Preprints
https://doi.org/10.5194/hess-2023-256
https://doi.org/10.5194/hess-2023-256
02 Nov 2023
 | 02 Nov 2023
Status: this preprint is currently under review for the journal HESS.

Simulation of spatially distributed sources, transport, and transformation of nitrogen from fertilization and septic system in an exurban watershed

Ruoyu Zhang, Lawrence E. Band, Peter M. Groffman, Amanda K. Suchy, Jonathan M. Duncan, and Arther J. Gold

Abstract. Excess export of reactive nitrogen in the form of nitrate (NO3) export from exurban watersheds is a major source of water quality degradation and threatens the health of downstream and coastal waterbodies. Ecosystem restoration and best management practices (BMPs) can be introduced to reduce in-stream NO3 loads by promoting vegetation uptake and denitrification on uplands. However, accurately evaluating the effectiveness of these practices and setting regulations for nitrogen inputs requires an understanding of how human sources of nitrogen interact with ecohydrological systems. We evaluated how the spatial and temporal distribution of nitrogen sources, and the transport and transformation processes along hydrologic flowpaths control nitrogen cycling, export, and the development of “hot spots” of nitrogen flux in suburban ecosystems.  We chose a well-monitored exurban watershed, Baisman Run in Baltimore County, Maryland, USA, to evaluate patterns of in-stream NO3 concentrations and upland nitrogen-related processes in response to three common activities: irrigation, fertilization, and on-site sanitary wastewater disposal (septic systems). We augmented a distributed ecohydrological model, RHESSys, with estimates of these additional loads to improve prediction and understanding of the factors generating both upland nitrogen cycling and stream NO3 concentrations. The augmented model predicted streamflow-weighted NO3 concentrations of 1.37 mg NO3-N/L, compared to observed 1.44 mg NO3-N/L, while the model predicted concentrations of 0.28 mg NO3-N /L without the additional loads from human activities from water year 2013 to 2017. Estimated denitrification rates in grass lawns, a dominant land cover in suburban landscapes, were in the range of measured values. The highest predicted denitrification rates were downslope of lawn and septic locations in a constructed wetland, and at a sediment accumulation zone at the base of a gully receiving street drainage. These locations illustrate the development of hot spots for nitrogen cycling and export in both planned and “accidental” retention features. Appropriate siting of best BMPs and the identification of spontaneously developed nutrient hot spots should be pursued to retain nutrients and improve water quality.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Ruoyu Zhang, Lawrence E. Band, Peter M. Groffman, Amanda K. Suchy, Jonathan M. Duncan, and Arther J. Gold

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-256', Anonymous Referee #1, 20 Dec 2023
    • AC1: 'Reply on RC1', Ruoyu Zhang, 08 Mar 2024
  • RC2: 'Comment on hess-2023-256', Anonymous Referee #2, 18 Jan 2024
    • AC2: 'Reply on RC2', Ruoyu Zhang, 08 Mar 2024
Ruoyu Zhang, Lawrence E. Band, Peter M. Groffman, Amanda K. Suchy, Jonathan M. Duncan, and Arther J. Gold
Ruoyu Zhang, Lawrence E. Band, Peter M. Groffman, Amanda K. Suchy, Jonathan M. Duncan, and Arther J. Gold

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Short summary
Human-induced nitrogen (N) is found as the primary N source in many urban watersheds. We developed a high-resolution ecohydrological model to consider the spatial patterns and loads of septic effluents and lawn fertilization. The comparable simulations to observations showed the ability of our model to enhance insights into current water quality conditions, identify high retention locations, and plan future restorations to improve urban water quality.