The global effects of climate change and policy decisions are simulated, in part, by land surface models; yet, the models often use incomplete soil information that may result in unreliable estimates of soil water storage and surface energy fluxes. The objectives of this study were to: 1) quantify the impact of better representation of vertical heterogeneity of soil characterization on simulated soil water storage and surface energy fluxes; and 2) to simulate the effect of abrupt soil textural change from sandy to clayey (i.e. presence of argillic horizons) on patterns of simulated surface energy fluxes.
In this study, the Root Zone and Water Quality Model: Version 2 (RZWQM2) and measurements of soil moisture from soil in Palestine, TX (loamy, siliceous, semiactive, thermic Arenic Plinthic Paleudult) and Bronte, TX (fine loamy, mixed, superactive, thermic Typic Paleustalf) were used. The results showed that more accurate representation of vertical soil textural heterogeneity and hydraulic parameters improved the predictions of soil water storage compared to measurements. Simulations under an abrupt texture discontinuity, such as sandy over clayey soil, increased the magnitude of differences in latent and sensible heat partitioning. Additionally, accounting for a simulated argillic horizon revealed a predictable pattern of simulated latent heat fluxes as a function of claypan and rooting depths, where the interquartile range of latent heat fluxes: 1) shift to a maximum for claypans above the rooting depth, 2) plateau until the rooting depth, 3) shift to a minimum for claypans below the rooting depth, and 4) steadily increase shift with diminishing returns after the minimum has been reached.
This study showed that accurately simulating vertical changes in soil texture with depth changed estimates of plant available water and improved soil water prediction accuracy. Subsequently, simulated ranges of latent heat fluxes were also affected. Given improved reliability in simulation of soil water and latent heat fluxes in land surface models, the representation of soil vertical heterogeneity and hydraulic parameters are anticipated to improve the performance of land surface models
