The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information.
Alternative Biomass Production Study for Resilient Economic Agricultural Practices in Morris, Minnesota The Tillage Study was established in 1997 to assess the effect of a variety of tillage intensities on soil C. The initial eight treatments included no-tillage, moldboard + disk tillage, chisel tillage, and fall and spring residue management, with or without strip-tillage and strip-tillage + subsoiling (Archer and Reicosky, 2009). In 2004, treatments were reduced to no-tillage, moldboard tillage, and fall and spring residue management without strip-tillage, but all had an early or late planting date. The last comprehensive set of soil samples were collected in 2006. In 2008, the strip-tilled subset of the Tillage Study plots were repurposed for the Alternative Biomass Production Systems study, which was designed to explore alternative strategies to support bioenergy including planting of cellulosic feedstock. The Alternative Biomass Production plots included perennials in an extended 6-year rotation, winter cereal rye cover crops in a corn-soybean rotation, and an alternative Sorghum-Sudan grass hybrid forage system, all of which have and will continue to be monitored for agronomic and soil properties.
Carbon Crops Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network and Resilient Economic Agricultural Practices in Morris, Minnesota The overall goal of the Carbon Crop study, established in 2000, was to assess strategies for increasing soil C sequestration including converting to no till systems and including perennial grasses (e.g., switchgrass and big bluestem) Overall, the goal of the study has remained constant, although individual treatments were changed after an incremental soil sampling, in response to new hypotheses and questions. Soil sampling is conducted as treatment changes are implemented. In 2012, two of the perennial grass systems (spring harvest of Switchgrass and Big Bluestem) were changed to corn/soybean rotations, beginning with a soybean entry point, to determine if the SOC accrued under the perennial system was lost by converting to a short annual rotation managed without tillage. The second change made was to compare the productivity between recent and traditional switchgrass cultivars. The final change was conversion of autumn harvest of Big Bluestem treatment replaced with an annual biomass crop – Sorghum-Sudan grass. Soil samples were taken to 1 m in 2000, 2006, 2011, and 2016. Nitrous oxide and carbon dioxide fluxes from the soil were measured from June 2009 through March 2012.
To assess lake ecological status using a phytobenthos diatom metric based on a revised Trophic Diatom Index - for WFD purposes. More information on this dataset can be found in the Freshwater Metadatabase - BF_W_62-L-NC (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_62-L-NC).
phytoplanktpon, macrophytes and background abiotic data of lakes in Estonia More information on this dataset can be found in the Freshwater Metadatabase - BF_W_32-L-CB (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_32-L-CB).
More information on this dataset can be found in the Freshwater Metadatabase - BF_W_17-LR-NCA (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_17-LR-NCA).
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
This page contains links to all available GIS elevation datasets, services, and related applications.
Contains data of biovolume and density of phytoplankton, absence/presence and abundance of macrophytes and fish in according with physico-chemistry and meteorological data of Italian lakes. More information on this dataset can be found in the Freshwater Metadatabase - BF_W_24-L-Al (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_24-L-Al).
Farming Systems Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Morris, Minnesota Tillage is decreasing globally due to recognized benefits of fuel savings and improved soil health in the absence of disturbance. However, a perceived inability to control weeds effectively and economically hinders no-till adoption in organic production systems in the Upper Midwest, USA. A strip-tillage (ST) strategy was explored as an intermediate approach to reducing fuel use and soil disturbance, and still controlling weeds. An 8-year comparison was made between two tillage approaches, one primarily using ST the other using a combination of conventional plow, disk and chisel tillage [conventional tillage (CT)]. Additionally, two rotation schemes were explored within each tillage system: a 2-year rotation (2y) of corn (Zea mays L.), and soybean (Glycine max [L.] Merr.) with a winter rye (Secale cereale L.) cover crop; and a 4-year rotation (4y) of corn, soybean, spring wheat (Triticum aestivum L.) underseeded with alfalfa (Medicago sativa L.), and a second year of alfalfa. These treatments resulted in comparison of four main management systems CT-2y, CT-4y, ST-2y and ST-4y, which also were managed under fertilized and non-fertilized conditions. Yields, whole system productivity (evaluated with potential gross returns), and weed seed densities (first 4 years) were measured. Across years, yields of corn, soybean and wheat were greater by 34% or more under CT than ST but alfalfa yields were the same. Within tillage strategies, corn yields were the same in 2y and 4y rotations, but soybean yields, only under ST, were 29% lower in the fertilized 4y than 2 yr rotation. In the ST-4y system yields of corn and soybean were the same in fertilized and non-fertilized treatments. Over the entire rotation, system productivity was highest in the fertilized CT-2y system, but the same among fertilized ST-4y, and non-fertilized ST-2y, ST-4y, and CT-4y systems. Over the first 4 years, total weed seed density increased comparatively more under ST than CT, and was negatively correlated to corn yields in fertilized CT systems and soybean yields in the fertilized ST-2y system. These results indicated ST compromised productivity, in part due to insufficient weed control, but also due to reduced nutrient availability. ST and diverse rotations may yet be viable options given that overall productivity of fertilized ST-2y and CT-4y systems was within 70% of that in the fertilized CT-2y system. Closing the yield gap between ST and CT would benefit from future research focused on organic weed and nutrient management, particularly for corn.
