Monitoring nitrogen loading and retention in an urban stormwater detention pond

Bernice R. Rosenzweig, James A. Smith, Mary Lynn Baeck, Peter R. Jaffe

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


Stormwater detention ponds have become ubiquitous in urbanized areas and have been suggested as potential hotspots of N transformation within urban watersheds. As a result, there is a great deal of interest in their use as structural best management practices to reduce the excessive N export from these watersheds. We conducted continuous monitoring of the influent and effluent N loads of a stormwater detention pond located on the Princeton University campus in Princeton, New Jersey. Our monitoring was conducted during four 21-d periods representing the four seasons of the northeastern United States. Water quality samples were collected and analyzed for nitrate (NO3-) during all four monitoring periods. During two of these periods, loads of ammonium (NH4+), dissolved organic N, and particulate N (PN) were measured. Our results show that NO3- dominated the influent N load, particularly in dry weather inflows to the detention pond. However, PN, which is often neglected in stormwater quality monitoring, made up as much as 30% of the total load and an even greater fraction during storm events. The results of our monitoring suggest that seasonal variation may play an important role in N retention within the detention pond. Although retention of NO3-, the most dominant fraction of N in the influent stormwater, was observed during the summer sampling period, no significant NO3- retention was observed during the spring or the two cold-weather sampling periods.

Original languageEnglish (US)
Pages (from-to)598-609
Number of pages12
JournalJournal of Environmental Quality
Issue number2
StatePublished - Mar 2011

All Science Journal Classification (ASJC) codes

  • Water Science and Technology
  • Pollution
  • Waste Management and Disposal
  • Management, Monitoring, Policy and Law
  • Environmental Engineering


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