بهبود برآورد ظرفیت تبادل کاتیونی خاک با استفاده از ابعاد فرکتالی

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه علوم خاک، دانشکده کشاورزی، دانشگاه شیراز، شیراز، ایران

چکیده

ظرفیت تبادل کاتیونی[1] (CEC) یکیاز مهم­ترین ویژگی­های شیمیایی خاک از نظر تغذیه گیاه و جذب سطحی آلاینده­ها در خاک است که اندازه­گیری آن زمان­­بر و پرهزینه است. بنابراین این پژوهش با هدف برآوردCEC  خاک با استفاده از مقادیر ماده آلی، اجزای بافت خاک و ابعاد فرکتالی تایلر و ویت­کرفت (DT) و سپاسخواه و تافته (DS) و همچنین بررسی کارایی ابعاد فرکتالی ذکر شده به­عنوان یک متغیر مستقل و تأثیر آن بر دقت روابط رگرسیونی پیش­بینی CEC خاک انجام شد. در این پژوهش از داده‌های 100 نمونه خاک مربوط به بانک اطلاعات خاک UNSODA[2]استفاده شد. توزیع اندازه ذرات اولیه خاک با استفاده از روش اسکگز و بعد فرکتالی اندازه ذرات اولیه خاک نیز با استفاده از دو روش پیشنهادی سپاسخواه و تافته و تایلر و ویت­کرفت محاسبه شد. نتایج نشان داد که مقادیر CEC دارای ارتباط منفی معنی­دار با مقدار شن و ارتباط مثبت معنی­دار با مقادیر لگاریتم (در پایه 10) ماده آلی، رس، DS و DT داشت. مقادیر ضرایب تبیین داده­های آموزش و آزمون، ریشه میانگین مربعات خطای نرمال شده[3] (درصد) و ضریب نش- ساتکلیف برای ارتباط رگرسیون چند متغیره بین CEC با لگاریتم (در پایه 10) ماده آلی و رس به­ترتیب برابر با 77/0، 84/0، 2/17 و 92/0؛ بین CEC با لگاریتم (در پایه 10) ماده آلی و DS به­ترتیب برابر با 77/0، 85/0، 2/17 و 92/0 و بین CEC با لگاریتم (در پایه 10) ماده آلی و DT به­ترتیب برابر با 77/0، 87/0، 0/14 و 93/0 بودند. بنابراین بیشترین دقت روابط رگرسیونی با ورود متغیرهای مستقل لگاریتم (در پایه 10) ماده آلی و DT حاصل شد و استفاده از بعد فرکتالیDT سبب افزایش دقت تخمین­ها شد.



[1] Cation exchange capacity (CEC)


[2] Unsaturated soil hydraulic database (UNSODA)


[3] Normalized root mean square error (NRMSE)

کلیدواژه‌ها


عنوان مقاله [English]

Improving the Estimation of Soil Cation Exchange Capacity Using Fractal Dimensions

نویسندگان [English]

  • Hasan Mozaffari
  • Ali Akbar Moosavi
  • Farnaz Ahmadi
Department of Soil Science, College of Agriculture,, Shiraz University, Shiraz,, Iran
چکیده [English]

Cation exchange capacity (CEC) is one of the most important soil chemical properties in terms of plant nutrition and pollutants adsorption in soil that its measurement is time-consuming and expensive. Therefore, this study aimed to estimate soil CEC using values of organic matter, soil textural components, and Tyler and Wheatcraft (DT) and Sepaskhah and Tafteh (DS) fractal dimensions and also to investigate the efficiency of mentioned fractal dimensions as an independent variable and its effect on the accuracy of regression relationships to estimate soil CEC. In this study, data from 100 soil samples of UNSODA soil database were used. Soil primary particles size distribution was calculated using the Skaggs approach and fractal dimension of soil primary particles was calculated using the Sepaskhah and Tafteh and Tyler and Wheatcraft approaches. Results showed that the CEC values had significant negative relationship with sand content, and significant positive relationship with logarithm (in base 10) of organic matter, clay, DS and DT values. Values of training and test data determination coefficients, normalized root mean square error (%) and Nash-Sutcliffe coefficient for multivariate regression relationship between CEC versus logarithm (in base 10) of organic matter and clay were respectively equal to 0.77, 0.84, 17.2 and 0.92; between CEC versus logarithm (in base 10) of organic matter and DS were respectively equal to 0.77, 0.85, 17.2 and 0.92 and between CEC versus logarithm (in base 10) of organic matter and DT were respectively equal to 0.77, 0.87, 14.0 and 0.93. Therefore, the most accuracy of regression relationships to estimate CEC obtained when organic matter and DT variables was used as independent variables. In other words, application of DT improved CEC estimation.

کلیدواژه‌ها [English]

  • Tyler and Wheatcraft fractal dimension
  • Sepaskhah and Tafteh fractal dimension
  • soil primary particles size distribution
  • clay
  • organic matter
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