This collection of files contains geographically registered polygons defining the shape of ocean basins and large lakes across the globe, designed for use in gridding and analysis of satellite-based observations of sea level. In particular, this data set was produced as part of the NASA-SSH (https://podaac.jpl.nasa.gov/NASA-SSH) effort, whose aim is to deliver continuously updated, climate-quality, global observations of sea level derived from radar altimeter observations.

The polygons were derived using products from free vector and raster map data Natural Earth (https://naturalearthdata.com). Ocean basins were derived from version 5.1.0 of the 1:10m Marine Areas:

https://www.naturalearthdata.com/downloads/10m-physical-vectors/

and Lakes were derived from version 5.0.0 of the 1:50m Lakes and Rivers polygons:

https://www.naturalearthdata.com/downloads/50m-physical-vectors/

For the lakes, only the largest 26 lakes and inland seas were retained, as most smaller lakes are not typically sampled by traditional nadir altimeters. For the marine basins, some polygons were joined or sometimes split in order to simplify grouping altimeter data by regions where it is expected to be geographically correlated. For example, southern sections were split from the South Pacific and South Atlantic Oceans to simplify separation of these basins across the South American Peninsula.

In addition to the polygons themselves, a table listing connections between polygons is also provided. This allows users to select observations in regions that are likely to be correlated over time scales of days to weeks or longer. Each polygon carries a unique numerical identifier (the Arctic Ocean is 1, the Southern Ocean is 2, etc…). For each identifier, the connection table lists all of the other identifiers that polygon is connected to. This is used in the NASA-SSH gridding process to down-select data used to estimate sea level at a specific location.

Both the ocean and lake polygons themselves, and the connection table can be easily visualized in Google Earth (or other geographic mapping software) using the KMZ file provided. The connection table provides sets of polygons connected to each individual feature. For example, the Arctic Ocean polygon is connected to the Beaufort Sea, the Greenland Sea, the Barents Sea, etc. These can be easily visualized by turning on subsets of features in the Basin Connections folder within the KMZ file.

Files contained in this dataset include:

basin_files.tar.gz – a tar gzip file that contains a .dbf, .prj, .shx, and .shp Shape file that can be loaded into a geographic mapping program such as QGIS or Google Earth. This contains the polygon definitions, including their names.

basin_name_table.txt – an ascii text file containing a list of all the basin ID numbers and simplified version of the basin names, separated by a colon “:”. A few basins were created for this dataset and do not have common geographic names. These are given names based on their ID number for example “Feature ID: 240”.

basin_connection_table.txt – an ascii text file containing a list of all the basin ID numbers that are geographically connected to a given basin ID. The basin ID number in question is listed first on each row, and the connected ID numbers follow a colon “:”, in a comma separated list.

NASA-SSH Basins.kmz – This KMZ file contains all of the polygon definitions, along with the set of polygons for each basin that shows which basins it is connected to. If loaded into Google Earth, it will create a folder in the Google Earth “Places” panel called “NASA-SSH Basins”. Below this, two subfolders will be created, one will be called “All Basin Polygons” and will contain all of the basins polygons colored red. Clicking on any one of the polygons will show the Basin ID number and name of this polygon. The second subfolder is called “Basin Connections” and contains a list of subfolders, one for each Basin ID. These can be turned on 1 at a time and will show a given basin polygon and all of the polygons it is connected to.

If you use these data please cite:

Willis, J.K., J. Sanchez, R. Santos, and S. Fournier, Ocean Basin and Lake Polygons for Sea Level Grids, at DOI:10.5281/zenodo.13910542.

A shapefile of 311 undersea features from all major oceans and seas has been created as an aid for retrieving georeferenced information resources. Version 1.1 of the data set also includes a linked data representation of 299 of these features and their spatial extents. The geographic extent of the data set is 0 degrees E to 0 degrees W longitude and 75 degrees S to 90 degrees N latitude. Many of the undersea features (UF) in the shapefile were selected from a list assembled by Weatherall and Cramer (2008) in a report from the British Oceanographic Data Centre (BODC) to the General Bathymetric Chart of the Oceans (GEBCO) Sub-Committee on Undersea Feature Names (SCUFN). Annex II of the Weatherall and Cramer report (p. 20-22) lists 183 undersea features that "may need additional points to define their shape" and includes online links to additional BODC documents providing coordinate pairs sufficient to define detailed linestrings for these features. For the first phase of the U.S. Geological Survey (USGS) project, Wingfield created polygons for 87 of the undersea features on the BODC list, using the linestrings as guides; the selected features were primarily ridges, rises, trenches, fracture zones, basins, and seamount chains. In the second phase of the USGS project, Wingfield and Hartwell created polygons for an additional 224 undersea features, mostly basins, abyssal plains, and fracture zones. Because USGS is a Federal agency, the attribute tables follow the conventions of the National Geospatial-Intelligence Agency (NGA) GEOnet Names Server (http://geonames.nga.mil/gns/html/).

