Science Inventory

EVALUATING PREDICTIVE ERRORS OF A COMPLEX ENVIRONMENTAL MODEL USING A GENERAL LINEAR MODEL AND LEAST SQUARE MEANS

Citation:

KNIGHTES, C. D. AND M. J. CYTERSKI. EVALUATING PREDICTIVE ERRORS OF A COMPLEX ENVIRONMENTAL MODEL USING A GENERAL LINEAR MODEL AND LEAST SQUARE MEANS. ECOLOGICAL MODELLING. Elsevier Science BV, Amsterdam, Netherlands, 186(3):366-374, (2005).

Impact/Purpose:



The objective of this task is to develop, support and transfer a wide variety of tools and mathematical models that can be used to support watershed and water quality protection programs in support of OW, OSWER, and the Regions.

Description:

A General Linear Model (GLM) was used to evaluate the deviation of predicted values from expected values for a complex environmental model. For this demonstration, we used the default level interface of the Regional Mercury Cycling Model (R-MCM) to simulate epilimnetic total mercury concentrations in Vermont and New Hampshire lakes based on data gathered through the EPAs Regional Environmental Monitoring and Assessment Program (REMAP).

Record Details:

Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Product Published Date: 08/25/2005
Record Last Revised: 11/16/2005
OMB Category: Other
Record ID: 114704

Organization:

U.S. ENVIRONMENTAL PROTECTION AGENCY

OFFICE OF RESEARCH AND DEVELOPMENT

NATIONAL EXPOSURE RESEARCH LABORATORY

ECOSYSTEMS RESEARCH DIVISION

REGULATORY SUPPORT BRANCH