Development and validation of an operational multi-layered model for estimation of soil moisture at point-scale in South Africa

Abstract

Data discontinuity is the major challenge that hinders the integrity of datasets from the sparse soil moisture monitoring networks in developing countries. In this study, a simplified, multi-layered soil water balance model to estimate daily soil moisture at point-scale from standard weather data and minimal physical soil properties was developed. The model requires values for soil water retentivity properties such as wilting point, field capacity and saturation of each soil layer. It also requires measurements or estimates of reference evapotranspiration (ETo ) in addition to rainfall as climate inputs. The developed model was evaluated using point-scale in-situ soil moisture measurements acquired over a minimum of two years from three well-calibrated stations representing different soil types and climatic conditions in South Africa. The results indicate that the proposed model was capable of estimating total soil moisture content at all three sites, with coefficient of determination (r 2) values greater than 0.84, index of agreement (d) values greater than 0.95 and root mean square error (RMSE) values less than 7.30 mm. The findings of this study suggest that the proposed model can be reliably used for daily estimation of soil moisture at point-scale using climate data and minimal soil physical properties, to fill in gaps, and to extend datasets in locations facing data-discontinuity.