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Comparison of the accuracy of two soil moisture sensors and calibration models for different soil types on the loess plateau
Author(s) -
Jia Junchao,
Zhang Pingping,
Yang Xiaofeng,
Zhen Qing,
Zhang Xingchang
Publication year - 2021
Publication title -
soil use and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.709
H-Index - 81
eISSN - 1475-2743
pISSN - 0266-0032
DOI - 10.1111/sum.12587
Subject(s) - water content , mean squared error , calibration , soil science , environmental science , loess , soil texture , remote sensing , loess plateau , coefficient of determination , pedotransfer function , soil water , hydrology (agriculture) , geology , mathematics , geotechnical engineering , statistics , geomorphology , hydraulic conductivity
The accurate monitoring of soil moisture is critical for many environmental and hydrological applications, and commercial sensors have been used widely to detect the soil water content. However, the sensitivity of these sensors to the soil texture and bulk density demands calibration before conducting determinations. In the present study, we calibrated two soil moisture sensors ( TDR ‐315L and Diviner 2000) for six common soil types found on the Loess Plateau, China. The root mean square error ( RMSE ), ratio of the lack‐of‐fit mean square error and mean square pure error were calculated to compare the accuracies of the sensors and models. The results indicated that TDR ‐315L was more accurate than Diviner 2000 for all of the samples. A new model that includes the bulk density and clay content obtained higher accuracy when calibrating the TDR ‐315L sensor. And it is showed that the RMSE of volumetric water content ( VWC ) from the new model compared to the gravimetry are less than 0.039 m 3 m −3 . For the Diviner 2000 sensor, adjusting the parameters in the calibration model allowed the accurate estimation of the VWC , where the RMSE of VWC from the calibration model compared to the gravimetry are less than 0.033 m 3 m −3 . The results obtained in this study may facilitate the use of sensors in soil moisture observational networks and environmental and hydrological applications.