Spatio-temporal variations of snow cover in the southern slope of central Alborz

Document Type : Full length article


1 Associate Professor of Climatology, Faculty of Geography, University of Tehran, Tehran, Iran

2 PhD student in Climatology, Faculty of Geography, University of Tehran, Tehran, Iran

3 Professor of Climatology, Faculty of Geography, University of Tehran, Tehran, Iran

4 Assistant Professor of Climatology, Faculty of Geography, University of Tehran, Tehran, Iran


Snow cover as one of the most important components of the Earth's surface plays an important role in the global hydro climate processes. Snow acts as a temporary reservoir of water and keeps the rivers flowing long time and recharges underground aquifers to provide water during the dry season for billions of consumer. Study of spatial and temporal variability of snow cover in arid and semiarid region such as Iran can indicate very high temporal and spatial variations of precipitation. In Iran, about 60% of surface water and 57% of groundwater is in snow covered areas. Hence, the purpose of this study is to evaluate the accuracy of MODIS snow products and combines remote sensing and terrestrial data to investigate the spatiotemporal changes of snow cover in South Central Alborz slopes.  Eventually, this research assesses the relevance of this change with climatic elements.
Materials and Methods
In the present study, we have used data from 16 synoptic stations located in the study area and MODIS data. At first,  the MOD10A and MOD10A2 products have been used to extract snow cover. Then,  snow depth, precipitation and temperature (on a scale of hourly and monthly) data of the selected stations have been used to evaluate the accuracy of MODIS data and relationship between snow cover changes and climatic elements. MODIS images have also been used for the detection of snow cover by the NDSI index = (band4-band 6) / (band4 + band6). In this equation, Band4 is the spectral reflectance in the visible band (0.555 micrometers) and band6 is the spectral reflectance in the intermediate-infrared band (1.64 micrometers). Hence, in this sensor products addition to snow other phenomena is indivisible. Therefore, in order to separate and identify the pixels of different phenomena, the images have been processed in ArcGIS. For evaluation of the pictures, daily images (MOD10A1) for three years (2007-2009) winter (December to February) have been processed and accuracy assessment conducted by snow depth data. If the depth of snow at the station is one centimeter or more, the pixel located at the station is considered as snow cover and otherwise as no snow. The adaptation degree between the image and the station has been obtained by a coefficient divided by the number of days for the correct classification (snow-snow and no snow-no snow) divided to the total number of days in each month, as a percentage.  Finally, the variability of snow cover has been evaluated by Mann-Kendall test. To examine the relationships of snow cover anomalies and climatic conditions, Z index has also been employed.
Results and discussion
The percentage of adaptation of the earth data and satellite images for three months of December, January, and February is 81, 67 and 75 percent, respectively. However, these results are the average of all the stations and in the snowy areas the average image precision is even reduced by 40%. The studies show that errors are often caused by clouds in the location pixel. Therefore, the second assessment has been performed by removing cloudy days. The results show that at this phase image accuracy and the adaption percentage is increased for each quarter to more than 95 percent. According to the movement of the clouds, the eight days product of this sensor has been used to monitor and evaluate changes in snow cover. The snowfall in the region began in October, with the fall in air temperature and increase in snow accumulation, reaching a maximum of 34 percent during the period ending January 9. The snow cover in January and February were 31.4 and 25.6 percent, respectively, with the highest monthly values. The highest and lowest snow cover values for these two months were 76.2% and 9.7%, respectively, in January 9, 2008, and February 2, 2015. The coefficient of snow cover variations is increased with decreasing height, and is extremely severe in less than 1500 m, while in the areas above 2500 m in autumn and winter, it is less than 20%. A survey of monthly snow cover changes shows that in October, November and March, the trend is increasing, although not significant. While in January, February, April, and especially in May most snow covers are declined over the last 15 years. This negative trend is significant in May with a score of -2.18. Comparison of the average rainfall, temperature and snow cover percentage indicate that most of the positive anomalies of snow cover with positive anomalies of rainfall and negative anomalies of temperature and its negative anomalies are consistent with the positive anomalies of temperature and negative rainfall.
The results of the satellite image accuracy estimation showed that the MODIS snow product has a good ability to estimate the snow cover area of the study area. But the cloud is one of the main limitations of MOD10A1. As in the present study, after removing cloudy days, the average accuracy of these images has risen from 67% to over 95% and even in snowflake stations to 100%. Since the clouds are changing rapidly and daily, but snow is gradual, it is recommended to use this sensor product (MOD10A2) to monitor the long-term snow cover. The monitoring results showed that the January and December have the highest ​​snow cover area. In terms of spatial changes, the continuity and the extent of snow cover decreases from West to East in the study area. The percentage of snow covers in the Shahrood and Karaj river basins are more than the Semnan and Hablehrood basins. The results of the trend show that although snow cover changes tend to be negative for most of the months and high altitude zones, rarely this decline is significant. The highest increase was observed in March with a score of 1and the most severe declining trend in May, with a score of -2.18, and a maximum reduction in peak space was also observed in the altitudes of 2500 to 3750 meters. In most of the years, the positive anomalies of the snow cover are coincided with the positive anomalies of rainfall and the negative anomalies temperature.


