriation system. Simulated diversions account for deliveries to all farms along a canal according to their water-rights ranking and for conveyance losses and gains. Simulated minimum streamflow requirements on diversions help guarantee supplies to senior farms located on downstream diverting canals. Prior appropriation can be applied to individual farms or to groups of farms modeled as “virtual farms” representing irrigation districts, irrigated regions in transboundary settings, or natural vegetation habitats. The integrated approach of jointly simulating canal diversions, surface-water deliveries subject to water-rights constraints, and groundwater allocations is verified on numerical experiments based on a realistic, but hypothetical, system of ranked virtual farms. Results are discussed in light of transboundary water appropriation and demonstrate the approach’s suitability for simulating effects of water-rights hierarchies represented by international treaties, interstate stream compacts, intrastate water rights, or ecological requirements.

Journal of Water Resources Planning and Management↗

USGS2016

Spatial and temporal variability of contaminants within estuarine sediments and native Olympia oysters: A contrast between a developed and an undeveloped estuary

Chemical contaminants can be introduced into estuarine and marine ecosystems from a variety of sources including wastewater, agriculture and forestry practices, point and non-point discharges, runoff from industrial, municipal, and urban lands, accidental spills, and atmospheric deposition. The diversity of potential sources contributes to the likelihood of contaminated marine waters and sediments and increases the probability of uptake by marine organisms. Despite widespread recognition of direct and indirect pathways for contaminant deposition and organismal exposure in coastal systems, spatial and temporal variability in contaminant composition, deposition, and uptake patterns are still poorly known. We investigated these patterns for a suite of persistent legacy contaminants including polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) and chemicals of emerging concern including pharmaceuticals within two Oregon coastal estuaries (Coos and Netarts Bays). In the more urbanized Coos Bay, native Olympia oyster ( Ostrea lurida ) tissue had approximately twice the number of PCB congeners at over seven times the total concentration, yet fewer PBDEs at one-tenth the concentration as compared to the more rural Netarts Bay. Different pharmaceutical suites were detected during each sampling season. Variability in contaminant types and concentrations across seasons and between species and media (organisms versus sediment) indicates the limitation of using indicator species and/or sampling annually to determine contaminant loads at a site or for specific species. The results indicate the prevalence of legacy contaminants and CECs in relatively undeveloped coastal environments highlighting the need to improve policy and management actions to reduce contaminant releases into estuarine and marine waters and to deal with legacy compounds that remain long after prohibition of use. Our results point to the need for better understanding of the ecological and human health risks of exposure to the diverse cocktail of pollutants and harmful compounds that will continue to leach from estuarine sediments over time.

Oregon↗

USGS2003

Simulation of streamflow and water quality in the Brandywine Creek subbasin of the Christina River basin, Pennsylvania and Delaware, 1994-98

The Christina River Basin drains 565 mi 2 (square miles) in Pennsylvania and Delaware. Water from the basin is used for recreation, drinking-water supply, and to support aquatic life. The Christina River Basin includes the major subbasins of Brandywine Creek, Red Clay Creek, White Clay Creek, and Christina River. The Brandywine Creek is the largest of the subbasins and drains an area of 327 mi 2 . Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the streams. A multi-agency water-quality management strategy included a modeling component to evaluate the effects of point and nonpoint-source contributions of nutrients and suspended sediment on streamwater quality. To assist in nonpoint-source evaluation, four independent models, one for each of the four main subbasins of the Christina River Basin, were developed and calibrated using the model code Hydrological Simulation Program—Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in small subbasins predominantly covered by one land use following a nonpoint-source monitoring plan. Under this plan, stormflow and base-flow samples were collected during 1998 at six sites in the Brandywine Creek subbasin and five sites in the other subbasins. The HSPF model for the Brandywine Creek Basin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into 35 reaches draining areas that ranged from 0.6 to 18 mi 2 . Three of the reaches contain regulated reservoir. Eleven different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the basin are forested, agricultural, residential, and urban. The hydrologic component of the model was run at an hourly time step and calibrated using streamflow data for eight U.S. Geological Survey (USGS) stream-flow-measurement stations for the period of January 1, 1994, through October 29, 1998. Daily precipitation data for three National Oceanic and Atmospheric Administration (NOAA) gages and hourly data for one NOAA gage were used for model input. The difference between observed and simulated streamflow volume ranged from -2.7 to 3.9 percent for the nearly 5-year period at the eight calibration sites. Annual differences between observed and simulated streamflow generally were greater than the overall error. For example, at a site near the bottom of the basin (drainage area of 237 mi 2 ), annual differences between observed and simulated streamflow ranged from -14.0 to 18.8 percent and the overall error for the 5-year period was 1.0 percent. Calibration errors for 36 storm periods at the eight calibration sites for total volume, low-flow-recession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were within the recommended criteria of 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the rainfall data. The water-quality component of the model was calibrated using monitoring data collected at six USGS streamflow-measurement stations with variable water quality monitoring periods ending October 1998. Because of availability, monitoring data for suspended solids concentrations were used as surrogates for suspended-sediment concentrations, although suspended-solids data may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulation. Comparison of observed to simulated loads for two to six individual storms in 1998 at each of the six monitoring sites indicate that simulation error is commonly as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved nutrients than for particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria, with much larger errors possible for individual events. Assessment of the water-quality calibration under stormﬂow conditions is limited by the relatively small amount of available water-quality data in the basin. Duration curves for simulated and reported sediment concentration at Brandywine Creek at Wilmington, Del., are similar, indicating model performance is better when evaluated over longer periods than when evaluated on individual storm events.

