Bottom dissolved oxygen (DO) data was extracted from environmental profiles acquired during the Southeast Fisheries Science Center Mississippi Laboratories summer groundfish trawl surveys of the Western and North-central Gulf of Mexico from 1982 to 1998. The data were distributed to hypoxia researchers in near real time and used to generate bottom DO maps as part of the Hypoxia Watch Project (http://www.ncddc.noaa.gov/hypoxia/). The profiles were acquired with a Sea-Bird Model SB9 profiler equipped with pressure, temperature, conductivity, fluorescence, and beam transmission sensors. The data were processed with Sea-Bird software using the standard processing protocol developed by the Mississippi Laboratories. Water temperature, beam transmission, and derived salinity, DO and DO percent saturation, and density were retained in the processed files. SAS software was used to extract the bottom DO and other relevant data (e.g., date, time, position, and station number) and format the data as comma-delimited ASCII files.

This data layer is an overview of project locations that were included in the National Centers for Coastal Ocean Science's HABs and Hypoxia Program Review.See the HABs and Hypoxia Program Review website https://experience.arcgis.com/experience/b82102ea67ba4d4f8339baecba2aa29f

Dissolved Oxygen data was compiled from data provided by different agencies around the Gulf of Mexico, research projects and cruises.

Data source: National Water Quality Monitoring Council (NWQMC), Environmental Protection Agency (EPA), United States Geological Survey (USGS), National Estuarine Research System (NERRS), Texas Commission on Environmental Quality (TCEQ), Florida Keys National Marine Sanctuary (FKNMS), National Park Water Services (NPWS), Louisiana Department of Environmental Quality (LDEQ), Louisiana Universities Marine Consortium (LUMCON), Mississippi Department of Environmental Quality (MDEQ), Alabama Department of Environmental Management (ADEM), Florida Department of Environmental Protection (FDEP) and Texas A&M University (TAMU).

Feature layer generated from running the Enrich layer solution. MPO_Forum_Dissolve were enriched

The NOAA Hypoxia Watch project provides near-real-time, web-based maps of dissolved oxygen near the sea floor over the Texas-Louisiana continental shelf during a period that extends from mid-June to mid-July. The NOAA National Marine Fisheries Service Mississippi Laboratories at Pascagoula and Stennis Space Center and the NOAA's National Centers for Environmental Information (NCEI) began the Hypoxia Watch project in 2001. Scientists aboard the NOAA Research Vessel Oregon II measure seawater properties, such as water temperature, salinity, chlorophyll, and dissolved oxygen, as the Oregon II cruises the waters south of Pascagoula, MS and then makes its way from Brownsville, Texas, to the mouth of the Mississippi River. A scientist aboard the ship processes the measurements from electronic dissolved oxygen sensors, checks the measurements periodically with chemical analyses of the seawater, then sends the data by FTP to the NCEI approximately every three to four days. Physical Scientists at NCEI transform the dissolved oxygen measurements into contour maps, which identify areas of low oxygen, or hypoxia. During the cruise, as the data is received from the ship, NCEI generates new maps and publishes them on the web. The first map will usually cover an area off the Mississippi coast, successive maps will add areas of the continental shelf from Brownsville to Corpus Christi, and the final map will usually cover the entire Texas-Louisiana-Mississippi coast. Maps are published every three to four days from approximately June 22 to July 20.

