Temporal Evolution of Soil Moisture Statistical Fractal: Seasonal and Rainfall Dynamics

Monday, 15 December 2014
Xinye Ji1, Chaopeng Shen1 and William J Riley2, (1)Pennsylvania State University Main Campus, University Park, PA, United States, (2)Lawrence Berkeley Natl Lab, Berkeley, CA, United States
Soil moisture statistical multi-fractal can potentially be an important tool for multi-scale hydrologic modeling. The fractal scaling exponents (τ), the slopes of the log-log relation between soil moisture moments and scales, have the potential to predict the parameters for soil moisture distribution at higher grid-resolution. We demonstrate here that the magnitude and temporal development of τ is related to basin water storage, seasonal mode of wetting and drying, and topography. We used PAWS + CLM, a physically-based surface-subsurface process model, to explore soil moisture spatial and temporal fractal patterns by running several scenarios in two Midwest basins of the United States. We applied homogenous meteorological forcing to focus on the control from heterogeneity of watershed static properties and examined the temporal evolution of τ in different soil depths and in non-freezing days. We found that τ in the top 10cm layer is approximately linearly related to basin-average water storage. In non-freezing seasons, τ shows strong hysteretic patterns. Wetting and drying dominated processes weakens previous organization, and reorganization process is linked to the hydrologic characteristics of the basin. We explained the difference between the seasonal and event dynamic of the fractal exponents.