Location: Hydrology and Remote Sensing Laboratory
Project Number: 8042-13610-030-038-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 15, 2018
End Date: Aug 14, 2023
Objective:
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. Therefore, 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 then be used to improve existing environmental fate models.
Approach:
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, personal care products from applied biosolids, particulate matter, and volatile organic compounds (VOCs). 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 producer and other stakeholder groups.
