Monitoring the Melting of Snow Stored in Snow Dumps (Yuzhno-Sakhalinsk, Russia)
Abstract
:1. Introduction
2. Study Object
3. Data Collection and Methods
3.1. Data Collection
3.1.1. Orthophoto Data
3.1.2. Meteorological Data
3.1.3. Snow Density Data
3.1.4. Debris Layer Data
3.1.5. Debris Temperature Data
3.2. Model Methods
3.2.1. The Enhanced Temperature Index (ETI)
3.2.2. Debris Enhanced Temperature-Index (DETI)
3.2.3. Debris Energy-Balance Model (DEB)
3.2.4. The Snow Melting According to Kuzmin Model
4. Results and Discussion
4.1. ETI
4.2. DETI
4.3. DEB
4.4. The Model of Kuzmin
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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City | The Mean Volume of Stored over the Year Snow (thous. m3) | The Mean Hard Precipitation Quantity Per the Winter (mm) | Settlement Area (km2) |
---|---|---|---|
Yuzhno-Sakhalinsk | 1500 | 220 | 160 |
Dolinsk | 200 | 299 | 5.1 |
Nevel’sk | 200 | 275 | 4.0 |
Kholmsk | 200 | 241 | 8.2 |
Korsakov | 150 | 191 | 6.0 |
Aniva | 100 | 281 | 1.1 |
Tomari | 100 | 274 | 1.4 |
Okha | 100 | 237 | 2.1 |
Uglegorsk | 100 | 211 | 7.7 |
Makarov | 100 | 204 | 1.7 |
Poronaysk | 100 | 151 | 8.4 |
Meteorological Parameter | Month | ||||||
---|---|---|---|---|---|---|---|
April | May | June | July | August | September | October | |
average | |||||||
Air temperature, °C | 1.6 | 7.0 | 11.5 | 15.7 | 17.1 | 13.1 | 6.3 |
Precipitation, mm | 57 | 69 | 59 | 86 | 107 | 103 | 99 |
Wind speed, m/s | 3.1 | 3.4 | 3.0 | 2.6 | 2.3 | 2.5 | 2.3 |
Total cloudiness, ball | 5.7 | 6.3 | 6.8 | 7.5 | 7.0 | 5.7 | 5.5 |
2018 | |||||||
Air temperature, °C | 2.7 | 8.3 | 10.6 | 15.3 | 16.5 | 13.3 | 7.7 |
Precipitation, mm | 23 | 61 | 76 | 96 | 49 | 63 | 86 |
Wind speed, m/s | 2.4 | 2.5 | 2.9 | 2.5 | 2.0 | 1.9 | 2.1 |
Total cloudiness, ball | 4.1 | 5.0 | 6.2 | 7.5 | 6.3 | 4.4 | 5.2 |
2019 | |||||||
Air temperature, °C | 3.3 | 10.5 | 11.8 | 15.7 | 15.9 | 13.8 | 7.2 |
Precipitation, mm | 21 | 42 | 105 | 53 | 114 | 57 | 45 |
Wind speed, m/s | 2.1 | 2.6 | 2.4 | 2.3 | 2.1 | 1.7 | 2.0 |
Total cloudiness, ball | 4.0 | 4.2 | 7.5 | 7.5 | 7.5 | 4.4 | 4.4 |
2020 | |||||||
Air temperature, °C | 1.7 | 7.8 | 11.9 | 16.4 | 16.3 | 14.5 | 7.4 |
Precipitation, mm | 57 | 56 | 65 | 66 | 155 | 76 | 157 |
Wind speed, m/s | 2.6 | 2.6 | 2.9 | 2.2 | 2.2 | 1.8 | 2.0 |
Total cloudiness, ball | 5.3 | 5.0 | 6.3 | 6.2 | 6.5 | 5.0 | 5.3 |
2021 | |||||||
Air temperature, °C | 3.0 | 6.7 | 13.2 | 20.4 | 17.3 | 14 | 6.3 |
Precipitation, mm | 69 | 103 | 51 | 13 | 95 | 111 | 81 |
Wind speed, m/s | 2.8 | 3.3 | 2.7 | 2.1 | 1.8 | 1.7 | 2.0 |
Total cloudiness, ball | 5.5 | 6.3 | 6.1 | 4.5 | 6.4 | 5.2 | 4.5 |
2022 | |||||||
Air temperature, °C | 3.7 | 8.5 | 11 | 17.8 | 18.3 | 14.5 | 6.8 |
Precipitation, mm | 64 | 101 | 106 | 52 | 113 | 106 | 91 |
Wind speed, m/s | 2.8 | 3.0 | 2.6 | 2.5 | 1.9 | 2.0 | 2.1 |
Total cloudiness, ball | 4.2 | 6.0 | 6.6 | 6.2 | 5.4 | 4.2 | 5.6 |
Parameters | Symbol | Unit | Value |
---|---|---|---|
Variables | |||
