Analysis of spatiotemporal variations of drought and soil salinity via integrated multiscale and remote sensing-based techniques (Case study: Urmia Lake basin)

Abstract

In this study, the spatiotemporal variations of drought and salinity were assessed for the Urmia Lake basin, which is a very critical and challenging ecosystem problem. The lowering of water level in the Urmia Lake and the associated risk of becoming a completely saline land has become an important issue in Iran. In the first step of the study, using the ground- and satellite-based datasets, a new multiscale technique based on Empirical Wavelet Transform (EWT) and Differential Symbolic Entropy (DSE) was proposed to monitor the variations of drought in the selected region. In the next step, variations in the water level and salinity of Urmia Lake and its impacts on the environment were investigated using satellite datasets. Results showed that the Southern parts of the basin were more prone to severe droughts, and there was a direct relationship between entropy and drought intensity. Based on the results, it was concluded that climate change had an impact on the shrinkage of the lake; however, these changes were not solely responsible of causing the dramatic water loss of the Lake. Variations of the Salinity Index (SI) showed that saline lands were mostly seen in the Eastern and Southern parts of the lake, causing negative impacts on air quality and agricultural activities in these parts. It was found that the proper management of water resources would play an effective role in the restoration of the lake.