Effects of Spatial Information on Estimated Farm Nonpoint Source Pollution Control Costs

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.