Investigating the causality of changes in the landscape pattern of Lake Urmia basin, Iran using remote sensing and time series analysis

Lake Urmia is the second largest hypersaline lake in the world in terms of surface area. In recent decades, the drop in water level of the lake has been one of the most important environmental issues in Iran. At present, the entire basin is threatened due to abrupt decline of the lake's water level and the consequent increase in salinity. Despite the numerous studies, there is still an ambiguity about the main cause of this environmental crisis. This paper is an attempt to detect the changes in the landscape structure of the main elements of the whole basin using remote sensing techniques and analyze the results against climate data with time series analysis for the purpose of achieving a more clarified illustration of processes and trends. Trend analysis of the different affecting factors indicates that the main cause of the drastic dry out of the lake is the huge expansion of irrigated agriculture in the basin between 1999 and 2014. The climatological parameters including precipitation and temperature cannot be the main reasons for reduced water level in the lake. The results show how the increase in irrigated agricultural area without considering the water resources limits can lead to a regional disaster. The approach used in this study can be a useful tool to monitor and assess the causality of environmental disaster.