Water-Resources Investigations Report↗

USGS2019

Point sources and agricultural practices control spatial-temporal patterns of orthophosphate in tributaries to Chesapeake Bay

Orthophosphate (PO 4 ) is the most bioavailable form of phosphorus (P). Excess PO 4 may cause harmful algal blooms in aquatic ecosystems. A major restoration effort is underway for Chesapeake Bay (CB) to reduce P, nitrogen, and sediment loading to CB. Although PO 4 cycling and delivery to streams has been characterized in small-scale studies, regional drivers of PO 4 patterns remain poorly understood because most water quality trend assessment focus on total P. Moreover, these trend assessments are usually at an annual timestep. To address this research gap, we analyzed PO 4 patterns over a 9-year period at 53 monitoring stations across the CB watershed to: 1) characterize the role of PO 4 in total P fluxes and trends; 2) describe spatial and temporal patterns of PO 4 concentrations across seasons and streamflow ; and 3) explore factors explaining these patterns. Agricultural watersheds exported the most total P compared with watersheds under different land uses (e.g., urban or forest), with PO 4 comprising up to 50% of those exports. Although PO 4 exports are declining at many sites, some agricultural regions are experiencing increasing trends at a rate sufficient to drive total P trends. Regression modeling results suggest that point source load reductions are likely responsible for decreasing PO 4 concentrations observed at many sites. Watersheds with more Conservation Reserve Program enrollment had lower summer PO 4 concentrations, highlighting the effectiveness of this practice. Manure inputs strongly predicted PO 4 concentrations at high flows across all seasons. Both manure applications and conservation tillage were correlated with changes in PO 4 concentrations at high flow, suggesting these activities could contribute to increasing PO 4 concentrations. This study highlights the effectiveness of point source control for reducing PO 4 exports and underscores the need for management strategies to target sources, practices, and landscape factors determining PO 4 loss from soils where manure inputs remain high.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2013

