مدل‌سازی محتوای کربن آلی خاک بر اساس شاخص‌های توپوگرافی و ویژگی‌های خاک کشت‌زارهای دیم گندم

نوع مقاله : مقاله کامل علمی پژوهشی

نویسندگان

1 دانشجوی دکتری / دانشگاه زنجان

2 دانشیار گروه خاکشناسی دانشگاه زنجان

3 عضو هیئت علمی مرکز تحقیقات کشاورزی استان زنجان

چکیده

سابقه و هدف: کربن آلی خاک از عوامل مهمی است که بر کیفیت خاک، آب و اتمسفر مؤثر است. محتوی کربن آلی خاک تابعی از اثرات متقابل اقلیم، پوشش گیاهی، زهکشی، مدیریت زراعی، کاربری اراضی و ویژگی‌های خاک از جمله بافت خاک، نوع کانی و ساختمان خاک است (7). درصد شیب و موقعیت‌های مختلف توپوگرافی بر حفظ رطوبت خاک و ایجاد شرایط مناسب برای استقرار گیاهی و در نتیجه میزان انباشته شدن و تجزیه کربن آلی خاک مؤثر می‌باشند (2). در میان اثر ویژگی‌های خاک بر کربن آلی خاک، بیش‌ترین پژوهش بر بررسی اثر اجزای بافت خاک صورت گرفته و نتایج متفاوتی در این خصوص گزارش شده است (16-18). هدف از این پژوهش ارائه مدل رگرسیونی است که با استفاده از شاخص‌های توپوگرافی و ویژگی‌های خاک، کربن آلی خاک را در کشت‌زارهای دیم واقع در منطقه نیمه خشک برآورد نماید.
مواد و روش‌ها: در این پژوهش 110 نمونه خاک به صورت تصادفی در سه تکرار از مزارع دیم گندم شهرستان خدابنده واقع در جنوب استان زنجان در سال 1392 تهیه شد. شاخص‌های توپوگرافی شامل درصد شیب، شاخص خیسی، همواری بستر دره دارای چند قدرت تفکیک و انحناهای قائم، افقی، عمومی، حداقل و حداکثر با استفاده از مدل ارتفاع رقومی با قدرت تفکیک 90 متر در 90 متر به دست آمدند. ویژگی‌های خاک شامل شن، سیلت و رس، pH گل اشباع و محتوی کربن آلی در آزمایشگاه اندازه‌گیر‌ی شدند. در صورت عدم تبعیت داده‌ها از توزیع نرمال از روش تبدیل جانسون استفاده شد. با به‌کارگیری روش رگرسیون حداقل مربعات جزئی، مدلی برای بیان تغییرات محتوی کربن آلی خاک (80=n) ارائه شد. روش اعتبارسنجی تقاطعی به صورت جداسازی تکی برای انتخاب بهترین مدل براساس تعداد مؤلفه‌های اصلی بکار رفت. سپس، مدل انتخاب شده با استفاده از مجموعه جدیدی از داده‌ها (30= n) مورد ارزیابی قرار گرفت. کل فرآیند ارائه مدل و آزمون آن در سه تکرار به صورت گروه‌بندی داده‌ها در قالب داده‌های مدل و آزمون آن صورت گرفت.
یافته‌ها: در میان شاخص‌های توپوگرافی کربن آلی خاک بیشترین همبستگی را به ترتیب با مقادیر نرمال‌شده شاخص خیسی (5901/0P

کلیدواژه‌ها

عنوان مقاله [English]

Modeling of soil organic carbon content using topographic indices and soil characteristics in rainfed wheat lands

نویسندگان [English]

  • Ali Reza Vaezi 2
  • Mehdi Taheri 3
1 phD student/Univeristy of Zanjan
2 Associate professor/ University of Zanjan
3
چکیده [English]

Background and objectives: Soil organic carbon is one of the crucial factors which affects soil quality, water and atmosphere. Soil organic carbon content is a function of climate, vegetation cover, drainage, crop management, land use and soil properties such as texture, mineralogy and structure (7). Slope steepness and different topographic positions are influencing on soil moisture retention and a suitable condition creation for plant establishment and eventually soil organic carbon accumulation and decomposition (2). Among soil properties affecting on soil organic carbon, the most researches have been done on soil texture constitutes and the different results has been reported (16-18). The aim of this study is developing a regression model to estimate soil organic carbon using topographic indices and soil characteristics.
Material and methods: In the present study, 110 soil samples were randomly collected from topsoil (0-30 cm) in three replicates from rainfed wheat farms of Khodabandeh County located in South Zanjan, in 2013. Topographic indices including slope steepness, topographic wetness index, multi-resolution valley bottom flatness and profile, plane, general, maximal and minimal curvatures were obtained using digital elevation model in 90m×90m resolution. Soil properties including sand, silt and clay, saturated paste pH and organic carbon content were measured in laboratory. If the data did not follow normal distribution, Johnson Transformation was performed. Applying partial least square regression, a model was developed for describing soil organic carbon variations (n=80). The cross validation by leave one out method was executed to select the optimal model based on principal components number. Then, the selected model were tested using new set of data (n=30). All the modeling, it validation and test processes were performed in three replicates by grouping the data in modeling-validation and test data sets.
Results: Among topographic indices, soil organic carbon demonstrated highest Pearson correlation coefficients with normalized topographic wetness index (r=0.59, P

کلیدواژه‌ها [English]

  • Leave-one-out cross validation
  • Maximal curvature
  • Wetness index
  • Regression

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مجله پژوهش‌های حفاظت آب و خاک
دوره 23، شماره 3
مرداد 1395
صفحه 111-129

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