This nowCOAST™ time-enabled map service provides maps depicting the geographic coverage of the latest NOAA/National Weather Service (NWS) WATCHES, WARNINGS, ADVISORIES, and STATEMENTS for long-duration hazardous weather, marine weather, hydrological, oceanographic, wildfire, air quality, and ecological conditions which may or are presently affecting inland, coastal, and maritime areas. A few examples include Gale Watch, Gale Warning, High Surf Advisory, High Wind Watch, Areal Flood Warning, Coastal Flood Watch, Winter Storm Warning, Wind Chill Advisory, Frost Advisory, Tropical Storm Watch, Red Flag Warning, Air Stagnation Warning, and Beach Hazards Statement. (A complete list is given in the Background Information section below.) The coverage areas of these products are usually defined by county or sub-county boundaries. The colors used to identify the different watches, advisories, warnings, and statements are the same colors used by the NWS on their map at weather.gov. The NWS products for long-duration hazardous conditions are updated in the nowCOAST map service approximately every 10 minutes. For more detailed information about the update schedule, please see: http://new.nowcoast.noaa.gov/help/#section=updateschedule. The coverage areas of these products are usually defined by county or sub-county boundaries, but for simplicity and performance reasons, adjacent WWAs of the same type, issuance, and expiration are depicted in this service as unified (merged/dissolved) polygons in the layers indicated with the suffix "(Dissolved Polygons)". However, a set of equivalent layers containing the original individual zone geometries are also included for querying purposes, and are indicated with the suffix "(Zone Polygons)". Corresponding zone polygon and dissolved polygon layers are matched together in group layers for each WWA category. The zone polygon layers are included in this service only to support query/identify operations (e.g., in order to retrieve the original zone geometry or other attributes such as a URL to the warning text bulletin) and thus will not be drawn when included in a normal map image request. Thus, the dissolved polygon layers should be used when requesting a map image (e.g. WMS GetMap or ArcGIS REST export operations), while the zone polygon layers should be used when performing a query (e.g. WMS GetFeatureInfo or ArcGIS REST query or identify operations). The colors used to identify the different watches, advisories, warnings, and statements are the same colors used by the NWS on their map at http://www.weather.gov. The NWS products for long-duration hazardous conditions are updated in the nowCOAST™ map service approximately every 10 minutes. For more detailed information about layer update frequency and timing, please reference the nowCOAST™ Dataset Update Schedule. Background Information NWS watches depict the geographic areas where the risk of hazardous weather or hydrologic events has increased significantly, but their occurrence, location, and/or timing is still uncertain. A warning depicts where a hazardous weather or hydrologic event is occurring, is imminent, or has a very high probability of occurring. A warning is used for conditions posing a threat to life or property. Advisories indicate where special weather conditions are occurring, imminent, or have a very high probability of occurring but are less serious than a warning. They are for events that may cause significant inconvenience, and if caution is not exercised, could lead to situations that may threaten life and/or property. Statements usually contain updated information on a warning and are used to let the public know when a warning is no longer in effect. NWS issues over 75 different types of watches, warnings, and advisories (WWAs). WWAs are issued by the NWS regional Weather Forecast Offices (WFOs) and also the NWS Ocean Prediction Center, National Hurricane Center, Central Pacific Hurricane Center, and Storm Prediction Center. The NWS WWAs are organized on the nowCOAST™ map viewer and within this map service by hazardous condition/threat layer groups and then by the geographic area (i.e. coastal & inland, immediate coast or maritime) for which the WWA product is targeted. This was done to allow users to select WWAs for hazardous conditions that are important to their operations or activities. Please note that the Tropical Storm and Hurricane Warnings are provided in both the High Wind Hazards: Maritime Areas and Coastal & Inland Areas layer groups and the Flooding Hazards: Coastal Areas layer group. These warnings are included in the Flooding Hazards/Coastal Areas layer group because the NWS uses those warnings