Abstract Soil moisture monitoring plays a critical role in water resource management, hydrological modeling, and climate studies, making sensor accuracy and reliability increasingly important. This study evaluates the performance of five soil moisture sensors—the CS655, HydraProbe, TDR‐315N, TEROS 12, and ThetaProbe—using their default calibrations. Using gravimetric ( θ core ) and neutron probe ( θ NP ) data as benchmarks, we analyzed sensor performance over 2 years using statistical metrics including mean absolute error (MAE), root mean square error, Nash–Sutcliffe efficiency (NSE), bias, and mean absolute difference (MAD) relative to another sensor. Sensor performance varied across sites and depths, primarily influenced by soil texture and horizon changes. The TDR‐315N, TEROS 12, and CS655 showed the smallest overall errors, with mean MAE values ranging from 0.053 to 0.062 m 3 m −3 depending on the reference method. Beyond accuracy, the TEROS 12 and TDR‐315N also demonstrated the highest level of correlation and repeatability, as shown by their consistently low MAD values. The ThetaProbe exhibited intermediate performance, while the HydraProbe consistently showed the largest errors on average (mean MAE = 0.097 m 3 m −3 ). Positive NSE values and near‐zero biases at shallower depths indicated good agreement with reference methods, while deeper clay‐rich layers exhibited reduced NSE and larger positive biases, reflecting consistent overestimation by most sensors. Our results emphasize the need for site‐specific calibration to reduce systematic errors and improve measurement reliability. These results can guide researchers and decision‐makers in selecting soil moisture sensors that balance accuracy and ease of installation.
Azizi et al. (Fri,) studied this question.