ABSTRACT: A shapefile of 311 undersea features from all major oceans and seas has been created as an aid for retrieving georeferenced information resources. The geographic extent of the shapefile is 0 degrees E to 0 degrees W longitude and 75 degrees S to 90 degrees N latitude. Many of the undersea features (UF) in the shapefile were selected from a list assembled by Weatherall and Cramer (2008) in a report from the British Oceanographic Data Centre (BODC) to the General Bathymetric Chart of the Oceans (GEBCO) Sub-Committee on Undersea Feature Names (SCUFN). Annex II of the Weatherall and Cramer report (p. 20-22) lists 183 undersea features that "may need additional points to define their shape" and includes online links to additional BODC documents providing coordinate pairs sufficient to define detailed linestrings for these features. For the first phase of the U.S. Geological Survey (USGS) project, Wingfield created polygons for 87 of the undersea features on the BODC list, using the linestrings as guides; the selected features were primarily ridges, rises, trenches, fracture zones, basins, and seamount chains. In the second phase of the USGS project, Wingfield and Hartwell created polygons for an additional 224 undersea features, mostly basins, abyssal plains, and fracture zones. Because USGS is a Federal agency, the attribute tables follow the conventions of the National Geospatial-Intelligence Agency (NGA) GEOnet Names Server (http://earth-info.nga.mil/gns/html).

This dataset includes i) River flows and ii) nutrient discharges to the Atlantic ocean basin:

River flow data are a subset of the WaterGAP 2.2d model (Monthly data on a 0.5° x 0.5° grid between 90°N and 60°S. 1901–2016) (Müller Schmied et al. 2020)

The original watergap2.2d data is provided in netcdf format. Our postprocessing includes the selection of the coastal cells and the extraction of the monthly values in these cells. The resulting dataset is provided as a shapefile (Global_YearMonthly_River_flow_watermap22_coast.shp), including Date, latitude and longitude of the coastal cell’s centroids and the discharge values (m3s-1).

Watergap2.2d outputs offers a very good spatio-temporal extent and resolution, and according to the Müller Schmied et al. 2020, the validation results for streamflow (or discharges values) are reasonably satisfactory, although there is some spatial variability in the performance results. Moreover, the recently published “Global Freshwater Fluxes into the World's Oceans (GRDC, 2021)” product and paper, uses the yearly outcomes of this model, which has also supported our selection.

River nutrient discharges are a subset of observations from the “Global River Water Quality Archive”. (Virro et al, 2021), that among the publicly available and downloadable datasets, gathers the highest number of observations as includes data from different international and national databases.

The GRQA data is provided as csv files (one file for each nutrient). These files have been processed to subset only observations at stations near the coastline. To do this a intersection between station locations and a buffer of 0.2 degrees around the coastline has been made. For each nutrient, a shapefile with the subsetted observations is provided.

All shapefiles provided are accompanied by a “.qmd” file that includes metadata information in QGIS 3 format.

This dataset represents a partition of the world oceans into provinces as defined by Longhurst (1995; 1998; 2006), and are based on the prevailing role of physical forcing as a regulator of phytoplankton distribution. The dataset represents the initial static boundaries developed at the Bedford Institute of Oceanography, Canada. Note that the boundaries of these provinces are not fixed in time and space, but are dynamic and move under seasonal and interannual changes in physical forcing. At the first level of reduction, Longhurst recognized four principal biomes (also referred to as domains in earlier publications): the Polar Biome, the Westerlies Biome, the Trade-Winds Biome, and the Coastal Boundary Zone Biome. These four Biomes are recognizable in every major ocean basin. At the next level of reduction, the ocean basins are partitioned into provinces, roughly ten for each basin. These partitions provide a template for data analysis or for making parameter assignments on a global scale. (source: VLIZ (2009). Longhurst Biogeographical Provinces. Available online at Longhurst Biogeographical Provinces References: Longhurst, A.R. (2006). Ecological Geography of the Sea. 2nd Edition. Academic Press, San Diego, 560p. Data available from: Ecological Geography of the Sea

This data set was acquired with a ship-based Navigation system during Vema expedition V3602 conducted in 1979 (Chief Scientist: Dr. Anthony Watts). These data files are of Shapefile format and include Navigation data and were processed after data collection.