National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio

The National Park Service (NPS) Vegetation Inventory Program (VIP) is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VIP is managed by the NPS Biological Resources Management Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey (USGS) Vegetation Characterization Program lends a cooperative role in the NPS VIP. The USGS Upper Midwest Environmental Sciences Center, NatureServe, and NPS Cuyahoga Valley National Park (CUVA) have completed vegetation classification and mapping of CUVA. Mappers, ecologists, and botanists collaborated to identify and describe vegetation types within the National Vegetation Classification Standard (NVCS) and to determine how best to map them by using aerial imagery. The team collected data from 221 vegetation plots within CUVA to develop detailed descriptions of vegetation types. Data from 50 verification sites were also collected to test both the key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 647 accuracy assessment (AA) sites were collected (of which 643 were used to test accuracy of the vegetation map layer). These data sets led to the identification of 45 vegetation types at the association level in the NVCS at CUVA. A total of 44 map classes were developed to map the vegetation and general land cover of CUVA, including the following: 29 map classes represent natural/semi-natural vegetation types in the NVCS, 12 map classes represent cultural vegetation (agricultural and developed) in the NVCS, and 3 map classes represent non-vegetation features (open-water bodies). Features were interpreted from viewing color-infrared digital aerial imagery dated October 2010 (during peak leaf-phenology change of trees) via digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type. A geodatabase containing various feature-class layers and tables shows the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial photographic centers. The feature-class layer and relate tables for the CUVA vegetation map provides 4,640 polygons of detailed attribute data covering 13,288.4 ha, with an average polygon size of 2.9 ha. Summary reports generated from the vegetation map layer show map classes representing natural/semi-natural types in the NVCS apply to 4,151 polygons (89.4% of polygons) and cover 11,225.0 ha (84.5%) of the map extent. Of these polygons, the map layer shows CUVA to be 74.4% forest (9,888.8 ha), 2.5% shrubland (329.7 ha), and 7.6% herbaceous vegetation cover (1,006.5 ha). Map classes representing cultural types in the NVCS apply to 435 polygons (9.4% of polygons) and cover 1,825.7 ha (13.7%) of the map extent. Map classes representing non-NVCS units (open water) apply to 54 polygons (1.2% of polygons) and cover 237.7 ha (1.8%) of the map extent. A thematic AA study was conducted of map classes representing natural/semi-natural types in the NVCS. Results present an overall accuracy of 80.7% (kappa index of 79.5%) based on data from 643 of the 647 AA sites. Most individual map-class themes exceed the NPS VIP standard of 80% with a 90% confidence interval. The CUVA vegetation mapping project delivers many geospatial and vegetation data products in hardcopy and/or digital formats. These products consist of an in-depth project report discussing methods and results, which include descriptions and a dichotomous key to vegetation types, map classification and map-class descriptions, and a contingency table showing AA results. The suite of products also includes a database of vegetation plots, verification sites, and AA sites; digital pictures of field sites; field data sheets; aerial photographic imagery; hardcopy and digital maps; and a geodatabase of vegetation types and land cover (map layer), fieldwork locations (vegetation plots, verification sites, and AA sites), aerial photographic index, project boundary, and metadata. All geospatial products are projected in Universal Transverse Mercator, Zone 17, by using the North American Datum of 1983. Information on the NPS VIP and completed park mapping projects are located on the Internet at <http://science.nature.nps.gov/im/inventory/veg> and <http://www.usgs.gov/core_science_systems/csas/vip/index.html>.

Natural Resource Technical Report↗

USGS2023

Salinization and sedimentation drive contrasting assembly mechanisms of planktonic and sediment-bound bacterial communities in agricultural streams

Agriculture is the most dominant land use globally and is projected to increase in the future to support a growing human population but also threatens ecosystem structure and services. Bacteria mediate numerous biogeochemical pathways within ecosystems. Therefore, identifying linkages between stressors associated with agricultural land use and responses of bacterial diversity is an important step in understanding and improving resource management. Here, we use the Mississippi Alluvial Plain (MAP) ecoregion, a highly modified agroecosystem, as a case study to better understand agriculturally associated drivers of stream bacterial diversity and assembly mechanisms. In the MAP, we found that planktonic bacterial communities were strongly influenced by salinity. Tolerant taxa increased with increasing ion concentrations, likely driving homogenous selection which accounted for ~90% of assembly processes. Sediment bacterial phylogenetic diversity increased with increasing agricultural land use and was influenced by sediment particle size, with assembly mechanisms shifting from homogenous to variable selection as differences in median particle size increased. Within individual streams, sediment heterogeneity was correlated with bacterial diversity and a subsidy-stress relationship along the particle size gradient was observed. Planktonic and sediment communities within the same stream also diverged as sediment particle size decreased. Nutrients including carbon, nitrogen, and phosphorus, which tend to be elevated in agroecosystems, were also associated with detectable shifts in bacterial community structure. Collectively, our results establish that two understudied variables, salinity and sediment texture, are the primary drivers of bacterial diversity within the studied agroecosystem, whereas nutrients are secondary drivers. Although numerous macrobiological communities respond negatively, we observed increasing bacterial diversity in response to agricultural stressors including salinization and sedimentation. Elevated taxonomic and phylogenetic bacterial diversity likely increases the probability of detecting community responses to stressors. Thus, bacteria community responses may be more reliable for establishing water quality goals within highly modified agroecosystems that have experienced shifting baselines.

