Bathymetry-embedded DEM for the Murray-Darling Basin version 2

Full description

Basin-wide Digital Elevation Models (DEMs) with embedded bathymetry for selected main rivers Murray-Darling Basin at 5 metre (GDA2020 Lambert Conformal Conic) and 1 second (WGS 1984) resolution.

This collection is an enhancement of the Seamless Composite High Resolution Digital Elevation Model (DEM) for the Murray Darling Basin, whereby available channel bathymetry has been incised into the input DEM.

This collection was produced for use in basin- wide flood extent and depth modelling which requires an accurate representation of channel bathymetry in the MDB's trunk rivers.
Lineage: The base DEM is the High resolution Digital Elevation Model (DEM) for the Murray Darling Basin (https://data.csiro.au/collection/csiro:64134)

BATHYMETRY
Bathymetry point data were received for large sections of the Murray River (Hume to Wellington), sections of the Darling Anabranches, Edward River, and for waterholes on the Darling and Barwon river. Additionally, bathymetry embedded LIDAR for the Murrumbidgee and Darling River LIDAR flown in 2015, when the riverbed was largely exposed due to dry conditions, was also utilised. See Collaborating Organisations and metadata document for complete list of bathymetry data sources

Some small sections were clearly derived from gridded bathymetry having dense regular spacing of 10 to 15m. Most of the points were a continuous line of points following either a zig-zag or square wave track, with the remainder being transects perpendicular to the riverbanks at regular intervals ranging from a few hundred metres to many kilometres apart. Coverage for the Murray downstream of Lake Hume was continuous in some form (grid, track or transect) save for gaps between Narrung and Mildura. Various techniques were developed to process these data to form a consistent bathymetry ready to be embedded into the DEM.

Grid derived points were interpolated directly to a 5m grid conforming to the DEM using Triangular Irregular Network (TIN) in ArcGIS. The remaining point configurations were unsuitable for direct interpolation to a DEM conforming raster in their received form, and so underwent a data point densification process to make them suitable.

A method was devised to form gridded bathymetry from observed data points through data point densification. This was achieved by first creating a dense regular array of points consisting of 30 to 40 files of closely spaced (~10- ~20m) points across the width of the channel and following the course of the channel.

Input bathymetry point data was transferred to its nearest (within 5m to 20m search radius) array point. Intervening array points within a given file that had not inherited a close neighbouring bathymetry datapoint value, then had a value linearly interpolated from its next upstream and downstream value.

Bathymetry data points confer their bathymetry value to nearby array points. Remaining array points then have an interpolated value calculated based on the next upstream and downstream conferred data in their file. This dense array of data was then interpolated to the DEM conforming 5m raster using TIN. The rasterised bathymetry data were then inserted into the DEM replacing the non-ground channel values with interpolated bathymetry values.

For the Murrumbidgee and Darling Rivers, existing LIDAR already had a good representation of river bathymetry, due to bathymetry embedding having already been implemented by a third party or the bed being exposed when LIDAR was flown. In these cases the LIDAR DEM values occurring within the channel were clipped out, resampled and reprojected to match the base DEM and then inserted into the base DEM.

For both the rasterised interpolated point data and the clipped LIDAR inserts, bathymetry was embedded into the base DEM by taking the minimum elevation occurring in the overlying cells.

This dataset was resampled to ≈ 30 m and used as an input to create the two-monthly maximum water depth spatial timeseries for the MDB version 2024 (https://doi.org/10.25919/1t0t-y110) and monthly maximum water depth spatial timeseries for the MDB (https://doi.org/10.25919/zffy-a921).