The NASA-SSH Simple Gridded Sea Surface Height from Standardized Reference Missions Only Version 1 dataset produced by NASA provides 2-D maps of sea surface height, or sea level, anomaly once every 7 days. The grids are based on observations of sea surface height from the radar altimeter satellites in the reference mission orbits, including TOPEX/Poseidon, the Jason series, and Sentinel-6. The data begin in Oct 1992 and continue through the present. They are created using the NASA-SSH Along-Track Sea Surface Height from Standardized Reference Missions Version 1 dataset.
The grids consist of 10-days worth of observations, which covers approximately 1 complete repeat cycle of observations from the reference missions. The grids are produced on a 0.5-degree latitude and longitude grid, by taking a simple gaussian weighted spatial average with a width of 100 km. The grids are produced every 7 days to allow for easy interpolation in time. However, since they are created using 10-days of data, there is some overlap of information between adjacent time steps. The grids are also created using the basin flags to avoid mixing data from distinct ocean basins (for example, to avoid mixing observations from the Caribbean Sea with observations from the Pacific across the Isthmus of Panama). Connected basins are allowed to share data, however. This is accomplished by using a table of connections between basins. The basin connection table is available (https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/basin_connection_table.txt). The basin definitions can be downloaded as a shape file from https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/basin_polygon_files.tar.gz, or as a kml file https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/NASA-SSH_Basins.kmz.
A new grid will be released approximately once per week, with a latency of a few weeks.

This data set was acquired with a ship-based Navigation system during Thomas Washington expedition RNDB14WT conducted in 1989 (Chief Scientist: Dr. James Hawkins). These data files are of Shapefile format and include Navigation data and were processed after data collection.

The NASA-SSH Along-Track Sea Surface Height from Standardized Reference Missions Version 1 dataset produced by NASA provide observations of sea surface height, or sea level, anomaly measured using radar altimeter satellites in the reference mission orbit. These include TOPEX/Poseidon, the Jason series, and Sentinel-6. The data begin in Oct 1992, with data from TOPEX/Poseidon, and continues to the present. In this data set all missions have been referenced to a common baseline, additional quality control has been performed, and errors with wavelengths around one orbital cycle have been reduced.
The data consist of along-track observations of sea surface height, collected approximately once per second (1 Hz), and are parsed into files containing one day’s worth of data per file. A flag variable is included to allow users to easily select only valid observations, and a variable containing sea surface height with the flag applied and a small amount along track smoothing (~20 km), is suggested for most users.
Additionally, a “basin” flag variable is provided, along with a table defining it. This allows users to easily select all observations from a specific body of water. The basin flag assigns a number to each point corresponding to a specific ocean basin or lake. A table is included with a text description of each basin number. A text version of that table is available (https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/basin_name_table.txt). The basin definitions can be downloaded as a shape file from https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/basin_polygon_files.tar.gz, or as a kml file https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/nasa-ssh/NASA-SSH_Basins.kmz.
New data will be released approximately once per week, with a latency of a few weeks.