Raw data on fish catches in Danish lakes. Aim is to describe fish communities and to calculate the BQE for the lakes. More information on this dataset can be found in the Freshwater Metadatabase - BF_W_53-LR-C (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_53-LR-C).
The data gathered in this database are very diverse, they concerned different BQE and physico chemical analyses. Different organisms collected these data from different protocols. Concerning the fish dB, the lakes are sampled on different GPS referenced points (different net settled for one lake). Fish sampling are connected to a particular campaign, identified by a beginning and a ending date, as well as all the physico chemical data available (thermo depth, oxycline depth, air temperature, secchi disk...)(as much as we can). All net settled during a campaign are described: CEN standard or not, stratum of the net, hour settlement, hour taking off...)and the fished catched are gathered in different type of lot (individual, batch of fish) with measurement and weight where possible(sex if possible). More information on this dataset can be found in the Freshwater Metadatabase - BF_W_92-L-CAAI (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_92-L-CAAI).
The Freshwater Ecosystems Explorer is a free and easy to use data platform providingnaccurate, up-to-date, high-resolution geospatial data depicting the extent freshwater ecosystems change over time. By helping decision-makers understand dynamic ecosystem changes, the data presented on this open access platform is intended to drive action to protect and restore freshwater ecosystems and enable countries to track progress towards the achievement of Sustainable Development Goal Target 6.6.
The Lake Water Products (lake water quality, lake surface water temperature) provide a semi-continuous observation record for a large number (nominally 4,200) of medium and large-sized lakes, according to the Global Lakes and Wetlands Database (GLWD) or otherwise of specific environmental monitoring interest. Next to the lake surface water temperature that is provided separately, this record consists of three water quality parameters: turbidity, trophic state index, and lake surface reflectances.
The Global Lakes and Wetlands Database (GLWD) includes the best available data sources and GIS functionality for global lakes and wetlands focused on three scales (1) large lakes and reservoirs, (2) smaller water bodies, and (3) wetlands. The map scaless provided range from 1:1 to 1:3 million resolution. Level 1 (GLWD-1) comprises the 3,067 largest lakes (area ≥ 50 km2) and 654 largest reservoirs (storage capacity ≥ 0.5 km3) worldwide, and includes extensive attribute data. Level 2 (GLWD-2) comprises permanent open water bodies with a surface area ≥ 0.1 km2 excluding the water bodies contained in GLWD-1. Level 3 (GLWD-3) comprises lakes, reservoirs, rivers and different wetland types in the form of a global raster map at 30-second resolution.
These hourly measurements of atmospheric and oceanic data were captured from the index of NOAA-GLERL. They include data from the Real-Time Meteorological Observation Network (RTMON) and NOAA's webcams. https://web.archive.org/web/*/https://www.glerl.noaa.gov//metdata/status/status_archive/
This GIS layer contains bathymetric elevation bands (derived from bathymetric contours) of selected freshwater lakes in Washington State. The majority of the bathymetric contours were digitized from maps contained in a series of seven documents: Reconnaissance Data on Lakes in Washington, Water-Supply Bulletin 43, Volume 1 through 7 by the United States Geological Survey in cooperation with the Washington State Department of Ecology. The exceptions are 1) Lake Chelan which was digitized in 2016 from the publication Morphometry of Lake Chelan (published in January 1987); 2) Lake Sammamish whose digital data was acquired from King County in 2013 and is derived from data collected during the publication of Development of a Three-Dimensional Hydrographic Model of Lake Sammamish (published in November 2008); and 3) Lake Crescent, whose digital bathymetric soundings were taken by a private party during 2013/2014 and provided to the Department of Ecology and were converted to contour lines in 2016.
