Density-Regulated Snow Depth–Snow Water Equivalent Scaling Under Thermodynamic and Accumulation Perturbations

Snowpack dynamics in continental climates are important for water-resource monitoring and snow water equivalent (SWE) estimation, yet the response of the snow depth–snow water equivalent (SD-SWE) relationship to changing thermodynamic and accumulation forcing remains insufficiently understood. This study develops a process-based framework to evaluate how moderate perturbations in air temperature and precipitation influence snowpack evolution and depth–mass coupling in representative snow regimes of northeastern Kazakhstan. SNTHERM (the Snow Thermal Model) simulations were combined with regression analysis, ANCOVA diagnostics, and bulk-density evaluation under controlled delta-change perturbations of air temperature (±1–2 °C) and precipitation (±5–10%). The results show that the SD-SWE relationship remains approximately linear within the tested perturbation range (R2 ≈ 0.78–0.84), although its parameters are partially sensitive to precipitation-driven accumulation. Temperature perturbations mainly affect melt timing, seasonal persistence, and snow-density redistribution, whereas precipitation modifies snowpack mass and overburden, enhancing mechanical compaction and increasing the regression slope. These findings indicate that snow density is a key integrative state variable linking energy balance, phase change, and compaction processes. Under the tested conditions, snow depth remains a physically consistent proxy for SWE, although the conclusions are limited by the one-dimensional model structure, reanalysis-based forcing, and restricted observational coverage.

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Publication Details

Journal
Applied Sciences
Published
2026-04-02
DOI
https://doi.org/10.3390/app16073476
Primary Topic
Cryospheric studies and observations
Type
article
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article

Density-Regulated Snow Depth–Snow Water Equivalent Scaling Under Thermodynamic and Accumulation Perturbations

Balgaisha Mukanova, Aliya Nugumanova, Anar Rakhimzhanova, Kamilla Rakhymbek et al.
Applied Sciences
Cryospheric studies and observations
article

Density-Regulated Snow Depth–Snow Water Equivalent Scaling Under Thermodynamic and Accumulation Perturbations

Balgaisha Mukanova, Aliya Nugumanova, Anar Rakhimzhanova, Kamilla Rakhymbek, Sultan Aubakirov
article en

Abstract

Snowpack dynamics in continental climates are important for water-resource monitoring and snow water equivalent (SWE) estimation, yet the response of the snow depth–snow water equivalent (SD-SWE) relationship to changing thermodynamic and accumulation forcing remains insufficiently understood. This study develops a process-based framework to evaluate how moderate perturbations in air temperature and precipitation influence snowpack evolution and depth–mass coupling in representative snow regimes of northeastern Kazakhstan. SNTHERM (the Snow Thermal Model) simulations were combined with regression analysis, ANCOVA diagnostics, and bulk-density evaluation under controlled delta-change perturbations of air temperature (±1–2 °C) and precipitation (±5–10%). The results show that the SD-SWE relationship remains approximately linear within the tested perturbation range (R2 ≈ 0.78–0.84), although its parameters are partially sensitive to precipitation-driven accumulation. Temperature perturbations mainly affect melt timing, seasonal persistence, and snow-density redistribution, whereas precipitation modifies snowpack mass and overburden, enhancing mechanical compaction and increasing the regression slope. These findings indicate that snow density is a key integrative state variable linking energy balance, phase change, and compaction processes. Under the tested conditions, snow depth remains a physically consistent proxy for SWE, although the conclusions are limited by the one-dimensional model structure, reanalysis-based forcing, and restricted observational coverage.

Applied SciencesVol. 16(7)
Sarsen Amanzholov East Kazakhstan University (KZ), Astana Medical University (KZ)
Climate action
Openalex Percentile: Top 23%
Cryospheric studies and observations
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