School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada; Building & Const. Engineering Dept., University of Technology, Baghdad, Iraq.
School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
Waste Manag. 2021 Feb 1;120:175-182. doi: 10.1016/j.wasman.2020.11.033. Epub 2020 Dec 9.
Research was completed to show that using the complex refractive index model (CRIM) to interpret GPR data can improve the estimation of in situ water content of the waste in the landfill. Literature shows that the Topp equation is normally used to analyse GPR data, despite the fact it fails to consider porosity and other properties of the landfill material or soil that can affect the electromagnetic properties of the material. The application of (CRIM) overcomes these limitations and more. Previously measured field GPR data were reanalyzed with CRIM and supported by synthetic GPR data to show that CRIM provides a better prediction of the water content of the landfill material. Further enhancement of GPR data interpretation was implemented by optimizing the frequency of the GPR scan and determining the ideal offset separation distance between the transmitter and the receiver using sensitivity tests. The sensitivity tests were based on synthetic 2D surface based-reflection GPR data sets generated by MATLAB®. The sensitivity results showed that the optimum frequency was 1 GHz, with an ideal offset distance of 0.75 m. After using the optimized values, it was possible to obtain a percentage of error of 1% between modelled water saturation and GPR measured water saturation.
研究表明，使用复折射指数模型（CRIM）来解释探地雷达数据可以提高对垃圾填埋场中废物原位含水量的估计。文献表明，通常使用 Topp 方程来分析探地雷达数据，尽管它没有考虑到会影响材料电磁特性的垃圾填埋场材料或土壤的孔隙率和其他特性。（CRIM）的应用克服了这些限制，并且更多。先前测量的现场探地雷达数据使用 CRIM 进行了重新分析，并辅以合成探地雷达数据，表明 CRIM 提供了对垃圾填埋场材料含水量的更好预测。通过优化探地雷达扫描频率和使用灵敏度测试确定发射器和接收器之间的理想偏移间隔距离，对探地雷达数据解释进行了进一步增强。灵敏度测试基于 MATLAB®生成的合成二维表面反射探地雷达数据集。灵敏度结果表明，最佳频率为 1GHz，理想的偏移距离为 0.75m。使用优化值后，可以在模型化的水饱和度和探地雷达测量的水饱和度之间获得 1%的误差百分比。
