Dong Jianzhi, Agliata Rosa, Steele-Dunne Susan, Hoes Olivier, Bogaard Thom, Greco Roberto, van de Giesen Nick
Water Resources Section, Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2600 GA Delft, The Netherlands.
USDA ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705-2350 USA.
Sensors (Basel). 2017 Sep 13;17(9):2102. doi: 10.3390/s17092102.
Several recent studies have highlighted the potential of Actively Heated Fiber Optics (AHFO) for high resolution soil moisture mapping. In AHFO, the soil moisture can be calculated from the cumulative temperature ( T cum ), the maximum temperature ( T max ), or the soil thermal conductivity determined from the cooling phase after heating ( λ ). This study investigates the performance of the T cum , T max and λ methods for different heating strategies, i.e., differences in the duration and input power of the applied heat pulse. The aim is to compare the three approaches and to determine which is best suited to field applications where the power supply is limited. Results show that increasing the input power of the heat pulses makes it easier to differentiate between dry and wet soil conditions, which leads to an improved accuracy. Results suggest that if the power supply is limited, the heating strength is insufficient for the λ method to yield accurate estimates. Generally, the T cum and T max methods have similar accuracy. If the input power is limited, increasing the heat pulse duration can improve the accuracy of the AHFO method for both of these techniques. In particular, extending the heating duration can significantly increase the sensitivity of T cum to soil moisture. Hence, the T cum method is recommended when the input power is limited. Finally, results also show that up to 50% of the cable temperature change during the heat pulse can be attributed to soil background temperature, i.e., soil temperature changed by the net solar radiation. A method is proposed to correct this background temperature change. Without correction, soil moisture information can be completely masked by the background temperature error.
最近的几项研究突出了主动加热光纤（AHFO）在高分辨率土壤湿度测绘方面的潜力。在AHFO中，土壤湿度可以根据累积温度（T cum）、最高温度（T max）或加热后冷却阶段确定的土壤热导率（λ）来计算。本研究调查了T cum、T max和λ方法在不同加热策略下的性能，即施加的热脉冲在持续时间和输入功率上的差异。目的是比较这三种方法，并确定哪种方法最适合电源有限的现场应用。结果表明，增加热脉冲的输入功率更容易区分干燥和湿润的土壤条件，从而提高准确性。结果表明，如果电源有限，加热强度不足以使λ方法得出准确的估计值。一般来说，T cum和T max方法具有相似的准确性。如果输入功率有限，增加热脉冲持续时间可以提高这两种技术的AHFO方法的准确性。特别是，延长加热持续时间可以显著提高T cum对土壤湿度的敏感性。因此，当输入功率有限时，推荐使用T cum方法。最后，结果还表明，热脉冲期间高达50%的电缆温度变化可归因于土壤背景温度，即由净太阳辐射引起变化的土壤温度。提出了一种校正这种背景温度变化的方法。未经校正，土壤湿度信息可能会被背景温度误差完全掩盖。
