Document Type

Article

Publication Date

8-18-2020

Publication Title

Science of The Total Environment

Volume

753

Issue

141731

Abstract

Quantifying temporal variability and fluxes within hydrologic catchments is critical to understanding the underlying chemical and physical processes leading to material transport. Measuring variability and fluxes requires sampling at time scales similar to the time scale of process occurrence. This demand has led to the development of automated sampling systems designed to sample at high frequencies, on the order of minutes. While widely deployed in a variety of systems, we installed two high-frequency sampling devices in a single drainage comprised of restored prairie and agricultural land uses in temperate Eastern Nebraska. The sampling systems determined flow rate, conductivity, and turbidity at 15-minute intervals for a twelve-month period. Conductivity was used as a proxy for total dissolved solids (TDS) concentrations and turbidity was used as a proxy for total suspended solids (TSS) concentrations. Using the high-frequency data, estimates of solids flux were calculated, error on the estimates was constrained, the effects of sample timing were considered, and conductivity and turbidity changes during precipitation events were examined. Overall, TDS fluxes were about three times higher than TSS fluxes from the catchment as a whole. However, the TSS fluxes were higher in the agricultural section of the catchment than from the restored prairie. Sheet and rill soil loss estimates from both the restored prairie and agricultural settings were low (<0.060 mm/yr). For TDS flux calculations, sampling at a monthly frequency gave a value that was only 11% lower than sampling every 15 min. For TSS flux calculations, sampling only during precipitation events (0.7% of the time) would capture 67% of the annual flux. Thus, minimizing error in sampling strategies depends on the constituent being analyzed.

Comments

The final, published version can be found here: https://doi.org/10.1016/j.scitotenv.2020.141731.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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