SNOW is a huge water resource in most parts of the world. SNOW water equivalent supplies 1/3 of the water requirement for farming and irrigation throughout the world. Water content estimation of a SNOW-COVER or estimation of SNOWmelt runoff is necessary for Hydrologists. Several SNOWmelt-forecasting models have been suggested, most of which require continuous monitoring of SNOW-COVER. Today monitoring SNOW-COVER patches is done through satellites imagery and remote sensing methods. MODIS have smaller Spatial Resolution and more bands in comparison with Meteorology Satellite like NOAA. Therefore, in this research we used MODIS data for creating SNOW COVER imagery. Existence of cloud in the study area is a major problem for SNOW COVER monitoring. Therefore, in this research SNOW COVER area CHANGES were estimated without MODIS data period, but with DEM imagery and regressions between temperature, height and aspect. For this purpose, on 10 Esfand when the image was suitable we estimated the SNOW COVER area. In comparison with real image, precision of the method was confirmed.

SNOW reservoirs are one of the most important sources of water supply in Iran. This study aims to investigate the CHANGES in SNOW COVER in Sefidrood basin and its sub-basins. To achieve this goal, SNOW COVER images of MODIS's MOD10cm product were used over a period of 19 years (2000 to 2019). After analyzing the images in ENVI software, the SNOW area of each image was calculated and, consequently, monthly values for all years of the study period were extracted and transferred to ArcGIS software. The modified Mann-Kendall test was applied to examine the annual and seasonal trends of SNOW COVER. Afterwards, Sen’ s slope estimator test was used to determine the rate of change. Based on the findings, it can be seen that the time of beginning and end of SNOW in Sefidrood basin and its subbasins has undergone very little change. The SNOW COVER of the basin starts in October and reaches its minimum in April after increasing towards the cold period of the year. January is the month with maximum SNOW COVER in all sub-basins. During the period under review, the range of SNOW COVER was maximum in the water year 2006-2007 and minimum in 2009-2010. Findings from the fit of the modified non-parametric Mann-Kendall test on the annual time series of the SNOW COVER of the basin indicate a decrease and of course insignificant trend in most of the basin area, although sometimes slight increasing trends are also seen. In terms of spatial distribution, in the central and eastern regions of the basin, there is a significant decreasing trend of SNOW COVER; its annual decreasing rate in some areas is 17. 77% per decade. Seasonal trends are also decreasing. The highest rate of decrease is related to winter, which in some areas reaches about 33% per decade.

In this study in order to monitor SNOW COVER, the Moderate Resolution Imaging Spectroradiometer (MODIS) optical images were used, while for detection of SNOW COVERed areas, the SNOW index-NDSI, was applied. The results showed-according to the climatic conditions of the region-during the following months: December, January, February and March, most of the area is COVERed by SNOW and the maximum extent of SNOW COVER occurred in January. In West Azerbaijan province there is found a negative trend of SNOW COVER with a drastically reduction in January, as well as the provinces East Azerbaijan and Ardebil showed the decreasing of SNOW COVER in this month. The results of this study show that, CHANGES in SNOW COVER imply a rise in temperature in this region leading to the reduction of SNOW COVER in January. This trend represents global warming and climate change impacts on SNOW COVER in the study area. Investigation of extreme indices confirms the assumption that by taking temperature increase into consideration, regional winter precipitation pattern has been changed from SNOW to rain, causing the reduction of SNOW storage in the catchment of study area. In addition, the extreme temperature index study in the period of 2011-2040 and the baseline by considering climate change approach in North West of Iran by using outputs of general circulation models under A2 scenario and downscaling models LARS-WG indicates the number of frost days or the number of icy days decreased compared to the baseline which is not unexpected according to reports by the Intergovernmental Panel on Climate Change (IPCC) as well as several studies confirmed global warming. Moreover, indices such as growth period increased, while diurnal temperature variation decreased compared to the baseline confirming SNOW COVER reduction in the region as a threat of SNOW storage in the region.

