UC Merced

Distributed groundwater discharges to the surface water (GW-SW discharge) in river systems remain difficult to measure across spatiotemporal scales yet are an important metric to understand with respect to nonpoint source constituent loading to rivers and downstream aquatic systems. The work focuses on a long reach (~38 river km) along the lower Merced River (LMR) in Central California, a reach in which GW-SS discharges are perennial. Coupled with elevated GW well concentrations for specific conductance (SC) and nitrate (NO3-), the loading of these constituents to the river and transport downstream are of particular interest. This study presents a method for high resolution, in situ synoptic sampling for SW SC and nitrate, and applies a simple mass-balance, mixing model to estimate distributed GW-SW discharge on 1-km intervals. SW data collection spanned from 2010-2012 covering a wide range of flows (1.3 to 31.6 m3 s-1). To assess the distributed GW-SW discharge, we assumed SC to be conservative and attributed changes in SW SC behavior to nonpoint source loading. We addressed model parameterization considerations in terms of spatial resolution discrepancies between the high resolution, synoptic sensor data and relatively sparse available GW well data, and also tested model sensitivity to GW source characteristics (GW sampling screen depth and timeframe). For spatial interpolations requiring a large number of wells (inverse distance weighting method with 12 wells), we found large differences in GW-SW discharge estimates, and attributed this to well data availability issues. Additionally, GW-SW distributed discharge estimates also showed noticeable variability between GW spatial parameterization methods. Cumulative GW-SW discharge estimates agreed reasonably with observed differential flows between two gauging stations. Distributed GW-SW discharge results clearly identify a zone of higher GW-SW discharge related to elevated hydraulic gradient and supported from previous studies. While SW SC expectedly diluted with increased SW flows, GW-SW discharge did not consistently decrease as anticipated, indicating more complex GW-SW interactions requiring further investigation. The SC-based distributed GW-SW discharge estimates were used to parameterize a reactive nitrate loading model using a similar mass-balance method, incorporating a first-order decay term to explain denitrification. We scaled the unitless decay term using local discharge estimates, and we varied the decay term to achieve the best model fit (i.e., lowest RMSE) to observed river nitrate concentrations. When we censored GW nitrate concentrations less than method detection limits, for GW parameterization, the best fit model agreed well with observed SW nitrate concentrations. The unitless decay term estimated for each synoptic event generally underestimated previous studies along a local GW flowpath, but showed a similar trend with a regional study for different flow regimes (higher nitrate loss for low flows). The methods and analysis presented in this work provide a practical and rapid assessment tool for estimating longitudinal GW-SW discharge and potential reactive constituent loading at resolutions of interest to land management/change studies, aquatic ecosystem sustainability, and maintaining water quality standards for human consumption.