Soil Heat Flow Model

The Penman-Monteith method for estimating evapotranspiration (ET) has been recommended by FAO. This method requires measures of temperature, wind speed, relative humidity and heat flow in the soil. This last variable is rarely available. Soil heat flow is generally small compared to the net radiation, and many times is ignored in the energy balance. Nevertheless, the addition or subtraction of this amount in the energy balance equation should be considered for evapo-transpiration calculation. Penman-Monteith method suggests approximate estimates of soil heat flows as the difference between the maxima and minimum daily temperatures multiplied by a convenient coefficient. However, such approach ignores important variations in this parameter occurring during the day, and could influence the accuracy of the result. This work proposes to estimate soil heat flows by means of a mathematical model that includes the estimate of soil temperatures profiles and heat flows as a function of thermal properties of the soil, such as difussivity and conductivity coefficients. The model calculates soil heat flows in three stages. The first estimates hourly air temperature based on the average daily temperature and Fourier series coefficients. The obtained hourly air temperature constitutes an input variable for the second stage of the model. Surface soil temperature is assumed to be equal to air temperature. The second stage, applies heat transfer principles, using the thermal properties of the soil in order to obtain the soil temperature profile in a one meter depth soil stratum. Finally, the results of the second stage are used to calculate the hourly heat flow in the soil and compare this estimate with other methods and with measured values. Calculated hourly temperatures reproduced observed values closely. Correlation coefficients between observed and calculated values for the three summer months are 0.98, 0.96 and 0.97. Hourly soil heat fluxes are also closely estimated, showing clear diurnal variations. Correlation coefficient for the entire study period between observed and estimated values is 0.96.