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(1) Research. (a) Refine the leaching and runoff risk models by (i) developing weightings for climate, soil/crop management, and additional pesticide and application variables (to be applied on a whole system basis unless field data are provided) and (ii) using mathematical functions or algorithms where possible to weight model inputs related to leaching, solution and adsorbed runoff to the input variables. (b) Model risk for the selected watersheds in Nebraska/Kansas, Missouri and Iowa. Validate the environmental output generated for selected watersheds by comparing model output with available water quality data for watersheds in Kansas, Missouri and Iowa. (c) Estimate behavioral (probability) models representing farmers in the high risk portions of the Nebraska/Kansas study area as identified in objectives (a) and (b). Using the probability models, generate personological typology maps (i.e. mapping personality characteristics to include motivation and how these are oriented, probabilities of adopting technologies that reduce pesticide movement) showing the behavioral features of the resident farm population in each high risk area. Data will be collected with a survey instrument and the farm locations will be georeferenced. <P>(2) Education. (a) Incorporate the principles of environmental risk modeling and behavioral analysis into existing undergraduate and graduate courses offered at the University of Nebraska-Lincoln and cooperating universities in the region. (b) Provide interdisciplinary education and training for graduate students. <P>(3) Extension/Outreach. (a) Use a survey tool to determine the practices and behaviors of producers in vulnerable areas, and their responsiveness to change, and devise a plan to educate these groups in a way that will result in adoption of appropriate conservation management practices. (b) Develop a software module for ESRI ArcView/Spatial Analyst 9.x that can be used by educators, consultants, and agency personnel to prepare the SSURGO and NHD data, run the risk models, and visualize the output. (c) Introduce and demonstrate environmental risk modeling at annual pesticide applicator education workshops and make the software available to educators, consultants, and agency personnel.
Non-Technical Summary: To protect water quality we need to better forecast environmental risks and guide conservation management decisions. Watershed vulnerability is determined by physical setting (soil, topography, and climate) and land management practices. If the most vulnerable areas can be determined, fields within those areas can be targeted for conservation management and mitigation of contamination. To implement effective conservation practices it is necessary to understand what motivates the behaviors of producers and land managers. A risk assessment model will be used to identify the most vulnerable areas within impaired watersheds in Nebraska/Kansas, Missouri, and Iowa. A behavioral assessment model will be used in selected areas upstream of Tuttle Creek, Kansas to predict the probability that producers and land managers will adopt the technologies and practices associated with TMDL recommendations, as well as the extent of adoption. Focus groups and a survey tool will be used to determine what motivates the behaviors of producers and land managers in choosing practices and technologies in these vulnerable areas. A statistical model will be used to predict their responsiveness to change and decision typologies will be mapped. The information gained in this project will be used to design policy, incentive structures, and educational programs leading to the adoption of conservation management practices that improve and protect water quality. <P> Approach: Initially we will (i) apply our risk assessment model in its current form to map vulnerability in selected Nebraska/Kansas, Missouri, and Iowa watersheds and validate the model with available watershed data, then (ii) improve the model by developing weightings for climate, land use, soil/crop management and pesticide variables using numerical gradations similar to those used in preliminary work for landscape and pesticide factors and (iii) reapply the model to those watersheds. Once the models have been validated and most vulnerable sites identified and prioritized, we will be able to specifically apply behavioral analysis and suitable mitigation plans to those areas. The behavioral analysis will be conducted in the Nebraska/Kansas watershed. Producers as stakeholders will be engaged through the use of focus groups in selected Nebraska/Kansas counties, with at least one such meeting prior to the survey being implemented in those counties, and then one more meeting after the analysis has been completed. The purpose of the first focus group involving 12-15 farmers will be to scope the problem of pesticide application and loss from their perspective. This focus group session will produce qualitative data on how producers see they are dealing with these problems, which will help in developing a survey instrument. The design of the kind of questions that will be asked, which probe deeply into farmer values and beliefs, draws heavily on standard approaches in behavioral economics and social psychology. This kind of questioning has been modified, consistent with the metaeconomics contention that farmers have dual interests, not only in profits but also in the environment, the shared community of interest. This approach gives specific insights into attitudes and community norms that need to change to achieve a change in behavior. After the risk models have been evaluated and revised as required, a user interface module will be developed using an image viewer adaptation of an existing decision support system. The module will be tested and evaluated by the principal investigators and cooperators. Additional watersheds will be selected for modeling through consultation with university scientists and their agency contacts at cooperating states within the north central region (initially Illinois, Indiana, Kansas, Michigan, Missouri, and Wisconsin). Cooperators, stakeholders and agency personnel will review the results and provide feedback, which will be used to make adjustments in the models. Environmental risk modeling will be incorporated into the syllabi of existing undergraduate and graduate courses. User software will be introduced to practitioners through established extension programs. Model output will be shared with the USDA, local natural resource districts, state agricultural and environmental agency personnel. Behavioral models will be integrated with the risk models in the sense that we will have a behavioral profile of producers in a particular area. In the context of this project, we will know the orientation of producers in a particular area toward practices that minimize runoff and sediment flows containing pesticides.