Project #4814

Evaluation of Data Needs for Nutrient Target-Setting Using the Nutrient Modeling Toolbox

$292,900
Completed
Principal Investigator
David
Dilks
Research Manager
Ms. Lola Olabode
Contractor
LimnoTech, Inc.

Abstract

This project examined the amount of data required to develop a mechanistic water quality model that can support water quality management actions for nutrients. Jackknife analyses were conducted to assess the relationship between the amount of data available to support model application and resulting model error. A range of model uncertainty analysis techniques was applied to determine their applicability for use with mechanistic nutrient models. State regulatory staff were interviewed, and an inventory of model applications reviewed, to assess requirements for model acceptance. A practical method for estimating uncertainty from complex models was developed, and specific recommendations are provided regarding data requirements (and other considerations) needed to support acceptance of model results. Published in 2019.

Originally funded as WERF project LINK3R16