论文标题
土壤水分图使用微波遥控传感器和顺序数据同化
Soil moisture map construction using microwave remote sensors and sequential data assimilation
论文作者
论文摘要
安装在中央枢轴灌溉系统上的微波遥控传感器提供了一种可行的方法,可以以水含量图的形式获取土壤水分信息,以实施闭环灌溉。诸如土壤水分测量中的大量时间延迟,传感器在中心枢轴固定的情况下提供土壤水分信息的主要挑战,以及传感器无法在根部提供土壤水分信息的情况下,降低了水含量图在有效实施闭环冲洗时的可用性。在本文中,我们试图解决上述挑战,因此描述了适合实施闭环灌溉的水含量图构造程序。首先,我们提出了Richards方程(现场模型)的圆柱坐标版本,该版本自然地模拟了配备了中心枢轴灌溉系统的场。其次,从微波传感器获得的测量值使用扩展的Kalman滤光片将其吸收到现场模型中,以形成信息融合系统,该系统将以水分含量图的形式提供频繁的土壤水分估计和预测。首先通过模拟的微波传感器测量结果研究了提出的信息融合系统的效用。然后,将信息融合系统应用于真正的大型农业领域,我们证明了它解决挑战的能力。三个绩效评估标准用于验证拟议的信息融合系统提供的土壤水分估计值和预测。
Microwave remote sensors mounted on center pivot irrigation systems provide a feasible approach to obtain soil moisture information, in the form of water content maps, for the implementation of closed-loop irrigation. Major challenges such as significant time delays in the soil moisture measurements, the inability of the sensors to provide soil moisture information in instances where the center pivot is stationary, and the inability of the sensors to provide soil moisture information in the root zone reduce the usability of the water content maps in the effective implementation of closed-loop irrigation. In this paper, we seek to address the aforementioned challenges and consequently describe a water content map construction procedure that is suitable for the implementation of closed-loop irrigation. Firstly, we propose the cylindrical coordinates version of the Richards equation (field model) which naturally models fields equipped with a center pivot irrigation system. Secondly, measurements obtained from the microwave sensors are assimilated into the field model using the extended Kalman filter to form an information fusion system, which will provide frequent soil moisture estimates and predictions in the form of moisture content maps. The utility of the proposed information fusion system is first investigated with simulated microwave sensor measurements. The information fusion system is then applied to a real large-scale agriculture field where we demonstrate the its ability to address the challenges. Three performance evaluation criteria are used to validate the soil moisture estimates and predictions provided by the proposed information fusion system.