Nitrogen Removal by Stormwater Management Structures: A Data Synthesis
Author ORCID Identifier
https://orcid.org/0000-0002-3570-3588 : Catherine Febria
Journal of the American Water Resources Association
Best management practices, Constructed wetland, Detention pond, Nitrogen removal, Nutrients, Performance, Retention basin, Stormwater management, Urban areas, Vegetated swale
A comprehensive synthesis of data from empirically based published studies and a widely used stormwater best management practice (BMP) database were used to assess the variability in nitrogen (N) removal performance of urban stormwater ponds, wetlands, and swales and to identify factors that may explain this variability. While the data suggest that BMPs were generally effective on average, removal efficiencies of ammonium (NH4), nitrate (NO3), and total nitrogen (TN) were highly variable ranging from negative (i.e., BMPs acting as sources of N) to 100%. For example, removal of NO3 varied from (median ±1 SD) -15 ± 49% for dry ponds, 32 ± 120% for wet ponds, 58 ± 210% for wetlands, and 37 ± 29% for swales. Across the same BMP types, TN removal was 27 ± 24%, 40 ± 31%, 61 ± 30%, and 50 ± 29%. NH4 removal was 9 ± 36%, 29 ± 72%, 31 ± 24%, and 45 ± 34%. BMP size, age, and location explained some of the variability. For example, small and shallow ponds and wetlands were more effective than larger, deeper ones in removing N. Despite well-known intra-annual variation in N fluxes, most measurements have been made over short time periods using concentrations, not flow-weighted N fluxes. Urban N export is increasing in some areas as large storms become more frequent. Thus, accounting for the full range of BMP performance under such conditions is crucial. A select number of long-term flux-based BMP studies that rigorously measure rainfall, hydrology, and site conditions could improve BMP implementation.
Koch, Benjamin J.; Febria, Catherine M.; Gevrey, Muriel; Wainger, Lisa A.; and Palmer, Margaret A.. (2014). Nitrogen Removal by Stormwater Management Structures: A Data Synthesis. Journal of the American Water Resources Association, 50 (6), 1594-1607.