Grantee Research Project Results
Linking Environmental and Social Performance Measurement for Management at National and Watershed Levels: Modeling and Statistical Approaches
EPA Grant Number: R828021Title: Linking Environmental and Social Performance Measurement for Management at National and Watershed Levels: Modeling and Statistical Approaches
Investigators: Farrow, Scott , Small, Mitchell J. , Van Houtven, George L. , Solow, Andrew R. , Sinnott, James , Schultz, Martin , Bondelid, Tim
Current Investigators: Small, Mitchell J. , Solow, Andrew R. , Fischbeck, Paul S. , Farrow, Scott , Bondelid, Tim , Sinnott, James , Schultz, Martin , Van Houtven, George L. , Schoen, Mary E. , Cooter, W.S.
Institution: Carnegie Mellon University , Desert Research Institute , Woods Hole Oceanographic Institution
EPA Project Officer: Packard, Benjamin H
Project Period: January 10, 2000 through January 9, 2003
Project Amount: $649,864
RFA: Water and Watersheds (1999) RFA Text | Recipients Lists
Research Category: Watersheds , Water
Description:
The objectives of the study are: 1) to estimate year-to-year changes in water quality for conventional water quality parameters at the national and watershed level by using index numbers, and multivariate and ordered mean rates of change for conventional and toxic pollutants, 2) to estimate the net benefits of alternative policies for Total Maximum Daily Loads (TMDL) trading, 3) to estimate the economic benefits of water quality improvement at the watershed level, 4) to improve modeling of wet weather events in a policy model and 5) to estimate the link between water quality pollution abatement and control expenditures at the facility level and water quality performance indicators for the nation and specific regions and watersheds.Approach:
Approach: To answer these questions, our approach involves both modeling and statistical approaches. The modeling approach extends a prototype model, the National Water Pollution Control Assessment Model (NWPCAM) to include: 1) a watershed-level analysis, 2) a theoretically consistent aggregation of water quality, 3) wet-weather modeling, and 4) incorporation of site-specific costs in order to model the environmental and economic impacts of allowing trading in order to meet TMDL-based standards. The statistical approach uses a two-stage procedure to estimate a regional trend from multiple monitoring sites, allowing for model validation and extension of predictions to a broader suite of water-quality parameters.Expected Results:
The project will integrate physical, ecological and social science models and data to provide an evaluation tool for surface water quality managers at various levels of spatial aggregation. Furthermore, time series of several water quality indicators and an analysis of policy are among the expected results.Publications and Presentations:
Publications have been submitted on this project: View all 16 publications for this projectJournal Articles:
Journal Articles have been submitted on this project: View all 4 journal articles for this projectSupplemental Keywords:
effluent, indicators, integrated assessment, public policy, cost-benefit, decision-making, modeling, agriculture, industrial sectors., RFA, Scientific Discipline, Water, Water & Watershed, Wet Weather Flows, Environmental Monitoring, Ecological Risk Assessment, Ecology and Ecosystems, Social Science, Watersheds, social impact assessment, watershed, social performance measurement, statistical approaches, multiple monitoring sites, decision making, cost benefit, decision model, integrated watershed model, water quality, economic benefit, National level, statistics, aquatic ecosystems, wet weather modelingProgress and Final Reports:
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.