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미국
Wetland
This dataset represents wetland CEFs identified during the development review process since 1995. Prior to 1995, data is either unavailable or lost.Wetland CEFs were digitized from construction plans, environmental assessments, and City of Austin staff field observations. Features were digitized into a versioned SDE database in ArcMap. Wetland delineation may be determined through a process of negotiation with land development interests and generally reflect the most protective arrangement that could be obtained. Additionally, “fringe wetlands” were drawn using a standard 2’ width on either side of a waterway.
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Tully constructed wetland – Water quality and hydrological monitoring data from 2023 – 2024 (GBRF WQ-TJ-006, Terrain NRM)
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This dataset consists of three Excel files containing multiple worksheets of data from a monitoring period starting in July 2023 and ending in April 2024, along with a set of three technical reports containing the monitoring methodology and findings generated from these datasets. The datasets capture water quality and hydrological data from a constructed wetland in Tully, within the Wet Tropics region of Queensland, Australia. The data were collected as part of a project assessing the wetland’s water treatment potential, specifically, its ability to remove dissolved inorganic nitrogen (DIN) and total suspended solids (TSS) from agricultural runoff. The Excel files include groundwater and surface water data from continuous, routine and event-based monitoring, including physicochemical parameters, nitrogen levels, total suspended solids (TSS), volatile suspended solids (VSS), particle size distribution, water velocity, local rainfall, and water heights at various sampling points. Informative one-off measurements include bore slug tests and cross-sectional area assessments of surface water sampling points. This dataset provides valuable insights into the hydrological and chemical characteristics of this wetland, enabling a comprehensive evaluation of its function and performance as treatment systems in a wet tropical environment, over a single wet season. The dataset supplied herein is derived from the Tully-Johnstone Wetland Monitoring Project conducted from July 2023 to March 2024. The primary purpose of the dataset is to assess the efficacy of constructed wetlands in the Wet Tropics region at removing dissolved inorganic nitrogen (DIN) and sediment from agricultural runoff. The data were collected to inform the development and validation of wetland models, to better understand the effectiveness of treatment wetlands at a landscape scale. The dataset is available on eAtlas for use by scientists and water quality managers, providing insights into water balance, contaminant removal, and hydrological processes occurring within a constructed wetland. The Tully wetland was constructed in 2019 as part of the Wet Tropics Major Integrated Project (WTMIP) and is known as Landscape Wetland #1 (LW01). This wetland was designed and constructed to optimise natural processes for improving water quality in the Great Barrier Reef (GBR) catchments. Further information on the treatment systems installed and monitored during the WTMIP can be found at https://mip.terrain.org.au/resources/. The 2023-24 monitoring activities, funded by the partnership between the Australian Government’s Reef Trust and the Great Barrier Reef Foundation, built on previous datasets from the WTMIP (2019-2021) and post-WTMIP monitoring (2021-2023), both funded by the Queensland Government, Office of the Great Barrier Reef. Methods: The methods used to gather and process this dataset follow a comprehensive monitoring plan designed according to the available funding. The monitoring plan incorporated recommendations from a multidisciplinary team of scientific partners and was aligned with established guidelines for wetland nitrogen removal monitoring. Data were collected from a constructed wetland in Tully, within the Wet Tropics region of Queensland, Australia. Data were collected from July 2023 to March 2024, including both routine and event-based sampling, focusing on groundwater and surface water quality, precipitation, and groundwater-surface water interactions. A combination of manual grab sampling and automatic ISCO Avalanche autosamplers was employed for surface water monitoring. The autosamplers were triggered by rising water levels, with the capacity to adjust sampling intervals to optimise coverage over the hydrograph during stream flow events. High-frequency surface water level recordings were gathered using Seametrics PT12 pressure and temperature sensors, telemetered continuously to the online platform eagle.io, while manual water velocity measurements were
L5 2009 GOM Fractional Land FAV SAV Water
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These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
L5 1997 GOM Fractional Land FAV SAV Water
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These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
L5 1997 GOM Fractional Land FAV SAV Water
공공데이터포털
These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
Gavan McGrath - Southwest Wetland Monitoring Program: Water Quality and Water Level Data (DBCA-077)
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A total of 159 wetlands were monitored on and off between 1977 and 2019 as part of the Southwest Wetland Monitoring Program, by the Department of Biodiversity Conservation and Attractions (DBCA) and its predecessors. Details of the monitoring program and the results can be found in Lane et al., (2017) and references therein (J.A.K. Lane, A.G. Clarke & Y.C. Winchcombe, 2017. South west wetlands monitoring program, 1977-2016. Department of Biodiversity Conservation and Attractions https://library.dbca.wa.gov.au/#record/142545). The data consists of a table of wetland site information, a table of water level and water quality measurements and a file describing the tables columns.
Victorian Wetland Inventory (Current Mapped Wetlands NVR Map)
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This dataset is a copy of the WETLAND_CURRENT dataset prior to the 2025 update. Polygons showing the extent and types of wetlands in Victoria. WETLAND_CURRENT was created in 2013 and was derived from WETLAND_1994 (the state's first wetland geospatial inventory) and several local and regional wetland datasets. A number of updates have occurred to the dataset during 2014, 2017 and 2021. The 2014 update incorporated new regional mapping, some supplementary mapping and repositioning of planimetrically inaccurate wetlands. Supplementary mapping involved identifying and delineating wetlands which had not previously been mapped, but did not modify the extent of existing wetlands. It was undertaken primarily using aerial photograph interpretation (photos from 2007 to 2011) supplemented with existing geospatial datasets that provided context and informed the identification of wetland boundaries (e.g. vegetation mapping, topography). Wetlands were classified (according to the new classification framework) into primary categories based on wetland system type, salinity regime, water regime, water source, dominant vegetation and wetland origin. The 2017 update improved the accuracy of the layer by updating wetland mapping and attributes in the Melbourne area and for alpine bogs and fens in East and West Gippsland catchment regions. It also involved correcting inaccurate classification attributes and correcting wetland polygons for individual wetlands based on new data and feedback from wetland inventory users. The 2021 update incorporates new mapping and refinements to existing wetland polygons for several regional wetland datasets. These include Tootgarook Swamp, Alpine Bogs, Mitchell River Floodplain Wetlands, Melbourne Water Billabongs and Mallee CMA Wetlands. The dataset currently consists of 38,799 polygons totalling 784,120 ha.
L5 1998 GOM Fractional Land FAV SAV Water
공공데이터포털
These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.