Distribution of temperature within the morainal layer | Td | °C | 1–8.5 |
Debris layer thickness | dz | m | 0.008–0.30 |
Time-step | i | h | 720–744 |
Air temperature [11] | T | °C | 1.7–20.4 |
Albedo [11] | α | – | 0.14–0.35 |
Incoming shortwave radiation [11] | I | Wm−2 | 551,390–783,330 |
Lag parameters accounting for the energy transfer through the debris layers | lagT | H | 0–10 |
lagI | h | 0–11 | |
Temperature factor [15] | TF | mm h−1 °C−1 | 0.0265–0.0984 |
Shortwave radiation factor [15] | SRF | m2mmW−1h−1 | 0.0001–0.0044 |
Average of the maximum air temperature | θmax | °C | 0.7–26.2 |
Average of the air temperature | θave | °C | −4.5–20.4 |
Mean daytime air temperature | θd | °C | −3.3–22 |
Mean night air temperature | θn | °C | −6.4–17.3 |
Mean daily wind speed | υd | m/s | 2.2–3.8 |
Mean night wind speed | υn | m/s | 1.1–2.7 |
Total cloudiness [11] | Nt | ball | 4.0–7.5 |
Low cloudiness [11] | Nl | ball | 4.2–6.6 |
Cloudiness coefficient | CN | – | 2–2.7 |
Snowmelt factor | β | – | 1–40 |
Snow water equivalent | S | mm | |
Constants | |||
Density of snow | pi | kg m−3 | 350–650 |
Latent heat of fusion of water | Lm | J kg−1 | 3.35 × 105 |
Debris thermal conductivity | kd | W m−1 K−1 | 2.1 |
R | W | S | H | T | P |
---|---|---|---|---|---|
W (melting volume) | 1.0 | ||||
S (snow dump base square) | 0.73 | 1.0 | |||
H (debris layer thickness) | −0.65 | −0.81 | 1.0 | ||
T (average air temperature) | 0.08 | −0.24 | 0.29 | 1.0 | |
P (precipitation quantity) | −0.18 | −0.38 | 0.32 | 0.07 | 1.0 |
Model | Correlation Coefficient | Predictors Quantity | Adjusted R-Squared |
---|---|---|---|
W from S | 0.74 | 1 | 0.5299 |
W from S, H | 0.77 | 2 | 0.5502 |
W from S, H, T | 0.80 | 3 | 0.5993 |
W from S, H, T, P | 0.81 | 4 | 0.5958 |
Model | Coefficients of Linear Regression | ||||
---|---|---|---|---|---|
k | a | b | c | d | |
W from S, H | 30,205.99 ± 27,210.15 | 0.88 ± 0.49 | −215,320.89 ± 147,591.03 | – | – |
W from S, H, T, P | 4000.57 ± 28,990.38 | 1.09 ± 0.48 | −216,743.27 ± 139,907.83 | 1290.78 ± 642.33 | 84.35 ± 94.14 |
Model | W from S, H | W from S, H, T, P | ETI |
---|---|---|---|
16 | 10 | 28 | |
n | 30 | 31 | 31 |
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Lobkina, V.; Muzychenko, A. Monitoring the Melting of Snow Stored in Snow Dumps (Yuzhno-Sakhalinsk, Russia). Geosciences 2025, 15, 205. https://doi.org/10.3390/geosciences15060205
Lobkina V, Muzychenko A. Monitoring the Melting of Snow Stored in Snow Dumps (Yuzhno-Sakhalinsk, Russia). Geosciences. 2025; 15(6):205. https://doi.org/10.3390/geosciences15060205
Chicago/Turabian StyleLobkina, Valentina, and Aleksandra Muzychenko. 2025. "Monitoring the Melting of Snow Stored in Snow Dumps (Yuzhno-Sakhalinsk, Russia)" Geosciences 15, no. 6: 205. https://doi.org/10.3390/geosciences15060205
APA StyleLobkina, V., & Muzychenko, A. (2025). Monitoring the Melting of Snow Stored in Snow Dumps (Yuzhno-Sakhalinsk, Russia). Geosciences, 15(6), 205. https://doi.org/10.3390/geosciences15060205