Considerations for using turbidity as a surrogate for suspended sediment in small, ungaged streams: Time‐series selection, streamflow estimation, and regional transferability

Abstract

AbstractSuspended sediment (SS) transport is an important and natural process in aquatic ecosystems. However, accelerated erosion due to anthropogenic land uses causes excessive sedimentation, which makes SS pollution one of the most prevalent stressors causing biological impairments of freshwater. Despite the ubiquitous nature of sedimentation and the ways in which it negatively impacts streams, inherent obstacles exist to effective measurement and characterization of fluvial SS loading. SS concentrations (SSCs) can vary widely during similar hydrologic conditions, making discharge an unreliable predictor variable. Alternatively, turbidity has been shown to be an effective surrogate for SSC, and methods using in situ optical turbidity sensors to indirectly measure SSCs have been developed. We present data and results from research using turbidity as a surrogate for SSC in five small, ungaged streams in the Chesapeake Bay watershed. Objectives of this study include presenting practical considerations and strategies for applying the turbidity–SSC surrogate method in small headwater streams. Empirical evidence is presented illustrating the potential correlation between land use and sediment loading. Additionally, accurate estimates of sediment loading require utilization of high frequency time‐series data and on‐site monitoring to capture timing and magnitude of streamflow, especially during intense, short‐duration runoff events. Similar turbidity–SSC relationships across watersheds suggest that regional regression curves could be established to allow more efficient and cost‐effective estimation of sediment loading. The broad application of this method would also benefit water resource management, by enabling prioritization of sites for stream restoration, standardizing techniques for monitoring stream recovery, or documenting impacts of discrete land‐use changes.