Influence of clearness index and soil moisture in the soil thermal dynamic in natural pasture in the Brazilian Pampa biome

Abstract

The soil thermal characterization is necessary to describe the storage and propagation of energy between surface and subsoil. Different weather conditions may influence soil energy exchange processes. Previous studies showed that the variables related to solar radiation and soil moisture (θ) have a significant influence on soil thermal dynamics. In this study, we analyzed the influence of these conditions in the dynamic of soil thermal variables (soil heat flux, G, soil temperature at 0.05 m, Ts5, and at 0.15 m, Ts15) and soil thermal properties (thermal conductivity, λ, thermal diffusivity, k, and thermal capacity, cv) obtained in two natural pasture experimental sites located over the Pampa biome in southern Brazil: Pedras Altas (PAS) and Santa Maria (SMA), with two datasets for both sites. The solar global radiation (Rg), represented by the clearness index, and the soil moisture were used to classify the dataset for different sky cover and dry and wet soil. We estimated the soil thermal properties using analytical methods and experimental data. We analyze the dependence of λ(θ) and we proposed a new empirical model to λ(θ) whose hypothesis takes into account a mathematical expression related to the physical phenomenon. Our results showed that, for both sites, the average daily experimental G values were negative and higher in wet soil than in dry soil (in absolute values), while an opposite behavior was found in daily Ts5 and Ts15. In a daily cycle, the hysteresis phenomenon was observed between G and Rg, and between air and soil temperatures. The clearness index influenced the pattern of these hystereses, independent of dry or wet soil period. The higher values of λ and k were found for wet soil periods in both sites. In general, λ and k values presented a variation of until 10% and 33% between the dataset, respectively. This variation in k induced the bigger variability in cv. The new empirical model for λ(θ) showed good results to represent the experimental λ and to estimate G, consequently has the potential for use in studying numerical algorithms for describing coupled heat and mass transfer processes. The results obtained here allowed a description of the soil thermal regime in the natural pasture over Brazilian Pampa biome and can also be incorporated into global land surface models that aim to represent the behavior of energy exchange between the soil-surface-atmosphere.