Phosphorus availability often limits primary production in freshwater ecosystems and excessive P inputs promote accelerated eutrophication. Microbial mechanisms may control O2-dependent uptake/release of P in stream sediments and biofilms, but specific organisms responsible for these cycles have not been identified. Polyphosphate Accumulating Organisms (PAOs) are purposely enriched in treatment plants to remove P from wastewater. PAOs release P under anaerobic conditions and take it up under aerobic conditions. It is hypothesized that alternating aerobic/anaerobic conditions promote patterns of P uptake/release similar to those attributed to PAOs in wastewater treatment. Intact, native stream biofilms were collected in the Cascadilla Creek Watershed in Tompkins County, New York, and subjected to laboratory treatments to impose conditions similar to what may occur because of diel oxygenic and respiratory cycles: 1) continuous sparging with air and 2) alternate sparging with air or anaerobic gas (20∶80% by volume CO2∶N2). PO43−, Ca, Mg, total Mn, K, Fe2+, and total S (TS) concentrations in the water were monitored and total P (TP) and polyphosphate (polyP) concentrations in the biofilms at the start and end of the experiment. Microscopy and polymerase chain reaction (PCR) were used to quantify the percentage of cells with stored intracellular polyP and to test for known PAO genes, respectively. This dataset comprises the data, analysis scripts, and visualization scripts for the paper by Saia et al. entitled 'Evidence for polyphosphate accumulating organism (PAO)-mediated phosphorus cycling in stream biofilms under alternating aerobic/anaerobic conditions. Complete dataset description including information on associated journal article, data, and data analysis R scripts can be found at https://github.com/sheilasaia/paper-p-cycling-in-stream-biofilms/tree/v1....

EPA no longer updates this information, but it may be useful as a reference or resource. Welcome to the STORET Legacy Data Center, site of the world's largest repository of ambient Water Quality Data. From this site you will be able to access a database that holds over 200 million water sample observations from about 700,000 sampling sites for both surface and ground water.This web site allows both scientists and the general public to access the historical data from the legacy STORET system. First-time users should narrow their search based on the options from the Query page, while experienced users may jump to the no-frills Advanced Query form for requesting data. Legacy STORET contains data of undocumented quality. Further, the data in this system is static, and all new data are being entered into Modernized STORET. Background information about the Office of Water and the history of STORET may be found by following the Purpose link. For more information on the layout of this site, please follow the Site Map link. Internet Archive URL: https://web.archive.org/web/*/https://www3.epa.gov/storet/legacy/gateway.htm

DNA barcoding gene sequences and files associated with their analysis

Surface agronomic P budgets for 61 cropping systems using field-scale P flux data across 24 research sites in the United States and Canada. Data are representative of P inputs and outputs associated with the production of each crop in a respective rotation year, ranging from 1 to 10 rotation years. This dataset provides a comparison of field-scale soil surface P fluxes and phosphorus budgets across sites and cropping systems.

Nutrient recycling is fundamental to sustainable agricultural systems, but few mechanisms exist to ensure that surplus manure nutrients from animal feeding operations are transported for use on nutrient-deficient croplands. As a result, manure nutrients concentrate in locations where they can threaten environmental health and devalue manure as a fertilizer resource. This data set is from a study advances the concept of the “manureshed” – the lands surrounding animal feeding operations onto which manure nutrients can be redistributed to meet environmental, production, and economic goals. Manuresheds can be managed at multiple scales, for example, on farms with both animals and crops, among animal farms and crop farms within a county, or even among animal farms and crop farms in distant counties. With a focus on redistribution among counties, we classified the 3109 counties of the contiguous United States by their capacity to either supply manure phosphorus (P) and nitrogen (N) from confined livestock production (“sources”) or to assimilate and remove excess P and N via crops (“sinks”) [see data for N tonnes, P tonnes, N kg/ha, P kg/ha]. Manure nutrient source counties were identified in 40 of the 48 states, with a substantial concentration in the southern US. Source counties for manure P greatly outnumbered source counties for manure N (390 vs. 100), and 99 of the 100 manure N source counties were also source counties for manure P. Conversely, sink counties for manure N outnumbered sink counties for manure P (2766 vs. 2317). We used the P balances of the source and sink counties to delineate four manuresheds dominated by various combinations of confined hog, poultry, dairy, and beef industries [see data for Manuresheds (tonnes)]. The four manuresheds differed in the transport distances needed to assimilate excess manure P from their respective source areas (from 147 ± 51 km for a beef dominated manureshed to 368 ± 140 km for a poultry dominated manureshed), highlighting the need for systems-level strategies to promote manure nutrient recycling that operate across local, county, regional, and national scales.

