DYNAMIC BASEFLOW STORAGE ESTIMATES AND THE ROLE OF TOPOGRAPHY, SURFICIAL GEOLOGY, AND EVAPOTRANSPIRATION ON STREAMFLOW RECESSION CHARACTERISTICS IN THE NEVERSINK RIVER BASIN, NEW YORK

Catchment dynamic storage is the portion of groundwater storage freely draining and contributing water to stream channels. Dynamic storage volumes derived from streamflow recession analyses were estimated for seven gauged catchments within the upper Neversink River Basin (NRB), a critical municipal source for New York City. Geomorphological, surficial geology, and meteorological properties were quantified and described in relation to time and spatially variable recession behavior and storage estimates across the NRB. The goals of this study are to provide storage estimates for baseflow regimes within gauged catchments within the NRB using both linear and nonlinear reservoir assumptions, and to investigate the influence of catchment geomorphological characteristics, sediment thickness, and evapotranspiration on streamflow recession characteristics. To explore these relationships, we 1) evaluated seasonal trends in streamflow recession behavior in relation to modeled potential evapotranspiration (PET) and basin runoff rates, 2) derived empirical streamflow models for cool-season runoff using both linear and nonlinear reservoir assumptions for baseflow, and 3) calculated metrics related to the geology and geomorphology of each catchment and compared these metrics to area normalized baseflow dynamic storage estimates. Results show that baseflow recession behaves as a nonlinear reservoir, and applying linear reservoir assumptions may underestimate the total dynamic storage volumes. Baseflow dynamic storage estimates for all seven gauged basins ranged between 0.25 10⁸ to 40.79 10⁸ gallons for nonlinear estimates and 0.22 10⁸ to 27.61 10⁸ gallons for linear assumptions. Streamflow recession rates in the growing season were sensitive to changes in PET. Catchment sediment thickness, topographic wetness index (TWI), and stream gradients were stronger predictors of normalized storage volumes than catchment area or surface topography alone.