Optimality and dynamic equilibrium conditions in a simulated hillslope under periodic, arid atmospheric forcing

Abstract:

Theories of optimality and self-organization are appealing when dealing with non-linear systems, because based on first principles of thermodynamic these theories may lead to an intuitive interpretation and prediction of absolute values, directions, and interactions of gradients and fluxes, and universal inference laws for effective conductances. In this context, for example, the maximum entropy production principle received attention, because of its foundation in non-equilibrium thermodynamics, which appears to be useful in e.g., eco-hydrologic and atmospheric applications. A number of studies successfully applied this principle in the optimization of conductances in simplified and well-mixed open systems with external (periodic) forcing. In support-scale simulations of a variably saturated hillslope, the study presented here relaxes major simplifying assumptions by applying a realistic, arid atmospheric time series in spinup simulations to create a dynamic equilibrium utilizing the integrated hydrologic model ParFlow-CLM. The simulated hillslope exhibits time-varying internal circulation patterns due to the periodic atmospheric forcing, topography, and also heterogeneity by utilizing and optimizing all degrees of freedom provided by the soil-water retention relationship and free-moving water table. Because of the extreme non-linearity of variably saturated flow under arid climate conditions, the system is never well mixed and optimality principles relying on time-integrated gradients and fluxes do not appear to be applicable in the currently available theoretical framework. Here, integrated support-scale simulations may be useful in deriving novel theories for the application to real systems in future.