A general approach to estimate soil water content from thermal inertia

Remote sensing is a promising technique for obtaining information of the earthʹs surface. Remotely sensed thermal inertia has been suggested for mapping soil water content. However, a general relationship between soil thermal inertia and water content is required to estimate soil water content from remotely sensed thermal inertia. In this study, we propose a new model that relates soil thermal inertia as a function of water content. The model requires readily available soil characteristics such as soil texture and bulk density. Heat pulse measurements of thermal inertia as a function of water content on nine soils of different textures were made to generate a universal Kerstan function. Model validation was performed independently in both laboratory and field, and the retrieved soil water contents from the new model were compared with previous models. Laboratory evaluation on an Iowa silt loam showed that the RMSE of the new model was 0.029 m3 m−3, significantly less than [Murray, T., Verhoef, A., 2007. Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements. I. A universal approach to calculate thermal inertia. Agric. For. Meteorol. 147, 80–87] model (0.109 m3 m−3) and [Ma, A.N., Xue, Y., 1990. A study of remote sensing information model of soil moisture. In: Proceedings of the 11th Asian Conference on Remote Sensing. I. November 15-21. International Academic Publishers, Beijing, pp. P-11-1single bondP-11-5.] model (0.105 m3 m−3). Similar results were obtained in a field test on a Chinese silt loam: the RMSE of the new model, [Murray, T., Verhoef, A., 2007. Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements. I. A universal approach to calculate thermal inertia. Agric. For. Meteorol. 147, 80–87] model, and [Ma, A.N., Xue, Y., 1990. A study of remote sensing information model of soil moisture. In: Proceedings of the 11th Asian Conference on Remote Sensing. I. November 15-21. International Academic Publishers, Beijing, pp. P-11-1single bondP-11-5.] model were 0.018, 0.071, and 0.159 m3 m−3, respectively. Additionally the model was validated using literature data in which soil thermal properties were estimated from in situ temperature measurements. The mean errors of estimated water content were generally less than 0.02 m3 m−3. We concluded that the new model was able to provide accurate water content predictions from soil thermal inertia.