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Accuracy calibration and evaluation of capacitance-based soil moisture sensors for a variety of soil

本站小编 Free考研考试/2024-01-13

Accuracy calibration and evaluation of capacitance-based soil moisture sensors for a variety of soil propertie
第一作者: Li, Bingze
英文第一作者: Li, Bingze
联系作者: Zheng, Xingming
英文联系作者: Zheng, Xingming
发表年度: 2022
卷: 273
摘要: Accurate measurement of soil moisture (theta) is key to hydrology and agriculture research. Soil moisture sensor technology is the predominant method for measuring theta, and such measurements are used as a standard for evaluating results from remote sensing and data assimilation. Therefore, improving the theta measurement accuracy of soil moisture sensors is of great significance. This study used the capacitance-based soil moisture sensor (5TM, Decagon Devices, Inc.) as an example to illustrate the necessity of calibration. The 5TM soil moisture sensor calculates theta by measuring the dielectric constant (epsilon) of the soil medium, and epsilon is affected by soil properties (texture, salinity, soil organic matter, etc.). Consequently, a common calibration model (CCM) was developed to calibrate theta from the 5TM sensor by incorporating the soil properties using soil samples collected from 17 sites in 13 provinces in China at 4 different depths. First, the theta change experiments were conducted in the laboratory for each soil sample. Second, a linear calibration model (LCM) was applied to calibrate the 5TM measured soil moisture (theta(5TM)) based on "true " soil moisture (theta(true)) assessed through the gravimetric method. The results indicated (1) high correlation coefficient (R = 0.95) was found for theta(5TM) and theta(true), but with a high root mean square error (RMSE) of 0.051 m(3)m(-3), and a more significant underestimation with increasing theta; (2) LCM calibration results (theta(LCM)) showed a higher R (0.99) and a lower RMSE (0.017 m(3)m(-3)). Finally, the CCM was established through relating the LCM coefficients (a(LCM) and b(LCM)) and soil properties based on multiple regression, with RMSE of 0.126 m(3)m(-3) and 0.023 m(3)m(-3) for a(CCM) and b(CCM) respectively. The CCM calibrated result (theta(CCM)) showed an RMSE of 0.02 m(3)m(-3) and R of 0.98. CCM can almost replace LCM in terms of similar accuracy. In this study, a CCM for soil moisture sensors is proposed, which provides a new approach for soil moisture sensor calibration.
刊物名称: Agricultural Water Management
参与作者: Li, B. Z. Wang, C. M. Ma, M. Li, L. Feng, Z. Z. Ding, T. Y. Li, X. F. Jiang, T. Li, X. J. Zheng, X. M.



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