Title page for ETD etd-08272003-180016


Type of Document Master's Thesis
Author Bonham, John G.
URN etd-08272003-180016
Title Effects of Spatial Information on Estimated Farm Nonpoint Source Pollution Control Costs
Degree Master of Science
Department Agricultural and Applied Economics
Advisory Committee
Advisor Name Title
Bosch, Darrell J. Committee Chair
Taylor, Daniel B. Committee Member
Wolfe, Mary Leigh Committee Member
Keywords
  • Phosphorous
  • Buffers
  • Nutrient Management
  • Spatial Information
Date of Defense 2003-07-02
Availability unrestricted
Abstract
In the state of Virginia, population growth and the associated increases in municipal

wastewater, along with the threat of EPA regulations, will increase the need for reductions in

phosphorous (P) loads in surface waters in order to meet and maintain water quality standards for

the Chesapeake Bay. Agriculture contributes 49% of P entering the Bay; therefore, it can be

expected that agriculture will be targeted as a source of P reductions.

Spatially variable physical and socioeconomic characteristics of a watershed and its

occupant farms affect both the decisions made by farmers and the transport of nutrients.

Evidence suggests that spatially variable characteristics should be considered when designing

policies to control nonpoint sources of water pollution. However, spatial information can be

expensive to collect and the evidence is not conclusive as to the level of information required to

analyze specific pollution-control policies.

The objective of this study was to estimate the accuracy of predicted compliance costs

and changes in P deliveries resulting from mandatory buffer installation and mandatory nutrient

management for three alternative levels of information, relative to the population of farms in a

Virginia watershed. For each information case, an economic model, FARMPLAN, was used to

determine the profit maximizing levels of inputs, outputs and gross margins. Selected crop

rotations and P applications were used as inputs to the physical model, PDM, which estimated

the levels of P delivered to the watershed outlet. The compliance cost and P reduction estimates

for the three alternative cases were compared to those of the population to determine their

accuracy.

The inclusion of greater levels of spatial information will lead to more accurate estimates

of compliance costs and pollution reductions. Estimates of livestock capacity are more important

to making accurate predictions than are farm boundaries. Differences in estimates made using

different levels of information will be greater when the farmers have greater flexibility in

meeting the policy requirements. The implications are that additional spatial information does

not aid in the selection of one policy over the other, but can be useful in when estimating costs

for budgeting purposes, or when evaluating how farmers will respond to the policy.

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