to inform the public that tropical storm or hurricane winds may be accompanied by significant coastal flooding but below the thresholds required for the issuance of a storm surge warning. In addition, a tropical storm or hurricane warning may remain in effect when dangerously high water or a combination of dangerously high water and waves continue, even though the winds may be less than hurricane or tropical storm force. The NWS does not issue a Coastal Flood Warning or Advisory when a tropical storm or hurricane warning is in effect; however that does not mean that there is not a significant coastal flooding threat. High Wind Hazards (Associated with Non-Tropical & Tropical Cyclones) Maritime Areas Brisk Wind Advisory Small Craft Advisory Small Craft Advisory for Winds Gale Watch Gale Warning Storm Watch Storm Warning Hurricane Force Wind Watch Hurricane Force Wind Warning Tropical Storm Watch Tropical Storm Warning Hurricane Watch Hurricane Warning Coastal & Inland Areas High Wind Watch Wind Advisory Lake Wind Advisory High Wind Warning Tropical Storm Watch Tropical Storm Warning Hurricane Watch Hurricane Warning Hazardous Seas, Surf, and Beach Conditions Maritime Areas Small Craft Advisory for Hazardous Seas Small Craft Advisory for Rough Bar Hazardous Seas Watch Hazardous Seas Warning Immediate Coast Beach Hazards Statement High Surf Advisory High Surf Warning Low Water Advisory Rip Current Statement Flooding Hazards Coastal Areas Coastal Flood Statement Coastal Flood Watch Coastal Flood Advisory Coastal Flood Warning Lakeshore Flood Watch Lakeshore Flood Advisory Lakeshore Flood Warning Lakeshore Flood Statement Storm Surge Watch Storm Surge Warning Tsunami Watch Tsunami Warning Tropical Storm Warning Hurricane Warning Inland Areas Flood Watch (Point) (also called River Flood Watch) Flood Watch (Areal) Flood Advisory (Point) (also called River Flood Advisory) Flood Advisory (Areal) Flood Warning (Point) (also called River Flood Warning) Flood Warning (Areal) Hydrologic Outlook Hydrologic Statement Reduced Visibility Hazards Maritime Areas Dense Fog Advisory Coastal & Inland Areas Ashfall Advisory Ashfall Warning Blowing Dust Advisory Blowing Dust Warning Dense Fog Advisory Dense Smoke Advisory Freezing Spray Hazards Maritime Areas Heavy Freezing Spray Watch Freezing Spray Advisory Heavy Freezing Spray Advisory Snow, Sleet, Freezing Rain, and Freezing Fog Hazards Coastal & Inland Areas Blizzard Watch Blizzard Warning Freezing Fog Advisory Freezing Rain Advisory Ice Storm Warning Lake-Effect Snow Watch Lake-Effect Snow Advisory Lake-Effect Snow Warning Winter Storm Watch Winter Weather Advisory Winter Storm Warning Cold and Heat Hazards Coastal & Inland Areas Excessive Cold Watch Excessive Cold Warning Excessive Heat Watch Heat Advisory Excessive Heat Warning Frost Advisory Freeze Watch Freeze Warning Wind Chill Advisory Wind Chill Warning Critical Wildfire Conditions Coastal & Inland Areas Fire Weather Watch Red Flag Warning Unhealthy Air Quality Coastal & Inland Areas Air Stagnation Advisory Air Quality Alerts from states are NOT available For descriptions of individual NWS watches, warnings, and advisories please see Section 2 of the NWS Reference Guide available at http://www.nws.noaa.gov/om/guide/Section2.pdf. Time Information This map service is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component. In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service. This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned. This service is configured with time coverage support, meaning that the service will always return the most relevant available data, if any, to the specified time value. For example, if the service contains data valid today at 12:00 and 12:10 UTC, but a map request specifies a time value of today at 12:07 UTC, the data valid at 12:10 UTC will be returned to the user. This behavior allows more flexibility for users, especially when displaying multiple time-enabled layers together despite slight differences in temporal resolution or update frequency. When interacting with this time-enabled service, only a single instantaneous time value should be specified in each request. If instead a time range is specified in a request (i.e. separate start time and end time values are given), the data returned may be different than what was intended. Care must be taken to ensure the time value specified in each request falls within the current time coverage of the service. Because this service is frequently updated as new data becomes available, the user must periodically determine the service's time extent. However, due to software limitations, the time extent of the service and

