

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 municipalwastewater, 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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