Deciphering Highly Variable Tracer Data from Geomorphically Complex Urban and Agricultural Streams

Multiple techniques have been developed to model nutrient uptake in streams, but all rely on uncluttered spatial or temporal tracer signals to estimate nutrient uptake and transient storage parameters. However, the results from our tracer injections on six stream reaches of varying geomorphic complexity, three on a Colorado Front Range urban stream and three on a mountainous agricultural stream in north-central Colorado, exhibit high variability. We discuss our methodological and analytical approaches for minimizing and deciphering this confounding noise and its implications for parameterizing biogeochemical and hydraulic models. Also, we will examine the relationship between data variability and measures of geomorphic complexity.