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Empirical two-point a-mixing model for calibrating the ECH_2O EC-5 soil moisture sensor in sands

机译：沙土中ECH_2O EC-5土壤湿度传感器校准的经验两点a混合模型

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摘要

Recently improved ECH_2O soil moisture sensors have received significant attention in many field and laboratory applications. Focusing on the EC-5 sensor, a simple and robust calibration method is proposed. The sensor-to-sensor variability in the readings (analog-to-digital converter (ADC) counts) among 30 EC-5 sensors was relatively small but not negligible. A large number of ADC counts were taken under various volumetric water contents (9) using four test sands. The proposed two-point a-mixing model, as well as linear and quadratic models, was fitted to the ADC - 9 data. Unlike for conventional TDR measurements, the effect of sensor characteristics is lumped into the empirical parameter a in the two-point a-mixing model. The value of a was fitted to be 2.5, yielding a nearly identical calibration curve to the quadratic model. Errors in 9 associated with the sensor-to-sensor variability for the two-point a-mixing model were ±0.005 cm3 cm~3 for dry sand and ±0.028 cm~3 cm~3 for saturated sand. In the validation experiments, the highest accuracy in water content estimation was achieved when sensor-specific ADC_(dry) and ADC_(sat) were used in the two-point a-mixing model. Assuming that α = 2.5 is valid for most mineral soils, the two-point a-mixing model only requires the measurement of two extreme ADC counts in dry and saturated soils. Sensor-specific ADC_(dry) and ADC_(sat) counts are readily measured in most cases. Therefore, the two-point a-mixing model (with a = 2.5) can be considered as a quick, easy, and robust method for calibrating the ECH_2O EC-5 sensor. Although further investigation is needed, the two-point a-mixing model may also be applied to calibrating other sensors.
机译：最近改进的ECH_2O土壤湿度传感器已在许多现场和实验室应用中引起了广泛关注。针对EC-5传感器，提出了一种简单而强大的校准方法。 30个EC-5传感器之间的读数（模数转换器（ADC）计数）之间的传感器差异相对较小，但不可忽略。使用四个测试砂在各种体积水含量下（9）进行了大量ADC计数。拟议的两点a混合模型以及线性和二次模型均已拟合到ADC-9数据。与常规TDR测量不同，传感器特性的影响被集中到两点a混合模型的经验参数a中。将a的值拟合为2.5，得出与二次模型几乎相同的校准曲线。两点式A混合模型的9个与传感器间差异相关的误差对于干砂为±0.005 cm3 cm〜3，对于饱和砂土为±0.028 cm〜3 cm〜3。在验证实验中，当在两点a混合模型中使用特定于传感器的ADC_（干）和ADC_（饱和）时，水含量估算的准确性最高。假定α= 2.5对大多数矿物土壤有效，那么两点a混合模型仅需要测量干燥和饱和土壤中的两个极端ADC计数。在大多数情况下，很容易测量传感器特定的ADC_（dry）和ADC_（sat）计数。因此，两点a混合模型（a = 2.5）可以被认为是一种用于校准ECH_2O EC-5传感器的快速，简便且可靠的方法。尽管需要进一步研究，但是两点混合模型也可以用于校准其他传感器。

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  • 来源
    《Water resources research》 |2010年第4期|p.W00D08.1-W00D08.8|共8页
  • 作者

    Toshihiro Sakaki; Anuchit Limsuwat; Kathleen M. Smits; Tissa H. Illangasekare;

  • 作者单位

    Center for Experimental Study of Subsurface Environmental Processes, Environmental Science and Engineering, Colorado School of Mines, 1500 Illinois Street, Golden, CO 80401, USA;

    Center for Experimental Study of Subsurface Environmental Processes, Environmental Science and Engineering, Colorado School of Mines, 1500 Illinois Street, Golden, CO 80401, USA;

    Center for Experimental Study of Subsurface Environmental Processes, Environmental Science and Engineering, Colorado School of Mines, 1500 Illinois Street, Golden, CO 80401, USA;

    Center for Experimental Study of Subsurface Environmental Processes, Environmental Science and Engineering, Colorado School of Mines, 1500 Illinois Street, Golden, CO 80401, USA;

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