Sources of runoff pollution may seem clear as mud downstream, but two researchers at UC Davis have developed a model to sleuth them out cost-effectively. The research of Richard Howitt, a professor of agricultural and resource economics, and Jonathan Kaplan, a doctoral student, was presented last month at the annual meeting of the American Agricultural Economics Association. Just as surveillance specialists can construct a useful image from a blurred original, the model can use limited measurements of sediment and water cloudiness downstream to identify the dirtiest of several sources of runoff pollution upstream. In a computer simulation, the researchers tracked rainstorms at three sites upstream along with changes in sediment and turbidity downstream. The observations were used to update pollution estimates, and, over time, the pattern of pollution emerged. "This model holds promise," says Howitt, "not only for identifying the most polluting sources but also for doing that economically. As a result, more money can be channeled to clean up the worst sites." In the next phase of their research, Howitt and Kaplan will apply their model to water pollution problems in California's Redwood National Park. Media contacts: Richard Howitt, Agricultural and Resource Economics, (530) 752-1521, ralph@primal.ucdavis.edu; Julia Ann Easley, News Service, (530) 752-8248, jaeasley@ucdavis.edu.