This GIS layer contains bathymetric elevation bands (derived from bathymetric contours) of selected freshwater lakes in Washington State. The majority of the bathymetric contours were digitized from maps contained in a series of seven documents: Reconnissance Data on Lakes in Washington, Water-Supply Bulletin 43, Volume 1 through 7 by the United States Geological Survey in cooperation with the Washington State Department of Ecology. The exceptions are 1) Lake Chelan which was digitized in 2016 from the publiclication Morphometry of Lake Chelan (published in January 1987); 2) Lake Sammamish whose digital data was acquired from King County in 2013 and is derived from data collected during the publication of Development of a Three-Dimensional Hydrographic Model of Lake Sammamish (published in November 2008); and 3) Lake Crescent, whose digital bathymetric soundings were taken by a private party during 2013/2014 and provided to the Department of Ecology and were converted to contour lines in 2016.
The Lakes Ecosystem Services Online GIS provides geospatial visualization, query, and analysis tool on the types of benefits provided by lakes, ponds, and reservoirs. The data in this dataset is used by the website to provide access to lakes monitoring data, modeled nutrient fluxes, state specific data sets analytical tools and scripts for exploring associations between nutrients and lake ecosystem services, tools for mapping lake ecosystem services. https://archive.epa.gov/aed/lakesecoservices/web/html/ Internet Archive URL: https://web.archive.org/web/*/http://gispub4.epa.gov/LES
lake benthic invertebrates per site from Austria, Germany & Italy More information on this dataset can be found in the Freshwater Metadatabase - BF_W_77-LR-MAl (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_77-LR-MAl).
The database includes raw data on macrophytes in Danish lakes. Aim is to describe the macrophyte communities and to calculate the BQE for the lakes. More information on this dataset can be found in the Freshwater Metadatabase - BF_W_50-L-BA (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_50-L-BA).
The Mobile Source Observation Database (MSOD) is a relational database being developed by the Assessment and Standards Division (ASD) of the US Environmental Protection Agency Office of Transportation and Air Quality (formerly the Office of Mobile Sources). The MSOD contains emission test data from in-use mobile air- pollution sources such as cars, trucks, and engines from trucks and nonroad vehicles. Data in the database was collected from 1982 to the present. The data is intended to be representative of in-use vehicle emissions in the United States.
More information on this dataset can be found in the Freshwater Metadatabase - BF42 (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF42).
National Hydrography Dataset
Macroinvertebrates in lakes, from EU FP6 project REBECCA. More information on this dataset can be found in the Freshwater Metadatabase - BF_W_63-L-6 (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_63-L-6).
More information on this dataset can be found in the Freshwater Metadatabase - BF_W_64-L-6 (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_64-L-6).
All reservoirs and lakes identified in the 2018 Virginia 305(b)/303(d) Water Quality Assessment. Line work and attributes should not be altered except by the developer (DEQ). This dataset constitutes the United States Environmental Protection Agency (EPA) approved digital version of the assessment hydrology for Virginia. Attributes assigned to each water segment are based on attributes associated with the ID305B (assessment unit ID) entered in the statewide water quality assessment database. QA/QC checks are performed on the database prior to linking attributes to the GIS data, however errors may still occur. Please direct any questions about attribute accuracy to the Data Distributor. The geospatial product is maintained and updated by VA DEQ each assessment cycle (biennially) using the most current NHD product where revisions were made to Virginia waters, the most recent aerial photography provided by the Virginia Geographic Information Network (VGIN), and by freehand digitizing where necessary. Metadata is provided in the data Fact Sheet which contains contact information, process steps, attribute descriptions, and distribution information.
