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LANDSCAPE CHARACTERIZATION & NON-POINT SOURCE NITROGEN MODELING IN SUPPORT OF TMDL DEVELOPMENT IN THE NEUSE RIVER BASIN, NC
Citation:
Lunetta, R S., J. Ediriwickrema, C. T. Garten, R. Green, J. Iiames, D. M. Johnson, J G. Lyon, A. McKerrow, AND D Pilant. LANDSCAPE CHARACTERIZATION & NON-POINT SOURCE NITROGEN MODELING IN SUPPORT OF TMDL DEVELOPMENT IN THE NEUSE RIVER BASIN, NC. Presented at US EPA Environmental Monitoring Technology Conference, Boston, MA, September 19-20, 2000.
Impact/Purpose:
Our research objectives are to: (a) develop new methods using satellite remote sensor data for the rapid characterization of LC condition and change at regional to national scales; (b) evaluate the utility of the new NASA-EOS MODIS (Moderate Resolution Imaging Spectrometer) leaf area index (LAI) measurements for regional scale application with landscape process models (e.g., biogenic emissions and atmospheric deposition); (c) provide remote sensor derived measurement data to advance the development of the next generation of distributed landscape process-based models to provide a predictive modeling capability for important ecosystem processes (e.g., nutrients, sedimentation, pathogens, etc.); and (d) integrate in situ monitoring measurement networks with UAV and satellite based remote sensor data to provide a continuous environmental monitoring capability.
Description:
Pfesteria-like toxic- blooms have been implicated as the causative agent responsible for numerous outbreaks of fish lesions and fish kills in the Mid-Atlantic and southeastern U.S. An increase in frequency, intensity, and severity of toxic blooms in recent years is thought to be a result of surface water nutrient enrichment, mediated by changing land-use practices. an coal of this research is to apply Im-id-cover/use information to quantify the extent and distribution of terrestrial sources of nitrogen contributing tor harmful algal blooms add possible Pfiesteria outbreaks. This is being accomplished by coupling high resolution land-cover data sets with-G1S-based nutrient models that will be calibrated and validated using a stratified subset of Neuse River Basin (NRB) sub-watersheds. A high resolution land-cover/use data set has been developed using advanced satellite based remote sensor systems. These include use of the new SPOT 4 (XS) and Landsat 7 Enhanced Thematic Mapper Plus (ETM') remote sensor systems to provide basin-wide land cover/use data at 0.4 ha. and 5.8 ha. minimum mapping units (MMU) or landscape patches. Also, use of the new IKONOS sub-meter stereo imagery was made for the characterization of riparian zone vegetation structure- NRB modeling includes the development and implementation of a nitrogen mass balance model to quantify patch specific potential nitrogen sources, coupled with a hydrologic model for routing nitrogen to water courses based event driven precipitation.