Mississippi↗

USGS2016

Mapping marginal croplands suitable for cellulosic feedstock crops in the Great Plains, United States

Growing cellulosic feedstock crops (e.g., switchgrass) for biofuel is more environmentally sustainable than corn-based ethanol. Specifically, this practice can reduce soil erosion and water quality impairment from pesticides and fertilizer, improve ecosystem services and sustainability (e.g., serve as carbon sinks), and minimize impacts on global food supplies. The main goal of this study was to identify high-risk marginal croplands that are potentially suitable for growing cellulosic feedstock crops (e.g., switchgrass) in the US Great Plains (GP). Satellite-derived growing season Normalized Difference Vegetation Index, a switchgrass biomass productivity map obtained from a previous study, US Geological Survey (USGS) irrigation and crop masks, and US Department of Agriculture (USDA) crop indemnity maps for the GP were used in this study. Our hypothesis was that croplands with relatively low crop yield but high productivity potential for switchgrass may be suitable for converting to switchgrass. Areas with relatively low crop indemnity (crop indemnity <$2 157 068) were excluded from the suitable areas based on low probability of crop failures. Results show that approximately 650 000 ha of marginal croplands in the GP are potentially suitable for switchgrass development. The total estimated switchgrass biomass productivity gain from these suitable areas is about 5.9 million metric tons. Switchgrass can be cultivated in either lowland or upland regions in the GP depending on the local soil and environmental conditions. This study improves our understanding of ecosystem services and the sustainability of cropland systems in the GP. Results from this study provide useful information to land managers for making informed decisions regarding switchgrass development in the GP.

GCB Bioenergy↗

USGS2009

Analytical Results for Agricultural Soils Samples from a Monitoring Program Near Deer Trail, Colorado (USA)

Since late 1993, Metro Wastewater Reclamation District of Denver (Metro District, MWRD), a large wastewater treatment plant in Denver, Colorado, has applied Grade I, Class B biosolids to about 52,000 acres of nonirrigated farmland and rangeland near Deer Trail, Colorado, USA. In cooperation with the Metro District in 1993, the U.S. Geological Survey (USGS) began monitoring groundwater at part of this site. In 1999, the USGS began a more comprehensive monitoring study of the entire site to address stakeholder concerns about the potential chemical effects of biosolids applications to water, soil, and vegetation. This more comprehensive monitoring program has recently been extended through 2010. Monitoring components of the more comprehensive study include biosolids collected at the wastewater treatment plant, soil, crops, dust, alluvial and bedrock groundwater, and stream bed sediment. Soils for this study were defined as the plow zone of the dry land agricultural fields - the top twelve inches of the soil column. This report presents analytical results for the soil samples collected at the Metro District farm land near Deer Trail, Colorado, during three separate sampling events during 1999, 2000, and 2002. Soil samples taken in 1999 were to be a representation of the original baseline of the agricultural soils prior to any biosolids application. The soil samples taken in 2000 represent the soils after one application of biosolids to the middle field at each site and those taken in 2002 represent the soils after two applications. There have been no biosolids applied to any of the four control fields. The next soil sampling is scheduled for the spring of 2010. Priority parameters for biosolids identified by the stakeholders and also regulated by Colorado when used as an agricultural soil amendment include the total concentrations of nine trace elements (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, and zinc), plutonium isotopes, and gross alpha and beta activity (Colorado Department of Public Health and Environment, Hazardous Materials and Waste Management Division, 1997; Colorado Department of Public Health and Environment,1998; U.S. Environmental Protection Agency, 1993). Since these were the identified priority parameters for the biosolids, the soils have the same set of priority parameters. Although the composite soils' priority analytes have been reported earlier to Metro District, the remaining elemental datasets for both the composite soils samples and selected fields' individual subsamples' data are presented here for the first time. More information about the other monitoring components is presented elsewhere in the literature (http://co.water.usgs.gov/projects/CO406/CO406.html). In general, the objective of each component of the study was to determine whether concentrations of priority parameters (1) were higher than regulatory limits, (2) were increasing with time, and(or) (3) were significantly higher in biosolids-applied areas than in a similar farmed area where biosolids were not applied. The method chosen for sampling the soils proved to be an efficient and reliable representation of the average composition of each field. This was shown by analyzing individual subsamples, averaging the resulting values, and then comparing the values to the composited samples' values. The soil chemistry shows distinct differences between the two sites, most likely due to the different underlying parent material. Biosolids data were used to compile an inorganic-chemical biosolids signature that can be contrasted with the geochemical signature of the agricultural soils for this site. The biosolids signature and an understanding of the geology and hydrology of the site can be used to separate biosolids effects from natural geochemical effects. Elements of particular interest for a biosolids signature after application in the soils include bismuth, copper, silver, mercury, and phosphorus. This signat

