برآورد مکانی ضریب تغییرات ذخیره کربن آلی خاک با استفاده از داده‌های طیفی و رقومی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 علوم خاک، دانشگاه گیلان، رشت، ایران

2 گروه علوم و مهندسی خاک، دانشگاه گیلان

3 دانشیار گروه علوم خاک، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران.

4 عضو هیئت علمی دانشگاه ارومیه

5 استادیار موسسه تحقیقات خاک و آب، کرج، ایران.

چکیده

موجودیت خاک وابسته به پارامترهای فیزیکی، شیمیایی و بیولوژیکی آن است. ذخیره کربن آلی خاک یکی از عوامل کلیدی خاک است که تغییرات آن برروی تمامی این پارامترها اثر دارد. در این راستا، این تحقیق به­منظور پهنه­بندی ضریب تغییرات ذخیره کربن آلی خاک در بخشی از حوضه آبخیز سیمینه­رود انجام شد. نمونه­برداری از خاک با استفاده از روش مکعب لاتین مشروط در 210 نقطه از عمق 30-0 سانتی­متری خاک سطحی انجام و مقدار کربن آلی خاک اندازه­گیری شد. سپس، ذخیره کربن آلی خاک تعیین گردید. در مرحله بعد، مدل جنگل تصادفی اجرا و پارامترهای مؤثر برای تخمین ذخیره کربن آلی خاک شناسایی شد (در این مرحله جهت مدل­سازی ذخیره کربن آلی خاک از شاخص بازتابش طیفی استاندارد شده و داده­های استخراجی از مدل رقومی ارتفاعی استفاده شد). در انتها، روش جنگل تصادفی 100 بار اجرا شد و پهنه­بندی مقادیر بیشترین (صدک 95)، کمترین (صدک 5) و میانگین ذخیره کربن آلی خاک برای هر پیکسل با قدرت تفکیک مکانی 30 ×30 متر به­دست آمد. جهت به­دست آوردن ضریب تغییرات با ضریب اطمینان 90 درصد، صدک 95 و 5 درصد از هم کسر شد و ضریب تغییرات با استفاده از تقسیم آن به میانگین به­دست آمد. نتایج نشان داد که ضریب دقت (R2) مدل جنگل تصادفی 81/0 و ضرایب صحت شامل RMSE و MAE به­ترتیب 44/0 و 34/0 ((kg m-2 می­باشد. نتایج پهنه­بندی ضریب تغییرات برای مقدار ذخیره کربن آلی خاک منطقه مورد مطالعه نشان داد که مقدار تغییرات این پارامتر بین 9/3­-55 درصد متغیر می­باشد. بر اساس نتایج حاصل از پهنه­بندی ضریب تغییرات منطقعه مورد مطالعه، میانگین بیشترین و کمترین میزان تغییرات در کاربری زراعت دیم و مراتع مشاهده شد. احتمالاً کشت مداوم و بازگشت کم ماده آلی در زراعت دیم، باعث افزایش ضریب تغییرات ذخیره کربن آلی خاک در کاربری زراعت دیم شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Spatial Estimation of Coefficient of Variation of Soil Organic Carbon Stocks Using Spectral and Digital Data

نویسندگان [English]

  • Kamal Khosravi Aqdam 1
  • Nafiseh Yaghmaeian Mahabadi 2
  • Hassan Ramezanpour 3
  • Salar Rezapour 4
  • Zohreh Mosleh 5
1 Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, IRAN.
2 Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, IRAN.
3 Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, IRAN.
4 Department of Soil Science, Faculty of Agriculture, Urmia University, Urmia, IRAN
5 Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, IRAN.
چکیده [English]

Soil entities depends on its physical, chemical, and biological characteristics. Soil organic carbon (SOC) stocks is one of the main factors whose variations affect all these parameters. So, this study was performed for mapping the coefficient of variations (CV) of SOC stocks in some parts of the Simineh Roud watershed. Soil sampling performed using the Latin Hypercube method (cLHm) at 210 points from 0 to 30 cm of the soil surface, and the organic carbon was measured, then SOC stocks was calculated. In the next step, using Random Forest (RF) model the effective parameters were calculated (in this step, to model the SOC stocks, standardized spectral reflectance index and extracted data from digital elevation model were used). Finally, RF model was performed 100 times, as well as mapping of the values of upper (95th %), lower (5th %), and average SOC stocks for each pixel with a spatial resolution of 30 × 30 m was obtained. To obtain the CV with a confidence coefficient of 90%, the percentile of 95% and 5% were subtracted. The CV was obtained by dividing it by the mean. The results showed that the accuracy coefficient (R2) for modeling SOC stocks by the RF model was 0.81 and the mean accuracy coefficients including RMSE and MAE were 0.44 and 0.34 (kg/m2), respectively. Also, the results of CV mapping for the amount of SOC stocks in the study area showed that the amount of variation of this parameter varies between 3.9- 55%. Based on the results of the CV mapping of the study area, the most and lowest variations were observed in dry farming and grasslands, respectively. Probably, continuous cultivation and low return of organic matter in dry farming have increased the CV of SOC stocks in dry farming use.

کلیدواژه‌ها [English]

  • Dry farming
  • Latin Hypercube method
  • Organic carbon
  • Random Forest

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  • تاریخ دریافت: 19 تیر 1400
  • تاریخ بازنگری: 15 مهر 1401
  • تاریخ پذیرش: 03 شهریور 1400

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