Invertebrate surveys of approximately 300 lakes. More information on this dataset can be found in the Freshwater Metadatabase - BF_W_15-L-NCA (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_15-L-NCA).
Points on streams and rivers where SMA jurisdiction begins as published in Chapter 173-18 WAC. This layer will not be updated. It is slowly becoming outdated as cities and counties update their list of SMA streams in their shoreline master program. See WAC 173-18-044 posted at http://apps.leg.wa.gov/wac/default.aspx?cite=173-18-044.Point locations were originally compiled for Ecology in 1972 by the US Geological Survey, Water Resources Division, Tacoma, WA, and released in STREAMS OF WASHINGTON UNDER THE REQUIREMENTS OF THE SHORELINE MANAGEMENT ACT OF 1971. Points were determined using multiple-regression techniques based on streamflow and basin precipitation records. Ecology has occasionally updated point locations, and added and subtracted points since 1972.
Streams and rivers published in Chapter 173-18-WAC. This layer will not be updated. It is slowly becoming outdated as cities and counties update their list of Shoreline Management Act streams in their shoreline master program. See WAC 173-18-044 posted at http://apps.leg.wa.gov/wac/default.aspx?cite=173-18-044.The upstream points where SMA jurisdiction begins were originally compiled for Ecology in 1972 by the US Geological Survey, Water Resources Division, Tacoma, WA, and released in STREAMS OF WASHINGTON UNDER THE REQUIREMENTS OF THE SHORELINE MANAGEMENT ACT OF 1971. Points were determined using multiple-regression techniques based on streamflow and basin precipitation records. Ecology has occasionally updated those points and added and subtracted SMA streams and portions of SMA streams since 1972.
Water bodies (lakes, wetlands, etc.) published in Chapter 173-20 WAC. These will be replaced by water body lists published in local government shoreline master programs. See Chapter 173-20-044 WAC.
The United States Geological Survey (USGS) Reservoir dataset is one of various hydrological datasets provided for the Southern Great Plains 1997 (SGP97) project. This dataset contains reservoir data from stations in SGP97 domain. The data collected at USGS gaging stations consist of records of stage and measurements of discharge of streams or canals, and stage, surface area, and contents of lakes or reservoirs. This dataset contains only the USGS reservoir data. For a lake or reservoir, capacity tables giving the contents for any stage are prepared from stage-area relation curves defined by surveys. The application of the stage to the capacity table gives the contents, from which the daily, monthly, or yearly change in contents is computed. If the stage-capacity curve is subject to changes because of deposition of sediment in the reservoir, periodic resurveys of the reservoir are necessary to define new stage-capacity curves. During the period between reservoir surveys, the computed contents may be increasingly in error due to the gradual accumulation of sediments. For some gaging stations there are periods when no gage-height record is obtained or the recorded gage height is so faulty that it cannot be used to compute daily discharge or contents. This happens when the recorder stops or otherwise fails to operate properly, intakes are plugged, the float is frozen in the well, or for various other reasons. For such periods, the daily contents may be estimated on the basis of operator's log, prior and subsequent records, inflow-outflow studies, and other information. The USGS reservoir data are provided in a single file and are provided "as is" in their original card image format. There are six different types of "cards images" which appear in the USGS reservoir dataset. Each card has a unique format, but the first character of a card image always indicates the card type. Depending upon the card type, the card image may contain metadata and/or data. No additional quality control was performed by the University Corporation for Atmospheric Research/Joint Office for Science Support (UCAR/JOSS).
each lake is a row, lake properties as variables: presence-absence data for each macrophyte species, water chemistry data, land use within lake catchment, lake properties (altitude, depth, area etc), ecological status, EQRs, lake coordinates More information on this dataset can be found in the Freshwater Metadatabase - BF_W_93-L-N (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_93-L-N).
Swedish Environmental Protection Agency national monitoring database for lakes. More information on this dataset can be found in the Freshwater Metadatabase - BF_W_67-LR-NCB (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_67-LR-NCB).
The Watershed Index Online (WSIO) is a national watershed indicator data library and analysis tool for comparing watershed characteristics within user-defined geographic areas.
USGS data and tools are the digital information in a format suitable for direct input to software that can analyze its meaning in the scientific, engineering, or business context for which the data were collected.
