The in-situ monitoring of soil suction and water content is important for a range of applications from civil engineering (e.g. estimation of groundwater infiltration) to agriculture (e.g. optimization of irrigation). The efficiency of field monitoring systems has recently improved thanks to the development of sensors that continuously record soil water status data and remotely transmit them through the internet. These data are, however, accessed by users only on a periodic basis, which impedes a timely detection of sensor failures. To overcome this limitation, this paper describes a method for automatically assessing the quality of suction and water content measurements in the field. The method is based on a real time comparison between field data and a reference soil-water retention curve. A tolerance box is introduced around each field data point, defined by a pair of suction and water content measurements. If the tolerance box intersects the reference soil-water retention curve, the suction and water content sensors are assumed to work correctly. Conversely, if the tolerance box falls outside the reference soil-water retention curve, at least one of the two sensors may have failed. The proposed method has been validated against measurements from five different agricultural soils confirming the efficiency of the tool in evaluating the accuracy of field data.

从土木工程（例如估算地下水入渗量）到农业（例如优化灌溉）的一系列应用中，土壤吸力和水含量的现场监测非常重要。得益于传感器的不断发展，该系统不断提高了现场监测系统的效率，这些传感器可以连续记录土壤水的状态数据并通过互联网远程传输。但是，用户只能定期访问这些数据，这妨碍了及时检测传感器故障。为克服此限制，本文介绍了一种在现场自动评估抽吸和含水量测量质量的方法。该方法基于田间数据与参考土壤水分保持曲线之间的实时比较。在每个现场数据点周围引入一个容差框，该容差框由一对吸力和水含量测量值定义。如果容差框与参考土壤水分保留曲线相交，则假定吸力和含水量传感器正常工作。相反，如果容差框落在参考土壤水分保持曲线的外部，则两个传感器中的至少一个可能已发生故障。该方法已针对五种不同农业土壤的测量值进行了验证，确认了该工具在评估现场数据准确性方面的效率。如果容差框落在参考的土壤水分保持曲线之外，则可能是两个传感器中的至少一个发生了故障。该方法已针对五种不同农业土壤的测量值进行了验证，确认了该工具在评估现场数据准确性方面的效率。如果容差框落在参考土壤水分保持曲线的外部，则两个传感器中至少有一个发生故障。该方法已针对五种不同农业土壤的测量值进行了验证，确认了该工具在评估现场数据准确性方面的效率。