Open AccessWe develop a new map of the dissolved organic carbon (DOC) transformation rate ( (P_r )) over the contiguous United States. This map is derived by combining the USGS riverine DOC observations, the HWSD v1.2 top layer (0-30cm) soil organic carbon data, the watershed characteristics from two existing datasets (medium-resolution NHDplus and ScienceBase), and state-of-the-art machine learning techniques.

Feature layer generated from running the Dissolve Boundaries solution.

Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. Data used to produce the …Show full descriptionAbstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. Data used to produce the predicted Total Dissolved Solids map for the Hutton Aquifer and equivalents in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et.al., 2014). There are four layers in the Hutton Aquifer and equivalents Total Dissolved Solids map data A. Location of hydrochemistry samples (Point data, Shapefile) B. Predicted Concentration (Filled contours , Shapefile) C. Predicted Concentration Contours (Contours, Shapefile) D. Prediction Standard Error (Filled contours , Shapefile) The predicted values provide a regional based estimate and may be associated with considerable error. It is recommended that the predicted values are read together with the predicted error map, which provides an estimate of the absolute standard error associated with the predicted values at any point within the map. The predicted standard error map provides an absolute standard error associated with the predicted values at any point within the map. Please note this is not a relative error map and the concentration of a parameter needs to be considered when interpreting the map. Predicted standard error values are low where the concentration is low and there is a high density of samples. Predicted standard errors values can be high where the concentration is high and there is moderate variability between nearby samples or where there is a paucity of data. Concentrations are Total Dissolved Solids mg/L. Coordinate system is Lambert conformal conic GDA 1994, with central meridian 134 degrees longitude, standard parallels at -18 and -36 degrees latitude. The Hutton Aquifer and equivalents Total Dissolved Solids map is one of four hydrochemistry maps for the Hutton Aquifer and equivalents and 24 hydrochemistry maps in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et.al., 2014). This dataset and associated metadata can be obtained from www.ga.gov.au, using catalogue number 81709. References: Hitchon, B. and Brulotte, M. (1994): Culling criteria for ‘standard’ formation water analyses; Applied Geochemistry, v. 9, p. 637–645 Ransley, T., Radke, B., Feitz, A., Kellett, J., Owens, R., Bell, J. and Stewart, G., 2014. Hydrogeological Atlas of the Great Artesian Basin. Geoscience Australia. Canberra. [available from www.ga.gov.au using catalogue number 79790] Dataset History SOURCE DATA: Data was obtained from a variety of sources, as listed below: Water quality data from the Queensland groundwater database, Department of Environment and Resource Management Geological Society of Queensland water chemistry database (1970s to 1980s). Muller, PJ, Dale, NM (1985) Storage System for Groundwater Data Held by the Geological Survey of Queensland. GSQ Record 1985/47. Queensland. Geoscience Australia GAB hydrochemistry dataset 1973-1997. Published in Radke BM, Ferguson J, Cresswell RG, Ransley TR and Habermehl MA (2000) Hydrochemistry and implied hydrodynamics of the Cadna-owie - Hooray Aquifer, Great Artesian Basin, Australia. Canberra, Bureau of Rural Sciences: xiv, 229p. Feitz, A.J., Ransley, T.R., Dunsmore, R., Kuske, T.J., Hodgkinson, J., Preda, M., Spulak, R., Dixon, O. & Draper, J., 2014. Geoscience Australia and Geological Survey of Queensland Surat and Bowen Basins Groundwater Surveys Hydrochemistry Dataset (2009-2011). Geoscience Australia, Canberra Australia Water quality data from the Office of Groundwater Impact Assessment, Department of Natural Resources and Mines, Queensland Government Geoscience Australia (2010) Hydrogeochemical collection. A compilation of quality controlled groundwater data taken from well completion reports from QLD and NSW. Water quality data from the Office of Groundwater Impact Assessment, Department of Natural Resources and Mines, Queensland Government BOUNDARIES: Data covers the extent of the Hutton Aquifer and equivalents as defined in Great Artesian Basin - Hutton Aquifer and equivalents - Thickness and Extent dataset (Available from www.ga.gov.au using catalogue number 81682). METHOD: Groundwater chemistry data was compiled from the data sources listed above. Data was imported into ESRI ArcGIS (ArcMap 10) as data point sets and used to create a predicted values surface using an ordinary kriging method within the Geostatistical Analyst extension. A log transform was applied to the Alkalinity, TDS, Na, SO4, Mg, Ca, K, F, Cl, Cl36 data prior to kriging. No transform was applied to the 13C, 18O, 2H, pH data prior to kriging. The geostatistical model was optimized using cross validation. The search neighbourhood was extended to a 1 degree radius, comprising of 4 sectors (N, S, E and W) with a minimum and maximum of 3 and 8 neighbours, respectively, per sector. The predicted values surface was exported to a vector format (Shapefile) and clipped to the aquifer boundaries and clipped further where there was no data within 100 km. QAQC: Prior to data analysis all hydrochemistry data was assessed for reliability by Quality Assurance/Quality Control (QA/QC) procedures. A data audit and verification were performed using various quality checking procedures including identification and verification of outliers. The ionic balance of each analysis was checked, and where the ionic charge balance differed by greater than 10%, these analyses were deemed unacceptable and were not considered for future analysis. Data that passed the initial QA/QC procedures were checked against borehole construction and stratigraphic records to determine aquifer intercepts. Data were discarded in cases where there was no recorded location information or screen interval/depth information (to cross reference with borehole stratigraphy). Groundwater chemistry data was sourced from multiple studies, government databases, and companies. Many of the studies used sub-sets of the same data. All duplicates were removed before mapping and analysis. The differences between data sources had to be reconciled to ensure that maximum value of the data was retained and for errors in the transcription to be avoided. This precluded any automated processing system. Random checks were routinely made against the source data to ensure quality of the process. Some source data was in the form of thousands of consecutive rows and required python scripts or detailed table manipulations to correctly re-format the information and re-produce records with all the well data, its location and hydrochemical data for a particular sample date on one row in the collated Excel spreadsheet. Alkalinity measurements, in particular, were often reported differently between studies and even within the same database and required conversion to a common unit. All data before 1960 was discarded. The study uses a data collection compiled from petroleum well completion reports from QLD and NSW. This data underwent a thorough QC process to ensure that drilling mud contaminated samples were excluded, based on the procedure described by Hitchon, B. & Brulotte, M. (1994). Less than 5% of the samples compiled passed the QC procedure, but these provide invaluable insight into the chemistry of very deep parts of the aquifers (typically 1 - 2km deep). Where multiple samples have been taken at the same well, an average of the analyses was used in the kriging but outliers were removed. Outliers were identified by looking for large differences between predicted and measured samples. Excessively high values compared to predicted values and typical measurements at the same bore were discarded. Dataset Citation Geoscience Australia (2015) Hutton Aquifer and equivalents Total Dissolved Solids map: Data. Bioregional Assessment Source Dataset. Viewed 11 April 2016, http://data.bioregionalassessments.gov.au/dataset/f5f16389-d97e-46b3-bd43-83255acf257d.

