Document Type : Original Article
Authors
1
Faculty Member, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.
2
PhD student in climatology at the Faculty of Social Sciences, University of Mohaghegh Ardabili , Ardabil, Iran.
10.22034/gsma.2026.2067083.1110
Abstract
1. Introduction
One of the most important impacts of climate change is the change in precipitation and temperature patterns, which directly affects the snow cover and reserves of mountainous areas and water flows. Mountain snow cover is not only known as a sensitive indicator of climate change, but also plays a vital role in providing freshwater, regulating river flows, and maintaining mountain ecosystems. In addition to providing freshwater, the Sabalan Mountain plays an important role in maintaining biodiversity and mountain ecosystems. Therefore, the aim of this study is to investigate the trend and temporal-spatial changes in the snow cover of the Sabalan Mountain in the past 25 years.
2. Methodology
In this study, the snow cover of the Sabalan and its changes in the 25-year period (2000-2024) from March 2000 to December 2024 were investigated using the sixth version of MOD10ACM obtained from MODIS sensor images of the Terra satellite. To achieve the research goals, first, the frequency of the percentage of snow cover on an annual scale from March 2000 to December 2024 was extracted, then the frequency of this cover for each of the months of January to June and November and December in the years under study was categorized into 7 classes (no snow cover, 1-10%, 10-30%, 30-50%, 50-70%, 70-90% and 90-100%). Then, the trend of changes in each of the classes of snow cover percentage in months (monthly snow cover time series) was evaluated using the Mann-Kendall test and Sen’s Slope statistical methods. Also, monthly average snow cover maps were drawn during the study period and monthly difference maps were drawn.
3. Results
An examination of the percentage of snow cover classes of the total area of the Sabalan Mountain in 8 months over 25 years (2000-2024) shows a significant decrease in complete snow cover (class 90-100%) in the cold months of the year (January and December) and accelerated snow melting in the warm months (April to June). In January, the average complete snow cover decreased by 8.5%, while the intermediate classes (30-70%) expanded. In December, 16.8% decrease in complete snow cover and an increase in areas with little snow were observed. Spring months such as April and May show a sharp decrease in complete snow cover and an increase in areas without snow, so that in June, complete snow cover has reached almost the minimum possible. November also showed a significant decrease in complete snow cover and a delay in the start of the snow cover season. These changes are probably due to increasing temperatures, changing precipitation patterns, and early snowmelt, which have hydrological consequences such as changes in the timing and amount of spring runoff and reduced water storage. Trending of snow cover changes in the Sabalan using the Mann-Kendall test and the Sen’s Slope showed that snow cover changes in the Sabalan Mountains follow a complex seasonal pattern, and the snow cover trend in the region is decreasing in autumn and increasing in winter, which can be attributed to the shortening of the snowfall period in this region. The results of the Mann-Kendall test and the Sen’s Slope indicate that in the 50-70% snow cover class, November shows a significant decreasing trend, while in December it increases, and in the 70-90% class, a significant increase in snow cover was observed in January. Although the amount of this increase is small, the presence of a positive slope and its statistical confirmation (Z= 2.41) indicate that the trend of snow changes in this region requires an investigation of precipitation and temperature patterns in the region. Differential snow cover maps of the Sabalan region during the period 2000-2024 showed that the greatest decrease in snow cover occurred in the months of December, January, and February, which can be interpreted as an indicator of winter warming and reduced snowfall. In contrast, the increase in snow cover in March and to some extent June is significant, indicating a change in the timing of snow melt or a shift in the precipitation phase towards later periods of the year.
4. Discussion
The existence of a decreasing trend in snow cover levels in the Sabalan Mountains is consistent with studies by other researchers, including Barnett et al. (2005); Immerzeel et al. (2010); Sorg et al. (2012); Marty et al. (2013); Chen et al. (2016); Huss et al. (2017); Wang et al. (2021); Faraji et al. (1402), who have studied changes in snow cover in mountainous areas and have pointed out the reduction in the area of snow cover in the mountains they studied. The reduction in snow cover in the Sabalan has serious consequences for the water resources of the region, because the melting of snow in this mountain is the main source of water for the rivers and aquifers of the region. These changes also negatively affect mountain ecosystems, agriculture and local communities. Similar studies in other mountainous areas of the world have also shown that climate change is increasingly affecting snow cover (IPCC, 2021). This study shows that climate change is greatly affecting mountainous areas, and this finding is consistent with the results of the research of Barnett et al. (2005); Immerzeel et al. (2010); Sorg et al. (2012); Marty et al. (2013); Pepin et al. (2015); Chen et al. (2016); Huss et al. (2017); López-Moreno et al. (2021); Wang et al. (2021); Liu et al. (2021); Zhang et al. (2021) and Faraji et al. (1402).
5. Conclusion
To address these challenges, there is a need to develop sustainable management strategies and policies to adapt to climate change and reduce its impacts. In this regard, several suggestions are presented: investigating the relationship between snow cover changes and climate parameters and conducting a long-term trend analysis of regional climate variables using time series data, more detailed studies on the impact of these changes on regional water resources, studying the relationship of this variable with climate indicators such as NAO, ENSO and AO to explain the mechanisms of changes observed in the region.
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