Project Number: 8070-13000-012-00-D
Project Type: Appropriated
Start Date: Apr 6, 2012
End Date: Apr 5, 2017
The overall objective of our research is to sustain agriculture and water resources in the northeastern US. Our basic research provides fundamental information on processes (chemical, physical, hydrologic), linking agricultural management with water resources. Our applied research advances nutrient management practices and strategies that balance production and agroecological services, helping agriculture to adapt to emerging water resource issues and, ultimately, promoting resilient agroecosystems that can respond to long-term challenges occurring at scales beyond the farm gate. Specific objectives are: (1) Describe and quantify processes controlling agriculturally related environmental contaminants (nutrients, trace metals, and sediments). (2) Adapt and develop management practices and strategies that farmers can use to reduce the environmental impacts of agriculturally derived contaminants. (3) Conduct watershed scale research to understand the long-term impacts of changing management and climate on water resources. (4) As part of the LTAR network, and in concert with similar long-term, land-based research infrastructure in Upper Chesapeake Bay region, use the UCB LTAR site to improve the observational capabilities and data accessibility of the LTAR network, to support research to sustain or enhance agricultural production and environmental quality in agroecosystems characteristic of the Upper Chesapeake Bay region, as per the LTAR site responsibilities and other information outlined in the 2012 USDA Long- LTAR Network Request for Information (RFI) to which the group successfully responded, and the LTAR Shared Research Strategy, a living document that serves as a roadmap for LTAR implementation. (5) Increase the resilience of U.S. agriculture to climate change and weather variability while developing strategies to mitigate greenhouse gas emissions. Support GRACEnet, LTAR and Climate Hub efforts to improve the profitability and environmental performance of crop and livestock systems. The following sub-objectives will apply: a) Apply experimental and monitoring information to assess the response of current and alternative farming systems to historical climate change. b) Evaluate the effect of alternative management strategies on the profitability and environmental impact of agriculture under a range of climate forecasts. c) Improve carbon sequestration and reduce greenhouse gas emissions from livestock, production facilities and land application of manure.
Research will span the four major physiographic provinces of the Chesapeake Bay watershed, relying upon core sites in the Atlantic Coastal Plain (Manokin watershed, MD), Appalachian Piedmont (Conewago watershed, PA), Appalachian Valley and Ridge (Mahantango Creek watershed, PA and Spring Creek watershed, PA), and Allegheny Plateau (Anderson Creek watershed, PA) (Figure 1). Research emphases will vary across these provinces, reflecting issues that are of current management or scientific relevance as well as constraints imposed by available resources (Figure 2). Our primary distinction is between the Atlantic Coastal Plain and upland physiographic regions, as hydrologic flow paths are dramatically different in these landscapes (subsurface flow is the dominant hydrologic pathway in the Atlantic Coastal Plain whereas overland and shallow lateral flows are the major pathways in the upland provinces). We have landowner contacts and research collaborators at all major (core) sites, and have a research infrastructure that enables routine measurement and chemical sampling of surface runoff, subsurface flow, and stream flow. When necessary, we move infrastructure from one location to another to provide a greater intensity of observations. We combine field observations with laboratory experiments in which greater control may be obtained over indirect variables. Our process-oriented research (Objective 1) involves observational and experimental studies, using parametric and nonparametric statistics to quantify temporal and spatial trends or to determine differences between management/land use, landscape units, and watershed components. Our applied research (Objectives 2 and 3) includes experimental studies, remote sensing and modeling. Experimentation involves a high degree of replication due to the inherent variability in processes impacting water quality. We have strong in-house statistical capability and, when necessary, consult with outside statisticians to ensure confidence in our findings.