Accounting for soil porosity improves a thermal inertia model for estimating surface soil water content

Abstract

Soil thermal inertia (P), a property that controls the temporal variation of near-surface temperature, has been used to estimate surface water content (θ) in remote sensing studies. The accuracy of θ estimates, however, is affected by surface soil porosity (n). We hypothesize that n can be derived using a simple linear n-P relationship of a dry surface soil layer, and that accounting for n improves the accuracy of θ estimation using a P(θ) model. The P of a surface layer was measured by using the heat pulse method during a drying period, and the feasibility of estimating θ with a P(θ) model that included n was explored. The approach was also tested with published P values derived from meteorological data and MODIS data against in situ θ measurements at two field sites in Arizona, USA. The results on a partially vegetated shrubland indicated that by using the P-derived n, the P(θ) model provided more accurate θ estimates than by using the literature n values. Discrepancies between modeled θ and in situ θ measurements were observed at small θ values, which were caused in part by the fact that the modeled θ represented soil layers a few millimeters thick, while the in situ measurements represented θ at the 5-cm depth. The new n-P function has potential for estimating surface θ accurately using multi-scale P data on bare soils or on sparsely vegetated lands.