'''DEFINITION''' This ocean monitoring indicator (OMI) consists of annual mean rates of changes in surface ocean pH (yr-1) computed at 0.25°×0.25° resolution from 1985 until the last year. This indicator is derived from monthly pH time series distributed with the Copernicus Marine product MULTIOBS_GLO_BIO_CARBON_SURFACE_REP_015_008 (Chau et al., 2022a). For each grid cell, a linear least-squares regression was used to fit a linear function of pH versus time, where the slope (μ) and residual standard deviation (σ) are defined as estimates of the long-term trend and associated uncertainty. Finally, the estimates of pH associated with the highest uncertainty, i.e., σ-to-µ ratio over a threshold of 1 0%, are excluded from the global trend map (see QUID document for detailed description and method illustrations). This threshold is chosen at the 90th confidence level of all ratio values computed across the global ocean. '''CONTEXT''' A decrease in surface ocean pH (i.e., ocean acidification) is primarily a consequence of an increase in ocean uptake of atmospheric carbon dioxide (CO2) concentrations that have been augmented by anthropogenic emissions (Bates et al, 2014; Gattuso et al, 2015; Pérez et al, 2021). As projected in Gattuso et al (2015), “under our current rate of emissions, most marine organisms evaluated will have very high risk of impacts by 2100 and many by 2050”. Ocean acidification is thus an ongoing source of concern due to its strong influence on marine ecosystems (e.g., Doney et al., 2009; Gehlen et al., 2011; Pörtner et al. 2019). Tracking changes in yearly mean values of surface ocean pH at the global scale has become an important indicator of both ocean acidification and global change (Gehlen et al., 2020; Chau et al., 2022b). In line with a sustained establishment of ocean measuring stations and thus a rapid increase in observations of ocean pH and other carbonate variables (e.g. dissolved inorganic carbon, total alkalinity, and CO2 fugacity) since the last decades (Bakker et al., 2016; Lauvset et al., 2021), recent studies including Bates et al (2014), Lauvset et al (2015), and Pérez et al (2021) put attention on analyzing secular trends of pH and their drivers from time-series stations to ocean basins. This OMI consists of the global maps of long-term pH trends and associated 1σ-uncertainty derived from the Copernicus Marine data-based product of monthly surface water pH (Chau et al., 2022a) at 0.25°×0.25° grid cells over the global ocean. '''CMEMS KEY FINDINGS''' Since 1985, pH has been decreasing at a rate between -0.0008 yr-1 and -0.0022 yr-1 over most of the global ocean basins. Tropical and subtropical regions, the eastern equatorial Pacific excepted, show pH trends falling in the interquartile range of all the trend estimates (between -0.0012 yr-1 and -0.0018 yr-1). pH over the eastern equatorial Pacific decreases much faster, reaching a growth rate larger than -0.0024 yr-1. Such a high rate of change in pH is also observed over a sector south of the Indian Ocean. Part of the polar and subpolar North Atlantic and the Southern Ocean has no significant trend. '''DOI (product):''' https://doi.org/10.48670/moi-00277

Two shapefiles mapping the locations of ancient and modern passive margin boundaries are presented. These data are a digital recreation of the work originally published by Bradley (2008). The ancient passive margin data were used as an evidential layer to map prospectivity for sediment-hosted Pb-Zn mineral systems (Lawley and others, 2022). The ancient passive margins dataset includes additional attributes related to the boundary's orogenic setting and history, the length of the boundary, its estimated lifespan, and its modern-day country location. Although only ancient passive margin boundaries were analyzed for the United States, Canada, and Australia for this study, boundaries for the world are included in the shapefile. The modern passive margin dataset includes an identifier for the margin segment, a margin name, the associated ocean, and age ranges of basin initiation, mean age and length of the respective passive margin segment. The modern passive margin data were not used in prospectivity modeling for ancient deposits. The passive margin boundaries in both files are mapped as line segments in geographic coordinates using a WGS84 datum. References Bradley, D.C., 2008, Passive margins through earth history: Earth-Science Reviews, v. 91, no. 1-4, p. 1-26, https://doi.org/10.1016/j.earscirev.2008.08.001. Lawley, C.J.M., McCafferty, A.E., Graham, G.E., Huston, D.L., Kelley, K.D., Czarnota, K., Paradis, S., Peter, J.M., Hayward, N., Barlow, M., Emsbo, P., Coyan, J., San Juan, C.A., and Gadd, M.G., 2022, Data-driven prospectivity modelling of sediment-hosted Zn-Pb mineral systems and their critical raw materials: Ore Geology Reviews, v. 141, no. 104635, https://doi.org/10.1016/j.oregeorev.2021.104635.

This phase of Project 3DGBR involved manual digitising of geomorphic map boundaries for the key seafloor features identified in the gbr100 grid, particularly for the inter-reefal area on the GBR shelf and in the Coral Sea Conservation Zone (CSCZ). See map for CSCZ boundary at: https://www.environment.gov.au/topics/marine/marine-reserves/coral-sea/conservation-zone

Methods:

GIS spatial analysis of the gbr100 grid was conducted in order to derive a number of useful background datasets for assisting in the digitising process, such as slope, aspect, hillshading, and dense contour lines.

