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Calibrated Passive Sampling - Multi-plot Field Measurements of NH3 Emissions with a Combination of Dynamic Tube Method and Passive Samplers
Published on: March 21, 2016
Nitrogen loss response to stacked, accretive conservation practices: A 10-year paired watershed study
Shoaib Ahmed1, Richa Babbar1, Leigh Ann Long1
1Department of Agricultural & Biosystems Engineering, Iowa State University, 605 Bissell Rd, Ames, IA, 50011, USA.
Abstract:
Tile-drained row-crop watersheds are efficient at moving water, and that same efficiency can move nitrate out of fields and into downstream waters. To evaluate nitrogen export patterns associated with stacked conservation practices over time, 10 years (2015-2024) of monitoring data during the March-November monitoring season was analyzed. Study sites included two paired sub-watersheds, S11 (low BMP) and S12 (high BMP) of the Black Hawk Lake watershed. Flow-weighted baseflow and event samples were collected and analyzed for NO3-N, total ammoniacal nitrogen (TAN), and total nitrogen (TN). Concentrations and loads were compared using nonparametric tests and effect sizes, and long-term and sub-period trends were evaluated using Seasonal Mann-Kendall and Innovative Trend Analysis approaches, which are commonly applied to non-normal environmental time series. Across the monitoring period, NO3-N was consistently higher in S11 than S12 (mean NO3-N: 27.0 vs 10.9 mg N/L), and NO3-N unit loads were about threefold higher in S11 (1.20 vs 0.39 kg N d-1 ha-1). Throughout the monitoring period, the high-BMP watershed exhibited a decline in NO3-N and TN export (70.5% and 54.2%), while S11 showed smaller reductions and an increasing trend after 2019 consistent with a drought-rewetting N flush. Overall, the contrasting trajectories between the paired watersheds suggest that greater and more consistent conservation-practice implementation was associated with lower nitrate export and improved long-term water quality outcomes, although differences in manure inputs, and source availability limit direct causal attribution.
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