This dataset contains 50-ft contours for the Hot Springs shallowest unit of the Ouachita Mountains aquifer system potentiometric-surface map. The potentiometric-surface shows altitude at which the water level would have risen in tightly-cased wells and represents synoptic conditions during the summer of 2017. Contours were constructed from 59 water-level measurements measured in selected wells (locations in the well point dataset). Major streams and creeks were selected in the study area from the USGS National Hydrography Dataset (U.S. Geological Survey, 2017), and the spring point dataset with 18 spring altitudes calculated from 10-meter digital elevation model (DEM) data (U.S. Geological Survey, 2015; U.S. Geological Survey, 2016). After collecting, processing, and plotting the data, a potentiometric surface was generated using the interpolation method Topo to Raster in ArcMap 10.5 (Esri, 2017a). This tool is specifically designed for the creation of digital elevation models and imposes constraints that ensure a connected drainage structure and a correct representation of the surface from the provided contour data (Esri, 2017a). Once the raster surface was created, 50-ft contour interval were generated using Contour (Spatial Analyst), a spatial analyst tool (available through ArcGIS 3D Analyst toolbox) that creates a line-feature class of contours (isolines) from the raster surface (Esri, 2017b). The Topo to Raster and contouring done by ArcMap 10.5 is a rapid way to interpolate data, but computer programs do not account for hydrologic connections between groundwater and surface water. For this reason, some contours were manually adjusted based on topographical influence, a comparison with the potentiometric surface of Kresse and Hays (2009), and data-point water-level altitudes to more accurately represent the potentiometric surface. Select References: Esri, 2017a, How Topo to Raster works—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/how-topo-to-raster-works.htm. Esri, 2017b, Contour—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro Raster Surface toolset at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/contour.htm. Kresse, T.M., and Hays, P.D., 2009, Geochemistry, Comparative Analysis, and Physical and Chemical Characteristics of the Thermal Waters East of Hot Springs National Park, Arkansas, 2006-09: U.S. Geological Survey 2009–5263, 48 p., accessed November 28, 2017, at https://pubs.usgs.gov/sir/2009/5263/. U.S. Geological Survey, 2015, USGS NED 1 arc-second n35w094 1 x 1 degree ArcGrid 2015, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html. U.S. Geological Survey, 2016, USGS NED 1 arc-second n35w093 1 x 1 degree ArcGrid 2016, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html.

The Seabed Landform Classification Toolset is a GIS toolbox designed to classify seabed landforms on continental and island shelf settings. The user is guided through a series of classification steps within an ArcGIS toolbox to classify prominent seabed features termed ‘seabed landforms’, which characterise the morphology of the seabed surface. Seabed landforms include reefs/banks, peaks, plains, scarps, channels and depressions. Plain areas can additionally be classified into high and low features at localised and broad scales to capture features within plain surfaces. Common variables for seabed classification are utilised, including slope, bathymetric position index and ruggedness, and a series of procedures are applied to identify reef outcrops and minimise noise. The classification approach applies a whole-seascape classification which is aimed to offer a flexible and user-friendly approach to extract key seabed features from high-resolution shelf bathymetry data.

This toolset was developed using ESRI ArcGIS Desktop 10.8 and requires an Advanced licence with Spatial Analyst and 3D Analyst and extensions. It utilises scripts within the Benthic Terrain Modeler toolset (Walbridge et al. 2018) and Geomorphometry and Gradients Metrics Toolbox (Evans et al., 2014).

Please read the User Guide and supporting documentation for information on how to run the toolset. A web explainer is available at: https://arcg.is/1Tqmv50

The Seabed Landform Classification Toolset is also available for download on GitHub (https://github.com/LinklaterM/Seabed-Landforms-Classification-Toolset/).

The toolset was developed by the Coastal and Marine Team, NSW Department of Climate Change, Energy, the Environment and Water (formerly NSW Department of Planning and Environment), funded by NSW Climate Change Fund through the Coastal Management Funding Package and the Marine Estate Management Authority.

Please cite this toolset as: Linklater, M, Morris, B.D. and Hanslow, D.J. (2023) Classification of seabed landforms on continental and island shelves. Frontiers of Marine Science, 10, https://doi.org/10.3389/fmars.2023.1258556.

Other toolsets utilised by the Seabed Landform Classification Toolset include: Benthic Terrain Modeler: Walbridge, S., Slocum, N., Pobuda, M., and Wright, D. J. (2018). Unified geomorphological analysis workflows with Benthic Terrain Modeler. Geosciences 8, 94. Geomorphometry and Gradients Metrics Toolbox: Evans, J., Oakleaf, J., and Cushman, S. (2014). An ArcGIS Toolbox for Surface Gradient and Geomorphometric Modeling, Version 2.0-0. https://github.com/jeffreyevans/GradientMetrics.