The digitising initially focused on the deep-water (>100 m) environment to develop geomorphic maps for the continental slope, Queensland and Townsville Troughs lying within the Great Barrier Reef World Heritage Area (GBRWHA), and for the Queensland Plateau, Coral Sea Basin, Tasman Basin, and Lord Howe Rise area lying within the adjoining Coral Sea Conservation Zone (CSCZ). The project lastly focuses on the shallow-water (<100 m) environment to develop geomorphic maps for the GBR shelf to complement the shallow reef feature maps provided by GBRMPA. These shallow-water geomorphic features will be added to the project as they come available.

Format:

This dataset consists of 21 shapefiles and a GeoTiff raster file containing hillshading. Each of the shapefiles is described below.

Group Layer 1. Boundaries: gbrwha_outer.shp This Great Barrier Reef World Heritage Area (GBRWHA) layer was initially provided by GBRMPA using a GDA94 datum. The shapefile was reprojected to the WGS84 datum, and then the western coastline boundaries deleted to derive a line shapefile showing only the outer boundary of the GBRWHA where it extends away from the mainland.

qld_gbrwha_cscz.shp This line shapefile combines both the GBRWHA and Coral Sea Conservation Zone (CSCZ) areas, with a western boundary limit at the Queensland mainland coastline. This area was used to clip all geomorphic features created in this project.

Group Layer 2. GBRMPA features: gbr_dryreef.shp The GBR shelf dryreefs shapefile was initially provided by GBRMPA for this project using a GD94 datum. The shapefile was reprojected to the WGS84 datum and not modified in any other way. It is provided here only for completeness but and products using this shapefile should also acknowledge GBRMPA (see under licensing).

gbr_features.shp The GBR shelf features were initially provided by GBRMPA for this project using a GDA94 datum. The shapefile was reprojected to the WGS84 datum, and then the Ashmore Reef polygon deleted due to a grossly incorrect position. The shapefile comprises Cay, Island, Mainland, Reef, Rock and Sand features. Users may contact GBRMPA to obtain details for the creation of these features. Any products using this shapefile should also acknowledge GBRMPA (see under licensing).

Group Layer 3. Finer-scale features: coralsea_cay.shp Cay is a sand island elevated above Australian Height Datum (AHD), and located on offshore coral reefs and seamounts. Cays were mapped initially using a shapefile provided by Geoscience Australia for this project, and then their boundaries checked or remapped using Landsat imagery as background source data to help delineate the white sand areas against the surrounding ocean.

coralsea_dryreef.shp Dryreef is rock/coral lying at or near the sea surface that may constitute a hazard to surface navigation. Dryreefs were mapped initially using a shapefile provided by Geoscience Australia for this project, which identified those reef areas lying above approximately Lowest Astronomic Tide (LAT). Landsat imagery was used as background source data to check or remap their boundaries.

coralsea_reef.shp Reef is rock/coral lying at or near the sea surface that may constitute a hazard to surface navigation. For this project, the boundaries of reef areas were mapped to show the outer-most extent of each coral reef that could be observed in Landsat imagery, thus identifying the greatest area of each reef observed in the Coral Sea. This methodology is consistent with the methodology used to map the outer-most extents of reefs on the GBR shelf conducted by GBRMPA.

coralsea_ridge.shp Ridge is a long, narrow elevation with steep sides. In this project, ridges were mapped as widely-scattered and uncommon, finer-scale features identified in the gbr100 grid. These elongate ridges are distinct from the smaller knolls or hills which have a more rounded shape. They are usually found on the plateaus of the Lord Howe Rise.

coralsea_bank.shp Bank is an elevation over which the depth of water is relatively shallow but normally sufficient for safe surface navigation. In this project, banks were mapped as the base or pedestal boundaries of the coral reefs found in the Coral Sea. For example, the coral atolls and reefs on the Queensland Plateau are considered banks and their bases digitised where they emerge from the surrounding flat seafloor.

coralsea_knoll.shp Knoll is a relatively small isolated elevation of a rounded shape. This shapefile also includes Abyssal hill, a low (100 – 500 m) elevation on the deep seafloor. For this project, knolls and abyssal hills were mapped using background datasets that showed relatively steep changes in elevation contours and variations in slope gradients. Knolls are numerous throughout the Coral Sea area and are greatly underestimated.