Introduction: Global warming has profoundly changed the climatic regions of the earth and the time and the place of SNOWfall, which has caused a lot of damage to humans, especially in recent decades. Indeed, depending on the nature of the climatic regions, these CHANGES are diverse and varied. Mountains and valleys play different roles in the uneven distribution of the temperature and SNOW. The effects of different directions can be very important in SNOW COVERage on the northern and southern slopes. In this research, using statistical models and satellite images in the Alvand, the role of the elevation, the direction of the slope, and the effect of temperature CHANGES on SNOW COVER in the recent decade (2015-2006) have been investigated. Materials & Methods: In this research, based on Landsat satellite 5, 7, and 8 imagery, the data from the visible and infrared bands were used to extract SNOW data based on the NDSI index. The NDSI index was applied using relationship (1) to produce SNOW maps on images. Indeed, the use of relative indices such as NDSI reduces the effect of the topography on the result. (1) To investigate the role of the Alvand in SNOWfall in both of its northern and southern slopes and the SNOWfall regime CHANGES in its windward slope and windsurf, the harmonic analysis was used. For this purpose, to analyze the SNOWfall co-ordinates and periodic behaviors and time variations, the monthly mean SNOWfall per cm with harmonic analysis was used. This analysis is given as a substring using a time series. Resultsand Discussion: According to the findings of the NDSI index, Tuyserkan area receives less SNOW (62%) than Hamadan (69%). The moist air mass ascending the western slopes of the Alvand's heights causes more rainfall than its eastern slopes. However, the temperature of Hamadan station is lower than that of Tuyserkan due to its northern slopes in the Alvand and the less energy it receives from the sun, which has made the SNOWfall on the northern slopes be more visible than it is on the southern slopes. The minimum and maximum temperatures have increased in the winter. This steep trend of increase in the winter temperatures along with lower SNOWfall indicates the effects of climate change and global warming on Hamadan and Tuyserkan regions. The value of the variance in the second harmonic reflects the effect of elevations on the region's climate. The value of the second harmonic variance in the northern slope which is 28% and significant shows the impact of topography on SNOWfall in the area. Indeed, the SNOWfall up to 28 % is related to the height and topography of the northern slopes of the Alvand. While at Tuyserkan Station, this amount is reduced to 20%, meaning that the northern altitude of the Alvand is more effective in the SNOWfall. Conclusion: The Alvand is a branch of the Zagros mountain range that passes through Hamedan province and has high peaks. The climatic phenomena of this mountain range are abundantly observed in the province. Severe winds and SNOWfall of the Alvand altitudes are among these phenomena. The mountainous cities of the province, including Hamadan and Tuyserkan, are among the most affected by the Alvand. This study by examining the hidden features of the climatic data by harmonic analysis and satellite images showed that the northern slope shared more than the southern slope in SNOWfall which was a significant amount in the second harmonic and a relative decrease in the temperature and SNOWfall. The northern slope was colder in the northern hemisphere and the sunrise of southern slope got more heat than those that were not exposed to the direct sunlight. The percentage of SNOW in the NDSI index on both sides of the Alvand confirmed this geographic reality. In general, the results showed a hidden feature of the rise in temperature and SNOW loss in the data and satellite imagery also recognized this fact. Considering the fact that the Alvand is a climatic region of the country's cold and mountainous regions and the sustainability of the natural environment depends on the relative stability of the climate, in order to achieve sustainable development and land use in the region, it seems that regional climate change should be considered in the context of climate change and the reduction of SNOWfall in the long time.

Examining the SNOW COVER and recognizing the patterns of SNOW formation can inform the environmental planners about the behavior of this phenomenon. In this research, by calling MODIS satellite data in Google Earth Engine environment and using NDSI index, the SNOW COVER condition of Khalkhal city in 2003-2022 was investigated. In order to model SNOW systems in Khalkhal city, data related to heavy SNOW report was received from Iran Meteorological Organization. Then, two general patterns for the SNOW systems of Khalkhal city were determined by the cluster analysis method on the sea level pressure values ​​on the days with SNOWfall. Then, by selecting a representative day from each model, the situation of sea level pressure, geopotential height, temperature, temperature wind, humidity drift, wind flow and wind speed were analyzed. The results showed that the SNOW deposits in the central and northern areas of Khalkhal city reach their maximum extent especially in the winter seasons. The results also showed that there are two general patterns for the transfer of cold air mass and SNOWfall to the study area, each of which has its own mechanisms. The first pattern is influenced by the gradient of pressure and western winds, while the second pattern is influenced by Siberian high pressure systems, air subsidence and northern winds.

The study and measure of SNOW level CHANGES as one of the main sources of water supply, is so important. Due to the harsh physical conditions of mountainous environment, it is not possible to conduct the earth measuring continuously to estimate the SNOW water resources and forming the database. So, using satellite images to identify SNOWy areas and assess its CHANGES has a great importance.The data used in this study are TERRA/MODIS sensing satellite images of Iran's North West region related to years 2000 up to 2009. The method used in this study is NDSI index, and Supervised and Unsupervised classifications, after comparing between the methods, the Supervised classification was selected as the appropriate method. Review of the maps related to CHANGES of SNOW COVER in April showed that during the study period, the lowest amount of SNOW is related to year 2008 with an area of about 1040.01 square kilometer and the highest area is for year 2007 with about 10471.78 square kilometer.This represents a 1000 percent CHANGES in SNOW COVER during one decade at the north west of Iran and shows vulnerable of water resources depending on melting SNOW. Also the results showed that in the years which the average of cold season temperature is lower, the area COVERed by SNOW is more than the other years, so that in year 2007, it had the lowest amount of SNOW COVERage during the last 10 years (2.6 co) while the highest amount of SNOW COVER during the last ten years is related to this year. (10471.78 km2).

