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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Research Project #444769

Research Project: Measuring, Modeling, and Mitigating Pollutants in Agroecosystems and Surrounding Landscapes

Location: Hydrology and Remote Sensing Laboratory

Project Number: 8042-13610-030-080-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 1, 2023
End Date: Aug 31, 2026

The effectiveness of conservation practices and the ecosystem services they provide is a function of numerous environmental processes. However, the factors that influence these processes are often not well understood and are often estimated in non-mechanistic models. Studies will be conducted to determine the chemical and physical processes controlling the fate of agricultural pollutants in the environment by measuring their fundamental chemical properties, developing innovative sampling techniques, and carrying out long-term sampling campaigns. These results will be used to improve existing environmental fate and predictive models.

This project will build on existing cooperative research with the University of Maryland Department of Civil and Environmental Engineering. Short and long-term studies will be conducted to examine the fate and transport of agriculturally-related pollutants, including nutrients, agrochemicals and their degradation products, veterinary pharmaceuticals, and potential pollutants from applied biosolids. Tracers of urban pollution across the agricultural-urban interface and through the environmental compartments (air, water, soil, and biota) will also be considered. Field samples will be collected within the Chesapeake Bay watershed, however, additional watersheds in the Long-Term Agroecosystem Research (LTAR) and the Conservation Effects Assessment Project networks will be included to extend the breadth of these studies. To interpret results, laboratory experiments maybe needed to examine fundamental chemical and physical properties and to measure degradation rates and partition coefficients under environmentally-relevant conditions. New measurement strategies and techniques, such as passive samplers and sensor technologies that are more sensitive and efficient and less costly, will be developed and utilized in field studies. Data will be utilized in predictive modeling efforts and risk analysis. Emphasis will be placed on determination of ground water mean residence times using a novel water age-dating technique, use of GIS technologies to interpret results from a landscape perspective, and development of improved agricultural management practices to protect environmental quality. Results will be communicated to the scientific community, producers, regulators, resource managers, and to the public through presentations, manuscripts, web-based documents, social media, and presentations to producers and other stakeholder groups.