رابطه بین ویژگیهای مکانیکی و منحنی هدایت هیدرولیکی غیراشباع خاکها

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی سابق کارشناسی ارشد دانشگاه بوعلی سینا- همدان

2 دانشیار گروه علوم خاک دانشگاه بوعلی سینا- همدان

3 استاد گروه علوم خاک دانشگاه بوعلی سینا- همدان

چکیده

هدایت هیدرولیکی خاک از مهمترین ویژگیهای فیزیکی خاک در حالت غیراشباع برای شناخت، بررسی و مدل-
سازی انتقال آب، نمکها و آلاینده ها در خاک است. هدف از این پژوهش برآورد هدایت هیدرولیکی غیراشباع با بهره گیری
از پارامترهای زودیافت خاک شامل خصوصیات فیزیکی، مکانیکی و شیمیایی با استفاده از روش رگرسیونی و شبکه
عصبی مصنوعی بود. در این پژوهش 148 نمونه از 5 استان مازندران، کرمانشاه، آذربایجان غربی و شرقی و همدان
با استفاده از خصوصیات فیزیکی، (α و n) جمعآوری شد. پارامترهای هدایت هیدرولیکی غیراشباع مدل ونگنوختن- معلم
مکانیکی و شیمیایی بهعنوان تخمینگر در 8 مرحله تخمین زده شدند. سپس با استفاده از پارامترهای تخمین زدهشده در
هر مرحله منحنی هدایت هیدرولیکی غیراشباع در دامنه 0 تا 1500 کیلوپاسکال بهدست آمد. برای ارزیابی دقت توابع،
منحنیهای تخمینی در هر مرحله با منحنیهای برآوردی از روی منحنی نگهداری آب خاک مقایسه شدند. نتایج شبکه
عصبی مصنوعی نسبت بهروش رگرسیونی بهتر بود. چون دامنه معیار آکایک در روش شبکه عصبی مصنوعی بین
4101 - و 1169 - و در روش رگرسیون بین 1379 - و 382 - بود. در میان توابع انتقالی ایجادشده با روش شبکه عصبی
مصنوعی، مرحله 8 که از مقاومت کششی علاوه بر خصوصیات پایه خاک بهعنوان برآوردگر بهرهگیری نموده بود،
بهبود بیشتری نسبت به سایر توابع انتقالی در برآورد هدایت هیدرولیکی غیراشباع داشت. متغیرهایی که تغییرپذیری
کمی دارند نتوانستند برآورد هدایت هیدرولیکی را بهبود دهند ولی پارامترهایی که تغییرپذیری بالایی دارند مانند مقاومت
کششی باعث بهبود برآورد هدایت هیدرولیکی شدند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Relationship between Mechanical Properties and Unsaturated Hydraulic Conductivity Curves of Soils

نویسندگان [English]

  • A Sedaghat 1
  • H Bayat 2
  • AA Safari 3
چکیده [English]

Soil unsaturated hydraulic conductivity is one of the most important soil physical properties
in recognizing, investigating and modeling the transport of water, solutes and pollutants in the soil.
The objective of this study was to estimate the soil unsaturated hydraulic conductivity using easy to
measure soil physical, mechanical and chemical properties by regression and artificial neural
networks (ANNs) methods. In this study, 148 soil samples were taken from five provinces of
Mazandaran, Kermanshah, West and East Azarbaijan and Hamedan. Pedotransfer functions were
developed using soil physical, chemical and mechanical properties to estimate unsaturated hydraulic
conductivity parameters of the van Genuchten- Mualem model (n and α) in 8 steps. The parameters
estimated in each step, were used to simulate unsaturated hydraulic conductivity curve in the range
of 0 – 1500 kPa. The accuracy of the estimated curves in each step was evaluated using curve by
curve comparison with the fitted (measured) unsaturated hydraulic condoctivity curve. The ANNs
performed better than the regression method, because, the AIC criterion values were obtained
between -4101 and -1169 for the ANNs and between -1379 and -382 for the regression. Among the
ANNs developed pedotransfer functions, the step 8 which utilized the tensile strength as an
estimator along with basic soil properties, performed better than the other models in estimating the
hydraulic conductivity. The results showed that the variables with little variability did not improve
the estimates of hydraulic conductivity but the parameters with high variability such as tensile
strength improved estimates of hydraulic conductivity.

کلیدواژه‌ها [English]

  • Estimation
  • Hydraulic conductivity models
  • Pedotransfer functions
  • Tensile strength
  • Unsaturated hydraulic conductivity
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