首页> 外文期刊>Polish Journal of Soil Science >PEDOTRANSFER FUNCTIONS CAPABILITY TO SIMULATE BEHAVIOUR OF SMECTITIC SOILS IN ESTIMATION OF VARIOUS SOIL WATER RETENTION CURVE MODELS
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PEDOTRANSFER FUNCTIONS CAPABILITY TO SIMULATE BEHAVIOUR OF SMECTITIC SOILS IN ESTIMATION OF VARIOUS SOIL WATER RETENTION CURVE MODELS

机译:估算各种土壤水分保持曲线模型中密土的行为的PEDO传递函数功能

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摘要

For modelling the flow transport in unsaturated conditions, we can use hydraulic properties which are expensive and time-consuming to be obtained directly because of high variability and complexity of soil systems. Few studies have been done about pedotransfer functions (PTFs) in smectitic soils. Moreover, the utility of fractal parameters in the prediction of soil water retention curve (SWRC) have not been investigated in these soils. In this study, PTFs have been made for estimating the parametersof van Genuchten (VG) and Dexter models by regression and artificial neural networks methods. Therefore, 69 soil samples were collected from Guilan Province, Iran. Fractal and non-fractal models were fitted to the particle size distribution (PSD) and micro-aggregate size distribution (ASD) and their parameters were calculated. To create PTFs, the parameters of PSD and ASD models were used as estimators. The comparison of the results of the two models of Dexter and VG shows the priority of Dexter model for the purpose of testing of smectitic soils. The results showed the superiority of Fredlund et al. PSD model parameters and fractal parameters of ASD, in the estimation of Dexter and VG SWRC models, respectively. This outcome may be related to the higher accuracy of Fredlund et al. PSD model in the description of % the PSD data in the clayey soils. However, the higher number of parameters in comparison to the number of fractal model parameters may be another reason.
机译:为了模拟非饱和条件下的水流传输,我们可以使用水力特性,由于土壤系统的高度可变性和复杂性,可以直接获取昂贵且费时的水力特性。关于薄壁土壤中的传脚传递功能(PTF)的研究很少。此外,在这些土壤中,尚未研究分形参数在预测土壤保水曲线(SWRC)中的用途。在这项研究中,已经通过回归和人工神经网络方法制作了用于估计van Genuchten(VG)和Dexter模型参数的PTF。因此,从伊朗的桂兰省收集了69个土壤样品。将分形和非分形模型拟合到粒度分布(PSD)和微骨料粒度分布(ASD),并计算它们的参数。为了创建PTF,将PSD和ASD模型的参数用作估计量。对Dexter和VG两种模型的结果的比较表明,Dexter模型用于测试黑土的优先级。结果表明Fredlund等人的优越性。分别在Dexter模型和VG SWRC模型的估计中,ASD的PSD模型参数和分形参数。这一结果可能与Fredlund等人的较高准确性有关。在描述粘土土壤中PSD数据的PSD模型中。但是,与分形模型参数相比,参数数量更多可能是另一个原因。

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