Stochastic modelling of soil water and plant water stress using cumulant expansion theory

In this study, a dynamic modelling scheme is presented to derive the probabilistic structure of soil water and plant water stress when subject to stochastic precipitation conditions. The newly developed model has the form of the Fokker-Planck equation, and its applicability as a model for the probabilistic evolution of soil water and plant water stress is investigated under climate change scenarios. This model is based on the cumulant expansion theory, and has the advantage of providing the probabilistic solution in the form of probability distribution function (PDF), from which one can obtain the ensemble average behaviour of the dynamics. The simulation result of soil water confirms that the proposed soil water model can properly reproduce the results obtained from observations, and it also proves that soil water behaves with consistent cycle based on the precipitation pattern. The plant water stress simulation shows two different PDF patterns according to the precipitation. Moreover, with all the simulation results with climate change scenarios, it can be concluded that the future soil water and plant water stress dynamics will differently behave with different climate change scenarios. Copyright (C) 2010 John Wiley & Sons, Ltd.