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Determining Forest Duff Water Content Using a Low-Cost Standing Wave Ratio Sensor

机译:使用低成本驻波比传感器确定林场的水分含量

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摘要

Forest duff (fermentation and humus) water content is an important parameter for fire risk prediction and water resource management. However, accurate determination of forest duff water content is difficult due to its loose structure. This study evaluates the feasibility of a standing wave ratio (SWR) sensor to accurately determine the forest duff water content. The performance of this sensor was tested on fermentation and humus with eight different compaction levels. Meanwhile, a commercialized time domain reflectometry (TDR) was employed for comparison. Calibration results showed that there were strong linear relationships between the volumetric water content (θV) and the SWR sensor readings (VSWR) at different compaction classes for both fermentation and humus samples. The sensor readings of both SWR and TDR underestimated the forest duff water content at low compacted levels, proving that the compaction of forest duff could significantly affect the measurement accuracy of both sensors. Experimental data also showed that the accuracy of the SWR sensor was higher than that of TDR according to the root mean square error (RMSE). Furthermore, low cost is another important advantage of the SWR sensor in comparison with TDR. This low-cost SWR sensor performs well in loose materials and is feasible for evaluating the water content of forest duff. In addition, the results indicate that decomposition of the forest duff should be taken into account for continuous and long-term water content measurement.
机译:森林油(发酵和腐殖质)的含水量是火灾风险预测和水资源管理的重要参数。但是,由于森林松散水的结构松散,因此很难准确测定。这项研究评估了驻波比(SWR)传感器准确确定林达夫水含量的可行性。该传感器的性能在八种不同压实水平的发酵和腐殖质上进行了测试。同时,采用商业化的时域反射仪(TDR)进行比较。校准结果表明,对于发酵和腐殖质样品,在不同压实等级下,体积水含量(θV)和SWR传感器读数(VSWR)之间存在很强的线性关系。 SWR和TDR的传感器读数在低压实水平下均低估了林达夫的水含量,证明林达夫的压实会显着影响两个传感器的测量精度。实验数据还表明,根据均方根误差(RMSE),SWR传感器的精度高于TDR。此外,与TDR相比,低成本是SWR传感器的另一个重要优势。这种低成本的SWR传感器在松散物料中表现良好,并且对于评估林木屑的水分含量是可行的。此外,结果表明,对于连续和长期的水分含量测量,应考虑林屑的分解。

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