ارزیابی تغییرات مکانی- زمانی کاربری/ پوشش زمین و شوری خاک و تاثیر آن بر مدیریت مناطق خشک (مطالعه موردی: بخشی از حوضه سیستان، جنوب شرقی ایران)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه محیط‌ زیست، دانشکدة شیلات و محیط‌ زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، گلستان، ایران.

2 گروه محیط‌ زیست، ، دانشکدة منابع طبیعی و کویرشناسی، دانشگاه یزد، یزد، ایران.

10.22059/jne.2024.367087.2611

چکیده

اثرات منفی شوری خاک بر محیط‌های طبیعی و انسانی این پدیده را به یکی از تهدیدات جدی در مدیریت پایدار مناطق خشک و نیمه خشک تبدیل کرده است. بنابراین، در مطالعه حاضر تغییرات مکانی– زمانی شوری خاک و تغییرات کاربری/ پوشش زمین در بخشی از حوضه سیستان واقع در مناطق خشک جنوب شرقی ایران که در سال‌های اخیر در معرض پدیده شوری خاک قرار گرفته است مورد بررسی قرار گرفت. در این مطالعه با استفاده از اندازه‌گیری‌های حاصل از نمونه‌برداری‌های زمینی و ابزارهایی نظیر سنجش از دور (RS) و سامانه اطلاعات جغرافیایی (GIS) نقشه‌های کاربری/ پوشش زمین و شوری خاک برای سال‌های 1989 و 2019 تهیه شد. بر اساس نتایج، میزان میانگین نرمال شده شوری خاک در سال 1989 برابر 322/0 بوده و در سال 2019 این میزان با رشد حدود 188/0 به 52/0رسیده است. همچنین، نتایج حاصل از مقایسه روند افزایش شوری و تغییرات کاربری/ پوشش زمین در منطقه نشان می‌دهد که این دو عامل متقابلا تاثیر به سزایی بر یکدیگر دارند. از سوی دیگر، تبدیل کاربری/ پوشش زمین از کاربری‌های کشاورزی آبی و بسترهای آبی به کاربری‌های مناطق بایر، کشاورزی دیم و مناطق انسان ساخت موجب کاهش پوشش گیاهی و مناطق آبی در منطقه شده که به دلیل ایجاد فرسایش حاصل از بادهای 120 روزه و نشست ذرات نمک در کل منطقه موجب افزایش شوری خاک می‌شود. اگرچه احداث چاه‌نیمه‌ها در این منطقه، اندکی از مشکلات محیط زیستی آن کاسته است. با این حال، بر طبق نتایج، این چاه نیمه‌ها نتوانسته‌اند اثرات منفی حاصل از تخریب زیستگاه‌ها و نیز خشکی بخشی از دریاچه هامون و رودخانه هیرمند را به طور کامل جبران کنند.

کلیدواژه‌ها

عنوان مقاله [English]

Assessing Spatio-temporal Variations in Land Use/Land Cover and Soil Salinity and their Impact on Managing Dry Areas (Case Study: A Part of Sistan Basin, Southeast of Iran)

نویسندگان [English]

  • Sajjad Karbalaei Saleh 1
  • Solmaz Amoushahi 1
  • Akram Sanaei 2

1 Department of Environmental Sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Golestan, Iran.

2 Department of Environmental Sciences, Faculty of Natural Resources & Desert Studies, Yazd University, Yazd, Iran.

چکیده [English]

The negative effects of soil salinity on natural and human environments have turned such phenomenon into one of the serious threats to the sustainable management of arid and semi-arid areas. The present study aims to evaluate the spatial-temporal variations in land use/land cover and soil salinity in a part of Sistan basin located in the arid regions of southeastern Iran, which has been exposed to the phenomenon of soil salinity during the recent years. To this aim, land use/land cover and soil salinity maps were prepared for 1989 and 2019 using the measurements obtained from ground sampling and instruments such as remote sensing (RS) and geographic information system (GIS). Based on the results, the normalized average soil salinity was 0.322 during 1989, reaching 0.52 during 2019 with a growth of 0.188. In addition, comparing the trend of salinity increase and land use/land cover variations in the region indicates that such factors affect each other significantly. Further, the conversion of land use/land cover from irrigated agricultural uses and water bodies to bare lands, rainfed agriculture, and man-made areas has decreased the vegetation cover and water areas, leading to an increase in soil salinity due to the erosion created by the 120- day wind of Sistan and sedimentation of salt particles in the whole region. Chah-nimehs have not been able to fully compensate for the adverse effects generated by the destruction of habitats and drying up of a part of Hamun Lake and Hirmand River, despite their slight success in reducing the environmental obstacles.

کلیدواژه‌ها [English]

  • Soil salinity changes
  • Land use/ land cover changes
  • Arid areas
  • Random forest algorithm
  • Google Earth Engine (GEE)
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