Open-File Report↗

USGS2008

Not all water becomes wine: Sulfur inputs as an opportune tracer of hydrochemical losses from vineyards

California's widespread and economically important vineyards offer substantial opportunities to understand the interface between hydrology and biogeochemistry in agricultural soils. The common use of native sulfur (S) as a fumigant or soil additive provides a novel way to isotopically differentiate among sulfate (SO 4 2− ) pools, allowing the estimation of water and SO 4 2− budgets. The objectives of this study were (1) to characterize the near‐surface hydrological flow paths in a vineyard during irrigation and storm events and (2) to determine how those flow paths affect the fate and transport of SO 4 2− across seasons. Integrating hydrological theory with measurements of SO 4 2− concentration and sulfate‐S isotopic ratios (expressed as [SO 4 2− ] and δ 34 S, respectively) in inputs, soil water, and leachate provided a means of determining flow paths. Low [SO 4 2− ] and δ 34 S in leachate during 4‐h irrigation events reflect minimal engagement of the soil matrix, indicating that preferential flow was the dominant path for water in the near surface. In contrast, high [SO 4 2− ] and δ 34 S values during 8‐h irrigation and storm events reflect near‐complete engagement of the soil matrix, indicating that lateral flow was the dominant pathway. Because hydrologic response and SO 4 2− mobility are tightly coupled in these soils, the magnitude of water fluxes through the near surface controls S cycling both on and off site. These results indicate that preferential flow is an important loss pathway to consider in managing both water resources and water quality (reactive elements) in vineyard land use systems.

Water Resources Research↗

USGS2003

Simulation of streamflow and water quality in the Red Clay Creek subbasin of the Christina River Basin, Pennsylvania and Delaware, 1994-98

The Christina River Basin drains 565 square miles (mi 2 ) in Pennsylvania and Delaware and includes the major subbasins of Red Clay Creek, White Clay Creek, Brandywine Creek, and Christina River. The Red Clay Creek is the smallest of the subbasins and drains an area of 54 mi 2 . Streams in the Christina River Basin are used for recreation, drinking-water supply, and to support aquatic life. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the stream. A multi-agency, waterquality management strategy included a modeling component to evaluate the effects of point and nonpointsource contributions of nutrients and suspended sediment on stream water quality. To assist in nonpointsource evaluation, four independent models, one for each of the four main subbasins of the Christina River Basin, were developed and calibrated using the model code Hydrological Simulation Program?Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in smaller subbasins predominantly covered by one land use following a nonpoint-source monitoring plan. Under this plan, stormflow and base-flow samples were collected during 1998 at 1 site in the Red Clay Creek subbasin and at 10 sites elsewhere in the Christina River Basin. The HSPF model for the Red Clay Creek subbasin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into nine reaches draining areas that ranged from 1.7 to 10 mi 2 . One of the reaches contains a regulated reservoir. Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the Red Clay Creek subbasin are agricultural, forested, residential, and urban. The hydrologic component of the model was run at an hourly time step and calibrated using streamflow data from three U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Daily precipitation data from one National Oceanic and Atmospheric Administration (NOAA) gage and hourly data from one NOAA gage were used for model input. The difference between observed and simulated stream- flow volume ranged from -0.8 to 2.1 percent for the 4-year period at the three calibration sites. Annual differences between observed and simulated streamflow generally were greater than the overall error for the 4-year period. For example, at a site near Stanton, Del., near the bottom of the basin (drainage area of 50.2 mi 2 ), annual differences between observed and simulated streamflow ranged from -5.8 to 6.0 percent and the overall error for the 4-year period was -0.8 percent. Calibration errors for 36 storm periods at the three calibration sites for total volume, low-flow-recession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the rainfall data. The water-quality component of the model was calibrated using nonpoint-source monitoring data collected in 1998 at one USGS streamflowmeasurement station and other water-quality monitoring data collected at three USGS streamflowmeasurement stations. The period of record for waterquality monitoring was variable at the stations, with an end date of October 1998 but the start date ranging from October 1994 to January 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspendedsediment concentrations, although suspended solids may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulation. Comparison of observed to simulated loads for ﬁve storms in 1998 at the one nonpoint-source monitoring site at Wooddale, Del., indicates that simulation error commonly is as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved utrients than particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria, with much larger errors possible for individual storm events. Assessment of the accuracy of the water-quality calibration under stormﬂow conditions is limited by the sparsity of available water-quality data in the basin. Users of the Red Clay Creek HSPF model should be aware of model limitations and consider the following when predictive scenarios are desired: streamﬂow-duration curves indicate the model simulates stream-ﬂow reasonably well when evaluated over a broad range of conditions and time, although streamﬂow and the corresponding water quality for individual storm events may not be well simulated; streamﬂow-duration curves for the simulation period compare well with duration curves for the 57.5-year period ending in 2001 at Wooddale, Del., and include all but the extreme high-ﬂow and low-ﬂow events; calibration for water quality was based on sparse data, with the result of increasing uncertainty in the water-quality simulation.

