Georeferenced Snow Depth and Snow Water Equivalent Dataset (2025) from East Kazakhstan Region
Chernykh D. Biryukov R. Lubenets L. Bondarovich A. Zhomartkan N. Maulit A. Nurekenov D. Rakhymbek K. Baiburin Y. Nugumanova A.
February 2026Multidisciplinary Digital Publishing Institute (MDPI)
Data
2026#11Issue 2
In this work, we present the Snow Depth and Snow Water Equivalent Dataset for specific areas located in the East Kazakhstan Region that can be exploited to monitor and understand water resource dynamics in mountain regions. 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. 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, and 2331 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. Dataset: https://zenodo.org/records/18242602 (accessed on 11 February 2026). Dataset License: CC-BY 4.0
East Kazakhstan Region , snow depth , snow water equivalent , snowpack
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Institute for Water and Environmental Problems, Siberian Branch of the Russian Academy of Sciences, Barnaul, 656038, Russian Federation
Department of Economic Geography and Cartography, Altai State University, Barnaul, 656049, Russian Federation
Laboratory of Digital Technologies and Modeling, Sarsen Amanzholov East Kazakhstan University, Ust-Kamenogorsk, 070004, Kazakhstan
Big Data and Blockchain Technologies Research Innovation Center, Astana IT University, Astana, 010000, Kazakhstan
Institute for Water and Environmental Problems
Department of Economic Geography and Cartography
Laboratory of Digital Technologies and Modeling
Big Data and Blockchain Technologies Research Innovation Center
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