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Regional Freshwater Index Layers
Description: The Regional Freshwater Index Layers dataset is composed of five single-band raster layers in GeoTIFF format. Each layer corresponds to a marine region, which generally coincide with the following layers from the Species Distribution Modelling Boundaries dataset: Nearshore_HG, Nearshore_NCC, Nearshore_QCS, Nearshore_WCVI, and Shelf_SalishSea. The main purpose of the dataset is to supplement existing layers that are used for species distribution modelling in the Pacific nearshore marine environment. Each regional freshwater index layer has the same spatial resolution and extent as other predictor layers for the corresponding region. While salinity layers exist from oceanographic models, they may not capture local difference from smaller scale rivers and streams entering the marine environment. Therefore, these layers are meant to complement salinity layers and are not suitable as a replacement for salinity data in species modelling. Methods: The cell values represent an estimate of freshwater influence on a 0-1 scale, where a higher value represents a greater level of freshwater influence. Details on how these values are determined is described in the supplemental information section of the metadata. The main data source for these derived products is the B.C. Freshwater Atlas, including the stream network and river polygons layers. Uncertainties: The values in the rasters are not a measure of salinity. The units are an index representing the level of freshwater influence weighted by the stream order and rescaled across regions on a 0-1 scale where only the region with the greatest value has a range of values 0-1 and the other regions are scaled relatively. This is done to ensure that values in one region can be compared to values in another region. As a result, some regions have very small values because the Salish Sea with the Fraser River is dominant, even after applying a rescale factor to the data.
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Water Modelling Regions
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Export DataThis layer represents Regions for stochastic climate and water modelling for NSW Regional Water Strategies. These Regions contain different type of modelling data such as Climate Data, Water Models and Modelled Data.Previous SEED service moved from 10.7 to 11. 1 Portal. Waiting for Metadata from DPIE.Metadata Portal Metadata InformationContent TitleWater Modelling RegionsContent TypeHosted Feature LayerDescriptionWater Modelling Regions in NSW.Initial Publication Date28/08/2024Data Currency28/08/2024Data Update Frequency APIContent Source APIFile TypeWeb Feature ServiceAttributionData Theme, Classification or Relationship to other DatasetsAccuracySpatial Reference System (dataset)GDA94Spatial Reference System (web service)OtherWGS84 Equivalent ToGDA94Spatial ExtentContent LineageData ClassificationUnclassifiedData Access PolicyOpenData QualityTerms and ConditionsCreative CommonStandard and SpecificationData CustodianNSW Department of Climate Change, Energy, Environment and WaterPoint of ContactNSW Department of Climate Change, Energy, Environment and WaterData AggregatorData DistributorAdditional Supporting InformationTRIM Number
National Aquatic Resources Survey datasets
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The 4 resource surveys (coastal, rivers and streams, lakes and reservoirs, and wetlands) each have datasets covering the biological, chemical, physical habitat, hydrologic and watershed data. This dataset is associated with the following publications: Stoddard , J., J. Van Sickle, A. Herlihy, J. Brahney, S. Paulsen , D. Peck , R. Mitchell , and A. Pollard. Continental-scale increase in stream and lake phosphorus: Are oligotrophic systems disappearing in the U.S.?. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(7): 3409-3415, (2016). Herlihy, A., M. Kentula, T. Magee, G. Lomnicky, A. Nahlik, and G. Serenbetz. Striving for consistency in the National Wetland Condition Assessment: developing a reference condition approach for assessing wetlands at a continental scale. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 327, (2019). Magee, T., K. Blocksom, and S. Fennessy. A national-scale vegetation multimetric index (VMMI) as an indicator of wetland condition across the conterminous United States.. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 322, (2019). Herlihy, A., J. Sifneos, G. Lomnicky, A. Nahlik, M. Kentula, T. Magee, M. Weber, and A. Trebitz. The response of wetland quality indicators to human disturbance indicators across the United States. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 296, (2019). Herlihy, A., S. Paulsen, M. Kentula, T. Magee, A. Nahlik, and G. Lomnicky. Assessing the relative and attributable risk of stressors to wetland condition across the conterminous United States. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 320, (2019). Lomnicky, G., A.T. Herlihy, and P. Kaufmann. Quantifying the extent of human disturbance activities and anthropogenic stressors in wetlands across the conterminous United States: results from the National Wetland Condition Assessment. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 324, (2019). Bowen, G., A. Putman, J.R. Brooks, D. Bowling, E. Oerter, and S. Good. Inferring the source of evaporated waters using stable H and O isotopes.. OECOLOGIA. Springer, New York, NY, USA, 187(4): 1025-1039, (2018). Fox, E., J. Ver Hoef, and T. Olsen. Comparing Spatial Regression to Random Forests for Large Environmental Data Sets.. PLoS ONE. Public Library of Science, San Francisco, CA, USA, 15(3): e0229509, (2020). Nahlik, A., K. Blocksom, A. Herlihy, M. Kentula, T. Magee, and S. Paulsen. Use of national-scale data to examine human-mediated additions of heavy metals to wetland soils of the US. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 336, (2019). Kentula, M., and S. Paulsen. The 2011 National Wetland Condition Assessment: Overview and an Invitation. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 325, (2019). Magee, T., K. Blocksom, A. Herlihy, and A. Nahlik. Characterizing nonnative plants in wetlands across the conterminous United States. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 344, (2019). Feio, M., R. Hughes, M. Callisto, S.J. Nichols, O.N. Odume, B.R. Quintella, M. Kuemmerlen, F.C. Aguiar, S.F.P. Almeida, P. Alonso-EguíaLis , F.O. Arimoro, F.J. Dyer , J.S. Harding , S. Jang , P. Kaufmann, S. Lee, J. Li, D.R. Macedo, A. Mendes, N. Mercado-Silva , W. Monk, K. Nakamura, G.G. Ndiritu , R. Ogden , M. Peat , T.B. Reynoldson , B. Rios-Touma , P. Segurado , and A.G. Yates. The biological assessment and rehabilitation of the world’s rivers: an overview. WATER. MDPI AG, Basel, SWITZERLAND, 13(3): 371, (2021).
Surface Hydrology Polygons (Regional)
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The Surface Hydrology polygon (Regional) dataset provides a set of related features classes to be used as the basis of the production of consistent hydrological information. This dataset contains a geometric representation of major hydrographic polygon elements - both natural and artificial. This dataset is the best available data supplied by Jurisdictions and aggregated by Geoscience Australia. It is intended for defining hydrological features wtih attributes.
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