Master's Projects - Executive Summary

[an example from a Nicholas Institute report by Olander et al. 2014] - full report here >

Executive Summary



[student's name]



Water quality trading (WQT) allows point-source permittees to meet their water quality obligations by purchasing credits from other point or nonpoint sources that have reduced their discharges. Non- permitted animal operations and permitted animal operations could be attractive partners in such a WQT program.

To incorporate animal operations into water quality trading, methods for quantifying pollutant reductions resulting from changes in management practices must be sufficiently accurate or conservative so that regulators and point-source purchasers can be confident in the results. Already under way in many places, water quality trading typically uses computer models or empirical data synthesis to estimate the water quality benefits of management practices. Any uncertainties are usually addressed by adjusting the trading ratio to result in a more conservative estimate of the amount of water quality benefit required to offset water quality impacts. This report provides an overview of existing measurement and modeling methods and tools to inform efforts to build updated and more integrated methods for quantifying water quality benefits of animal operation management for use in WQT programs. This is an academic review of models and methods, not a guide to how these tools can be adapted for use in water quality trading programs. For a more practical exploration of model application see Electric Power Research Institute (2011) evaluation of the Nutrient Trading Tool and Watershed Analysis and Risk Management Framework.

The first section of this report provides an overview of how the Clean Water Act underlies water quality trading programs, how animal operations fit in, and how water quality trading works. It also reviews that needs to be quantified for different types of management practices in order to determine changes in pollutant loading and how improved quantification can help support water quality trading programs.

The second section provides an overview of models used to estimate various aspects of animal management-water quality relationships. The discussion starts with models of animal production of nutrient waste, reviews models for surface water transport, and then covers hydrological, empirical, and mechanistic process-based models used to assess transport and transformation of pollutants in watersheds.

The section then describes the potential for quantifying unexpected effects of nutrient transformation and transport by considering losses to groundwater and the atmosphere. This section also summarizes how quantification may be different for rangeland and grazing land systems as compared to confined feeding operations.

The third section of the report describes how direct measurement and monitoring of nutrient losses is evolving with new technologies and how it can be used to improve the quantification and modeling of nutrients over time, to measure cumulative change in a water body, and perhaps eventually how it could be used to quantify edge-of-field losses.

The fourth section of the report recommends how to update and refine existing models and tools to reduce uncertainties in water quality quantification, how to make sure they are viable for use by practitioners, and how they should be built to improve over time.

Ultimately, water quality trading requires quantification of the nutrient loading reductions associated with management practices and some estimate of the uncertainty associated with this quantification. This process can be straightforward and robust for some practices, such as reducing nutrients imported to an animal operation or wastes exported from a watershed, but there is much less confidence in quantification of other practices that rely on chemical or microbial processes to reduce pollutant transport, for example, microbial denitrification to reduce nitrate loading to streams. Because water quality trading carries the logistical and economic implications of changing animal production practices as well as trading pollution credits, reliable estimates of the load reduction from new practices on water quality are important. When they are lacking, animal system managers bear the burden of higher trading ratios, which lowers the number of credits they receive for their estimated load reduction. Ultimately, targeted and coordinated investment in developing, improving, and integrating selected animal production and hydrologic models at both the farm and watershed scales will be needed to improve quantification.

This report makes several key points and recommendations:

  • The computational foundation of many water quality models has not been updated for 20 or more years.
  • The federal government could provide support to state WQT programs by using a rigorous external and academic review to select the best empirical and process-based models and to focus resources on improving and adapting these models to address the needs of WQT programs.
  • Models should be developed in linkable modules and updated as technologies become available. They should integrate spatial methods and creating opportunities for user-friendly interfaces.
  • Given the uncertainties in groundwater and emissions modeling, modeling outcomes may be best used to indicate potential risks and areas for additional assessment. Effort should be directed toward incorporating methods or linking models to estimate the likelihood that certain management practices would increase groundwater contamination or atmospheric emissions.
  • WQT programs need tools to create simple and defensible crediting calculations.



(MP adviser signature here)

Dr. (MP Adviser Name printed)



Master's Project submitted in partial fulfillment of the requirements for the Master of Environmental Management degree in the Nicholas School of the Environment, Duke University May 2009

Submission. When the final report has been approved by the MP adviser, the "official copy" is to be uploaded to DukeSpace following specific instructions. The separate executive summary with adviser’s signature must be submitted at the same time. Deadlines for submission are as follows:

  • For May graduation:  Friday of Reading Week for the spring semester

  • For September graduation: last Friday in August

  • For December graduation: Friday of Reading Week for the fall semester