Drought analysis in the Lakes of Iran (Case study: Lake Urmia and Gavkhuni Swamp)

The lakes are vulnerable to the effects of drought. In this study, Lake Urmia and Gavkhuni Swamp were selected to detect the changes in moisture levels and analysis of drought severity using the SPEI index. This article aims to introduce the appropriate spectral indices for detecting the changes in the humidity of lakes and find the role of teleconnection patterns in the drought of the lakes. Based on the results the MNDWI index has better performance to identify humidity anomalies than the NDWI index in the Gavkhuni Swamp. While in Lake Urmia, the NDWI humidity index revealed the humidity anomalies better than MNDWI. The statistical trend analysis of the meteorological drought indicates a significant increasing trend of drought severity in both lakes at the significant level of ۱% during the last decades, and the severity of drought in Lake Urmia was more intense than the Gavkhuni Swamp. In contrast, the water equivalent thickness analysis indicated a more intense negative trend in the underground water level of Gavkhuni compare to the Urmia basin which can be because of the significant anthropogenic effects in the basin. To investigate the cause of the dryness in Iranian lakes, the correlation between the selected teleconnection indices and the meteorological drought index was examined. The results indicated that the drought of Lake Urmia located in the northwest of Iran has a significant correlation with teleconnection indices of the AMO and SOI, and this correlation is more robust in the Lake Urmia basin than the central basin.

Keywords:

moisture composite spectral index , ocean-atmospheric oscillation , remote sensing , teleconnection patterns