Discipline: Ecology Environmental and Earth Sciences
Malcolm Peoples - University of Arkansas at Pine Bluff
Agriculture has been criticized as the leading source of freshwater pollution via erosion and nutrient runoff. Excessive loading of this into aquatic systems can be harmful to aquatic organisms, humans, and the environment. Hence a number of Best Management Practices (BMPs) have been developed via research to alleviate this issue. To assess the effectiveness of these BMPs, there is a need for continuous monitoring of water quality matrices in-field or at edge of fields. A water quality analysis of runoff entails expensive procedures and is too time consuming to quantify. Identifying the relationships of these water quality parameters will provide a better understanding of how parameters influence other water quality metrics. While some of the matrices can be tedious and time consuming to assess, some are relatively faster to monitor. Hence this research focus was to assess possible correlation relationships between nutrient concentrations (more tedious measurements) and other water matrices (less tedious and faster measurements). To assess these relationships, water samples were collected from varying agricultural sites and were analyzed for nutrient concentrations, pH, hardness, alkalinity, turbidity, conductivity, total suspended solids, and suspended sediment concentration. Water samples were retrieved from field sites weekly from April 18, 2017 to June 19, 2018. The samples were analyzed for the specified nutrients (NH4+, NO2-, NO3-, and PO43-) using standard colorimetric methods. Overall, there was no strong correlations found among water matrices except between total suspended solids and turbidity (p<0.001; r=0.5) and salinity and hardness (p<0.001; r=0.661).
Funder Acknowledgement(s): Cooperative Agreement between United States Department of Agriculture, ARS Delta Water Management Research Unit and Arkansas State University Office of Diversity at Astate, Arkansas Bioscience Institute Bridging the Divide: A program to Broaden Participation in STEM Ph.D. NSF Grant #1348389
Faculty Advisor: Dr. Arlene Adviento-Borbe, Arlene.AdvientoBorbe@ars.usda.gov
Role: I traveled to various agricultural sites, collect water samples, test them for their water qualities, record the data onto a lab notebook and Excel, and analyze their correlations on Minitab.