Agrosystems, Geosciences & Environment (Jan 2021)

Sectional model of a prairie buffer strip in a laboratory flume for water quality research

  • Andrew J. Craig,
  • Michelle L. Soupir,
  • Chris R. Rehmann

DOI
https://doi.org/10.1002/agg2.20133
Journal volume & issue
Vol. 4, no. 1
pp. n/a – n/a

Abstract

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Abstract Vegetative buffers have shown promising results in reducing runoff volume, sediment, nutrients, and manure‐borne contaminants in runoff from agricultural fields. Although these vegetative buffer systems have been extensively tested in field and plot‐scale studies that utilize either natural or simulated rainfall, studies of such systems under highly controlled conditions in the laboratory have been limited. Here, we present the development of a new system for laboratory testing of a full‐scale, sectional, physical model of a new practice under the Continuous Conservation Reserve Program (CRP) Clean Lakes, Estuaries, and Rivers (CLEAR) Initiative, CP‐43 Prairie Strips. This work includes the extraction of prairie strip sections from the field and their integration into an existing laboratory flume facility with specific auxiliary features to facilitate overland flow experimentation. As a proof of concept run, a potassium chloride (KCl) tracer study was conducted to verify system functionality and inform future work. The tracer pulse was injected under saturated conditions and the response was monitored through surface water (upstream and downstream of the prairie strip model) and subsurface water (infiltrated) sampling with continuous flow rate monitoring at the sampling locations. The tracer test provided highly resolved breakthrough curves (BTCs) with 93.5% of the injected tracer mass recovered, and provided useful information on flow partitioning, velocities, and dispersion characteristics along the surface and through the subsurface profile of the model. This model prairie strip system is expected to be useful in optimizing the performance of prairie strips under highly controlled flow and contaminant source conditions.