Domínguez-Niño Jesús María, Bogena Heye Reemt, Huisman Johan Alexander, Schilling Bernd, Casadesús Jaume
Program of Efficient Use of Water in Agriculture, Institute of Agrifood Research and Technology (IRTA), Parc de Gardeny (PCiTAL), Fruitcentre, 25003 Lleida, Spain.
Institute of Bio- and Geosciences, Agrosphere Institute (IBG-3), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany.
Sensors (Basel). 2019 Jul 13;19(14):3101. doi: 10.3390/s19143101.
Soil water content (SWC) monitoring is often used to optimize agricultural irrigation. Commonly, capacitance sensors are used for this task. However, the factory calibrations have been often criticized for their limited accuracy. The aim of this paper is to test the degree of improvement of various sensor- and soil-specific calibration options compared to factory calibrations by taking the 10HS sensor as an example. To this end, a two-step sensor calibration was carried out. In the first step, the sensor response was related to dielectric permittivity using calibration in media with well-defined permittivity. The second step involved the establishment of a site-specific relationship between permittivity and soil water content using undisturbed soil samples and time domain reflectometry (TDR) measurements. Our results showed that a model, which considered the mean porosity and a fitted dielectric permittivity of the solid phase for each soil and depth, provided the best fit between bulk permittivity and SWC. Most importantly, it was found that the two-step calibration approach (RMSE: 1.03 vol.%) provided more accurate SWC estimates compared to the factory calibration (RMSE: 5.33 vol.%). Finally, we used these calibrations on data from drip-irrigated almond and apple orchards and compared the factory calibration with our two-step calibration approach.
土壤含水量（SWC）监测常用于优化农业灌溉。通常，电容式传感器用于此任务。然而，工厂校准常常因其有限的精度而受到批评。本文的目的是以10HS传感器为例，测试与工厂校准相比，各种传感器和土壤特定校准选项的改进程度。为此，进行了两步传感器校准。第一步，使用在具有明确介电常数的介质中进行校准，将传感器响应与介电常数相关联。第二步涉及使用原状土样和时域反射仪（TDR）测量，建立介电常数与土壤含水量之间的特定地点关系。我们的结果表明，一个考虑了每种土壤和深度的平均孔隙率以及固相拟合介电常数的模型，在体积介电常数和土壤含水量之间提供了最佳拟合。最重要的是，发现两步校准方法（均方根误差：1.03体积%）与工厂校准（均方根误差：5.33体积%）相比，能提供更准确的土壤含水量估计。最后，我们将这些校准应用于滴灌杏仁园和苹果园的数据，并将工厂校准与我们的两步校准方法进行了比较。
