Assessment of Some Environmental Stresses in the Shadegan Wetland: Analysis of Satellite Data, Water Quality Indicators, and Dust Storm Pathways
سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 242
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شناسه ملی سند علمی:
JR_IJEE-16-2_017
تاریخ نمایه سازی: 21 آذر 1403
چکیده مقاله:
The study investigated the water quality, wetland area, and dust storm impacts on the Shadegan wetland in Iran from ۲۰۱۸-۲۰۲۳ using satellite data. The results highlight the severe challenges the wetland has faced in recent years. Key water quality indices, including water temperature, turbidity, and CDOM levels, indicate increasing pollution, particularly in ۲۰۲۲-۲۰۲۳. Water temperatures were highest in ۲۰۱۸ and ۲۰۲۱, peaking at ۵۲°C, while turbidity and CDOM levels reached their maximum in ۲۰۲۲, affecting the northern, western, and southern parts of the wetland. The study also revealed a significant reduction in the wetland area, with considerable drying observed in the northern, eastern, and western sections during ۲۰۱۸, ۲۰۲۱, and ۲۰۲۲, with critical implications for the wetland's ecological health. Dust storm frequency and intensity have escalated, peaking in ۲۰۲۲-۲۰۲۳, correlating with periods of poor water quality and reduced wetland area. The highest dust pollution levels were recorded in ۲۰۱۸, ۲۰۲۱, ۲۰۲۲, and ۲۰۲۳, with over ۲۱۴ dust days in the northern parts and over ۱۴۶ dust days in the southern and southeastern parts of the wetland in ۲۰۲۲. Wind analysis and HYSPLIT show the pollution from the drying wetland affects a broad regional area, including Khuzestan province and the western, northwestern, and southwestern regions of Iran. The findings emphasize the urgent need for wetland conservation and restoration, as well as regional cooperation to rehabilitate the ecosystem and implement effective water resource management strategies.
کلیدواژه ها:
نویسندگان
A. Yousefi Kebriya
Agricultural Meteorology, Department of Water Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
M. Nadi
Agricultural Meteorology, Department of Water Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
E. Ghanbari Parmehr
Remote Sensing, Geomatics Department, Babol Noshirvani University of Technology, Babol, Iran
Z. Sun
International Research Center of Big Data for Sustainable Development Goals, ۱۰۰۰۹۴, Beijing, China
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