Linking landscape structure and rainfall runoff behaviour in a thermodynamic optimality context

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Our main objective is to explore an alternative thermodynamic perspective on rainfall runoff generation on the hillslope and headwater scale. From a thermodynamic perspective any water mass flux is equal to a ¿potential gradient¿ divided by a ¿resistance¿, and fluxes deplete due to the second law of thermodynamics their driving gradients. Relevant potentials controlling rainfall runoff are soil water potentials, piezometric heads and surface water levels and their gradients are associated with spatial differences in associated forms of free1 energy. Rainfall runoff processes thus are associated with conversions of capillary binding energy, potential energy and kinetic energy. These conversions reflect energy conservation and irreversibility as they imply small amounts of dissipation of free energy into heat and thus production of entropy. Energy conversions during rainfall runoff transformation are, though being small, nevertheless of key importance, because they are related to the partitioning of incoming rainfall mass into runoff components and storage dynamics. This splitting and the subsequent subsurface dynamics is strongly controlled by preferential flow paths as they reduce subsurface flow resistances along their main extent, resulting in accelerated fluxes against the driving gradient. This implies an enlarged power in the subsurface flux and with it either enlarged free energy export or increased depletion of internal driving gradients, and thus a faster relaxation back towards local thermodynamic equilibrium. Thermodynamic optimality principles allow for a priory optimization of the resistance field at a given gradient, not in the sense how they exactly look like but in the sense how they function with respect to export and dissipation of free energy. We will thus explore the possibility of independent predictions of rainfall runoff in this project, in the sense that the a-priory optimum model structures should match independent observations at the hillslope and headwater scale. We also explore whether an apparent disequilibrium in landscape structure (reflected in topography, vegetation pattern, soil catena and apparent preferential pathways) implies temporally persistent patterns of soil moisture states in the sense that they coincide with local thermodynamic equilibria. This might offer the opportunity for useful backward predictions of distributed state dynamics by using observed dynamics of stream and ground water levels as boundary conditions characterizing the levels of relevant minima in geo-potential and zero matric potential in the subsurface. Last not least we test the feasibility to define hydrological similarity with respect to free energy stocks and conversions related to rainfall runoff (instead of focusing directly on the mass balance) with respect to classify catchments and hillslopes with respect to similar behavior.