The MANAGE (Measured Annual Nutrient loads from AGricultural Environments) database was developed to be a readily-accessible, easily-queried database of site characteristic and field-scale nutrient export data (Harmel et al., 2006). Initial funding for MANAGE was provided by USDA-ARS to support the USDA Conservation Effects Assessment Project (CEAP) and the Texas State Soil and Water Conservation Board as part of their mission to understand and mitigate agricultural impacts on water quality. The original version of MANAGE, which drew heavily from an early 1980’s compilation of nutrient export data (Reckhow et al., 1980; Beaulac, 1980; Beaulac and Reckhow, 1982), created an electronic database with nutrient load data and corresponding site characteristics from 40 studies on agricultural (cultivated and pasture/range) land uses. The first revision in 2008 added N and P load data from 15 additional studies along with N and P runoff concentration data for all 55 studies (Harmel et al., 2008). The second revision in 2016 added 30 runoff studies from forested land uses, 91 drainage water quality studies from drained land, and 12 additional runoff studies from cultivated and pasture/range (Christianson and Harmel, 2015; Harmel et al., 2016). In this expansion, fertilizer application timing, crop yield, and N and P uptake data were added to facilitate analysis of 4R Nutrient Stewardship. The latest revision (Harmel et al., 2022) added 27 studies and Level II ecoregion delineations for each of the 94 studies such that data are now available from 11 of the 50 North American Level II ecoregions, representing the major U.S. agricultural regions. With these updates, MANAGE contains data from a vast majority of published peer-reviewed N and P export studies on homogeneous cultivated, pasture/range, and forested land uses in the US under natural rainfall-runoff conditions, as well as artificially drained agricultural land. Thus MANAGE facilitates expanded spatial analyses and improved understanding of regional differences, management practice effectiveness, and impacts of land use conversions and management techniques, and it provides valuable data for modeling and decision-making related to agricultural runoff. The Manage Database v5 04-04-2018 zip file resource superseded the previously available v4 and was added to this record on May 30, 2018. Resource MANAGE Database v6 added Nov 17, 2022.

This study presents a novel concept for estimating net ecosystem production (NEP), the export of organic carbon (OC) from the productive surface layer to the deep-water (hypolimnion) of eleven seasonally stratified lakes, varying in depth and trophic state. As oxygen remineralizes settling OC at a constant ratio, NEP is equivalent to the areal hypolimnetic mineralization rate (AHM) plus burial in the sediment (net sedimentation, NS). Two major interferences have to be considered, however. First, OC from terrestrial sources, not originating from primary production, consumes a fraction of oxidants. Second, sediment diagenetic processes of lakes in trophic transition (e.g. undergoing eutrophication or reoligotrophication) that are not in quasi-steady-state with actual fluxes of OC in the productive surface layer, bias the estimation of NEP. In these cases, we suggest subtracting the flux of reduced substances diffusing from the sediment. This results in some overestimation for lakes with high allochthonous loads, and slight underestimation in lakes that are not in quasi-steady-state, because the fraction of the actual sediment burial of autochthonous OC is small but not negligible. The presented approach requires data from routinely available chemical monitoring and thus can be applied to historic data. The seasonal time integration makes the estimation of NEP quite robust. Exemplary, NEP of Lake Geneva was estimated from the export of P and N from the productive zone during the summer season to the hypolimnion assembling seasonal budgets. Based on a historic data record of 47 years, NEP estimations from AHM rates agreed well with P and N budgets and helped to verify and constrain the uncertainty of the estimates.

The USEPA participated in the 2015 Cooperative Science and Monitoring Initiative (CSMI) focus year for Lake Michigan. This work is describd here: http://www.iiseagrant.org/pdf/LakeMichiganCSMI2015FullReport.pdf As a small sub-component of this work EPA staff collected water quality data at the locations listed in grand_musk_tp.csv. The fields in grand_musk_tp.csv are described in grand_musk_tp.metadata.csv. This data was collected to support (provide validation data for) EPA nearshore nutrient modeling work described in the paper (in prep.) “Nearshore Nutrient Circulation in the Great Lakes - can a simple model provide transparency and utility?”.

On-Farm Residue Removal Study for Resilient Economic Agricultural Practices in Morris, Minnesota Interest in harvesting crop residues for energy has waxed and waned since the oil embargo of 1973. Since the at least the late 1990’s interest has been renewed due to concern of peak oil, highly volatile natural gas prices, replacing fossil fuel with renewable sources and a push for energy independence. The studies conducted on harvesting crop residues during the 1970’s and1980’s focused primarily on erosion risk and nutrient removal as a result early estimates of residue availability focused on erosion control (Perlack et al., 2005). More recently, the focus has expanded to also address harvest impacts on soil organic matter and other constraints (Wilhelm et al., 2007; Wilhelm et al., 2010). In West Central Minnesota, crop residues have been proposed a replacement for natural gas (Archer and Johnson, 2012) while nationally residues are also be considered for cellulosic ethanol production (US DOE, 2011). The objective of the on-farm study was to assess the impact of residue harvest on working farms with different management systems and soils. Indicators of erosion risk, soil organic matter, and crop productivity is response to grain plus cob, or grain plus stover compared to grain only harvest.

