Modeling Influence of Soil Properties in Different Gradients of Soil Moisture: The Case of the Valencia Anchor Station Validation Site, Spain

The prediction of spatial and temporal variation soil water content brings numerous benefits in the studies soil. However, it requires a considerable number covariates to be included study, complicating analysis. Integrated nested Laplace approximations (INLA) with stochastic partial differential equation (SPDE) methodology is possible approach that allows inclusion an easy way. current study has been conducted using INLA-SPDE moisture area Valencia Anchor Station (VAS), validation site for European Space Agency SMOS (Soil Moisture Ocean Salinity). data used were collected typical ecosystem semiarid Mediterranean conditions, subdivided into physio-hydrological units (SMOS units) which presents certain degree internal uniformity respect hydrological parameters capture at local fine scale. paper advances knowledge influence hydrodynamic properties on VAS (texture, porosity/bulk density organic matter land use). With goal understanding factors affect variability pixel (50 km × 50 km), five states are proposed. We observed model all effect lowest DIC value. In addition, correlation coefficient was close 1 relationship between predicted values. applied possibility analyze significance different having effects. This process substantially faster more effective than traditional kriging. findings this demonstrate advancement framework, demonstrating previous methodologies, provides individual covariates, reproducible, compare models.