(Link to Metadata) VHDCARTO is a simplified version of the local resolution Vermont Hydrography Dataset (VHD) that has been enriched with stream perenniality, e.g., "intermittent" vs. "perennial", as well as, Strahler stream order attribution for the single linear feature class only. The primary means of accessing this information cartographically is via the FCODE and STREAM_ORDER fields, respectively. See the Entity and Attribution Information section for details. NOTE! Perenniality data does not exist for stream reaches contained within, or intersected by, Essex or Caledonia counties, thus the FCODE "46000" in these areas. The absence of Soil SUrvey GeOgraphic (SSURGO) database information in these areas precluded the computation of perenniality. These areas will be processed at some future date. For information on the FCODE symbol for attribution or analysis see the following document https://www.usgs.gov/national-hydrography/national-hydrography-dataset (NHDFlowline). A two dimensional feature class for lakes, ponds and larger streams is also included in VHDCARTO. Both layers are derived from the latest National Hydrography Dataset (NHD) data. The NHD is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. For information on the science behind computing perenniality attribution please refer to the following U.S. Geological Survey Scientific Investigative Report (SIR) # 2006-5217 - https://pubs.usgs.gov/sir/2006/5217/pdf/SIR2006-5217_report.pdf
(Link to Metadata) VHDCARTO is a simplified version of the local resolution Vermont Hydrography Dataset (VHD) that has been enriched with stream perenniality, e.g., "intermittent" vs. "perennial", as well as, Strahler stream order attribution for the single linear feature class only. The primary means of accessing this information cartographically is via the FCODE and STREAM_ORDER fields, respectively. See the Entity and Attribution Information section for details. NOTE! Perenniality data does not exist for stream reaches contained within, or intersected by, Essex or Caledonia counties, thus the FCODE "46000" in these areas. The absence of Soil SUrvey GeOgraphic (SSURGO) database information in these areas precluded the computation of perenniality. These areas will be processed at some future date. For information on the FCODE symbol for attribution or analysis see the following document https://www.usgs.gov/national-hydrography/national-hydrography-dataset (NHDFlowline). A two dimensional feature class for lakes, ponds and larger streams is also included in VHDCARTO. Both layers are derived from the latest National Hydrography Dataset (NHD) data. The NHD is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. For information on the science behind computing perenniality attribution please refer to the following U.S. Geological Survey Scientific Investigative Report (SIR) # 2006-5217 - https://pubs.usgs.gov/sir/2006/5217/pdf/SIR2006-5217_report.pdf
(Link to Metadata) The Vermont Hydrography Dataset (VHD) is compliant with the local resolution (also known as High Resolution) National Hydrography Dataset (NHD) and is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. Data users are highly encouraged to read this metadata thoroughly in order to avoid using the data beyond its limitations. This dataset is ONLY available for download from USGS's FTP site as a pre-staged ESRI File Geodatabase only (shapefile not available). Refer to VHDCARTO if you're looking for a layer of surface water data for cartographic purposes only. The VHD is based primarily on the Vermont Mapping Program (VMP) digital orthophotos, vmp "break line" features, and to a lesser degree on historical surface water data, NAPP cir multi-spectral aerial photography and CIR satellite imagery (lamoille and white subbasins only). The original VMP orthos had source dates ranging from 1994-2000 and these are being updated yearly. The VHD is organized at the subbasin level, a.k.a., the eight digit cataloging unit (HUC 8). The 17 Subbasins within or intersecting Vermont include: Black-Ottauquechee Rivers (1080106), Connecticut-Bellows Falls to Vernon Dam (1080107), Connecticut-Johns River to Waits River (1080103), Connecticut-Waits River to White River (1080104), Deerfield River (1080203), Hudson-Hoosic Rivers (2020003), Lake Champlain (2010008), Lake George (2010001), Lamoille River (2010005), Middle Connecticut River (1080201), Mississquoi River (2010007), Otter Creek (2010002), Passumpsic River (1080102), St. Francois River (1110000), Upper Connecticut River (1080101), White River (1080105) and Winooski River (2010003).
A Lake Champlain subset of the VHDCARTO dataset--which is a simplified cartographic-purpose version of the local resolution Vermont Hydrography Dataset (VHD).The full VHDCARTO dataset is composed of two layers--a line layer and a polygon layer.