Main Subjects

ایلدرمی، ع.؛ حبیب‏نژاد، م.؛ صفری شاد، م. و دلال اوغلی، ع. (1394). استفاده از تصاویر ماهواره‏ای MODIS و شاخص NDSI به منظور تهیة نقشة پوشش برف (مطالعة موردی: حوضة بهار)، فضای جغرافیایی، 5: 125ـ140.
طاهری، ح. و ارکیان، ف. (1392). بررسی تغییرپذیری تعداد روزهای برفی و عمق برف در ایران، نیوار، 82ـ83: 47ـ58.
ابراهیمی، ه.؛ غیبی، ا. و ملکوتی، ح. (1391). روند تغییرات پوشش برف در مناطق برف‏خیز ایران با استفاده از داده‏های سنجندة مادیس، نیوار، 78ـ79: 3ـ10.
تماب (1375). بولتن وضعیت آب کشور، 8(12): 890.
دادشی، م.؛ مختاری، م. و طیبا، ع. (1393). محاسبة سطح برف با استفاده از تصاویر سنجندة مودیس (مطالعة موردی: استان تهران)، اولین همایش ملی کاربرد مدل‏های پیشرفتة تحلیل فضایی، دانشگاه آزاد یزد.
رسولی، ع.ا. و ادهمی، س. (1386). محاسبة آب معادل پوشش برفی با پردازش تصاویر سنجندة مودیس، جغرافیا و توسعه، 10: 23ـ36.
فتاحی، ا. و وظیفه‏دوست، م. (1390). برآورد دمای سطح برف و گسترة پوشش برف با استفاده از تصاویر سنجندة MODIS مطالعة موردی: حوضه‏های استان گلستان، تحقیقات جغرافیایی، 102: 149ـ168.
کیخسروی کیانی، م.ص. و مسعودیان، ا. (1395). واکاوی پیوند روزهای برف‏پوشان با ارتفاع، شیب، و وجه شیب در ایران‌زمین، پژوهش‏های جغرافیای طبیعی، 48(1): 1ـ14.
میرموسوی، ح. و صبور، ل. (1393). پایش تغییرات پوشش برف با استفاده از تصاویر سنجندة مودیس در منطقة شمال‏ غرب ایران، جغرافیا و توسعه، 35: 181ـ200.
میریعقوب‏زاده، م.ح. و قنبرپور، م.ر. (1389). بررسی کاربرد نقشه‏های پوشش برفی حاصل از تصاویر ماهواره‏ای مودیس در مدل‏سازی رواناب ذوب برف (مطالعة موردی: حوضة آبخیز سد کرج)، علوم زمین، 76: 140ـ148.
نجفی، ا. ؛  قدوسی، ح. ؛ ثقفیان، ب. و پرهمت، ج. (1386).  برآورد رواناب ذوب برف با استفاده از سنجش از دور و سامانه اطلاعات جغرافیایی در حوضه شهرچای ارومیه، فصلنامه پژوهش و سازندگی، 20: 177-185.
Bednorz, E. (2004). Snow cover in Eastern Europe in relation to temperature, precipitation and circulation, Int. J. Clim, 24: 591-601.
Bormann, K.; McCabe, M. and Evans, J. (2012). Satellite based observations for seasonal snow cover detection and characterization in Australia, Remote Sensing of Environment, 123: 57-71.
CunJian, Y.;  ZiJian, Z. and Jing, N. (2012). Temporal and spatial analysis of changes in snow cover in western Sichuan based on MODIS images, Sci China Earth Sci, 8: 1329-1335.
Dadashi, M.; Mokhtari, M. and Tayeba, A. (2014). Calculate the area of snow cover using MODIS data (case study: Tehran Province), The first Conference on Application of advanced spatial analysis models, Islamic Azad University of Yazd.
Dai, L. and Che, T. (2014). Spatiotemporal changes in snow cover from 1987 to 2011 in Northern China, 7th EARSeL LISSIG Workshop, Bern.
Dedieu, J.P.; Fontaine, A. and Ravazzani, G. (2014). Shifting mountain snow patterns in a changing climate from remote sensing retrieval, Science of the Total Environment, 493: 1267-1279.
Dietz, A.,; Conrad, Ch. and Kuenzer, C. (2014). Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data, Remote Sens, 6: 12752-12775.