Water-Resources Investigations Report↗

USGS2021

Determination of vadose zone and saturated zone nitrate lag times using long-term groundwater monitoring data and statistical machine learning

In this study, we explored the use of statistical machine learning and long-term groundwater nitrate monitoring data to estimate vadose zone and saturated zone lag times in an irrigated alluvial agricultural setting. Unlike most previous statistical machine learning studies that sought to predict groundwater nitrate concentrations within aquifers, the focus of this study was to leverage available groundwater nitrate concentrations and other environmental variables to determine mean regional vertical velocities (transport rates) of water and solutes in the vadose zone and saturated zone (3.50 and 3.75 m yr −1 , respectively). The statistical machine learning results are consistent with two primary recharge processes in this western Nebraska aquifer, namely ( 1 ) diffuse recharge from irrigation and precipitation across the landscape and ( 2 ) focused recharge from leaking irrigation conveyance canals. The vadose zone mean velocity yielded a mean recharge rate (0.46 m yr −1 ) consistent with previous estimates from groundwater age dating in shallow wells (0.38 m yr −1 ). The saturated zone mean velocity yielded a recharge rate (1.31 m yr −1 ) that was more consistent with focused recharge from leaky irrigation canals, as indicated by previous results of groundwater age dating in intermediate-depth wells (1.22 m yr −1 ). Collectively, the statistical machine learning model results are consistent with previous observations of relatively high water fluxes and short transit times for water and nitrate in the primarily oxic aquifer. Partial dependence plots from the model indicate a sharp threshold in which high groundwater nitrate concentrations are mostly associated with total travel times of 7 years or less, possibly reflecting some combination of recent management practices and a tendency for nitrate concentrations to be higher in diffuse infiltration recharge than in canal leakage water. Limitations to the machine learning approach include the non-uniqueness of different transport rate combinations when comparing model performance and highlight the need to corroborate statistical model results with a robust conceptual model and complementary information such as groundwater age.

Nebraska↗

USGS2015

Assessment of interim flow water-quality data of the San Joaquin River restoration program and implications for fishes, California, 2009-11

After more than 50 years of extensive water diversion for urban and agriculture use, a major settlement was reached among the U.S. Departments of the Interior and Commerce, the Natural Resources Defense Council, and the Friant Water Users Authority in an effort to restore the San Joaquin River. The settlement received Federal court approval in October 2006 and established the San Joaquin River Restoration Program, a multi-agency collaboration between State and Federal agencies to restore and maintain fish populations, including Chinook salmon, in the main stem of the river between Friant Dam and the confluence with the Merced River. This is to be done while avoiding or minimizing adverse water supply effects to all of the Friant Division contractors that could result from restoration flows required by the settlement. The settlement stipulates that water- and sediment-quality data be collected to help assess the restoration goals. This report summarizes and evaluates water-quality data collected in the main stem of the San Joaquin River between Friant Dam and the Merced River by the U.S. Bureau of Reclamation for the San Joaquin River Restoration Program during 2009-11. This summary and assessment consider sampling frequency for adequate characterization of variability, sampling locations for sufficient characterization of the San Joaquin River Restoration Program restoration reach, sampling methods for appropriate media (water and sediment), and constituent reporting limits. After reviewing the water- and sediment-quality results for the San Joaquin River Restoration Program, several suggestions were made to the Fisheries Management Work Group, a division of the San Joaquin River Restoration Program that focuses solely on the reintroduction strategies and health of salmon and other native fishes in the river. Water-quality results for lead and total organic carbon exceeded the Surface Water Ambient Monitoring Program Basin Plan Objectives for the San Joaquin Basin, and results for copper exceeded the U.S. Environmental Protection Agency Office of Pesticide Programs' aquatic-life chronic and acute benchmarks for invertebrates. One sediment sample contained detections of pyrethroid pesticides bifenthrin, lambda-cyhalothrin, and total permethrin at concentrations above published chronic toxicity thresholds.