(Link to Metadata) This datalayer is comprised of lakes extracted from the USGS DLGs DLG Surface Waters coverage. Digital line graph (DLG) data are digital representations of cartographic information. DLG's of map features are converted to digital form from maps and related sources. Intermediate-scale DLG data are derived from USGS 100,000-scale 30- by 60-minute quadrangle maps. If these maps are not available, Bureau of Land Management RF 100,000 are used. (1)Public Land Survey System; (2) boundaries (3) transportation; (4) hydrography; and (5) hypsography. All DLG data distributed by the USGS are DLG - Level 3 (DLG-3), which means the data contain a full range of attribute codes, have full topological structuring, and have passed certain quality-control checks. VCGI currently offers VGIS users the following DLG datalayers; WaterHydro_DLGLAKES - extracted from WaterHydro_DLGSW (4). UtilityTransmit_DLGMTT - DLG miscellaineous Transmisson Lines (1). TransRoad_DLGRD - Roads (3). TransRail_DLGRR - Railroads (3). WaterHydro_DLGSW - DLG surface waters (4). BoundaryTile_DLGTILES - Quadrangle map boundaries (1).
This dataset contains the status results for lake waterbodies (LWB) and status assigned to unmonitored WFD LWBs as part of the EU Water Framework Directive (2000/60/EC) with the objectives to achieve or maintain at least good ecological status and good chemical status
This web map contains datasets representing the National Hydrography Dataset (NHD) of Washington State, labels for NHD features, and the Watershed Boundary Dataset (WBD) basins for Hydrologic Unit Code (HUC) levels 4, 8, and 12. The NHD dataset has been adopted as the Washington State hydrography standard. The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all.This high-resolution NHD, generally developed at 1:24,000/1:4,800 scale. Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.This map contains a BETA version of WaterType attached to the Skagit River Basin NHDflowlines. This Beta version of the Watertype is the result of a pilot project and will be refined over the next six months. The field is for users of NHD who want access to Water Type and who are not under Forest Practices rules. The WaterType uses Shorelines Master Program type S streams and Fish Presence Data from both WA Dept Natural Resources and WA Dept Fish and Wildlife.
Waterbase is the generic name given to the EEA's databases on the status and quality of Europe's rivers, lakes, groundwater bodies and transitional, coastal and marine waters, on the quantity of Europe's water resources, and on the emissions to surface waters from point and diffuse sources of pollution. The dataset contains time series of nutrients, organic matter, hazardous substances and other chemicals in rivers, lakes and groundwater, as well as data on biological quality elements (BQEs) such as phytobenthos and macroinvertebrates in rivers and lakes. A list of monitoring site identifiers with selected attributes, reported through WFD and WISE Spatial data reporting, is added to dataset as spatial reference. The data has been compiled and processed by EEA. Please refer to the metadata for additional information.
Location and extent of Melbourne Water natural and constructed (man-made) wetlands and lakes. Captured using the Top Water Level (TWL) of each, includes wetland or lake name, asset section (for As Constructed drawings) and key attributes. Data set required to indicate the location and types of assets used for stormwater treatment (treatment and removal of pollutants from the stormwater system) and flow management (helping maintain the flow of water and reduce the impacts of floods), for ongoing condition monitoring, maintenance and hydrologic or vegetation analysis and to assist with the planning and design, construction of future stormwater management (WSUD) options.NOTE: Whilst every effort has been taken in collecting, validating and providing the attached data, Melbourne Water Corporation makes no representations or guarantees as to the accuracy or completeness of this data. Any person or group that uses this data does so at its own risk and should make their own assessment and investigations as to the suitability and/or application of the data. Melbourne Water Corporation shall not be liable in any way to any person or group for loss of any kind including damages, costs, interest, loss of profits or special loss or damage, arising from any use, error, inaccuracy, incompleteness or other defect in this data.
Phytoplankton community composition data from Lake Windermere (south basin) collected fortnightly. Data from 1989 onwards, held in Oracle. More information on this dataset can be found in the Freshwater Metadatabase - BF_W_23-L-NCA (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=BF_W_23-L-NCA).