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United States Department of Agriculture

Agricultural Research Service

Research Project: Strategic Investigations to Improve Water Quality and Ecosystem Sustainability in Agricultural Landscapes

Location: Water Quality and Ecology Research

Project Number: 6060-13660-008-00-D
Project Type: In-House Appropriated

Start Date: Jan 26, 2017
End Date: Jan 25, 2022

Objective:
1. Assess and quantify ecological processes that influence water resources in agricultural ecosystems. 1a. Identify and quantify environmental factors that drive processes that are related to retention or removal of agricultural contaminants. 1b. Examine relationships between physical, chemical, and biological factors and ecological responses impacted by agriculture in the Lower Mississippi River Basin. 2. Assess and quantify the benefits of water resource management practices to enhance agricultural ecosystems. 2a. Quantify the long-term effects of conservation practices on aquatic and terrestrial resources in the Lower Mississippi River Basin. 2b. Assess the benefits and risks of management strategies and practices on soil and water resources at multiple scales. 3. Develop a watershed-scale integrated assessment of ecosystem services in agricultural landscapes of the Lower Mississippi River Basin. 3a. Develop technologies and tools to assess water and conservation management strategies in agricultural watersheds. 3b. Evaluate how ecosystem services derived from conservation practices improve water quality and ecology in agricultural watersheds. 4. As part of the LTAR network, and in concert with similar long-term, land-based research infrastructure in the Mid-South region, use the Lower Mississippi River Basin LTAR site to improve the observational capabilities and data accessibility of the LTAR network and support research to sustain or enhance agricultural production and environmental quality in agroecosystems characteristic of the Mid-South region. Research and data collection are planned and implemented based on the LTAR site application and in accordance with the responsibilities outlined in the LTAR Shared Research Strategy, a living document that serves as a roadmap for LTAR implementation. Participation in the LTAR network includes research and data management in support of the ARS GRACEnet and/or Livestock GRACEnet projects. 4a. Develop the Lower Mississippi River Basin LTAR location addressing issues of long-term agroecosystem sustainability specific to the region, participating in the Shared Research Strategy, and contributing to network-wide monitoring and experimentation goals. 4b. Enhance the Lower Mississippi River Basin CEAP watershed longterm data sets and integrate with other long-term data sets in the Lower Mississippi River Basin to address agroecosystem sustainability at the basin scale.

Approach:
Many experiments described in the following involve collection and analysis of water quality samples from field sites within the Lower Mississippi River Basin (LMRB). Data acquisition (sample collection, preservation, handling, analysis, quality control), except where otherwise noted, follows standard procedures (APHA, 2005). Base flow samples are collected manually, while storm event or runoff samples are collected using automated pumping samplers (ISCO GLS Compact Composite Samplers) activated by acoustic Doppler water level and area velocity water flow sensors (ISCO 2100). All samples are placed on ice for transport to the laboratory for analysis and held in cold storage (4o C). Storm samples are retrieved within 24 h of collection. All water samples are analyzed for total and dissolved solids (drying at 105o C), total P and total Kjeldahl N (block digestion and flow injection analysis using a Lachat QuikChem® 8500 Series 2 Flow Injection Analysis System). Additional analyses conducted for certain experiments include hardness (EDTA titrimetric method) alkalinity (titration method), turbidity (calibrated Hach electronic turbidimeter); NH4-N, NO3-N, NO2-N, and soluble (filterable) P (all with the Lachat system), and chlorophyll a (pigment extraction with spectrophotometric determination).

Last Modified: 05/22/2017
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