Moisture Index (MI) for the state of Utah is calculated from a spatial raster of annual actual (ETact) and potential (PET) evapotranspiration data from 2000 to 2013 derived from the MODIS instrumentation (Mu, Zhao, & Running, 2011; Mu, Zhao, & Running, 2013; Numerical Terradynamic Simulation Group, 2013). Moisture Index (MI) was created to compare the suitability of settlement locations throughout Utah to explain initial Euro-American settlement of the region. MI is one of two proxies created specifically for Utah for comparison of environmental productivity throughout the state. Moisture index (MI) was originally used by Ramankutty et al. (2002) on a global scale to understand probability of cultivation based on a series of environmental factors. The Ramankutty et al. (2002) methods were used to build a regional proxy of agricultural suitability for the state of Utah. Adapting the methods in Ramankutty et al. (2002), we were able to create a higher resolution dataset of MI specific to the state of Utah. Unlike S, MI only accounts for evapotranspiration rates.The Moisture Index is calculated as: MI = ETact / PET Where ETact is the actual evapotranspiration and PET is the potential evapotranspiration. This calculation results in a zero to one index representing global variation in moisture. MI is calculated for the study area (Utah) using a raster of annual actual (ETact) and potential (PET) evapotranspiration data from 2000 to 2013 derived from the MODIS instrumentation (Mu, Zhao, & Running, 2011; Mu, Zhao, & Running, 2013; Numerical Terradynamic Simulation Group, 2013). Using the ArcMap 10.3.1 Raster Calculator (Spatial Analyst), a raster dataset is created at a resolution of 2.6 kilometer square, which contain values representative of the average Moisture Index for Utah over a fourteen year period (ESRI, 2015). The data were collected remotely by satellite (MODIS) and represents reflective surfaces (urban areas, lakes, and the Utah Salt Flats) as null values in the dataset. Areas of null values that were not bodies of water are interpolated using Inverse Distance Weighting (3d Analyst) in ArcMap 10.3.1 (ESRI, 2015). Download the moisture index (MI) data below. If you have any questions or concerns, please contact me at PYaworsky89@gmail.com. Citations ESRI. (2015). ArcGIS Desktop: Release (Version 10.3.1). Redlands, CA: Environmental Systems Research Institute. Mu, Q., Zhao, M., & Running, S. W. (2013). MODIS Global Terrestrial Evapotranspiration (ET) Product (NASA MOD16A2/A3). Algorithm Theoretical Basis Document, Collection, 5. Retrieved from http://www.ntsg.umt.edu/sites/ntsg.umt.edu/files/MOD16_ATBD.pdf Mu, Q., Zhao, M., & Running, S. W. (2011). Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sensing of Environment, 115(8), 1781–1800. Numerical Terradynamic Simulation Group. (2013, July 29). MODIS Global Evapotranspiration Project (MOD16). University of Montana. Ramankutty, N., Foley, J. A., Norman, J., & Mcsweeney, K. (2002). The global distribution of cultivable lands: current patterns and sensitivity to possible climate change. Global Ecology and Biogeography, 11(5), 377–392. http://doi.org/10.1046/j.1466-822x.2002.00294.x

Thickness of Paleogene-Neogene sequence overlying the Great Artesian Basin

Data is available as isopachs and raster. Isopachs are in Shapefile format. Rasters are in both ESRI grid and ASCII grid formats.

This GIS data set was produced for the Great Artesian Basin Water Resource Assessment and used in: Figure 3.2 of Ransley TR and Smerdon BD (eds) (2012) Hydrostratigraphy, hydrogeology and system conceptualisation of the Great Artesian Basin. A technical report to the Australian Government from the CSIRO Great Artesian Basin Water Resource Assessment. CSIRO Water for a Healthy Country Flagship, Australia. Figure 3.3 of Smerdon BD, Ransley TR, Radke BM and Kellett JR (2012) Water resource assessment for the Great Artesian Basin. A report to the Australian Government from the CSIRO Great Artesian Basin Water Resource Assessment. CSIRO Water for a Healthy Country Flagship, Australia.

This dataset and associated metadata can be obtained from www.ga.gov.au, using catalogue number 76538.

LINEAGE (Continued from Lineage field due to space constraints) METHOD:

Data covering the areas of Upper Darling, Lower Namoi was supplied by the NSW government.

Contours in the Macquarie region NSW were interpreted from the Cenozoic isopachs taken from Macaulay, S. & Kellett, J. (2009)

Lower Balonne Deep Lead tertiary isopach contours captured from a National Action Plan for Salinity and Water Quality report (Chamberlain, T. & Wilkinson, K., 2004; Kellett et.al. 2004).

Isopachs in the southern portion of the GAB were captured from the Cainozoic Structural Features page 22 of Palaeogeographic Atlas of Australia: Cainozoic (Langford & Wilford, 1995)

Isopachs over the Poolowanna Trough and Cooper Basin region were taken from Tertiary Stratigraphy and Tectonics, Eromanga Basin (Moussavi-Harami, R. & Alexander, E., 1998)

Isopachs in the central Eromanga Basin, Queensland came from Senior 1978.

Position and boundary of the Condamine Basin from Klohn, Crippen & Berger, 2011 - feasibility of injecting CSG water into the central Condamine Alluvium - Summary. Report prepared for department of Environment and Resource Management, Queensland, 8p. Isopachs came from the Cainozoic Structural Features page 22 of Palaeogeographic Atlas of Australia: Cainozoic (Langford & Wilford, 1995)

Drill-hole data sourced from PIRSA (2007) and GABLOG (Habermehl, 2001) databases, Gibson et al 1974, and well completion reports from GSQ (Queensland Department of Natural Resources and Mines, 2012).

Data were used to interpolate a surface using the Topo to Raster tool in the ArcGIS Spatial analyst toolset and the resulting raster was clipped to the Great Artesian Basin Water Resource project boundary.

Isopach contours were generated from the raster, using the Contour tool in the 3d analyst toolset in ArcGIS.

METHOD