The Influence of SW-GW Exchange on Whole Stream Metabolism Estimates

Abstract:

In recent years, the dynamic connection between SW-GW has been documented across a wide range of aquatic ecosystems. However this appreciation for dynamic GW exchange has not yet been fully incorporated into our interpretation and quantification of stream ecological processes. To address this, we explored the influence of GW exchange on estimates of net ecosystem productivity (NEP) in real time over 4 months in a snowmelt-dominated catchment in Montana. We examine how metabolism varied seasonally, and assess how the relationship between GW exchange and in-stream processes evolved over the snowmelt-baseflow recession.

Traditional 1-station metabolism methods do not fully incorporate hydrologic information into NEP estimates. They are generally insensitive to variation in discharge, and do not incorporate travel times or account for GW exchange. Here we demonstrate that failing to account for both gains and losses can bias NEP estimates and fluxes, particularly in systems with high rates of GW exchange. At our site, accounting for GW exchange during high flow conditions when GW-SW exchange was highest increased instantaneous NEP rates by 2.6 times. Over the entire growing season, this led to a 2.4-fold increase in cumulative growing season NEP.

Ecosystem metabolism is a biologically mediated process that is often obfuscated by physical hydrological processes. In order to assess the magnitudes of biotic processes, we must first disentangle them from co-occurring physical processes. We demonstrate that SW-GW exchange is an influential physical process that exerts a strong influence on metabolism estimates. We posit that incorporating GW into metabolism methods will influence NEP estimates across a wide range of systems, particularly those with high rates of exchange or strong seasonality in gains and losses. Incorporating hydrology more fully into stream ecological methods is necessary for accurate understanding and quantification of carbon cycling in streams.