Numerical studies on soil moisture distributions in heterogeneous catchments

The paper deals with numerical studies of basin-scale dynamics of soil moisture in arbitrarily heterogeneous conditions (i.e., in presence of heterogeneity of climate, soil, vegetation and land use). Its relevance stems from comparative analysis of the probabilistic structure of spatially averaged soil moisture fields with the corresponding exact solutions of the underlying simplified stochastic point processes. The probabilistic structure of coarse-grained soil moisture fields is largely controlled by temporal fluctuations of intermittent rainfall fields. Averaged properties are also affected by heterogeneous soil and vegetation features and by the spatial scale of aggregation. Here, we employ results from extended Montecarlo simulations of a continuous model of the hydrologic response that proved suitable to describe observed events. The comparison of numerically derived soil moisture probability density functions with exact simplified solutions suggests, somewhat unexpectedly, that the analytical model can reasonably describe the large-scale behavior of spatially-averaged hydrologic fluxes through physically meaningful, basin-scale soil and vegetation parameters. The application of a seasonally variable, stochastic climate model shows pronounced daily fluctuations in the relationship between water losses and soil moisture, related to the underlying climatic fluctuations. The resulting spatially averaged soil moisture probability density functions in heterogeneous catchments, however, do not show appreciable differences with respect to the ones obtained assuming constant mean climate conditions. We thus conclude that effective basin-scale states, which average highly heterogeneous (spatial/temporal) properties allowing exact probabilistic descriptions, indeed exist, with implications for large scale estimates of soil-atmosphere interactions