Prospects for Reducing Environmental Risk at the Watershed Level
from Pesticide Loss from Farm Fields Using Alternative Management Practices

Poster Presentation at the 53rd Annual SWCS Conference

San Diego, California, July 5-9, 1998

Joe Bagdon, Natural Resources Conservation Service, Amherst, Massachusetts

Steve Plotkin, Natural Resources Conservation Service, Amherst, Massachusetts

Eric Hesketh, Natural Resources Conservation Service, Amherst, Massachusetts

Robert L. Kellogg, Natural Resources Conservation Service, Washington, D.C.

Susan Wallace, consultant for the Natural Resources Conservation Service, Washington, D.C.

Project Objective

The objective of this study is to demonstrate the extent to which environmental risk from pesticides can be reduced within watersheds with more extensive adoption of environmentally beneficial farming practices.

• A simulation of pesticide loss from farm fields was conducted for 36 watersheds comprising three large river basins--the Iowa-Cedar River Basin, the Lower Illinois River Basin, and the White River Basin in Indiana.
• Baseline environmental risk was estimated for each watershed using farmer survey data on pesticide use and farming practices.
• Alternative pesticide management practices were simulated to show the potential for reducing risk on a watershed basis.

Background

Federal policies rely primarily on voluntary approaches by farmers and ranchers to curb externalities of agricultural production. Research has shown that the loss of agricultural chemicals from farm fields can be substantially reduced by using farm management practices tailored to: specific soils, local climatic conditions, the nature and extent of pest problems, and crops grown. Many believe that if these farming systems and practices were used more widely, significant improvements in water quality would result. Government programs are designed to provide technical assistance and cost sharing to encourage the voluntary adoption of these practices in areas that have potential for water quality impacts.

This study provides insight on how much water quality improvement might be attained by wider adoption of environmentally beneficial pesticide management practices.

Approach

• The National Resources Inventory (NRI) was used as a modeling framework, treating each NRI sample point as a "representative field." The statistical weight for each sample point is a measure of the number of acres associated with each "representative field."
• NAPRA (National Agricultural Pesticide Risk Analysis), which incorporates the GLEAMS process model, was used to estimate pesticide leaching and runoff loss at each NRI sample point. Simulations were conducted for corn and soybeans, which represent 62 percent of the nonfederal land use in the 36 watersheds.
• Data on planting date, tillage type, cultivation, and pesticide use (methods of application, application rate, and timing), and crop rotation were obtained from farmer surveys for 1,935 NRI sample points. All chemicals (total of 64) reported in the surveys were included in the simulation. Survey data were for 1991 for the White River basin and 1992 for the Iowa-Cedar River basin and the Lower Illinois River basin.
• Soils characteristics needed to run GLEAMS were either taken from the NRI or derived from soils data at NRI sample points.
• Climate data were taken from representative weather stations. Simulations were conducted for 50 years of daily weather data to capture annual variation in pesticide loss owing to variations in temperature and rainfall amounts and timing.
• Annual concentrations in leachate leaving the bottom of the root zone and in runoff (dissolved fraction) at the edge of the field were calculated for each chemical at each NRI sample point. Annual concentrations were determined as the ratio of the total annual mass loss of each pesticide divided by the corresponding annual volume of water percolating to the bottom of the root zone or running off the edge of the field.

Measuring Risk Using Threshold Exceedence Units (TEUs)

Aggregate environmental risk scores were calculated for each of the 36 watersheds.

• The concentration of each chemical leaving the field was compared to "safe" thresholds for human and fish chronic exposure. Health Advisories (HAs) and Maximum Contaminant Levels (MCLs) were used as "safe" thresholds for humans for pesticides that have been assigned drinking water standards by EPA. For other pesticides, "safe" thresholds were estimated from EPA Reference Dose values and cancer slope data. Maximum Acceptable Toxicant Concentrations (MATCs) were used as "safe" thresholds for fish, which were calculated using toxicity data published by EPA. When data for more than one fish species were available, the "safe" threshold for the most sensitive species was used.
• The extent to which the concentration exceeded the threshold was used as a measure of risk for each pesticide. First, the concentration-threshold ratio minus 1 was calculated for each of the 50 years of the simulation. Negative values were discarded on the assumption that there was no risk associated with concentrations below the threshold. The annual average of these values was calculated as the measure of risk for each pesticide.
• Risk at a sample point was estimated by aggregating the risk per chemical over all chemicals used at a sample point.
• An aggregate risk measure for the watershed--Threshold Exceedence Units (TEUs) per watershed--was calculated by multiplying the risk measure at each sample point by the number of acres represented by the sample point, and then summing over the sample points in the watershed.

TEUs are similar in concept to the acre-feet volumetric measure, since they are a multiple of acres times a measure of magnitude at a point. They are used here only to measure relative risk from one watershed to another; the higher the TEU score, the higher the risk.

