Biological Indicator Development

• Paleolimnological analysis of nutrient enrichment for criteria development in New Jersey and New York lakes - Final Report
  
• Forecasting Algal blooms in Surface Water Systems with Artificial Neural Networks - March 2006
  The original objectives of this study were: 1) to assess the feasibility of using artificial neural networks (ANNs) as a real-time tool or accurately forecasting cyanobacteria counts, more commonly knows as blue-green algae, in surface water systems; 2) through sensitivity analyses conducted with the ANNs, identify critical climate, hydrologic, and water quality factors (i.e. variables) that may influence algae levels; 3) assess the feasibility of using ANNs with formal optimization for optimizing water treatment processes for reducing algae levels; 4) assess and provide guidance for improving data collection/organization for the purpose of improving algae level forecasting capability with the ANN technology.
• Research Project Summary
• Full Report (2.87 MB - 211 pages)
• Appendix (4.07 MB - 298 pages)

Water Quality and Chemistry