TY - JOUR
T1 - Improved reconstruction of soil thermal field using two-depth measurements of soil temperature
AU - Huang, Fan
AU - Zhan, Wenfeng
AU - Ju, Weimin
AU - Wang, Zhihua
N1 - Funding Information:
This work is supported by the National 863 plan under Grant 2013AA122801, by the National Natural Science Foundation of China under Grant 41301360 , by the Jiangsu Provincial Natural Science Foundation of China under Grant BK20130566 , and by the Open Fund of State Key Laboratory of Earth Surface Processes and Resource Ecology under Grant 2013-KF-01 . We thank the financial support from the DengFeng Program-B of Nanjing University. We also thank the National Water & Climate Center (NWCC) for providing validation data through Soil Climate Analysis Network (SCAN).
Publisher Copyright:
© 2014 Elsevier B.V.
PY - 2014/11/7
Y1 - 2014/11/7
N2 - The accurate estimation of soil thermal field is crucially important because soil temperature is a key parameter widely used in many related fields. This paper proposed an improved heat-conduction-equation (HCE) method to reconstruct soil thermal field using two-depth measurements of soil temperature. The revised HCE method employed a direct approach as well as an indirect approach to estimate both the daily average soil temperature (DST) and the instantaneous soil temperature (IST), during which the annual temperature cycle and the diurnal temperature cycle are combined. Two validation experiments (i.e., Test-1 and Test-2) were performed with soil temperature measurements at five stations chosen from the Soil Climate Analysis Network (SCAN). The results show that the revised HCE method improves the accuracy of modeling soil thermal field in comparison to its traditional form. The root mean square errors (RMSEs) of the ISTs estimated by the traditional HCE method range from 1.0 to 2.1 °C (2.4 to 4.8 °C) in Test-1 (Test-2); while the errors of the revised HCE method by the indirect approach are reduced to less than 1.0 °C in both Test-1 and Test-2; the errors by the direct approach are further reduced to less than 0.7 °C in both Test-1 and Test-2. The improved method has further potential to estimate soil heat flux, a variable that can be inferred using soil temperature gradients associated with soil apparent thermal conductivity.
AB - The accurate estimation of soil thermal field is crucially important because soil temperature is a key parameter widely used in many related fields. This paper proposed an improved heat-conduction-equation (HCE) method to reconstruct soil thermal field using two-depth measurements of soil temperature. The revised HCE method employed a direct approach as well as an indirect approach to estimate both the daily average soil temperature (DST) and the instantaneous soil temperature (IST), during which the annual temperature cycle and the diurnal temperature cycle are combined. Two validation experiments (i.e., Test-1 and Test-2) were performed with soil temperature measurements at five stations chosen from the Soil Climate Analysis Network (SCAN). The results show that the revised HCE method improves the accuracy of modeling soil thermal field in comparison to its traditional form. The root mean square errors (RMSEs) of the ISTs estimated by the traditional HCE method range from 1.0 to 2.1 °C (2.4 to 4.8 °C) in Test-1 (Test-2); while the errors of the revised HCE method by the indirect approach are reduced to less than 1.0 °C in both Test-1 and Test-2; the errors by the direct approach are further reduced to less than 0.7 °C in both Test-1 and Test-2. The improved method has further potential to estimate soil heat flux, a variable that can be inferred using soil temperature gradients associated with soil apparent thermal conductivity.
KW - Daily average soil temperature
KW - Heat conduction in soils
KW - Instantaneous soil temperature
KW - Soil temperature
KW - Soil temperature variability
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U2 - 10.1016/j.jhydrol.2014.08.014
DO - 10.1016/j.jhydrol.2014.08.014
M3 - Article
AN - SCOPUS:84906774351
SN - 0022-1694
VL - 519
SP - 711
EP - 719
JO - Journal of Hydrology
JF - Journal of Hydrology
IS - PA
ER -