TY - JOUR
T1 - The impacts of heating strategy on soil moisture estimation using actively heated fiber optics
AU - Dong, Jianzhi
AU - Agliata, Rosa
AU - Steele-Dunne, Susan
AU - Hoes, Olivier
AU - Bogaard, Thom
AU - Greco, Roberto
AU - van de Giesen, Nick
PY - 2017/9/13
Y1 - 2017/9/13
N2 - 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 (Tcum), the maximum temperature (Tmax), or the soil thermal conductivity determined from the cooling phase after heating (λ). This study investigates the performance of the Tcum, Tmax 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 Tcum and Tmax 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 Tcum to soil moisture. Hence, the Tcum 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.
AB - 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 (Tcum), the maximum temperature (Tmax), or the soil thermal conductivity determined from the cooling phase after heating (λ). This study investigates the performance of the Tcum, Tmax 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 Tcum and Tmax 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 Tcum to soil moisture. Hence, the Tcum 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.
KW - Active DTS
KW - Heating strategy
KW - Soil moisture
KW - Soil temperature
KW - OA-Fund TU Delft
UR - http://resolver.tudelft.nl/uuid:6d5c18a5-99c4-457c-86e6-1b440baa509d
UR - http://www.scopus.com/inward/record.url?scp=85029671225&partnerID=8YFLogxK
U2 - 10.3390/s17092102
DO - 10.3390/s17092102
M3 - Article
SN - 1424-8220
VL - 17
SP - 1
EP - 11
JO - Sensors
JF - Sensors
IS - 9
M1 - 2102
ER -