Country Specific – Norway

Quick Facts NDH DTM1

Cell Size1x1 m
Coordinate SystemETRS89 / UTM 33N
Vertical ReferenceNN2000
Flight Years2016–

Our elevation model of Norway is based primarily on the DTM1 data made available by Kartverket's nasjonal detaljert høydemodell (NDH) project, and has a grid resolution of 1x1 meter. The project started in 2016 and currently covers most of Norway. More data is being acquired continuously. We strive to keep our model up to date with the latest sources.

In order to use an elevation model for hydrological analysis such as watershed and flow accumulation computations, two primary conditions need to be met:

  • The upstream area of any river should be covered by the elevation model.
  • Structures on top of the terrain should only be present in case they actually block water from flowing under or through them.

Below, we discuss how we process the model to fulfill these conditions as well as possible.

Extensions

In order to cover all of Norway including upstream areas of all rivers, we have extended the DTM1 model in the following areas:

  • For Sweden we use Lantmäteriet's Laserdata Nedladdning, skog point cloud where available.  In the figure below, this area is highlighted in green.
  • For remaining areas of Norway and Sweden not covered by the NDH/DTM1 data, we have used the Kartverket's DTM 10 data set from 2013.
  • To cover the upstream area of the Vefsna river (Nordland) in Sweden, we have included some data from the 30m EU-DEM data set, which in turn is based on SRTM and ASTER GDEM data (yellow in the figure below).
  • To cover the upstream area of the Tana and Neiden rivers (Finnmark), we have included parts of the national Finnish elevation models:

A full overview of which data source is used for which part of the model is available by clicking the gear icon next to an elevation layer, selecting the "Source" tab, and "Show source information". Use point query to see more details for individual areas as provided by Kartverket. Multiple styles are available for this layer to colour sources by e.g. collection date. Note that the DTM 10 data set is not shown since it's used everywhere no other data set was available.

Overview of sources used for the elevation model.

Buildings

Apart from vegetation and major bridges, also buildings have been removed from the terrain model during construction. When computing water flow paths, more realistic results are generally obtained when the elevation model includes buildings as water can be simulated to flow around them. In SCALGO Live, we accomplish this by adding buildings back into the model using a data set of building footprints,. Here, we raise all grid cells covered by a building to a height of 10 m above the highest terrain point within the building footprint. This model is called Terrain/Buildings and is the basis for all nationwide hydrological computations.

The building footprint data set used is the FKB N5 Bygning data set from Kartverket/Geovekst.

Flow paths routed around buildings.

Bridges, underpasses and hydrological corrections

Major bridges have generally been removed from the model, but for many smaller bridges and underpasses, additional hydrological corrections that allow water to flow through such structures may be necessary. SCALGO Live Norway includes a nationwide hydrological correction set based primarily on the N20 Vann layer from Kartverket/Geovekst, as well as culverts (stikkrenner) from Statens Vegvesen's NVDB, Elveg 2.0  and the Banenettverk dataset from Bane Nor SF.

Corrections have been generated at locations where rivers intersect roads or railroads, as well as at river sections marked subsurface ("medium=U") where the river e.g. runs through a longer covered/piped area. Secondly, corrections have been generated at road overpasses and tunnels.  Thirdly, NVDB's stikkrenner are included.

Each correction thus follows a line in the river or road network, or a known culvert, with end points adjusted to match the elevation model as well as possible. In places where the elevation model is already hydrologically corrected (e.g. at large bridges), corrections are not generated.

This data set is machine-generated, so some errors should be expected. However, since we only include corrections along known river and road lines, we believe it to be conservative in terms of water flow.

The set of corrections is available under the Hydrological Corrections category in the Library.

The national analyses use these corrections, and workspaces created using the predefined "Flash Flood Map" or "Sea-Level Rise" buttons also include them by default. If you create a workspace through any other means than the predefined buttons (e.g. if you upload your own model), you can include corrections in that workspace through the workspace Actions tab by clicking Import corrections, they will not be included automatically.

Corrections and flow accumulation around Burudelva and Engabekken in Lommedalen.

Soil type and land cover

Soil type: SCALGO Live uses the superficial deposits from Geological Survey of Norway for watershed soil type query. NGU's quaternary geological mapping (superficial deposits mapping) shows which type of soil predominates in the upper meters of the terrain surface. Thick and thin layers of other soil types may appear farther down the soil profile. We refer to Geonorge for more information.

Land cover: SCALGO Live uses the area type from NIBIO for watershed land use queries. We combined two area type data sets called AR5 and AR50. AR5 data is used by default, but it does not cover the entire area of SCALGO Live Norway. Where AR5 data is not available, we have used the coarser-resolution AR50 dataset. Where neither AR5 nor AR50 has data, the area is marked as unclassified.

AR50 coverage (green) and AR5 coverage (yellow). If a location is covered by AR5, we use AR5 data, else we use AR50 data. If no data is available (red hatched area) the land cover type is unclassified.

If a category is the same in both AR5 and AR50, it will be merged into one category in SCALGO Live, e.g., the Skog category is present in both AR5 and AR50. Where AR5 has a finer categorization than AR50, we show the AR50 data as a separate subcategory. For instance, a watershed might include Jordbruk data which is just Jordbruk in AR50 but further subdivided in AR5. In that case, we include a special Jordbruk (AR50) category as a subitem under the general Jordbruk type. This ensures that the area covered only by the AR50 Jordbruk and not by one of the AR5 sub-types is still included in the total for the Jordbruk category. For an example of this, see the figure below.

A big watershed close to Oslo includes both AR5 and AR50 data. The Jordbruk category in AR5 is subdivided into three different subcategories. This has not been done for AR50, which is therefore shown as a fourth Jordbruk (AR50) item under Jordbruk.