Date: Thursday, June 16th
Baseline Water Quality Inventory for Paterson Great Falls
by Eileen Brown and Liam Kenefic
Eileen Brown is a geographer for the USGS New Jersey Water Science Center. She graduated from The George Washington University in May 2021 with her degree in geography and has since been working as part of the Water Quality Investigations Program. Eileen has a strong interest in GIS, cartography, and water quality, and works closely with the New England Water Science Center to update FEMA flood hazard maps for the region.
Liam Kenefic is a Hydrologist with the USGS New Jersey Water Science Center within the Ground Water Modeling Unit. Liam received his BS from the University of New Hampshire in Earth Sciences with a concentration in Geophysics, and his MS from Keele University in Geoscience Research focused on paleoglacial and paleoclimate reconstructions. His work for the USGS focuses on integrated water science including domestic water use, water quality, and groundwater and surface water modeling.
Mapping the Groundwater Resources of the New Jersey Coastal Plain
by Stephen Cauller
Stephen Cauller is a Hydrologist and GIS Specialist in the USGS NJ Water Science Center. He has worked on groundwater quality investigations in Long Island, NY; the database design and application development team of the National Water Information System (NWIS) in Reston, VA; and directed numerous groundwater studies in the Coastal Plain of New Jersey. His work has involved groundwater levels and mapping, chloride concentrations in groundwater, hydrogeologic framework analysis, water quality summaries, multiple aquifer 3D groundwater flow model development and particle tracking, advective transport of nitrogen in groundwater, stream network derivation in different physiographic provinces, and flood inundation mapping in West Virginia and Maine. His current investigation involves measurement and mapping of the potentiometric surface in 10 confined aquifers of the NJ Coastal Plain, with results presented via a web-map interface.
This talk is eligible for 1 AICP CM self-reporting credit
