Detection of the effect of climate change on the snow areas of the Northern Alborz Watershed by CPA method

In the mountainous regions of Iran, a significant part of the precipitation is in the form of snow, which is considered an important source of river flow. Accurate knowledge of the quantity of these resource is necessary in terms of the ever-increasing value of fresh water and also in terms of the optimal use of water resources. From a global point of view, snow monitoring and accurate information on the spatial distribution of snow cover, are necessary for weather forecasting and hydrological and meteorological modeling. An important feature of mountainous regions is the snow cover, which has a high reflectivity, has a great influence on the local weather, reduces the net radiation at the surface and as a result, transfers energy. In addition to being an important factor for ecosystem development, snow cover is very important for human activities. Accurate estimation of the coverage level is considered as one of the central and fundamental operations in the field of water resources management, especially in areas where snowfall is a major part of precipitation. Revealing and determining different characteristics of snow and ice using remote sensing data, which is widely used in hydrology, has created a new method to obtain the required parameters of hydrology.

The Alborz Mountain range which is under study of the current research, separates the coastal plains of Mazandaran Province from the interior of Iran. The eastern half of Western Alborz and all of Central Alborz and a part of Eastern Alborz are within Mazandaran Province. In this way, along with other natural factors, certain geographical conditions have emerged. In this region, snow plays a key role in the hydrological cycle and hydroclimate, and a significant part of the total annual runoff in this region is the result of snowmelt. So that global warming affects the management of watersheds and the downstream water requirements of its sub-basins. First, MODIS sensor data was obtained daily with a spatial resolution of 500×500 meters from NASA's National Snow and Ice Database (NSIDC). The received images are related to the period of 2000-2018. To process the images, first pre-processing wacovered ars applied in the ENVI 5.3 software environment. The NDSI index was used to monitor the snowed area. Mann-Kendall test, Sen’s slope estimator, and Pettitt's homogeneity test were used to investigate the snow cover variation trend. Also, the seasonal and annual anomalies of snow cover, temperature and precipitation in the study area were investigated based on standard Z score.

The results of the Mann-Kendall test and the Sen’s slope estimator method in the northern slope of Central Alborz, show that the largest reduction of the snow covered area occurred in January and winter season, respectively, equal to 220.39 and 50.41 km2 each year. The results of Petit's homogeneity test, using the Change Point Analysis (CPA) method, in January 2010 for the snow-covered area and May 2014 and June 2010 for the monthly mean temperature, showed a climatic jump at 0.05 significant level. Also, the change point in the snow-covered area time series of January has been descending, but the change point in the mean temperature time series of May and June has been ascending. Comparing the snow cover conditions with the mean temperature and total precipitation conditions, shows that in most cases the negative anomalies of snow cover are consistent with the positive anomaly of temperature and the negative of precipitation. The obtained results are a warning about the climate change in this region, which is known as the phenomenon of global warming and meteorological drought. Surely, these changes have a direct effect on the reduction of water resources for the agricultural and drinking sectors.

In general, the analysis of the snow-covered area variations in January during the studied 19 years, shows that for an increase in the average temperature of 0.13°c, the snow-covered area in this month decreased by 220.39 km2  every year. Also, according to the results of Pettitt's homogeneity test in 2010 and 2014, it can be concluded that global warming and meteorological drought caused a sudden change in the snow-covered area and temperature in these years and months. The comparison of precipitation and temperature conditions with the snow cover condition showed that in most years, the negative anomaly of snow cover was simultaneous with the positive anomaly of temperature and the negative anomaly of precipitation. The greatest effect of temperature increase has been observed in spring. Therefore, with the increase in temperature and the change in climatic conditions, the winter precipitation that will turn into snow accumulation has decreased and can affect the runoff caused by these precipitations in the spring season. Since this region has the ability to receive snow from mid-autumn to early spring, information about the snow covered area in this region is essential for many hydrological, meteorological, and climatological applications, as well as hydroelectric power generation and flood forecasting.