New Zealand 8m Nationwide Hydrologically Conditioned DEM and Hydraulic Roughness Map

This is an 8m hydraulically conditioned DEM and hydraulic roughness dataset covering the three main islands of New Zealand (North, South and Rakiura Islands) to a minimum distance of 20km offshore. The dataset is separated into 526 30km by 30km tiles included in geofabrics-tiles-2025-04-07-8m.tar. Each tile is stored as netCDF file containing four layers: hydrologically conditioned DEM, hydraulic roughness, data source and LiDAR source. The data source and LiDAR source layers provide pixel-wise metadata about the processes and data contributing to each pixel. The location of these tiles is defined in the tile.gpkg file. The dataset was developed for freshwater flood modelling. Land elevations are primarily derived from LiDAR surveys, and offshore elevations from a curated elevation dataset developed for tidal modelling, integrated on an unstructured mesh with spatial resolution down to 5 m in estuaries to 15 km offshore. Hydrological conditioning was achieved using the GeoFabrics software package (Pearson, R et al, 2023). This included the direct inclusion of measured bed elevations for 97 estuaries and rivers, and 57 lakes; and the estimation and inclusion of bed elevations for a further 98 rivers and river mouths. Additionally, all culverts and waterways (as defined on Open Street Map) were daylighted (obstructions removed and opened to the sky). Finally, the crest elevation of 5368 stop banks were preserved. This data has been prepared by the Earth Sciences New Zealand (ESNZ) for its own internal purposes. The information contained in this data is derived from multiple data sources, including 3rd party data sources. As there is always uncertainty associated with such data, ESNZ gives no warranties of any kind concerning its assessment and estimates, including accuracy, completeness, timelines or fitness for purpose and accepts no responsibility for any actions taken based on, or reliance placed on them by any person or organisation. ESNZ excludes to the full extent permitted by law any liability to any person or organisation for any loss, damage or expense, direct or indirect, and however caused, whether through negligence or otherwise, resulting from any person or organisations use of, or reliance on the information contained in this data. Pearson, R et al., 2023, Geofabrics 1.0.0: An Open-Source Python Package for Automatic Hydrological Conditioning of Digital Elevation Models for Flood Modelling. Environmental Modelling and Software. http://dx.doi.org/10.2139/ssrn.4463610