Average concentrations in 2014 for Phosphate (mg/lP) in samples from monitoring locations on the Irish Environmental Protection Agency Water Framework Directive (WFD) Groundwater Monitoring Network.

The dataset includes names and geographic coordinates of gauge stations where flow and water quality (sediment, nitrogen, phosphorus) are measured in the Upper Mississippi River Watershed, Ohio River Basin, and Maumee River Basins. The data include estimates of risk indices (reliability, resilience, vulnerability) and a composite watershed health measure at gauge the stations, distributional properties of the indices, sensitivity to water quality standards, scale dependency of the indices, and statistical significance of the relationship between composite watershed health measure and land uses (agricultural, forested, and urban). This dataset is associated with the following publication: Ganeshchandra Mallya , G., M. Hantush, and R. Govindaraju. Composite measures of watershed health from a water quality perspective. JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 214: 104-124, (2018).

St. Louis River Area of Concern surface water nutrient (TP, TN, NOx-N, NH4-N), dissolved oxygen, and particulate (TSS, chlorophyll a) concentration data from 2012 and 2013 reported in Bellinger et al. 2016, Journal of Great Lakes Research 42:28-38. This dataset is associated with the following publication: Bellinger, B., J. Hoffman , T. Angradi , D. Bolgrien , M. Starry, C. Elonen , T. Jicha , L. Lehto, L. Seifert-Monson, M. Pearson , L. Anderson, and B. Hill. Water quality in the St. Louis River Area of Concern (AOC), Lake Superior: An historical perspective with assessment implications. JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 42(1): 28-38, (2016).

The data set contains stream water concentrations of herbicides and nutrients for 153 sites in the northern Missouri/southern Iowa region from 1994 to 1995. The data are available in Microsoft Excel 2010 format. Sheet 1 (Metadata) of the file contains supporting information regarding the length of record, site locations, parameters measured, concentrations units, method detection limits, describes the meaning of zero and blank cells, defines the major land resource areas (MLRAs) of the region, and provides a link to the U. S. Geological Survey discharge data. Sheet 2 (Site names and locations) has a list of the site names by MLRA, river system, and site name. It also contains site locations, provided as Universal Transverse Mercator coordinates, drainage areas, and indicates which sites were co-located at U. S. Geological Survey gauge sites. Sheet 3 (Concentration Data) contains data for 15 herbicide and nutrient analytes along with the corresponding site name, river system, and MLRA. Atrazine concentrations in Goodwater Creek Experimental Watershed (GCEW) were shown to be among the very highest of any watershed in the United States based on comparisons using the national Watershed Regressions for Pesticides (WARP) model and by direct comparison with the 112 watersheds used in the development of WARP. The herbicide data collected in GCEW are documented at plot, field, and watershed scales. This 20-yr-long (1991-2010) effort was augmented with a spatially broad effort within the Central Mississippi River Basin encompassing 12 related claypan watersheds in the Salt River Basin, two cave streams on the fringe of the Central Claypan Areas in the Bonne Femme watershed, and 95 streams in northern Missouri and southern Iowa. The research effort on herbicide transport has highlighted the importance of restrictive soil layers with smectitic mineralogy to the risk of transport vulnerability. Near-surface soil features, such as claypans and argillic horizons, result in greater herbicide transport than soils with high saturated hydraulic conductivities and low smectitic clay content.

Where agricultural measures are needed to restore water quality, the Subbasin are highlighted with one or more coloured flags to indicate the types of water quality issues associated with that Subbasin: Red (potential point source), Orange (nitrate losses) and/or Navy (phosphorus/sediment losses).

This data are composed of precipitation, wetland water depth, volumetric soil moisture, nitrogen and carbon concentrations measured into and out of a wetland, and model computed soil moisture content as well as nitrogen and carbon loading from the wetland. The wetland is a restored treatment wetland, located in Kent Island, MD. This dataset is associated with the following publication: Sharifi, A., M. Hantush, and L. Kalin. Modeling Nitrogen and Carbon Dynamics in Wetland Soils and Water Using Mechanistic Wetland Model. Rao S. Govindaraju Journal of Hydrologic Engineering. American Society of Civil Engineers (ASCE), Reston, VA, USA, 22(1): 1-18, (2017).