Document Type : Research Paper

Authors

• Ali Teymouri ¹
• Ali Mohammadian Behbahani
• Mohsen Hosseinali Zadeh ²
• Khalil Valizadeh Kamran ³

¹ PhD student in Desert management and control, Department of Desert area management, Faculty of Rangeland and Watershed, University of Agricultural Sciences and Natural Resources, Gorgon, Iran

² Associate Professor, Department of Desert area management, Faculty of Rangeland and Watershed, University of Agricultural Sciences and Natural Resources, Gorgon, Iran

³ Professor, Department of Remote Sensing and Geographic Information System, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran

Abstract

Abstract
Background and objectives
  The receding water of Lake Urmia and its gradual drying have caused the formation of numerous dust centers in these areas. Therefore, there is a need to identify critical centers of wind erosion as the first step to control it. This study aimed to accurately identify the internal sources of dust production in a part of the eastern area of ​​Lake Urmia using a combined method of Google Earth Engine (GEE) and Geographic Information System (GIS).
Methodology
   In this study, in order to identify critical wind erosion hotspots, data on wind speed, slope, soil moisture, precipitation, vegetation index, and soil salinity were used as the main layers. The main layers were extracted by performing the necessary computational process on the Landsat 8 satellite image in the time periods of 2013 to 2021. In the next step, the main layers were normalized after data preparation and then using the Fuzzy Membership operator on each of the layers. Then, the layers were superimposed with the Fuzzy Overlay operator and the gamma method for each season (wet-dry) in each year, and finally, 18 maps of wind erosion hotspots were extracted in each season and each year, and finally, a map of stable wind erosion hotspots in the study area was prepared.
Results
   After determining the membership for each of the layers related to the effective parameters on the wind erosion phenomenon in the study area and implementing the model, the final map of stable wind erosion centers was obtained based on the Fuzzy Overlay operator and the And method. The results of the study showed that areas that are located far from Lake Urmia or are at a higher altitude are less at risk of wind erosion, and the closer we get to the shores of the lake, due to topographic, ecological, climatic, land use and edaphic conditions, the area is more at risk of wind erosion. If the centers of these areas are not identified, in the near future, dust and salt storms resulting from them will be a major threat to urban areas, agriculture, gardens and human health, and will ultimately cause harmful environmental and socio-economic problems. The results of this study also showed that the areas near the villages of Shangal Abad, Koshk, Qale Hassan Abad, Qom Tepe, Qezel Dizaj, Mahdinlu, Qeshlaq, Bahram Abad, Timorlu, and Khurkhor constitute the focus of wind erosion during the years 2013 to 2021. According to this map, the areas with a very high risk of wind erosion are located in the area close to the lake's edge, and in these areas, due to high soil salinity, high temperature, low vegetation cover, and higher wind speed, the risk of soil erosion is high in these areas, which are mostly plains and flat and have a small slope.
Conclusion
   The study of related factors (soil, vegetation, climate) affecting wind erosion at a medium scale with the aim of identifying stable wind erosion hotspots and expressing the method of its origination using remote sensing, Google Earth Engine (GEE) and Geographic Information System (GIS) showed that the highest risk of wind erosion occurs in the eastern parts of the study area due to the presence of areas without vegetation or with very low vegetation cover, high soil salinity and soil structure destruction, the presence of saline-alkaline soils, high temperatures and frequent and strong winds, and this indicates the fact that the risk of wind erosion threatens the entire region. This model allows us to identify the most vulnerable areas to wind erosion. The results of this study showed that areas in Shabestar and Osku counties with an area of ​​about 77,000 hectares out of the total 690,000 hectares of the study area are most at risk of wind erosion and were identified as wind erosion hotspots. Therefore, the need for planning to deal with this phenomenon in order to prevent its development seems essential, and effective protection against wind erosion (biological-management and biomechanical) should be implemented in order to achieve a more comprehensive understanding of areas susceptible to wind erosion.

Keywords

• Dust source
• Geographic Information System
• Google Earth Engine
• Landsat satellite
• Remote Sensing