Studying and evaluating CHANGES in SNOW COVER, as one of the most significant sources of water supply is very important. Due to the conditions of inaccessible mountainous areas, it is not possible to make permanent ground measurements to estimate SNOWfall resources and form a database. Therefore, the use of satellite imagery in identifying SNOW-COVERed areas and evaluating its CHANGES is very important and necessary. In this study, satellite imagery of MODIS sensor in Marber Basin located in the south of Isfahan province for the 20-year period from 2000 to 2019 was used. It is noteworthy that in this study, the Google Earth Engine system, or GEE, was used, which is a new and very useful system. In the present study, more than 7000 images of daily SNOW COVER were used, which are available in GEE in the shortest time. TFPW-MK test was used to evaluate the trend of SNOW COVER CHANGES. In this study, in addition to programming and calling images and extracting SNOW COVER values in the engine system and process analysis by performing TFPW-MK test, ArcGIS10. 5 software was also used in preparing the outputs. The results showed that the trend of CHANGES in SNOW COVER levels during the mentioned 20-year period has been decreasing, so that from about 120 square kilometers to less than 60 square kilometers in 2018, according to the percentage of trust (p-column in The TFPW method has a significant negative trend at the level of 5% in January and August and a significant negative trend at the level of 10% in June. The annual trend was also examined by TFPW test and shows a significant negative trend at the level of 5%.

Introduction The SNOWs of the Alborz mountain range play an important role in providing underground and surface water for the settlements around it and the densely populated Caspian Plain, and the permanent rivers of the northern and southern slopes of Alborz are fed by the SNOWs of the high places of Alborz. Global warming has caused CHANGES in the atmospheric-climatic parameters of Iran,in such a way that temperature and evaporation have increased and precipitation, especially SNOW, has decreased. These CHANGES, which are considered as independent variables, will cause CHANGES in the dependent variable, which is the SNOW COVER of the high points of the Alborz Mountains. Its consequences can be accelerating the melting of SNOW, increasing the process of flooding of rivers in the catchment areas of the study area, and the destruction of habitats and settlements downstream. Therefore, the monitoring of Alborz SNOW area can be used in formulating water management strategies and sustainable development. Materials and methods In this study, the temporal-spatial variations of the Central Alborz SNOW COVER on a seasonal scale for the years 1985 to 2020 were monitored using Landsat TM, ETM+ and OLI for 1985, 1995, 2005, 2015 and 2020. For each season of the year, an image was prepared that was a combination of 4 satellite images and radiometric and geometric corrections were made on it. SVM algorithm was used to extract the SNOW COVER. The area of SNOW COVER was obtained by transferring the classified map to the ArcGIS. Results and discussion The results showed that the kappa coefficient for the classified maps was more than 0. 91. The average SNOW COVERs for winter, autumn, spring and summer were 1. 19, 0. 47, 0. 14 and 0. 004 million hectares, respectively. SNOW COVERs have been declining from 1985 to 2020, reaching 1. 98 million hectares in 2020 from 1. 68 in 1985 to 1. 68 in winter. In the autumn, it increased from 0. 84 in 1985 to 0. 15 million hectares in 2020. In winter and autumn, SNOW COVER in the eastern part of central Alborz has decreased sharply compared to the western part. In the winter of 1985, SNOW started at an altitude of 1, 500 meters, but by 2020 it reached 2, 500 meters. In the summer, SNOW was more than 3, 900 meters high in 1985, but peaks more than 4, 200 meters in 2015 and 2020. The area of SNOW COVER in Central Alborz has a decreasing trend, which has the highest rate in winter. In order to increase the spatial accuracy of SNOW, the present research used Landsat series images with 30 meters pixels, and its results are more favorable than the output of MODIS images. Conclusion Therefore, the results of this study showed that the accuracy of the support vector machine algorithm is more than 0. 91% in the classification of Landsat images, this method can be used to extract SNOW patches,in such a way that it separated the shadow SNOW and cloud from the SNOW and identified the accumulation of SNOW in the valleys. It can be concluded that using images with spatial resolution of 30 meters and applying classification algorithms for SNOW extraction is better than using NDSI index and MODIS images. On the other hand, the process of SNOW COVER in central Alborz has been such that during 25 years, the area of SNOW has decreased from about 0. 7 million hectares and a large amount of fresh water storage in Alborz has been lost.

