Norwegian snow stations (NVE HydAPI)

The Norwegian Water Resources and Energy Directorate (NVE) runs snow pillows that report SWE and snow depth daily and hourly, plus snow-depth stations at its climate and hydrometric sites, all served through HydAPI. Parameter 2003 is SWE and 2002 is snow depth; daily_only keeps the stations that carry either at daily resolution.

There is one route, source="nve", HydAPI v1, and it is the one station network that needs a credential: a free API key in NVE_API_KEY (request one at https://hydapi.nve.no/). The key is read through the nve auth provider, so a missing one raises CredentialError with the setup steps before any request is made. The station inventory does not need it, because it comes from the published archive.

The figures show the daily stations across Norway, coloured by which snow variable they report, and one water year of SWE and snow depth at two pillows.

import matplotlib.pyplot as plt

import easysnowdata as esd

print(f"easysnowdata {esd.__version__}")

easysnowdata 0.3.9.dev1+gd97689c2f

Where the product comes from, and whether the key is configured.

for src in esd.catalog.get("nve-stations").sources:
    print(f"{src.id:20} {src.title:45} {', '.join(src.requires) or 'no account'}")
print(esd.auth.status().loc["nve"])

nve                  NVE HydAPI v1                                 nve
title              NVE HydAPI
configured               True
how           env:NVE_API_KEY
optional                False
env_vars          NVE_API_KEY
needed_by        nve-stations
Name: nve, dtype: object

Every NVE station with a probe-verified daily SWE or snow-depth record. This reads the published inventory, so no key is involved yet.

inv_gdf = esd.stations.inventory(networks="nve", daily_only=True)
inv_gdf["reports"] = inv_gdf["has_daily_swe"].map(
    {True: "SWE and depth", False: "depth only"}
)
print(f"{len(inv_gdf)} NVE snow stations with a daily record")
print(inv_gdf["reports"].value_counts().to_string())

32 NVE snow stations with a daily record
reports
SWE and depth    21
depth only       11

Not all of them are on the mainland. One is on Svalbard, and HydAPI also serves the four snow stations NVE helps run in Nepal’s Langtang and Mustang valleys, so a box around Norway misses them. The map is the mainland.

mainland = (4.5, 57.5, 31.5, 72.0)
in_norway_gdf = esd.stations.inventory(mainland, networks="nve", daily_only=True)
in_norway_gdf["reports"] = inv_gdf["reports"]
elsewhere_gdf = inv_gdf.loc[~inv_gdf.index.isin(in_norway_gdf.index)]
print(elsewhere_gdf[["name", "latitude", "longitude"]].to_string())
ax = esd.plotting.points(
    in_norway_gdf,
    column="reports",
    legend_label="daily snow variables",
    title="NVE stations with a daily snow record",
)

                                          name  latitude  longitude
code
1977.1.1                      Langtang - Lower  28.19214   85.57043
1977.1.4                    Langtang - GangaLa  28.15441   85.56250
1977.2.1          Mustang - Upper Snow Station  28.13995   84.54465
1977.2.2  Mustang - Lower snow station 4320mas  28.13093   84.54485
400.18.0                           Linnèvatnet  78.06694   13.77737
/home/runner/work/easysnowdata/easysnowdata/docs/gallery/stations/plot_nve_stations.py:54: GeographicAxesWarning: The data are in a geographic CRS (EPSG:4326), so one axis unit is a degree, not a metre. The axes use a latitude-corrected aspect (1/cos(64.7°) = 2.34) so shapes are not stretched; for a true equal-area grid load the product with crs='utm'.
  ax = esd.plotting.points(

One water year of SWE and snow depth at two long-running pillows. This is the call that needs the key; the codes are NVE’s dotted station numbers.

obs_ds = esd.stations.load(
    ["12.142.0", "121.2.0"], variables=["swe", "snwd"], time="2023-10/2024-09"
)
print(obs_ds)

<xarray.Dataset> Size: 22kB
Dimensions:               (station: 2, time: 365)
Coordinates: (12/27)
  * station               (station) <U8 64B '12.142.0' '121.2.0'
    network               (station) <U3 24B 'nve' 'nve'
    name                  (station) <U19 152B 'Bakko' 'Maurhaugen - Oppdal'
    client                (station) <U3 24B 'nve' 'nve'
    network_code          (station) <U3 24B 'NVE' 'NVE'
    latitude              (station) float64 16B 60.68 62.66
    ...                    ...
    metadata_fetched_at   (station) <U19 152B '2026-11-07 00:00:00' '2026-11-...
    station_id            (station) <U8 64B '12.142.0' '121.2.0'
    hemisphere            (station) <U8 64B 'northern' 'northern'
  * time                  (time) datetime64[us] 3kB 2023-10-01 ... 2024-09-29
    water_year            (time) int64 3kB 2024 2024 2024 ... 2024 2024 2024
    dowy                  (time) int64 3kB 1 2 3 4 5 6 ... 361 362 363 364 365
Data variables:
    snwd                  (station, time) float64 6kB 0.0 0.0 0.0 ... nan nan
    swe                   (station, time) float64 6kB 0.0 0.0 0.0 ... nan nan
Attributes:
    source:                nve
    source_id:             nve
    source_title:          NVE HydAPI v1
    source_url:            https://hydapi.nve.no/api/v1
    product_id:            nve-stations
    title:                 Norwegian snow pillows and snow-depth stations (NV...
    data_citation:         Norges vassdrags- og energidirektorat (NVE). Hydro...
    license:               Norwegian Licence for Open Government Data (NLOD)
    easysnowdata_version:  0.3.9.dev1+gd97689c2f
    interval:              daily

The archive inventory carries no elevation for NVE stations, so the legend shows names alone where the other networks’ examples show name (elev m).

fig, axes = plt.subplots(2, 1, figsize=(9, 7), sharex=True)
esd.plotting.timeseries(obs_ds["swe"], ax=axes[0], title="Water year 2024")
esd.plotting.timeseries(obs_ds["snwd"], ax=axes[1], title="", legend=False)
fig.tight_layout()

Norway’s melt season runs later than the western United States at the same elevation, and the snow-depth stations without a pillow are still useful: depth alone tracks the timing of accumulation and melt-out, if not the water.