California↗

USGS2019

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

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

Science of the Total Environment↗

USGS2022

Response of soil respiration to changes in soil temperature and water table level in drained and restored peatlands of the southeastern United States

Extensive drainage of peatlands in the southeastern United States coastal plain for the purposes of agriculture and timber harvesting has led to large releases of soil carbon as carbon dioxide (CO 2 ) due to enhanced peat decomposition. Growth in mechanisms that provide financial incentives for reducing emissions from land use and land-use change could increase funding for hydrological restoration that reduces peat CO 2 emissions from these ecosystems. Measuring soil respiration and physical drivers across a range of site characteristics and land use histories is valuable for understanding how CO 2 emissions from peat decomposition may respond to raising water table levels. We combined measurements of total soil respiration, depth to water table from soil surface, and soil temperature from drained and restored peatlands at three locations in eastern North Carolina and one location in southeastern Virginia to investigate relationships among total soil respiration and physical drivers, and to develop models relating total soil respiration to parameters that can be easily measured and monitored in the field.

North Carolina↗

USGS2015

Science from genes to landscapes

Wherever flowering plants flourish, pollinating bees, birds, butterflies, bats, and other animals are at work, providing vital and often unnoticed services. Many of these species are in serious decline, a situation if unabated, threatens agricultural production, maintenance of natural plant communities, and other important services. Responding to this urgent challenge, the U.S. Geological Survey (USGS) is part of efforts to provide scientific information to support pollinator conservation, including the implementation of a national pollinator health strategy ( http://www.usgs.gov/ecosystems/wildlife/pollinators/ .) This science is but one example of how the Ecosystems Science Mission Area of the USGS conducts science to support sound management and conservation of our Nation’s biological resources. It does this through research, technical assistance, and education conducted by Cooperative Research Units and Science Centers located in nearly every State. The quality of life and economic strength in America hinges on healthy ecosystems that support living things and natural processes. Ecosystem science better enables society to understand how and why ecosystems change, to predict and forecast future changes, and to guide actions that can prevent damage to, and restore and sustain ecosystems. It is through this knowledge that informed decisions are made about natural resources that can enhance our Nation's economic and environmental well-being.

