Policy Implications of Ranking Distributions of Nitrate Runoff and Leaching from Corn Production by Region and Soil Productivity
1997
Boisvert, Richard N. | Regmi, Anita | Schmit, Todd M.
The purpose of this study was to understand the implications of farm-to-farm and regional variations in N runoff and leaching for targeting specific policies to reduce nutrient contamination. To do this, we estimated distributions of nitrate runoff and leaching for individual soils on nearly 150 farms in three farm production regions of New York and ranked the distributions according to second degree stochastic dominance criteria (SSD). Based on these rankings, it was evident that cropland across farms and regions of New York is so heterogeneous that it is impossible to target policies to reduce nitrate contamination based on farm or regional characteristics. A much clearer ranking was found when soils were grouped by productivity group as measured by corn (Zea mays L.) yield. Based on the estimated elasticities of nitrate runoff and leaching with respect to N application, one can target those areas where contamination problems are most severe by focusing on soils with potential yields greater than 125 bu/acre. For it to make sense to target lower productivity soils, the productivity of additional N application at the margin on the highest yielding soils would have to be about double that of the lower yielding group. Evidence indicates that the ratios of productivities are less than unity in all three production regions. Research QuestionThe effectiveness of policies to reduce nonpoint source pollution from agricultural production is often frustrated by regional and farm-to-farm differences in cropping patterns and practices, as well as differences in the vulnerability of local farmland and other natural resources to environmental contamination. One strategy to account for these differences is to design policies to focus on or target those production practices or resource situations where the environmental risk is the greatest. The focus of this research is on differences in soil resources. The empirical question posed is: Can we measure and then systematically characterize or rank the farm-to-farm and regional variations in N runoff and leaching from corn production by soil characteristics and identify the implications of this ranking for targeting specific policies to reduce nutrient contamination from agricultural production? The study, made possible in large measure because of the availability of a unique data set containing detailed soils information for a sample of 142 farms, focuses on three major production regions in New York. Literature SummaryThere is increased realization that effective policies to control nonpoint source pollution must recognize differences in land or soil resources, but research aimed at targeting policies to take advantage of these differences is relatively new, Much of the work to date has focused on the special problems of highly erosive soils or wetlands or coastal areas. Much less emphasis has been given to investigating the importance for policy design of farm-to-farm or regional differences in soils between or within major production regions across the country. Very general screening procedures have been used to indicate those areas where problems of nutrient and pesticide contamination are likely to be most severe, but more research is needed to quantify these differences in contamination potential and to assess their effects on the design of effective policies to reduce pollution levels. Study DescriptionTo accomplish the study's objectives, we first obtain estimates of N runoff and leachate generated using GLEAMS for a wide range of soils using different length corn rotations and fertilization rates. These data are used to estimate several equations that relate nitrate runoff and leaching from corn production to soil characteristics, weather, rotations, and fertilization. In turn, these equations are used in conjunction with weather data and the detailed soils information on a sample of 142 farms in New York to generate 30-yr distributions of nitrate runoff and leachate by farm, region, and soil productivity group. The rankings of these distributions, according to second degree stochastic dominance (SSD) criteria, have important implications for policies to limit nitrate Contamination. These policy implications were underscored by using the elasticities of combined runoff and leaching with respect to a change in N application to assess the differential effectiveness of reducing N application by region and soil productivity group. Applied QuestionsFor policy purposes, can New York farms or agricultural regions be differentiated in terms of the combined nitrate runoff and leaching of their soils to provide more effective targeting of policies to reduce potential contamination of water sources? There are only three of a sample of nearly 150 farms where the 30-yr distributions of average combined runoff and leaching are consistently lower so that these farms dominate the others by SSD. This SSD procedure is a commonly accepted algorithm for ranking distributions and is consistent with risk aversion where decisionmakers utility or level of satisfaction increases with an improvement in environmental quality (e.g., less runoff and leaching), but at a decreasing rate. Put differently, this means that the higher the initial level of environmental quality, the smaller is the increase in utility associated with any additional improvement in the quality of the environment. The implication of this result is that cropland on farms across New York is so heterogeneous that ranking farms on any consistent basis in terms of the N runoff and leaching potential of the soils is nearly impossible. When these farms are grouped into three regions, the situation is slightly different. At this aggregate level, the runoff and leaching potential of the soils in one of the three regions dominates the runoff and leaching potential in the other two regions by SSD, but just barely since the distributions are very similar and cross several times. A much clearer ranking is found when the soils in each region are grouped by productivity as measured by corn yield. In terms of nitrate runoff and leaching potential, soils in the low yield category dominate the high yield categories by SSD, lending support to targeting policies to reduce nitrate contamination toward those higher yielding soils. By targeting policies to soils in different productivity groups, does the improved effectiveness in reducing nitrate loss potential come at the expense of higher reductions in farm income? There is higher nitrate loss on soils in the higher productivity group in part because recommended N application rates are slightly higher for higher yielding soils; but, to answer this question, we must examine the calculated elasticities of combined nitrate loss with respect to N application for each soil productivity group and region (e.g., the percentage change in nitrate loss due to a percentage change in N applied). These elasticities for the high yield group are about twice those for the low yield group in all three regions; thus, a reduction in N application on the high yielding soils will be about twice as effective at reducing nitrate loss as it would be on the low yielding soils. In terms of the policy's effect on agricultural income, the only way it would make sense to target the lower productivity soil group is if the ratios of the elasticities of net return with respect to N application between the high and low groups were greater than the ratio of the nitrate loss elasticities. Evidence indicates that the ratios of N productivity between high and low yielding soils are well below unity. Thus, reductions in N application rates below current recommended levels lead to smaller reductions in net return on the higher yielding soils than on the lower yielding ones. By targeting soils in the highest productivity group, one can focus policies to reduce N application on those areas where the largest reduction in nitrate loss can be achieved while at the same time minimizing the necessary reductions in output and farm income.
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