Aim The aim of this study was to investigate the spatio-temporal CHANGES of SNOW COVER and SNOW water equivalent in Karun, Karkheh and Dez basins and the effect of CHANGES in the discharge of these basins. Methodology In order to extract SNOW COVER and measure SNOW water equivalent and their correlation with the discharge of Karun, Karkheh and Daz basins, from the thresholding method on reflective and thermal bands, Man Kendal method, Spearman correlation and MODIS measurement data (2000-2020), available images of AMSR-2/AMSR-E sensor (2003-2020) and monthly discharge at the same time with the mentioned satellite images have been used. Findings The results of time series analysis in all three studied basins show a decreasing trend of SNOW COVER area and volume of the SNOW water equivalent in most months And The most decreasing CHANGES in SNOW COVER area were observed in Dez basins and March with a value of-3. 26 and the most decreasing CHANGES of SNOW water equivalent were observed in Karun basin and February with a value of-3. 86. The highest correlation in all three basins was related to Dez basin in June with a value of 0. 775 (p<0. 01) and the lowest was related to Karkheh basin in February with a value of 0. 183. Examination of the relationship between discharge and SNOW water equivalent AMSR-E/AMSR-2 images also showed that the highest correlation was related to Karun Basin in January with a value of 0. 721 (p<0. 01). Conclusion Generally, in the observed years, the area of SNOW COVER and SNOW water equivalent in all months has decreased and is more severe in Karun and Dez basins. In addition, in most months, there is no significant relationship between SNOW COVER area and basin discharge.

Introduction North Karun Basin is one of the SNOW-COVERed regions of Iran and its SNOWfall has a great role in the water supply situation in the central and southern regions of the country. In this research, an attempt has been made to investigate the CHANGES in the SNOW-COVERed surface in the study basin. Access to this information in high and impassable areas is possible only with the help of remote sensing techniques. The MODIS sensor has multiple spectral bands, but the ETM+ sensor has a better spatial resolution. The purpose of this study is to monitor, compare and map SNOW-COVERed areas by MODIS and ETM+ data in the northern part of the Karun Basin. Materials and Methods The research has been conducted in the northern part of Karun Basin, as one of the SNOWy areas in Iran. This area is geographically between 31°,19' 9'' to 31°,39' 17'' northern latitude and 49°,33' 56'' to 51°,54' 23'' eastern longitude. The study basin is over 14802 square kilometers, about 90% of Chaharmahal and Bakhtiari Province and 23% of Karun Basin. The height of the study area is changing between 800 m at Karun No. 4 dam to 4440 m at the Peak of Zard Kooh Mountain. The satellite data included MODIS and ETM+ sensors over a period of 15 years (2000 to 2015) used to calculate NDSI. The satellite pass-times were at Julian day number 360, 333, 365, 355, 360, 363, 331, 350, 336, 355, 342, 345, 363, 334 and 1. Results and Discussion The minimum and maximum SNOW-COVERed areas produced by MODIS in 2010 and 2013 were 107, 295 and 1, 364, 118 ha, respectively, and for ETM+ sensor, were 128, 758 and 1, 090, 580 ha, in 2010 and 2006, respectively. The SNOW-COVERed areas estimated by MODIS in 14 dates were more than the corresponding values for ETM+. The exception was 2011 when the SNOW-COVERed area in the ETM+ was greater than MODIS (3067 ha or 1. 36%). Based on the results in 15 years, the MODIS sensor overestimated the SNOW-COVERed area equivalent to 26. 95% compared to ETM+. In a small SNOW-COVERed area, deviation from the 1: 1 line was small but, by increasing SNOW-COVERed area, deviation increased. The overall difference in SNOW pixels in the 15 years between the two sensors was 26. 95%. As MODIS pixels are 500 by 500 m, and ETM+ pixels are 30 by 30 m, the size of the pixels in ETM+ resized to 500 m by resampling method in which to use same pixel size for another comparison. After resampling, the slope of the regression line slightly dropped. However, there are no-significant differences. Using data from MODIS and ETM+ sensors had a good performance to monitor spatio-temporal and map SNOW-COVERed surfaces in North Karun Basin. Conclusion Due to spatio-temporal frequency in obtaining MODIS imageries via internet freely in temporal resolution of eight-days and one-day, and also at very wide area COVERage, short-time monitoring is possible for hydrological studies, forecasting and flood warning. On the other hand, the ability and better spatial resolution of ETM+, small SNOWy fields could be estimated and mapped better than MODIS. Although it may be need to mosaic several ETM+ imageries to COVER wide areas. However, paying attention to geographical characteristics and time of the study area, end user decides to choose one or both sensor data.