Watershed Scale Project in East Tennessee’s Oostanaula Creek

F.R. Walker, C.D. Clark, J. DeBruyn, M. Essington, S. Hawkins, D.M. Lambert, A. Layton, A. Ludwig, J. Schwartz and L.-B. Reynolds

University of Tennessee, Knoxville

Problem and Project Goal• The overall objective of our research efforts

in the Watershed have been to use the best available science to identify sources of water quality degrading pollutants in the Watershed and to encourage agricultural producers and other stakeholders to adopt cost-effective BMPs to reduce the pollutant loading.

• Objective A. Develop a watershed-scale sediment budget that identifies dominant sources of fine sediment to Oostanaula

• Objective B. Conduct an economic cost-benefit analysis of sediment source-dependent BMPs specific to the Oostanaula Creek watershed

• Objective C. Assess the behavior response of farmer’s willingness to implement sediment BMPs

• Objectives D and E. Conduct comprehensive watershed-wide education program to inform farmers, youth and adult residents and demonstrate that BMPs can simultaneously improve water quality and increase agricultural productivity

Study Region

Figure 1. Cattle path sediment study and heavy-use cattle traffic lane (Objective A 3)

Figure 2. Conceptual Model of the Sediment Fingerprinting Technique (Objective A4)

Research Objective A. Develop a watershed-scale sediment budget using a coupled sediment fingerprinting and source modeling approachA1. Characterization of microbial communities in bank sediments and pasture soils• Taxonomic identification of potential

diagnostic groups of bacteria (>2 % total sequences) for sediment, cattle manure and poultry litter

Figure 3. Principal component analyses of manures and sediments (a), microbial community structures (b) and different sources of potential sediment (c)• A total 7,565,516 Illumina sequencing reads,

comprised of 72,980 OTUs, were generated from 30 samples of sediment source and suspended and deposited creek sediment. Principal component analysis of the metagenomic data indicated that sediment –microbial source tracking can differentiate the consortium of bacteria in creekwater sediment and parent materials. Cropland soil bacterial communities were most similar to creek sediment bacterial communities.

A2. Assess microbial communities in water samples• Water samples collected from 9 sites every

other month • Analyzed for E.coli and turbidity. Total

Bacteroides and bovine-associate Bacteriodesstill to be analyzed

• E. coli concentrations in 2014 are similar to those observed in 2013 and reduced from the concentrations observed in 2011 particularly at site 9. The decrease in E. coli in 2013 was attributed to closing of a dairy at that location

A3. Develop watershed sediment budget• Sediment source data for gully or edge of field,

cattle/dairy cow tracks to waterways, and dirt roads were collected

Figure 4. Sediment vs Storm intensity

• Cattle trails contribute to sediments loads, but were not correlated to storm intensity or total rainfall

Acknowledgements: This project was supported by Agriculture and Food Research Initiative Competitive Award No. #2012-51130-20246 from the USDA National Institute of Food and Agriculture. Contact: Forbes Walker, frwalker@utk.edu, (865) 974-6402.

A4. Conduct watershed sediment chemical fingerprinting• 70 samples were selected throughout the

watershed• Field samples were analyzed using ICP-OES for

29 elements (Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cu, Fe, Hf, K, La, Li, Mg, Mn, Mo, Nd, Ni, P, Pb, Rb, S, Se, Sr, Ti, V, Zn, Zr)

• Discriminant function analysis (DFA) identified 5 elements for source group discrimination, hierarchical cluster analysis (HCA) the number of groups and canonical discriminate function analysis (CDA) was used to define group membership. But clusters based on the CDA did not correspond to the four sediment source groups. Sediment sources could not be differentiated by their measured geochemical properties due to the similarity of the source groups is attributed to the geologically homogeneity of the watershed.

Objectives B and C. Conduct an economic cost-benefit analysis of sediment source-dependent BMPs and assess farmer’s willingness to implement sediment BMPs• Mail survey of 5,150 farmland owners in

McMinn, Bradley, and Monroe Counties on willingness to adopt four best management practices (BMPs) - pasture improvement showed the greatest level of adoption interest

• Younger, more educated producers with higher income levels were more willing to adopt one or more of the BMPs

• Cost-share incentives did not play a substantial role in explaining adoption

Objectives D and E. Outreach and Education• 1,000s of contacts with stakeholders• BMP implementation – cattle exclusion fences,

alternative water systems, pasture renovation, cattle crossings etc.

• Publications, presentations, talks to >2,000 kids at farm city days, festivals (Tennessee Wetlands Festival), volunteer days (live Staking Volunteer Day with 30 volunteers staked approximately 300 ft of streambank with over 500 live stakes)

Potential Impacts and Expected Outcomes

• Identification of sources of sediment in Oostanaula and cost-effective BMPs to improve water quality;

• Implementation of agricultural and urban BMPs: several 100 acres of pastures were renovated, several miles of cattle exclusion fencing, heavy use cattle lanes, and cattle waterers were installed during this project

• It is anticipated that significant reaches of Oostanaula creek will be “de-posted” (a prelude to de-listing from 303 d list) in mid-2015

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