The goal of this study was to develop a suite of inter-related water quality monitoring approaches capable of modeling and estimating spatial and temporal gradients of particulate and dissolved total mercury (THg) concentration, and particulate and dissolved methyl mercury (MeHg), concentration, in surface waters across the Sacramento / San Joaquin River Delta (SSJRD). This suite of monitoring approaches included: a) data collection at fixed continuous monitoring stations (CMS) outfitted with in-situ sensors, b) spatial mapping using boat-mounted flow-through sensors, and c) satellite-based remote sensing. The focus of this specific Child Page is to document a series of derived remote sensing products for turbidity and fluorescent dissolved organic matter (fDOM) based on Sentinel 2 (S2) A/B Multispectral Imager (MSI) imagery acquired between June 1, 2019 and May 31, 2021 for the SSJRD. These remote sensing products were developed using S2 A/B Level 1C input data with less than 25 ...

Overview map of the spatial distribution of dissolved manganese concentrations in the groundwater of Lower Saxony. The map shows the area-based evaluation of 1540 groundwater analyses from depths of 20 – 50 m below the terrain surface. The colour-graded overview map represents only the spatial distribution of the measured manganese concentrations and does not take into account any influences of the geological structures and properties of the subsoil. The interpolation method of inverse distance weighting was used to create the map.