Dong, Ch. and Menzel, L. (2016). Improving the accuracy of MODIS 8-day snow products with in situ temperature and precipitation data, Journal of Hydrology, 534: 466-477.
Ebrahimi, H.; GHeibi, A. and Malekuti, H. (2012). The trend of snow cover in snow-prone regions of Iran using MODIS data, Nivar, 78-79: 3-10.
Fatahi, E. and VazifehDoost, M. (2011). Estimate the snow cover and snow surface temperature using MODIS images (case study: Basin in Golestan province), Geography Research Quarterly, 102: 149-168.
Gafurov, A. and Bardossy, A. (2009). Cloud removal methodology from MODIS snow cover product, Hydrol. Earth Syst. Sci, 13:1361-1373.
Garen, D. and Marks, D. (2005). Spatially distributed energy balance snowmelt modeling in a mountainous river basin: estimation of meteorological inputs and verification of model results, Journal of Hydrology, 315:126-153.
Hall, D.K.; Riggs, G.A.; Salomonson, V.V.; DiGirolamo, N.E. and Bayr, K.J. (2002). MODIS snow-cover products, Remote Sensing of Environment, 83: 181-194.
Ilderami, A.; Habibnejad, M.; Safarishad, M. and Dalal oghli, A. (20015). Using satellite MODIS images AND NDSI index for snow cover mapping (case study: Bahar basin), Journal of Geographic Space, 50: 125-140.
Joshi, R.; Kumr, K.; Pandit, J. and Plani, S.M. (2015). Dynamics of Climate Change and Water Resources of Northwestern Himalaya, Springer International Publishing, 203P.
Keikhosrvai Kiany, M.S. and Masoudian, A. (2016). Exploring the Relation of Snow-Covered Days with Elevation, Slope and Aspect in Iran, Physical Geography Research Quarterly, 1: 1-14
Kostadinov, T.S. and Lookingbill, T.R. (2015). Snow cover variability in a forest ecotone of the Oregon Cascades via MODIS Terra products, Remote Sensing of Environment, 164: 155-169.
Lindsay, CH.; Zhu, J.; Miller, A.E. and Wilson, T.L. (2015). Deriving Snow Cover Metrics for Alaska from MODIS, Remote sensing, 7: 12961-12985.
Ma, L.; Qin, D.; Bian, L.; Xiao, C. and Luo, Y. (2011). Assessment of Snow Cover Vulnerability over the Qinghai-Tibetan Plateau, Advances in climate change research, 2: 93-100.
Malcher, P.; Floricioiu, D. and Rott, H. (2003). Snow mapping in Alpine areas using medium resolution spectrometric sensors, International Geoscience and Remote Sensing Symposium, 2835-2837.
Mir Mousavi, H. and Sabour, L. (2014). Snow cover monitoring using MODIS data in northwestern Iran, Geography and Development Iranian journal, 35: 181-200.
Mir Yaghoubzadeh, M.H. and GHanbarpour, M.R. (2010). Investigation to MODIS Snow Cover Maps Usage in Snowmelt Runoff Modeling (Case Study: Karaj river basin), Journal of Geoscience, 76:140-148.
Najafi, A.; Ghodoosi, H.; Saghafian, B. and Porhemmat, j. (2007). Snowmelt runoff estimation by using RS & GIS (A case study in Shahar-chi watershed- Orumiyeh), Pajouhesh & Sazandegi, 76: 177-185
