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Estimation of electrical conductivity of a soil solution from the monitored TDR data and an extracted soil solution

机译:从监测的TDR数据和提取的土壤溶液中估算土壤溶液的导电性

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摘要

In order to establish sustainable agricultural practices and to avoid excess fertiliser application, it appears important to understand the process of water and solute transport. With a view to analysing transport through the soil, based on the data obtained by means of time domain reflectometry, the relationship between the volumetric water content, the apparent electrical conductivity, and the soil solution electrical conductivity should be known. This paper proposes a new method for estimating the three parameters relationship by optimising the parameters obtained through Rhoades model with the Levenberg-Marquardt method. The proposed method systematically determines the initial parameter set required to conduct nonlinear optimisation. The method was used to estimate the continuous apparent electrical conductivity data based on the time domain reflectometry dataset, obtained from the field and occasional measurement of soil solution electrical conductivity data of the soil water, which was extracted by means of a suction sampler installed in the field. Compared with the conventional method where the parameters of Rhoades model are calibrated with a 2-step linear regression by means of laboratory experiment, the soil solution electrical conductivity estimated with the proposed method was closer to the field data, yielding smaller root mean square error values. Supplementary use of the dataset obtained through a laboratory experiment under dry and wet conditions improved the accuracy of parameter estimation.
机译:为了建立可持续的农业实践并避免过量的肥料应用,了解水和溶质运输过程似乎很重要。为了通过时间域反射测量测量获得的数据来分析通过土壤的运输,容积含水量,表观电导率和土壤溶液之间的关系应该是应该知道的。本文提出了一种新方法,用于通过利用Revenberg-Marquardt方法优化通过Rhoades模型获得的参数来估计三个参数关系的方法。所提出的方法系统地确定了进行非线性优化所需的初始参数集。该方法用于估计基于时域反射区数据集的连续表观电导率数据,从现场获得的土壤水域的土壤溶液电导率数据的轨道测量,通过安装在内的吸入采样器提取场地。与通过实验室实验用2步线性回归校准Rhoades模型的参数的传统方法相比,用所提出的方法估计的土壤溶液电导率更接近现场数据,产生较小的根均方误差值。通过在干燥和湿条件下通过实验室实验获得的数据集提高了参数估计的准确性。

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