“Hot moments” of carbon and nitrogen in streams: Key insights from in-situ, high-frequency optical sensors from the North East Water Resources Network (NEWRnet)

Abstract:

Sharp or unexpected changes in stream water solute concentrations and fluxes can often provide important insights into potential sources, supply versus transport controls, and threshold behavior in watersheds. Identifying these “hot moments” is critical for furthering our understanding of biogeochemical processes and for developing accurate mechanistic models to manage water quality. Use of in-situ, high-frequency optical sensors, while in its infancy, has shown considerable promise in capturing fine resolution time series data on solute concentrations. Here, we highlight key lessons from the North East Water Resources Network (NEWRnet), a regional water quality network (Delaware, Rhode Island and Vermont) instrumented with optical sensors on a suite of stream sites (forested, agricultural, and urban watersheds in each state). Sensor data is coupled with traditional hydrologic and water chemistry sampling for baseflow and storms, laboratory-based UV and fluorescence excitation-emission matrices (EEMs) to characterize organic matter composition, and stable carbon (C) and nitrogen (N) isotopes to identify solute sources. Both dissolved and particulate forms of C and N are being studied. Sampling is performed throughout the year with special attention to large storm events, droughts, diel variations, and key seasonal transitions including snowmelt and autumn leaf fall. We leverage these complimentary data to reveal both – process controls on C and N as well as methodological constraints and challenges with the sensors. Particulate and dissolved concentrations of C and N are compared for large storm events to disentangle supply and transport controls. Simultaneously, the accuracy of sensors is evaluated for interferences from varying particle size classes. Coupled changes in C and N concentrations and shifts in C composition during autumn leaf fall and snowmelt are investigated to identify biogeochemical/ecological controls. However, we also investigate how variability in organic matter composition may affect sensor predictions and calibrations within and across the study sites. Climate-change predictions indicate an intensification of the hydrologic cycle, thus, these sensors represent a critical tool for capturing and understanding water quality hot moments in aquatic ecosystems.