Map of seasonal averages of dissolved inorganic Nitrogen (uM) indicator for eutrophication for the past 10 years (2005-2014) in the Atlantic basin. It will be generated using in situ measurements of the different parameteres required to assess the dissolved inorganic Nitrogen indicator and the OSPAR Convention Common procedure methodology (OSPAR 2013, Common Procedure for the Identification of the Eutrophication Status of the OSPAR Maritime Area. Agreement 2013-08. 67 pp).

Overview map of the spatial distribution of dissolved iron concentrations in the groundwater of Lower Saxony. The map shows the area-based evaluation of 1180 groundwater analyses from depths from 50 m below the terrain surface. The colour-graded overview map represents only the spatial distribution of the measured iron concentrations and does not take into account any influences on the geological structures and properties of the substrate. The interpolation method of inverse distance weighting was used to create the map.

ADEOS-II/GLI L3 STA Map Absorption of colored dissolved organic matter (1month,9km) is obtained from the GLI (Global-Imager) sensor onboard ADEOS-II and produced by the Japan Aerospace Exploration Agency (JAXA). Global environment change has become a worldwide concern in recent years. In order to clarify these environmental changes, the Advanced Earth Observing Satellite (ADEOS-II, renamed "Midori II" after launch) has been developed for the purpose of monitoring the Earth environment using remote sensing technology from space. Midori II carries mission instruments that are particularly dedicated to clarify the water energy cycle and the carbon cycle, and is expected to be utilized for international climate change research programs. GLI an optical sensor that observes the reflected solar radiation from the Earth's surface, including land, oceans and clouds and/or infrared radiation with a multi-channel system for measuring the biological content. The SGLI has a swath of 1600 km. This product includes CDOM absorption at 440nm. The physical unit is 1/m. This product is the representative values, which are estimated from level 3 binned products and projected onto map. The provided format is HDF. The spatial resolution is 9 km. The statistical period is 1month, also 1 day and 8 days statistics are available. Map projection is EQR. The generation unit is global. The current version of the product is "Version 2".

A results paper for this dataset is in preparation for the Geoscience Data Journal as Ito T. (2021) Optimal interpolation of global dissolved oxygen: 1965-2015.

We develop two new maps of the dissolved organic carbon (DOC) transformation rate ((P_r)) over the contiguous United States. Those maps are derived by combining the USGS riverine DOC observations, soil organic carbon (SOC) data from two sources—HWSD v1.2 and SoilGrids 2.0, and the watershed characteristics from two existing datasets medium-resolution NHDplus and ScienceBase, and state-of-the-art machine learning techniques.

GCOM-C/SGLI L3 Map Colored dissolved organic matter (8-Days,1/24 deg) is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. Level 3 products are defined to be products derived from Level 1B and Level 2 products by statistically processing the Level 1B and Level 2 products in time and space domains. This dataset is 8 days map-projected statistics product. This dataset includes colored dissolved organic matter. The physical quantity unit is m-1. The stored statistics values are average (AVE) and quality flag (QA_flag). The provided format is HDF5. The Spatial resolution is 1/24 degree. The statistical period is 8 days, also 1 day and 1 month statistics are available. The projection method is EQR. The generation unit is Global. The current version of the product is Version 3. The Version 2 is also available.

Set of maps showing dissolved oxygen by depth linearly interpolated from CARS2000 mean and seasonal fields to 0.1 degree spaced grid. These maps form part of a series of maps showing the variation of temperature, salinity, oxygen, silicate, phosphate, and nitrate in Australia's Oceans. Each feature in the series has been separately mapped at depths of 0, 150, 500, 1000 and 2000 metres. These maps have been produced by CSIRO for the National Oceans Office, as part of an ongoing commitment to natural resource planning and management through the 'National Marine Bioregionalisation' project.

Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. Data used to produce the …Show full descriptionAbstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. Data used to produce the predicted Total Dissolved Solids map for the Cadna-owie - Hooray Aquifer in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et.al., 2014). There are four layers in the Cadna-owie - Hooray Aquifer Total Dissolved Solids map data A. Location of hydrochemistry samples (Point data, Shapefile) B. Predicted Concentration (Filled contours , Shapefile) C. Predicted Concentration Contours (Contours, Shapefile) D. Prediction Standard Error (Filled contours , Shapefile) The predicted values provide a regional based estimate and may be associated with considerable error. It is recommended that the predicted values are read together with the predicted error map, which provides an estimate of the absolute standard error associated with the predicted values at any point within the map. The predicted standard error map provides an absolute standard error associated with the predicted values at any point within the map. Please note this is not a relative error map and the concentration of a parameter needs to be considered when interpreting the map. Predicted standard error values are low where the concentration is low and there is a high density of samples. Predicted standard errors values can be high where the concentration is high and there is moderate variability between nearby samples or where there is a paucity of data. Concentrations are Total Dissolved Solids mg/L. Coordinate system is Lambert conformal conic GDA 1994, with central meridian 134 degrees longitude, standard parallels at -18 and -36 degrees latitude. The Cadna-owie - Hooray Aquifer Total Dissolved Solids map is one of 14 hydrochemistry maps for the Cadna-owie - Hooray Aquifer and 24 hydrochemistry maps in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et. al., 2014). This dataset and associated metadata can be obtained from www.ga.gov.au, using catalogue number 81693. References: Hitchon, B. and Brulotte, M. (1994): Culling criteria for ‘standard’ formation water analyses; Applied Geochemistry, v. 9, p. 637–645 Ransley, T., Radke, B., Feitz, A., Kellett, J., Owens, R., Bell, J. and Stewart, G., 2014. Hydrogeological Atlas of the Great Artesian Basin. Geoscience Australia. Canberra. [available from www.ga.gov.au using catalogue number 79790] Dataset History SOURCE DATA: Data was obtained from a variety of sources, as listed below: Water quality data from the Queensland groundwater database, Department of Environment and Resource Management Geological Society of Queensland water chemistry database (1970s to 1980s). Muller, PJ, Dale, NM (1985) Storage System for Groundwater Data Held by the Geological Survey of Queensland. GSQ Record 1985/47. Queensland. Geoscience Australia GAB hydrochemistry dataset 1973-1997. Published in Radke BM, Ferguson J, Cresswell RG, Ransley TR and Habermehl MA (2000) Hydrochemistry and implied hydrodynamics of the Cadna-owie - Hooray Aquifer, Great Artesian Basin, Australia. Canberra, Bureau of Rural Sciences: xiv, 229p. Feitz, A.J., Ransley, T.R., Dunsmore, R., Kuske, T.J., Hodgkinson, J., Preda, M., Spulak, R., Dixon, O. & Draper, J., 2014. Geoscience Australia and Geological Survey of Queensland Surat and Bowen Basins Groundwater Surveys Hydrochemistry Dataset (2009-2011). Geoscience Australia, Canberra Australia Water quality data from the Office of Groundwater Impact Assessment, Department of Natural Resources and Mines, Queensland Government Geoscience Australia (2010) Hydrogeochemical collection. A compilation of quality controlled groundwater data taken from well completion reports from QLD and NSW. Water quality data from the Office of Groundwater Impact Assessment, Department of Natural Resources and Mines, Queensland Government BOUNDARIES: Data covers the extent of the Cadna-owie-Hooray Aquifer and Equivalents as defined in Great Artesian Basin - Cadna-owie-Hooray Aquifer and Equivalents - Thickness and Extent dataset (Available from www.ga.gov.au using catalogue number 81678) METHOD: Groundwater chemistry data was compiled from the data sources listed above. Data was imported into ESRI ArcGIS (ArcMap 10) as data point sets and used to create a predicted values surface using an ordinary kriging method within the Geostatistical Analyst extension. A log transform was applied to the Alkalinity, TDS, Na, SO4, Mg, Ca, K, F, Cl, Cl36 data prior to kriging. No transform was applied to the 13C, 18O, 2H, pH data prior to kriging. The geostatistical model was optimized using cross validation. The search neighbourhood was extended to a 1 degree radius, comprising of 4 sectors (N, S, E and W) with a minimum and maximum of 3 and 8 neighbours, respectively, per sector. The predicted values surface was exported to a vector format (Shapefile) and clipped to the aquifer boundaries. QAQC: Prior to data analysis all hydrochemistry data was assessed for reliability by Quality Assurance/Quality Control (QA/QC) procedures. A data audit and verification were performed using various quality checking procedures including identification and verification of outliers. The ionic balance of each analysis was checked, and where the ionic charge balance differed by greater than 10%, these analyses were deemed unacceptable and were not considered for future analysis. Data that passed the initial QA/QC procedures were checked against borehole construction and stratigraphic records to determine aquifer intercepts. Data were discarded in cases where there was no recorded location information or screen interval/depth information (to cross reference with borehole stratigraphy). One exception was chemistry data obtained from the NSW Governments Triton database. Groundwater chemistry data obtained from bore records in the Triton database that was also identified as GAB bores in the NSW Governments Pinneena database were assumed to be in the Pilliga Sandstone and were allocated to the Cadna-owie Hooray equivalent aquifer, despite many not recording depth information. Groundwater chemistry data was sourced from multiple studies, government databases, and companies. Many of the studies used sub-sets of the same data. All duplicates were removed before mapping and analysis. The differences between data sources had to be reconciled to ensure that maximum value of the data was retained and for errors in the transcription to be avoided. This precluded any automated processing system. Random checks were routinely made against the source data to ensure quality of the process. Some source data was in the form of thousands of consecutive rows and required python scripts or detailed table manipulations to correctly re-format the information and re-produce records with all the well data, its location and hydrochemical data for a particular sample date on one row in the collated Excel spreadsheet. Alkalinity measurements, in particular, were often reported differently between studies and even within the same database and required conversion to a common unit. All data before 1960 was discarded. The study uses a data collection compiled from petroleum well completion reports from QLD and NSW. This data underwent a thorough QC process to ensure that drilling mud contaminated samples were excluded, based on the procedure described by Hitchon, B. & Brulotte, M. (1994). Less than 5% of the samples compiled passed the QC procedure, but these provide invaluable insight into the chemistry of very deep parts of the aquifers (typically 1 - 2km deep). Where multiple samples have been taken at the same well, an average of the analyses was used in the kriging but outliers were removed. Outliers were identified by looking for large differences between predicted and measured samples. Excessively high values compared to predicted values and typical measurements at the same bore were discarded. Dataset Citation Geoscience Australia (2015) GABATLAS - Cadna-owie - Hooray Aquifer Total Dissolved Solids map: Data. Bioregional Assessment Source Dataset. Viewed 11 April 2016, http://data.bioregionalassessments.gov.au/dataset/5044a067-35d1-4d6d-98a6-17974aa9226a.

