PS 3-67 - Identifying green infrastructure BMPs for reducing nitrogen export to a Chesapeake Bay agricultural stream: Model synthesis and extension of experimental data

Monday, August 6, 2012
Exhibit Hall, Oregon Convention Center
Robert B. McKane1, Alex Abdelnour2, Allen Brookes3, Connie A. Burdick4, Kevin Djang5, Thomas E. Jordan6, Bonnie Kwiatkowski7, Feifei Pan8, William T. Peterjohn9, Marc Stieglitz2 and Donald E. Weller6, (1)U.S. Environmental Protection Agency, Corvallis, OR, (2)School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, (3)US Environmental Protection Agency, Corvallis, OR, (4)National Health & Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Corvallis, OR, (5)CSC, Corvallis, OR, (6)Smithsonian Environmental Research Center, Edgewater, MD, (7)Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, (8)Department of Geography, University of North Texas, Denton, TX, (9)Biology, West Virginia University, Morgantown, WV
Background/Question/Methods

The effectiveness of riparian forest buffers and other green infrastructure for reducing nitrogen export to agricultural streams has been well described experimentally, but a clear understanding of process-level hydrological and biogeochemical controls can be difficult to ascertain from data alone.  We previously applied a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to further elucidate how riparian forest buffers reduce stream inputs of dissolved nitrogen in runoff from upland agricultural practices in an intensively studied catchment in the Rhode River Watershed along the western shore of Chesapeake Bay, USA.  Simulated and observed daily stream flow and export of ammonium and nitrate were in generally good agreement over the period of record (2000-2003) for which complete daily stream flow and chemistry data were available.  For the present study we used sensitivity analysis to explore the model’s potential for extending the experimental data to identify upland and riparian best management practices (BMPs) that most effectively reduce stream nitrogen loads.  Candidate BMPs considered the sensitivity of nitrogen reduction to the timing and rate of upland fertilization and to green infrastructure extent (buffer width), type (forest or grass) and management (stand age). 

Results/Conclusions

The model suggests that riparian forest buffers are more effective than grass buffers in reducing stream nitrogen loads.  Greater buffer width and stand age increase nitrogen reductions, but gains in effectiveness diminish asymptotically for both variables.  Green infrastructure solutions alone may be insufficient for achieving water quality standards where riparian flow paths are predominantly deep or where upland fertilization approaches rates often used for intensive agriculture.  The model also quantitatively describes the trade-off between agronomic production and nitrogen export to surface waters and the relative importances of denitrification and plant uptake in reducing nitrogen export under different upland and riparian management scenarios.