There are approximately 21.5 million acres of corn and soybeans in the three study areas, with an average of 0.6 million acres per watershed. If at each "representative field," the per-sample-point risk measure was 1, total TEUs per watershed would be about 0.6 million. (A per-sample-point risk measure of 1 would occur if the concentration equaled the threshold for one chemical for each of the 50 years.)

Simulating Alternative Management Practices

A wide variety of economically feasible alternatives are available for farmers to use to reduce pesticide loss from farm fields. For example, potential alternative practices addressing herbicide use include:

• Banding at a 15-inch band with 30-inch row spacing allowing about a 50% reduction of herbicide use.
• Banding at a 10-inch band with 30-inch row spacing allowing about a 67% reduction of herbicide use.
• Half-rate application with timely row cultivation.
• Scouting and applying spot treatment only where needed.
• Buffer strips and/or conservation tillage (e.g., no till, mulch till and ridge till)
• Foliar applications, soil incorporation, or soil injection.

Potential alternative practices addressing insecticide use include:

• Application of insecticides as needed based on scouting.
• Spot treatment.
• Directed sprays over rows.
• Spraying in ditches, fence lines and waterways (where insects such as grasshoppers hatch) to eliminate need to spray in fields.
• Insect attracting bates (e. g., cucumber juice) mixed with pesticides that allows reduced use.
• Use of economic thresholds for determining application rates.
• Insect resistant crops.
• Integrated Pest Management (IPM) practices.

Although most of these alternatives can be simulated using NAPRA, it is not practical to do so without more information about specific pest problems than was provided by the farmer surveys. Instead, generic alternative management strategies were simulated as proxies for pesticide use reductions that could be achieved using combinations of the above practices. Three generic alternative management strategies were simulated:

1. A 50% reduction in application rates by simulating banding. Application rates were not changed for survey sample fields already using banding or spot treatments.
2. Substitution of reduced-rate Carbaryl for other corn insecticides. Carbaryl is less toxic than most insecticides to fish and humans.
3. Substitution of mulch tillage for survey sample points where conventional tillage was used. This applied to about 29% of the sample points.

Caveats

• TEUs are not a measure of absolute risk. TEUs are derived from loss estimates at the edge of the field and the bottom of the root zone. Dilution from noncropland runoff and leaching as well as degradation after leaving the field would be expected to reduce concentrations actually found in wells or in rivers and streams. Rather, TEUs represent a relative measure of risk for estimating percent reductions that could be attained by changes in management practices.
• Concentrations are calculated based on annual pesticide loss and annual water movement from the field. Actual concentrations leaving a field would be determined by specific rainfall events, and can be higher or lower than the annual average.

Summary of Findings

Simulation of the adoption of environmentally beneficial farming practices demonstrates that substantial reductions in environmental risk are possible. For the 36 watersheds combined, simulation of alternative management practices reduced environmental risk as follows:

Results by watershed are shown graphically in Maps 1-20, and numerically in four tables in the Appendix.

Using NAPRA for Watershed Planning

NAPRA is an automated analytical tool for evaluating environmental risk of pesticide loss from farm fields. NAPRA utilizes the USDA/ARS environmental fate computer model GLEAMS to simulate pesticide loss in runoff and leachate. Concentrations of pesticides leaving the field are related to thresholds based on water quality standards and toxicities to provide a measure of environmental risk.

The NAPRA process for evaluating the need for technical assistance within a watershed has 3 basic steps:

1. Identify the areas within a watershed that have the highest risk because of the interactions of soil characteristics, landscape characteristics, climate, and present pesticide use and farm management practices.

2. Identify the kinds of alternative management practices that can reduce environmental risk in the highest risk areas.

3. Simulate the extent to which environmentally beneficial management practices need to be adopted in the highest risk areas to meet a specific goal of risk reduction within a watershed.

Water quality goals for a watershed will be determined by state and local governments. To achieve these water quality goals, the relatively simple field-by-field approach currently being implemented by NRCS must be expanded to assess the effects of alternative practices on a watershed basis. NAPRA can be used with the Natural Resources Inventory (NRI) or other land use and soils data to identify areas within a watershed that need special emphasis pest management planning. Field office staff in these areas can then consult with producers and crop consultants to ascertain existing practices, and to promulgate economically feasible alternatives. NAPRA can be used again to test the alternatives to determine if they are adequate to meet water quality goals for the watershed. Using NAPRA to target technical assistance to high risk areas within high risk watersheds is a practical way to substantially improve water quality with limited resources.

The ultimate goal is to help farmers choose pesticide management alternatives that reduce hazardous pesticide losses in environmentally sensitive areas. Adoption of practices such as reductions in pesticide use, improved efficacy of pesticide applications through integrated pest management, matching pesticide and management practice selection to site conditions, and the use of pesticides that are less toxic to the environment will be necessary. Using models such as NAPRA to estimate the environmental benefits of these practices can help agricultural producers make more informed decisions that meet the environmental goals of conservation planning.

Maps

Appendix: Results by Hydrologic Unit