Parajka, J. and Bloschl, G. (2006). Validation of MODIS snow cover images over Austria, Hydrol. Earth Syst. Sci, 10: 679-689.
Paudel. K. and Andersen, P. (2001). Monitoring snow cover variability in an agro pastoral area in the Trans Himalayan region of Nepal using MODIS data with improved cloud removal methodology, Remote Sensing of Environment, 115: 1234-1246.
Ramsay, B.H. (1998). The interactive multisensor snow and ice mapping system, Hydrological Processes, 12: 1537-1546.
Rasouli, A.A. and Adhami, S. (2007). Calculate Snow water equivalent by processing MODIS data, Geography and Development Iranian journal, 10: 23-36
Riggs, G.; Hall, D.K. and Salomonson, V. (2006). MODIS Snow Products User Guide to Collection 5,
Romanov, P. (2003). Mapping and monitoring of the snow cover fraction over North America, Journal of Geophysical Research, 108: 1-15.
RUGSL (2011). Fall, Winter, and Spring Northern Hemisphere Snow Cover Extent from the Rutgers University Global Snow Lab.Climate Science: Roger Pielke Sr.
Saberi, N.; Homayouni, S. and Motagh, M. (2013). Snow Runoff Modeling Using Meteorological, Geological and Remotely Sensed Data, Intl. J. Humanities, 2: 79-100.
Shahroudi, N. and Rossow, W. (2014). Using land surface microwave emissivities to isolate the signature of snow on different surface types, Remote Sensing of Environment, 152: 638-653.
Sorman, A.; Akyurek, Z. and Tekeli, A. (2007). Commentary on comparison of MODIS snow cover and albedo products with ground observations over the mountainous terrain of Turkey, Hydrol. Earth Syst. Sci, 11: 1353-1360.
Taheri, H. and Arkian, F. (2013). Variability of number of days with snowfall and snow depth in Iran, Nivar, 82-83: 47-58.
Tamab (1996). Bulletin of country's water situation, 8, Tehran.
Tahir, A.; Adamowski, J. and Chevallier, P. (2016). Comparative assessment of spatiotemporal snow cover changes and hydrological behavior of the Gilgit, Astore and Hunza River basins (Hindukush–Karakoram–Himalaya region, Pakistan), Meteorol Atmos Phys, Online First.
Tahir, A.; Chevallier, P.; Arnaud, Y. and Ashraf, M. (2015). Snow cover trend and hydrological characteristics of the Astore River basin (Western Himalayas) and its comparison to the Hunza basin (Karakoram region), Science of the Total Environment, 505: 748-761.
UNEP (2007). Global outlook for ice and snow, United Nations Environment Programme, ISBN: 978-92-807-2799-9, 235P.
Zhang, B.; Wu, Y.; Lei, L.; Li, J. and Liu, L. (2013). Monitoring changes of snow cover, lake and vegetation phenology in Nam Co Lake Basin (Tibetan Plateau) using remote SENSING (2000–2009), Journal of Great Lakes Research, 39: 224-233.
Zhou, H.; Aizen, E. and Aizen, V. (2013). Deriving long term snow cover extent dataset from AVHRR and MODIS data: Central Asia case study, Remote Sensing of Environment, 136: 146-162.