The NOAA Hypoxia Watch project provides near-real-time, web-based maps of dissolved oxygen near the sea floor over the Texas-Louisiana continental shelf during a period that extends from mid-June to mid-July. The NOAA National Marine Fisheries Service Mississippi Laboratories at Pascagoula and Stennis Space Center and the NOAA's National Centers for Environmental Information (NCEI) began the Hypoxia Watch project in 2001. Scientists aboard the NOAA Research Vessel Oregon II measure seawater properties, such as water temperature, salinity, chlorophyll, and dissolved oxygen, as the Oregon II cruises the waters south of Pascagoula, MS and then makes its way from Brownsville, Texas, to the mouth of the Mississippi River. A scientist aboard the ship processes the measurements from electronic dissolved oxygen sensors, checks the measurements periodically with chemical analyses of the seawater, then sends the data by FTP to the NCEI approximately every three to four days. Physical Scientists at NCEI transform the dissolved oxygen measurements into contour maps, which identify areas of low oxygen, or hypoxia. During the cruise, as the data is received from the ship, NCEI generates new maps and publishes them on the web. The first map will usually cover an area off the Mississippi coast, successive maps will add areas of the continental shelf from Brownsville to Corpus Christi, and the final map will usually cover the entire Texas-Louisiana-Mississippi coast. Maps are published every three to four days from approximately June 22 to July 20.