coralsea_canyon.shp Canyon is a relatively narrow, deep depression with steep sides, the bottom of which generally has a continuous slope, developed characteristically on continental slopes. Canyons were mapped by closely following the narrow sides of canyon axes, digitising from the foot of the canyon where they merge with the surrounding basin floor, and up to the canyon head and into any connecting side gullies. This project identified numerous canyons on any slope gradient >1° and are also greatly underestimated across the area.

coralsea_seamount.shp Seamount is a large isolated elevation >1000 m in relief above the seafloor, characteristically of conical form. This shapefile also includes Guyot, a seamount having a comparatively smooth flat top. Seamounts and guyots were mapped mostly within the Tasmantid Seamount Chain with elevations >1000 m. This project identified several large knolls and hills close to 1000 m in height within this chain that may also be seamounts but currently lack detailed bathymetry data.

Group Layer 4. Broader-scale features: gbr_shelf.shp Shelf is a zone adjacent to a continent (or around an island) extending from the low water line to a depth at which there is usually a marked increase of slope towards oceanic depths. The eastern boundary of the Queensland continental shelf was mapped by closely following the change in gradient along the shelf edge. The shelf break in the north was at approximately 80 m and became deeper at about 110 m towards the south. The western boundary was clipped at the Queensland mainland coastline.

coralsea_slope.shp Slope lies seaward from the shelf edge to the upper edge of a continental rise or the point where there is a general reduction in slope. The continental slope was mapped lying adjacent to the shelf and extending into the adjacent deep basins and troughs. The shelf feature was used to erase the western boundary of the slope and the various basins and troughs erased the eastern slope border. The slope has extensive canyons incising its surface.

coralsea_terrace.shp Terrace is a relatively flat horizontal or gently inclined surface, sometimes long and narrow, which is bounded by a steeper ascending slope on one side and by a steeper descending slope on the opposite side. In this project, one broad-scale terrace feature was mapped lying on the slope between the Swains Reefs and Capricorn-Bunker Group of reefs, and near the Capricorn Trough.

coralsea_plateau.shp Plateau is a flat or nearly flat area of considerable extent, dropping off abruptly on one or more sides. Extensive areas of plateaus were mapped across the Coral Sea with the largest being the Queensland Plateau. Lord Howe Rise consists of a series of plateaus separated by broad-scale valleys linking adjacent basins and troughs. Plateau boundaries were mapped around their bases where the gradient first becomes steeper. The exceptions are the Marion and Saumarez Plateaus on the Queensland continental slope, where the boundaries were mapped as the slope gradient becomes flat or nearly flat.

coralsea_valley.shp Valley is a relatively shallow, wide depression, the bottom of which usually has a continuous gradient. This term is generally not used for features that have canyon-like characteristics for a significant portion of their extent. The shapefile includes Hole, a local depression, often steep sided, of the seafloor. Valleys and holes were mapped as long shallow depressions that often separated the numerous plateaus. These features link the basins and troughs that surround these plateaus, and in some cases can be incised with finer-scale canyons.

coralsea_trough.shp Trough is a long depression of the seafloor characteristically flat bottomed and steep sided and normally shallower than a trench. In this project, two trough features were mapped that are essentially long basins. The larger feature is a combined Queensland and Townsville Trough lying between the continental slope and the Queensland Plateau. The smaller feature is the Bligh Trough separating the northern slope and Eastern Plateau. Both trough features feed into the Osprey Embayment and huge Bligh Canyon.

coralsea_rise.shp Rise is a gentle slope rising from the oceanic depths towards the foot of a continental slope. For this project, an elongate rise is mapped between the Queensland Plateau and the adjacent Coral Sea Basin. The Queensland Plateau is remnant continental crust from the Gondwana breakup and so its seaward edge provides a geomorphic extension of the Australian margin, albeit at a

This data set was acquired with a ship-based Navigation system during Roger Revelle expedition KIWI11RR conducted in 1998 (Chief Scientist: Dr. Nancy Kanjorski). These data files are of Shapefile format and include Navigation data and were processed after data collection.

This study presents the first digital seafloor geomorphic features map (GSFM) of the global ocean. The GSFM includes 131,192 separate polygons in 29 geomorphic feature categories. This dataset contains the feature category basins. Basins are depressions in the seafloor, often formed by tectonic processes, providing distinct deep-water environments with unique sediment deposition patterns.

