A Spectral Analysis to Explore Signal Filtering Properties of Watersheds

It is well established that watersheds act as low-pass filters damping and attenuating climatic signals as they propagate through a watershed. This `reddening' of climatic signals is a well observed phenomenon; however, the ways watershed properties control the nature of this filtering are less understood. This is especially true with respect to groundwater surface water interactions. We know that groundwater can serve as an important temporal buffer to watersheds, but temporal shifts between precipitation, soil moisture and groundwater are not well quantified. To develop a better understanding of the filtering mechanisms of watersheds, idealized hillslopes of increasing complexity and semi-idealized watersheds are modeled using a physics-based fully-integrated hydrologic model (ParFlow). Multi-decadal simulations are run with synthetically-generated climatic forcing derived from historical climatic data to capture variability and identify trends in groundwater storage, streamflow, and soil moisture present at this scale. Spectral and Fourier methods are used to analyze the resultant time series of these variables, and to quantify the temporal scaling behavior of various configurations. Ensembles of varying hillslope and watershed configurations are created to explore the impact of filtering variables such as hillslope geometry, hydraulic conductivity, and topography on filtering properties. With this controlled numerical approach alterations to the input signal can be readily observed and directly quantified. This will provide insights into how a watershed's configuration alters the temporal scaling of the specified variables as the signal propagates through the system.