Fact Sheet↗

USGS2023

Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States

Executive Summary In 2022, the U.S. Geological Survey (USGS) established the Saline Lake Ecosystems Integrated Water Availability Assessment (IWAAs) to monitor and assess the hydrology of terminal lakes in the Great Basin and the migratory birds and other wildlife dependent on those habitats. Scientists from across the USGS (with specialties in water quantity, water quality, limnology, avian biology, data science, landscape ecology, and science communication) formed the Saline Lake Ecosystems IWAAs Team. The team has developed this regional strategic science plan to guide data collection and assessment activities at terminal lakes in the Great Basin. The U.S. Congress requested the USGS to establish the Saline Lake Ecosystems IWAAs in response to historically low water levels at terminal lakes and associated wetlands across the Great Basin. Not all Great Basin terminal lakes have high salinity; however, all terminal lakes occur in endorheic, closed, basins with no surface-water outflow. Low lake levels across the Great Basin are the result of increased water use for agriculture and municipalities, drought conditions, and a warming climate. Great Basin terminal lake water extents have decreased by as much as 90 percent over the last 150 years, and terminal lake wetlands have decreased in area by as much as 47 percent since 1984. Lake elevations and wetland areas are primarily supported by freshwater inputs from snowmelt feeding upgradient rivers, streams, and springs. These freshwater inputs have been severely reduced because of continued and increased surface-water diversions and surface-water capture through groundwater pumping for agriculture, mining, and public supply as well as unprecedented drought conditions and warming temperatures related to climate change. Water quality, specifically salinity, is highly variable for terminal lakes of the Great Basin, and this variability is a result of the balance between freshwater inflow and evaporation. Variability of salinity at each of the terminal lakes can be affected by lake morphology, hydrogeologic features of the basin, annual variability in weather patterns, and changes in upgradient water use. Hypersaline terminal lakes provide abundant food resources such as brine shrimp and brine flies that support nesting and migrating birds. The density and composition of invertebrates are closely tied to lake salinity. Increased salinity can exceed the tolerance of invertebrates, severely limiting their biomass. In contrast, decreased salinity can lead to altered invertebrate community composition, reducing the abundance of optimal avian prey resources. Great Basin terminal lake ecosystems, including open-water and adjacent aquatic and terrestrial environments, provide resources necessary to sustain many animal populations throughout the year. Although a variety of taxa use terminal lakes, these ecosystems are of acute importance for the millions of migratory waterbirds (for example, shorebirds, wading birds, and waterfowl) dependent on the network of terminal lakes and their associated wetlands. Migratory birds transiting the Pacific and Central Flyways use Great Basin terminal lake ecosystems throughout the year to feed, nest, and transit between wintering and breeding ranges. As such, successful conservation of birds and their habitats requires coordinated management of water and habitats across the Great Basin network of terminal lakes and wetlands. The linkages between water availability and ecosystem vulnerability of terminal lakes in the Great Basin are not well understood. The vulnerability of terminal lakes is related to the factors driving change and adaptive capacity of the lake ecosystem. Saline lake ecosystems are vulnerable when changes in water quantity affect ecosystem function. Water quantity affects salinity, which affects food webs and habitat; these linkages can be investigated with water-quality and food web monitoring. Water quantity also affects inundated habitat, which can be quantified through remote sensing. It is necessary to quantify hydroclimatic and water use controls on water availability to terminal lakes to assess the response of the ecosystems. Remotely sensed data can provide a broad-scale and long-term synoptic view of terminal lake hydrologic characteristics, but ground observations are required to interpret changes in water quality and ecological functions. Some terminal lake basins have ongoing monitoring and modeling efforts within the Great Basin (for example, Great Salt Lake, Carson River Basin), yet most monitoring locations are hydrologically upgradient and too far away from lake inflows to provide an accurate assessment of hydrological trends for the lake ecosystems. Other terminal lakes have no long-term hydrological monitoring in their respective watersheds (for example, Lake Abert). Ecological data collection in the Great Basin is also insufficient to understand how many birds exist on the landscape, how birds use the mosaic of terminal-lake habitats as an interconnected system, and how Great Basin terminal lakes are linked to the larger continental system of the Pacific and Central Flyways. Across agencies and organizations, tracking bird movement, abundance, and diversity is inconsistent, with some lakes having once- or twice-a-year bird survey efforts and a few locations having more intensive ecological data-gathering efforts (for example, Great Salt Lake, Lake Abert). Bridging hydrological and ecological information gaps will improve understanding of the trends in water supply and water quality, habitat availability and usage, and impacts on vulnerable waterbird species, all of which would be used by managers in coordinated conservation of this unique network of terminal-lake habitats. The terminal lakes of the Great Basin are part of the Basin and Range physiographic province that extends from the Colorado Plateau on the east to the Sierra Nevada on the west, and from the Snake River Plain on the north to the Garlock fault and the Mojave block on the south. The Great Basin is larger than 650,000 square kilometers and encompasses most of the State of Nevada but also extends to western Utah, eastern California, southeastern Idaho, southwestern Wyoming, and southeastern Oregon. The climate is arid to semiarid with a hydrologic regime that is snowmelt dominated, providing as much as 75 percent of total annual runoff for the region. Terminal lakes of the Great Basin occupy the lowest areas of closed (endorheic) drainage basins, such that lake levels and water quality respond rapidly to surface-water inflow. Terminal lakes provide local and regional economic value to the States in the Great Basin, including mineral extraction, aquaculture, public works, and recreational uses. As an example, assessments of Great Salt Lake’s ecological health and economic impact find hemispheric importance for the former and regional importance for the latter. Great Salt Lake creates about 7,000 jobs and $2 billion of economic output per year, most of which would be lost with further declines in lake level. The objectives of this Science Strategy are threefold: (1) to identify how changing water availability affects the quality, diversity, and abundance of habitats supporting continental waterbird populations; (2) to highlight the scientific monitoring and assessment needs of Great Basin terminal lakes; and (3) to support coordinated management and conservation actions to benefit those ecosystems, migratory birds, and other wildlife. There are long-term hydrological, ecological, and societal challenges associated with terminal lakes ecosystems in the Great Basin. This Science Strategy benefits partners by providing a conceptual model, nested at different spatial extents, that identifies key scientific information needs to inform coordinated implementation of management and conservation plans within and among hydrologic basins to address these complex challenges.

California, Idaho, Nevada, Oregon, Utah, Wyoming↗