Abstract:
Remote sensing is a powerful instrument to monitor snow cover in distant and unreachable areas, where a lot of the precipitation events happening occur as snow. As there is increased pressure on water resources due to climate change, uncontrolled development, and overpopulation, knowledge about the seasonal snow accumulation in the Mediterranean Mountains is vital for the water budget and the region’s water management strategies. Snowmelt importance lies in its substantial contribution to the recharge of the karst aquifers supplying water during the dry season, to agriculture as well as domestic and industrial uses in Lebanon. This research consists of a daily, monthly, annual and seasonal remote-sensing based analysis of Albedo, Snow Depth (SD), and a time series analysis of snow cover area (SCA), snow cover days (SCD) of Levant Mountains using Google Earth Engine, between 1985 and 2019. We analyzed MODIS Terra and Aqua daily snow cover product, and all the Landsat archive to generate NDSI for the Levant. The study region covers an area of 28,620 km2 and a maximum elevation of 3088m covering Mount and Anti-mount Lebanon. The model analyzes the visible, near-infrared, and shortwave infrared bands, subject to a pixel-based screening process to extract snow extent. The screening process includes a cloud mask, vegetation mask, low reflectance mask, temperature mask, low NDSI, and high SWIR masks. Snow Water Equivalent (SWE) and snow density regressed against remotely sensed and field measurements obtained from literature and regressed against Albedo between 2015-2016 in three different Mediterranean watersheds. Results showed there is a 25-30percent decrease in snow cover area, when comparing the means of 1985-2005 and 2005-2019 (2005 year mean change), with a yearly decrease of 12 km2 in snow area, representing 1.18 percent of the average snow area since 1985 and a non-significant decrease in annual snow cover days by 0.07 day-year since 1985 using Landsat analysis and a significant decrease of the snow cover using the
Description:
Thesis. M.S. American University of Beirut. Department of Irrigation, 2019. ST:7172.
Advisor : Dr. Hadi, Jaafar Assistant Professor, Agriculture ; Members of Committee : Dr. Issam Bashour, Professor, Agriculture science ; Dr. Ali Chalak, Associate Professor, Agriculture science.
Includes bibliographical references (leaves 72-76)