多传感器电容探针在估算土壤含水量和田间容量中的性能

IF 1.2 4区 农林科学 Q3 AGRICULTURAL ENGINEERING
Mukesh Mehata, S. Datta, S. Taghvaeian, T. Ochsner, A. Mirchi, D. Moriasi
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引用次数: 0

摘要

在六个制造商校准中,默认校准导致的误差最大。较高的粘土含量和盐度对传感器性能有不利影响。基于传感器的现场容量估算方法不一致且存在空间差异。摘要维持作物生产的经济和环境可持续性需要使用先进技术优化灌溉管理,如土壤水分传感器。在这项研究中,在俄克拉何马州西部的灌溉农田条件下,评估了市售的多传感器电容探头的性能。研究了粘土含量和矿化度对传感器性能的影响。此外,在实验室中确定了在研究地点收集的土芯的田间容量(FC)。这些实验室FC值用于评估两种基于传感器的FC估计方法的性能:主要浇水事件后达到实验室FC的天数和收集的传感器读数代表实验室FC的百分位数。结果表明,在制造商提供的6种校准中,默认和粉质粘土壤土校准分别产生最大和最小的土壤含水量误差。除重黏土校正误差随黏土含量的增加而提高外,其他校正误差随黏土含量的增加而增加。与其他校准相比,默认校准和砂校准对粘土和盐度的增加更为敏感。在基于传感器的FC情况下,平均需要一到三天才能达到实验室FC,范围很大,为一到九天。代表实验室FC的百分位数平均为56%,范围为3%-97%。总的来说,基于传感器的方法产生了不一致和高度可变的FC估计。关键词:校准,粘土含量,灌溉调度,盐度,传感器精度,土壤水分阈值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance of a Multi-Sensor Capacitance Probe in Estimating Soil Water Content and Field Capacity
Highlights Among six manufacturer calibrations, the default calibration resulted in the largest errors. Sensor performance was negatively affected by higher clay content and salinity. Sensor-based approaches to estimating field capacity were inconsistent and spatially variable. Abstract. Maintaining the economic and environmental sustainability of crop production requires optimizing irrigation management using advanced technologies such as soil water sensors. In this study, the performance of a commercially available multi-sensor capacitance probe was evaluated under irrigated field conditions across western Oklahoma. The effects of clay content and salinity on sensor performance were investigated too. In addition, the field capacity (FC) of soil cores collected at study sites was determined in the laboratory. These laboratory FC values were used to assess the performance of two sensor-based approaches for estimating FC: the days to reach laboratory FC after major watering events and the percentile of collected sensor readings that represented laboratory FC. The results showed that among the six calibrations provided by the manufacturer, the default and silty clay loam calibrations produced the largest and smallest soil water content errors, respectively. Errors generally increased with clay and salinity, except for the heavy clay calibration, which showed improved performance with increasing clay content. The default and sand calibrations were more sensitive to increases in clay and salinity compared to other calibrations. In the case of sensor-based FC, on average, one to three days were required to reach laboratory FC, with a large range of one to nine days. The percentiles representing laboratory FC had an average of 56% and a range of 3%-97%. Overall, the sensor-based approaches produced inconsistent and highly variable estimates of FC. Keywords: Calibrations, Clay content, Irrigation scheduling, Salinity, Sensor accuracy, Soil water threshold.
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