نوع مقاله : مقاله پژوهشی

نویسنده

دانشگاه آزاد اسلامی، واحد خرم آباد، باشگاه پژوهشگران جوان ونخبگان، خرم آباد، ایران

چکیده

گنجایش تبادل کاتیونی خاک (CEC) یکی از ویژگی­های بسیار مهم خاک است. این ویژگی می­تواند نشان‌دهنده بسیاری از ویژگی­های خاک از جمله حاصلخیزی، سطح ویژه و میزان نگهداشت آب خاک باشد. از آنجائی­که اندازه­گیری این ویژگی پرهزینه، زمان­بر و نیاز به دستگاه­های آزمایشگاهی ویژه­ای دارد، از این رو برآورد آن با استفاده از توابع انتقالی خاک و به کمک ویژگی­های زودیافت خاک در مطالعات خاکشناسی اهمیت زیادی دارد. لذا هدف از این مطالعه، پی­ریزی توابع انتقالی رگرسیونی در برآورد گنجایش تبادل کاتیونی با استفاده از بعد فرکتال اندازه ذرات خاک است. برای این منظور 106 سری داده از بانک اطلاعاتی آمریکا (UNSODA) انتخاب، بعد فرکتال اجزای بافت محاسبه و از آن­ها برای پی­ریزی تابع انتقالی استفاده شد. کارایی تابع پیشنهادی با استفاده از خصوصیات زودیافت خاک مقایسه گردید. نتایج نشان داد از میان همه ویژگی­های زودیافت خاک تنها ضرایب بعد فرکتال، درصد رس و ماده­ آلی معنی­دار و در مدل رگرسیونی وارد شدند. مدل رگرسیونی پیشنهادی فرکتالی (62/0=R2، 3/5=RMSE و 004/0-=ME) و اعتبارسنجی (59/0=R2، 4/5=RMSE و 054/0-=ME) کارایی بسیار بهتری در مقایسه با توابع پیشنهادی، توابع بل و ونکولن و بروسما و همکاران داشت.

کلیدواژه‌ها

عنوان مقاله [English]

Prediction of Cation Exchange Capacity using fractal dimension of soil particle size distribution

نویسنده [English]

  • Mahmood Reza Sadikhani

Young Researchers and Elite Club, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran

چکیده [English]

Cation exchange capacity (CEC) is one of the most important soil properties. This property can describe many of soil properties such as soil fertility, specific area and soil water content. Whereas measuring this property is expensive, time-consuming and laboratory tools needed, hence, prediction of CEC using pedotransfer function (PTF) and soil easily properties is very important in soil science studies. So, the objective of the present study was to develop regression pedotransfer functions to predict the CEC using fractal dimension of soil particles. Consequently, 106 soil samples of UNSODA dataset were used. Fractal dimension of soil particle size was calculated and then was used to develop a PTF to predict the soil CEC. Performance of suggested fractal regression was compared the existed functions that use other soil properties as input. Results showed that between all soil easily properties only fractal dimension, % clay and organic matter had a significant coefficient. Suggested fractal regression model (R2= 0.62, RMSE= 5.3 and ME= 0.004) and validation (R2= 0.59, RMSE= 5.4 and ME= 0.054) had a better performance that other functions including suggested function, Bell and Vankulen. With considering of good performance of the suggested fractal function, applying fractal dimension that shows effects of soil texture with a number is approved.

کلیدواژه‌ها [English]

  • Transfer Function
  • Fertility
  • Soil Texture
  • Readily available soil properties
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