Continuous monitoring of watershed signals: Disentangling compounded processes

Brian L McGlynn1, Erin Cedar Seybold2, Margaret A Zimmer1, Kendra E Kaiser1, John McDevitt Mallard3, Anna Bergstrom4, Kelsey G Jencso5 and Fabian Nippgen1,6, (1)Duke University, Nicholas School of the Environment, Durham, NC, United States, (2)University of Kansas, Kansas Geological Survey, Lawrence, United States, (3)Duke University, Durham, United States, (4)Boise State University, Boise, ID, United States, (5)University of Montana, Missoula, MT, United States, (6)University of Wyoming, Laramie, WY, United States
Abstract:
Matching observation and process time scales is critical for uncovering and quantifying ecosystem processes and developing new understanding of key drivers of observed behavior. Fortunately, real-time monitoring of hydrological and biogeochemical signals across watershed and stream systems is becoming more common. Unfortunately, disentangling compounded biological and physical processes operating and transported across often asynchronous time scales presents new challenges for realizing the potential of real-time sensor technology. Here we focus on challenges to interpreting in-stream observations as well as opportunities to use these emerging technologies to gain new insight into system behavior through enhanced observational networks and analysis that can reduce equifinality in process attribution of observed signals.