Predicting continuous form of soil-water characteristics curve from limited particle size distribution data
Detailed information derived from a soil moisture characteristics curve (SMC) helps in water flow and solute transport management. Hence, prediction of the SMC from soil particle size distribution (PSD), which is easy to measure, would be convenient. In this study, we combine an integrated robust PSD-based model and a Van Genuchten SMC model to predict a continuous form of SMC using sand, silt and clay percentages for 50 soils selected from the UNSODA database. We compare the performance of the proposed approach with some previous prediction models. The results indicated that the SMC can be predicted and modelled properly by using sand, silt, clay and bulk density data. The model’s bias was attributed to the high fine particle and organic carbon (OC) content. We concluded that independence of the proposed method from the database and any empirical coefficients make predictions more reliable and applicable for large-scale water and solute transport management.
Keywords: relative improvement, ROSETTA software, scaling approach, UNSODA database