A Numerical Model to Estimate the Soil Thermal Conductivity Using Field Experimental Data

Abstract

Soil thermal conductivity is an important parameter for understanding soil heat transfer. It is difficult to measure in situ with available instruments. This work aims to propose a numerical model to estimate the thermal conductivity from the experimental measurements of soil heat flux and soil temperature. The new numerical model is based on the Fourier Law adding a constant empirical parameter to minimize the uncertainties contained in the data from field experiments. Numerically, the soil thermal conductivity is obtained by experimental linear data fitting by the Least Squares Method (LSM). This method avoids numerical indetermination when the soil temperature gradient or soil heat flux is very close to zero. The new model is tested against the different numerical methodology to estimate the soil heat flux and validated with field experimental data. The results indicate that the proposed model represents the experimental data satisfactorily. In addition, we show the influence of the different methodologies on evaluating the dependence of the thermal conductivity on the soil water content.

The Influence of Land Surface Temperature in Evapotranspiration Estimated by the S-SEBI Model

“…The soil heat flux (G) is responsible for lower energy consumption, representing less than 10% in studied in pampa biome [43,45,46]. The model used in our study to produced G overestimate all the flux tower measurement, and they have produced the estimation of RMSE and Bias with 43.45 (W/m 2 ) and 40.4 (W/m 2 ), respectively.…”