The effect of weather variation on pesticide losses was estimated with the Erosion-Productivity Impact Calculator (EPIC) model. Weather variations had little effect on pesticide loss from a hypothetical site near Memphis, TN, but the effect was more dramatic and in the expected direction at Des Moines, IA. Atrazine losses at Des Moines were reduced by lowering relative humidity or rainfall intensity. Increasing the CO2 level from 300 to 660 ppm slightly increased atrazine losses. Results from these two sites are very limited and only serve to demonstrate modeling potential for addressing weather/pesticide problems. Further, more comprehensive studies are needed to better estimate pesticide loss sensitivity to weather variation.

A screening procedure to minimize adverse water quality impacts of pesticide application is presented that matches pesticide parameters to site-specific soil ratings. The pesticide parameters include a Relative Leaching Potential Index (RLPI), a Relative Runoff Potential Index (RRPI), the U.S. Environ. Prot. Agency (USEPA) lifetime health advisory level (HAL), and aquatic toxicity (LC50). Criteria used in developing soil ratings are described. Pesticide selection is accomplished by matching pesticide parameters values for the array of pesticides that control the pest of interest to soil ratings at the application site using selection criteria. A worksheet is presented to facilitate organization of information for the selection procedure and to serve as a record of the pesticide applicator's decision. The linking of an environmental fate model to a geographic information system (GIS) to create thematic maps of pesticide leaching potentials in terms of probability of exceeding the HAL in groundwater is described. A cost vs. groundwater hazard index frontier is described that suggests a method to assess the economic consequences of alternative pesticide selections.

In support of the registration and reregistration processes under FIFRA ‘88, numerical models are used to estimate the dissolved runoff and soil erosion loadings of pesticides to surface waters and the subsequent fate and transport of pesticides in the receiving waters. Uses for simulations include:

1. Helping to determine whether additional studies on the fate and distribution of a candidate chemical in the environment and/or ecological effects may be needed when full chemical characterization is incomplete.

2. Helping to more fully integrate data submissions of laboratory and field observations.

3. Estimating probable fate and distribution of an agrochemical after a severe runoff event.

4. Comparing alternative chemical application rates and methods for the same chemical/soil/crop/environmental combinations.

5. Comparing different soil/crop/environmental combinations representing different geographical areas with the same chemical.

6. Evaluating preliminary designs of proposed field studies.

7. Gaining insight into the environmental fate of modern chemicals that are applied at 1 to 2% of the rates of older chemicals when sampling designs and analytical methods are not available.

The Office of Pesticide Programs (OPP) commonly employs the SWRRB (45, 46) and PRZM (8, 9) models for runoff and EXAMS II (5), a fate and transport model, for surface waters. These three models are used in conjunction with appropriate databases for soils, chemical properties, and meteorological and other environmental parameters. Registrants are encouraged to clearly state assumptions, identify values for parameters by citation, report results of simulations with summary tables and graphics, and interpret their results in relation to current scientific disciplines.

The ARS Pesticide Properties Database (PPD) is a compendium of chemical and physical properties of a collection of widely used pesticides. At present, there are 92 compounds in the database and we have focused on 19 of the most important properties impacting on groundwater and atmospheric quality. The PPD relies upon experimentally determined data points. With the help of the National Agricultural Chemicals Association (NACA) we have been communicating directly with manufacturers to obtain the original experimental data with which they characterize pesticide properties and fulfill requirements for federal and state regulations. This provides the basis for the PPD which is augmented with data from the scientific literature. Features of the PPD are: 1. 19 parameters are provided for each pesticide. 2. References are given for all data. 3. When there are several values for a given property, all are cited. 4. All data have been verified and provide the latest, most reliable figures available.

Registrant use of computer simulation modeling is generally accepted by regulators in lieu of some experimental data for risk assessment, provided worst-case assumptions and extremely conservative criteria for negligible risk are used. These requirements taken together mean that only extreme cases escape the requirement for actual environmental data. This conservatism reflects the uncertainty in both exposure estimates by the models and in the hazard estimates from toxicologists. Until the credibility of estimated environmental concentrations given by models is improved by more experimental data and experience on the part of both registrants and regulators, the models will continue to be considered not-validated by many. There are four current developments that provide a compromise between the two impossible extremes of total model validation and total field measurement: (1) as models develop more process detail the parameters become more fundamental in nature and these are generally more amenable to independent estimation or measurement; (2) the reporting of probabilistic analyses and probable errors of results by modelers will enhance credibility; (3) the development of data sets for specific crop/site/pesticide/weather scenarios will allow users to modify those parts of the input they are concerned with while retaining confidence that parameters with which they are unfamiliar will have reasonable values; and (4) meso-scale and micro-scale physical simulation experiments can fill the gap between laboratory and field results. The most important need for enhancing model credibility is full access by the pesticide science community to all the information available, so that we may increase our understanding. Legal mechanisms should be considered for longer ownership of exclusive marketing rights of active ingredients, in exchange for complete public disclosure of the environmental fate and toxicology data submitted to regulatory agencies.

I, too, would like to add my welcome to each of you on behalf of the 32nd annual Weed Science Society of America meeting. I would especially like to recognize our special guest this morning, Dr. C. Everett Koop. I know each of you will find the Clarion Plaza facilities and the program to be excellent due to an outstanding effort by Joe Antognini and the Program Committee and Joan Dusky and the Local Arrangements Committee. We owe all of these folks a tremendous debt of gratitude for the success of this meeting.

A group of scientists from academia, government, and industry, along with ecologists, regulators, conservationists, and grower representatives have formed an International Organization for Resistant Pest Management (IOPRM) to review and delineate proactive and retroactive management strategies for specific cases of pesticide resistance. Within IOPRM, technical working groups were appointed to deal with each pest group. The Weed Resistance Management Working Group (WRMWG) is chaired by Drs. Jonathan Gressel and Leonard Saari, and will deal with the analysis and promoting of alternative control strategies for case studies where a high risk of herbicide resistant weeds exists. Based on our experience to date, crops such as wheat, corn, and soybeans and weeds such as kochia, annual ryegrass and blackgrass, will be used as models to develop optimum weed resistance management programs. The group is especially looking for herbicide and weed control data on negative-cross resistance, econometric models, novel management procedures, and quantitative data from weed scientists and other research and extension communities that could facilitate reaching optimal management decisions. All recommendations and experiences will be communicated through a worldwide network.

A select few of our present-day weeds are descended from much grander primeval forms. Field horsetail (Equisetum arvense L. ♯ EQUAR) and related species are “degenerate” herbaceous plants whose tree-sized ancestors dominated forests in the Carboniferous period about 300 million years ago. Indeed, early equisetums contributed significantly to the formation of coal beds (12).