The Effect of Salt Dust Storms on the Health of Plants in the Eastern Basin of Urmia Lake

Document Type : Original Article


1 Ph.D. Student, Dep. of Geography, Marand Branch, Marand Islamic Azad University

2 Prof. of Faculty of Planning and Environmental Sciences, Tabriz University, Tabriz


Urmia Lake is one of the largest saltwater lakes in the world, which unfortunately is drying up and has caused many dangers and concerns, especially in relation to salt dust in its dried areas. Therefore, in this research, we tried to investigate the relationship between vegetation and dust in the cities around Lake Urmia. Salinity in plants causes physiological disorders; salt stress causes growth, photosynthesis, protein, respiration, energy production, premature senescence, water reduction in plants. Considering these effects, it was tried to evaluate the overall health of plants by using related indicators including NDVI, CIre, GCI, CRI2, NDWI, NDII, MSI, PSRI. These indicators evaluate the amount of plant water, plant water stress, photosynthesis capacity, plant growth and water deficit, the amount of chlorophyll, nitrogen and pigments, which are related to plant energy and health. According to these indicators, the health of plants is generally in a favorable condition, and mostly the highest numerical values of the indicators were assigned to gardens. Using Landsat and Sentinel 2 images and the NDVI index, the vegetation changes of the region were determined in the period from 2010 to 2020, and then using the MERRA-2 database, the amount of dust concentration was also extracted for the mentioned years. The results showed that the average NDVI in the studied area follows a constant trend with an overall average of 0.2957 and sometimes it increases or decreases due to the influence of external factors such as dust. Based on this, the highest (0.3495) average NDVI is related to 2018 and the lowest (0.2579) is related to 2013. Also, two methods of linear and logarithmic regression were used to investigate the relationship between vegetation cover and dust, and the results showed that based on the linear (0.7703) and logarithmic (0.7915) regression, the highest coefficient of explanation between the two mentioned indicators was in May.


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