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تعیین محتوی ذخیرة کربن در مخزن‌های مختلف تحت کاربری‌های متفاوت در منطقة میاندوآب با استفاده از دورسنجی و مدل InVEST | ||
| نشریه محیط زیست طبیعی | ||
| دوره 77، شماره 2، شهریور 1403، صفحه 241-253 اصل مقاله (1.57 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jne.2024.377051.2677 | ||
| نویسندگان | ||
| بهمن ویسی نبی کندی* 1؛ فرزین شهبازی2 | ||
| 1گروه مهندسی فضای سبز، دانشکدة کشاورزی، دانشگاه تبریز، تبریز، ایران. | ||
| 2گروه علوم و مهندسی خاک، دانشکدة کشاورزی، دانشگاه تبریز، تبریز، ایران. | ||
| چکیده | ||
| فضاهای اکولوژیک نقش اساسی در نمایش تغییر اقلیم و گرمایش جهانی با تأکید بر ذخیره و جذب CO2 از جو دارند. در نتیجه، کمی سازی و رصد محتوی کربن ذخیره شده گام اصلی در راستای رسیدن به اهداف توسعة پایدار می باشند. هدف اصلی این مطالعه، توسعة مدل دقیق برای محاسبة محتوی کربن ذخیره شده در چهار مخزن مختلف شامل زیست‌تودة زنده بالای زمین (AGC)، زیست‌تودة زنده زیر زمین (BGC)، کربن آلی خاک (SOC) و مواد آلی مرده (DOC) تحت کاربری های مختلف می باشد. بدین منظور، سایتی به مساحت تقریبی 243204 هکتار از منطقة میاندوآب واقع در استان آذربایجان غربی به دلیل داشتن کاربری های مختلف انتخاب گردید. با توجه به اینکه کاربرد تلفیقی داده های دورسنجی و فناوری های نوین ضمن تسهیل در پیش بینی ها دقت مدل سازی را نیز افزایش می دهد، بنابراین در این تحقیق سامانة تحت وب گوگل ارث انجین (GEE) و مدل InVEST برای تهیة نقشة کاربری و پوشش اراضی (LULC) و همچنین پیش بینی محتوی ذخیرة کربن آلی مورد استفاده قرار گرفت. پیش بینی ها نشان داد که در سال 2023 حدود 106×11/52 تن کربن در محدودة مورد مطالعه ذخیره شده است. بررسی های تفصیلی نشان داد که بیشترین مقدار ذخیرة کربن مربوط به مخزن SOC و سپس AGC می باشد و دلیل اصلی آن هم به فعالیت اغلب موجودات زنده در سطح خاک برمی گردد. از نظر کاربری های مختلف موجود در منطقة مورد مطالعه بدون مد نظر قرار دادن مساحت هر کدام از کاربری های موجود، بیشترین مقدار ذخیرة کربن آلی مربوط به کاربری مرتع و سپس پوشش درختی، کشاورزی، مناطق شهری، پهنه های آبی و اراضی بایر است. در نهایت می توان نتیجه گرفت که کاربرد داده های دورسنجی و تلفیق آنها با فناوری های مناسب، تأثیر تغییرات کاربری اراضی بر محتوی ذخیرة کربن را نیز با موفقیت آشکار می‌نماید. | ||
| کلیدواژه‌ها | ||
| خدمات اکوسیستم؛ ذخیرة کربن؛ شهرستان میاندوآب؛ کاربری اراضی؛ مدل InVEST | ||
| عنوان مقاله [English] | ||
| Determining carbon storage content at different pools under various land uses in Miandoab region using remotely-sensed data and InVEST model | ||
| نویسندگان [English] | ||
| Bahman Veisi Nabikandi1؛ Farzin Shahbazi2 | ||
| 1Landscape Architecture Department , Faculty of Agriculture, University of Tabriz, Tabriz, Iran. | ||
| 2Department of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran. | ||
| چکیده [English] | ||
| Ecological spaces play a crucial role in addressing climate change and global warming with focusing on storing and capturing CO2 from atmosphere. Consequently, quantifying and monitoring carbon storage content is the main step to toward achieving sustainable development goals. The main objective of this study is to develop a precise model for calculating carbon storage content at four pools i.e., aboveground carbon (AGC), belowground carbon (BGC), soil organic carbon (SOC) and dead organic carbon (DOC) under different land uses. For this, a site with an area extent about 243204 ha was selected from Miandoab region (West Azerbaijan Province) by the fact that it represents various land uses. Since application of integrated remotely-sensed data and novel technologies facilitates predictions as well as increases the modeling accuracy, the Google Earth Engine (GEE) platform and the InVEST model were implemented in preparing land use/land cover (LULC) maps and then carbon storage content. The prediction for 2023 showed that the total carbon storage in the aforementioned region would be approximately 11.52 × 106 ton. In addition, the detailed evaluations illustrated that the highest carbon storage content related to SOC and AGC as expected. A possible reason is that living mass is located on the surface. In terms of different land-uses without paying attention to their areas in themselves, the highest carbon storage content was for pasture, followed by tree cover, agriculture, urban area, water bodies and barren. Finally, it is concluded that applying the respective remote sensing data integrating with a suitable technique uncovers the impact of LULC changes on carbon storage with success. | ||
| کلیدواژه‌ها [English] | ||
| Carbon storage, Ecosystem services, InVEST model, Land use/Land cover, Miandoab county | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 392 تعداد دریافت فایل اصل مقاله: 187 |
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