نوع مقاله : مقاله پژوهشی

نویسندگان

• علی افروزی ¹
• فرشید تاران ²

¹ دانشگاه بوعلی سینا

² موسسه تحقیقات فنی و مهندسی کشاورزی؛ سازمان تحقیقات، آموزش و ترویج کشاورزی؛ کرج؛ ایران

چکیده

در این مطالعه، روند زمانی بارش برف در این استان در دوره 1982-2023 بررسی شد. برای این منظور، داده‌های سطح پوشش برف (SC)، آب معادل برف (SWE) و عمق برف (SDepth) برای ماه‌های مختلف با استفاده از تصاویر ماهواره‌ای حاصل از محصول FLDAS استخراج شد. نتایج نشان داد که با افزایش 33/3 درجه سانتی‌گرادی متوسط دما در این دوره، SC با کاهش 13/90 درصدی مواجه شده و سال‌های 1982 و 2021 به ترتیب با مجموع 04/41043 و 12/4048 کیلومتر مربع بیشترین و کمترین SC را داشته‌اند. به طور میانگین، پوشش برف در ماه‌های می تا اکتبر وجود نداشته و در آپریل و نوامبر ناچیز (به ترتیب 10/170 و 72/286 کیلومتر مربع) بوده است. ژانویه بیشترین SC را با 22/5182 کیلومتر مربع داشته و در فوریه، مارس و دسامبر نیز پوشش برف مشاهده شده که هم‌ز‌مان با اواخر پاییز تا اوایل بهار ایران است. نتایج آزمون‌های من-کندال و شیب تایل-سن نشان داد که روند SC، SWE و SDepth در ژانویه، فوریه و مارس کاهشی و معنی‌دار بوده است. در هر چهار ماه ژانویه، فوریه، مارس و دسامبر، روند دمای هوا افزایشی و روند بارش کاهشی بوده است. در ژانویه و دسامبر، SC به ترتیب تندترین و ملایم‌ترین شیب کاهشی را داشته است. مقادیر ضریب پیرسون بیانگر همبستگی معکوس و معنی‌دار (در سطح 01/0) SC، SWE و SDepth با دما است. در کل، همبستگی این پارامترها با دما در مقایسه با بارش بیشتر بوده است، به ویژه در فوریه و مارس که دمای بیشتری نسبت به دسامبر و ژانویه داشته‌اند.

کلیدواژه‌ها

• تصاویر ماهواره ای
• چگالی برف
• شیب تایل-سن
• من-کندال
• همبستگی پیرسون

موضوعات

• منابع و مصارف آب

عنوان مقاله [English]

Monthly Changes in Snow Cover, Snow Depth and Snow Water Equivalent and their Correlation with Temperature and Precipitation; Case Study: The Province of Hamedan

نویسندگان [English]

• Ali Afruzi ¹
• Farshid Taran ²

¹ Bu Ali Sina University

² Agricultural Engineering Research Institute (AERI; Agricultural Research, Education and Extension Organization (AREEO); Karaj; Iran

چکیده [English]

Introduction

Snow is an important source for water supply in the agricultural sector, electricity production in factories, groundwater reserves, and rivers. This natural resource is important since it stores water in winter with low demand and releases it in hot seasons with high demand. Melted snow flow can be very useful in low-water seasons. In arid and semi-arid regions, snow is considered a basic source of fresh water. Significant spatiotemporal changes in distribution of snow on the scale of a basin can be important in determining the time and amount of snow melting in spring. The lack of sufficient and correct information about snow reserves can lead to inappropriate use of water resulting from snow melting and, as a result, irreparable damages. Therefore, measuring the surface covered by snow and its water equivalent, along with other information such as snow density, especially in areas where snow accounts for a large share of precipitation, is essential for resource planning and management. However, it is not possible to measure it in many areas due to harsh environmental conditions. Also, the data measured at one point cannot be generalized to a wide area of a basin. Thus, the use of satellite images can be considered as one of the methods of investigating spatial and temporal changes in distribution of snow in a region.



Materials and methods

To obtain the monthly values of snow cover (SC), snow water equivalent (SWE) and snow depth (SDepth) from January 1982 to December 2023, the FLDAS (Famine Early Warning Systems Network—FEWS NET—Land Data Assimilation System) product from the Noah 3.6.1 Land Surface model was used. This product is at latitude 90° to -60° and longitude 180° to -180° with a spatial resolution of 0.1°×0.1° in netCDF format and its images are monthly available from January 1982 until now.

The non-parametric Mann-Kendall test was used to investigate the increasing, decreasing or constant trend of the data during specific time intervals in the period. The Theil-Sen slope was used to calculate the slope of the trends. The correlation of the temporal distribution of snow cover with the two meteorological parameters of temperature and precipitation was determined using the Pearson's method.



Results and discussion

The results showed that the year 1982 with a total of 41043.04 km2 had the highest and the year 2021 with a total of 4048.12 had the lowest SC. These data indicate a 90.13 percent decrease in SC in 42 years, which is understandable considering the 35.08 percent increase in the mean temperature (from 9.49 to 12.82 ºC) in this period. The monthly average of SC in this period showed that there was no snow cover from May to October, and in April and November it was very insignificant and negligible compared to in January, February, March and December. Among these four months, January had the highest average SC.

According to the Mann-Kendall test, the trends of SC, SWE and SDepth was decreasing in all the four months of January, February, March and December. Temperature and precipitation values had increasing and decreasing trends, respectively.

According to the Teil-Sen slope test, SC had the steepest and gentlest decreasing slope in January and December, respectively. In the case of SWE and SDepth, the steepest decreasing slope was related to February, and the gentlest decreasing slope occurred in December. The increase in temperature had the gentlest slope in the two consecutive months of December and January and the steepest slope in the two consecutive months of February and March. The steepest and gentlest slope of decrease in precipitation occurred in March and February, respectively.

The Pearson's correlation coefficient values indicated that SC, SWE and SDepth have inverse correlation with temperature and direct correlation with precipitation. Overall, SC, SWE, and SDepth were more correlated with temperature than precipitation, especially in February and March when temperature was higher than in December and January.



Conclusion

In this study, using the satellite images obtained from the FLDAS product, the data of snow cover, snow water equivalent and snow depth were obtained in the province of Hamedan for the 42-year period of 1982-2023. The results showed a significant decrease in the snow cover during this period, which was expected due to climate change and temperature increase. The snow cover, snow water equivalent and snow depth have had decreasing trends. The trends of the two climatic parameters, temperature and precipitation, have been increasing and decreasing, respectively. The steepest and gentlest slope of the decrease in snow cover occurred in January and December, respectively. There was an inverse correlation of snow cover, snow water equivalent and snow depth with temperature, and a direct correlation with precipitation. In general, the correlation of snowfall parameters with temperature, especially in warmer months, was more than their correlation with precipitation.

کلیدواژه‌ها [English]

• Mann-Kendall
• Pearson correlation
• Satellite images
• Snow density
• Theil-Sen slope