An evolutionary approach to modelling the soil–water characteristic curve in unsaturated soils

In this paper a new approach is presented based on evolutionary polynomial regression (EPR) for modelling of soil–water characteristic curve in unsaturated soils. EPR is an evolutionary data mining technique that generates a transparent and structured representation of the behaviour of a system directly from data. This method can operate on large quantities of data in order to capture nonlinear and complex relationships between variables of the system. It also has the additional advantage that it allows the user to gain insight into the behaviour of the system. Results from pressure plate tests carried out on clay, silty clay, sandy loam, and loam are used for developing and validating the EPR model. The model inputs are the initial void ratio, initial gravimetric water content, logarithm of suction normalised with respect to atmospheric air pressure, clay content, and silt content. The model output is the gravimetric water content corresponding to the assigned input suction. The EPR model predictions are compared with the experimental results as well as the models proposed by previous researches. The results show that the proposed approach is very effective and robust in modelling the soil–water characteristic curve in unsaturated soils. The merits and advantages of the proposed approach are highlighted.