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Published January 15, 2026 | Version v1
Dataset Open

GEOREFERENCED SNOW DEPTH AND SNOW WATER EQUIVALENT DATASET (2025) FROM EAST KAZAKHSTAN REGION

  • 1. ROR icon Institute for Water and Environmental Problems of the Siberian Branch of the Russian Academy of Sciences
  • 2. ROR icon Altai State University
  • 3. ROR icon Sarsen Amanzholov East Kazakhstan University

Description

Overview of the snow survey dataset

The present dataset represents a georeferenced collection of snow depth, snow density, and derived snow water equivalent (SWE) measurements obtained through manual snow surveys.

Snow survey observations were conducted during field campaigns in the East Kazakhstan Region during the period of maximum snow accumulation, from 27 February to 6 March 2025.

At each snow survey site, consisting of two perpendicular transects, 21 snow depth measurements were performed (10 along each transect and one at the central point). The distance between measurement points was 5 m, reduced to 2 m on steep slopes and in other terrain conditions where standard measurements were difficult. Snow density was measured five times at each site. Snow depth was measured using a metal snow probe with a measurement resolution of 1 cm, while snow density was measured using a VS–43 gravimetric snow sampler. Snow density was calculated as the ratio of the mass of the snow sample to its volume and expressed in g/cm3.

Snow survey sites were selected to maximize coverage of diverse landscape settings and snow accumulation conditions. In total, 111 snow survey sites were established across the East Kazakhstan Region, where 2,331 snow depth measurements and 555 snow density measurements were collected.

In post-field (laboratory) processing, snow water equivalent (SWE) was calculated for all snow survey sites based on measured snow depth and snow density values using the following formula: SWE=10hd, where h is the mean snow depth (cm), d is snow density (g/cm3), and the factor 10 converts the result to millimeters of water equivalent (mm).

Summary dataset description

The file _EKR_SSP_2025_summary.csv contains information on the mean values of snow depth, snow density, and snow water equivalent (SWE) at the snow survey sites. It also describes the main geographical characteristics of the sites. 

Structure of data for the summary table of snow survey observations

  • Point ID – sequential number of the snow survey site (from 1 to 111)
  • Point Name – name of the measurement point
  • Latitude – latitude WGS84 (in degrees)
  • Longitude – longitude WGS84 (in degrees)
  • Elevation – elevation above sea level (m)
  • Slope – slope angle (in degrees)
  • Aspect – slope aspect (in degrees, 0–360)
  • Snow Depth – mean snow depth at the snow survey site (cm)
  • Snow Density – mean snow density at the snow survey site (g/cm3)
  • Snow Water Equivalent (SWE) – mean snow water equivalent (SWE) at the snow survey site (mm)
  • Landform – landform type (or Terrain type)
  • Land cover – land cover type (or Vegetation / Surface cover type)
  • Landscape Province – landscape province (or Physiographic province / Region)

Category Values

  • Landform: Depressions, Ridges, Valleys.
  • Land cover: Coniferous Forest, Deciduous Forest (small-leaved), Grassland, Shrubland.
  • Landscape Province: Altai Mountains, Kalbinsky Range, Zaisan Depression, Saur Ridge.

Primary (Raw) Measurement Data Description

The files 1_EKR_SSP_2025.csv – 111_EKR_SSP_2025.csv contain data on the primary (raw) measurements of snow depth and snow density at individual snow survey sites (1–111).

Structure of data for tables of primary (raw) snow survey measurements at the site

  • id_point – sequential number of an individual snow depth measurement within a specific snow survey site (from 1 to 21)
  • day – day of measurement
  • month – month of measurement
  • year – year of measurement
  • point_name – name of the measurement point
  • depth_cm – snow depth at the measurement point (measured with snow probe/ruler), cm
  • sample_weight_1_g – mass/weight of the snow sample №1 taken with the snow sampler (gravimetric tube), g
  • sample_weight_2_g – mass/weight of the snow sample №2 taken with the snow sampler (gravimetric tube), g (if present)
  • sample_weight_3_g – mass/weight of the snow sample №3 taken with the snow sampler (gravimetric tube), g (if present)
  • sample_weight_4_g – mass/weight of the snow sample №4 taken with the snow sampler (gravimetric tube), g (if present)
  • sample_depth_1_cm – thickness/height of the snow sample №1 taken with the snow sampler (gravimetric tube), cm
  • sample_depth_2_cm – thickness/height of the snow sample №2 taken with the snow sampler (gravimetric tube), cm (if present)
  • sample_depth_3_cm – thickness/height of the snow sample №3 taken with the snow sampler (gravimetric tube), cm (if present)
  • sample_depth_4_cm – thickness/height of the snow sample №4 taken with the snow sampler (gravimetric tube), cm (if present)
  • mean_density_g_cm3 – mean snow density at the measurement point, calculated from all collected samples, g/cm3

 

 

 

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_EKR_Snow_Survey_2025.zip

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Additional details

Funding

Ministry of Science and Higher Education of the Republic of Kazakhstan
Development of a system for forecasting catastrophic floods in the East Kazakhstan region using remote sensing data, GIS technologies, and machine learning BR24992899