"One belt, one road" delineation of the key Asian regional watershed boundaries is based on the following principles: Principle 1: along the Silk Road Principle 2: located in arid and semi-arid areas Principle 3: high water risk Principle 4: watershed integrity 1. Division basis of arid area Food and Agriculture Organization of the United Nations. FAO GEONETWORK. Global map of aridity - 10 arc minutes (GeoLayer). (Latest update: 04 Jun 2015) Accessed (6 Mar 2018). URI: http://data.fao.org/ref/221072ae-2090-48a1-be6f-5a88f061431a.html?version=1.0 2. Water resources risk data: Gassert, F., M. Landis, M. Luck, P. Reig, and T. Shiao. 2014. Aqueduct Global Maps 2.1. Working Paper. Washington, DC: World Resources Institute. 3. Poverty index data: Elvidge C D, Sutton P C, Ghosh T, et al. A global poverty map derived from satellite data. Computers & Geosciences, 2009, 35(8): 1652-1660. https://www.ngdc.noaa.gov/eog/dmsp/download_ poverty.html 4. Basic basin boundary data: (1) Watershed boundaries were derived from HydroSHEDS drainage basins data (Lehner and Grill 2013) based on a grid resolution of 15 arc-seconds (approximately 500 m at the equator), which can be free download via https://hydrosheds.cr.usgs.gov/hydro.php (2) AQUASTAT Hydrological basins: This dataset is developed as part of a GIS-based information system on water resources. It has been published in the framework of the AQUASTAT - programme of the Land and Water Division of the Food and Agriculture Organization of the United Nations. The map is also available in the SOLAW Report 15: “Sustainable options for addressing land and water problems – A problem tree and case studies”. Data can be free download via http://www.fao.org/nr/water/aquamaps/ (3) HydroBASINS: https://www.hydrosheds.org/downloads 5. The GloRiC provides a database of river types and sub-classifications for all river reaches globally. https://www.hydrosheds.org/page/gloric 6. HydroATLAS offers a global compendium of hydro-environmental sub-basin and river reach characteristics at 15 arc-second resolution. https://www.hydrosheds.org/page/hydroatlas It covers an area of 1469400 square kilometers, including the following areas: Nujiang River Basin, Dead Sea basin, Sistan River Basin, Yellow River Basin, Jordan Syria eastern basin, Indus River Basin, Iran inland flow area, urmiya Lake Basin, Shiyang River Basin, hallelud mulgarb River Basin, Lianghe River Basin, Shule River Basin, Heihe River Basin, issekkor Lake Basin, Tata River Basin Limu River Basin, Turpan Hami basin, Ebinur Lake Basin, Junggar basin, Amu Darya River Basin, Manas River Basin, ulungu River Basin, Emin River Basin, Chu River Talas River Basin, Xil River Basin, Ili River Basin, Caspian Sea basin, Lancang River Basin, Yangtze River Basin, Qinghai lake water system, Eastern Qaidam Basin, western Qaidam Basin and Qiangtang plateau District, Yarlung Zangbo River Basin

This data set was acquired with a ship-based Navigation system during Vema expedition V3601 conducted in 1979 (Chief Scientist: Dr. Roger Larson). These data files are of Shapefile format and include Navigation data and were processed after data collection.

This data set was acquired with a ship-based Navigation system during Robert D. Conrad expedition RC1212 conducted in 1968 (Chief Scientist: Dr. Robert Houtz). These data files are of Shapefile format and include Navigation data and were processed after data collection.

This data set was acquired with a ship-based Navigation system during Thomas Washington expedition RNDB13WT conducted in 1989 (Chief Scientist: Dr. Stephen P. Miller). These data files are of Shapefile format and include Navigation data and were processed after data collection. Data were acquired while the Thomas Washington was in transit.

This data set was acquired with a ship-based Navigation system during Marcus G. Langseth expedition MGL0901 conducted in 2009 (Chief Scientist: Dr. Anthony Johnson). These data files are of Shapefile format and include Navigation data and were processed after data collection. Data were acquired while the Marcus G. Langseth was in transit.

This data set was acquired with a ship-based Navigation system during Melville expedition WEST06MV conducted in 1994 (Chief Scientist: Dr. John Hildebrand). These data files are of Shapefile format and include Navigation data and were processed after data collection.