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Can I read Testing the Riparian Ecosystem Management Model (REMM) on a Riparian Buffer with Dilution from Deep Groundwater on EtoBox?

Testing the Riparian Ecosystem Management Model (REMM) on a Riparian Buffer with Dilution from Deep Groundwater is a Environmental Science article available to read on EtoBox.

What is Testing the Riparian Ecosystem Management Model (REMM) on a Riparian Buffer with Dilution from Deep Groundwater about?

The Riparian Ecosystem Management Model (REMM), developed to quantify water quality benefits of riparian buffers, was field-tested using five years (2005)(2006)(2007)(2008)(2009) of measured hydrologic and water quality data on a site in the upper coastal plain of North Carolina. This buffer site received nitrate-nitrogen (NO 3 -N) loading from a pasture fertilized with poultry litter. Field results showed reductions in groundwater NO 3 -N concentrations moving through the buffer to the stream for the five-year period; however, further analysis of the groundwater data indicated that dilution was a one of the contributing factors to those observations. Previous testing of REMM was carried out at riparian sites having minimal groundwater dilution. This modeling study is the first attempt to calibrate and validate REMM on a riparian buffer site showing reductions in NO 3 -N concentrations due to groundwater dilution. REMM was calibrated using daily measured water table depths (WTDs) and monthly groundwater NO 3 -N concentrations. Results of model testing showed simulated WTDs and NO 3 -N concentrations in good agreement with measured values. The mean absolute error (MAE) and Willmott'

Who reads Testing the Riparian Ecosystem Management Model (REMM) on a Riparian Buffer with Dilution from Deep Groundwater?

It is typically read by researchers, students, and practitioners in Environmental Science.

Publisher
American Society of Agricultural and Biological Engineers; American Society of Agricultural and Biological Engineers (ASABE) (ISSN 2151-0032)
Published
2017
Language
EN
Field
Environmental Science (Physical Sciences)