106-1 Spatial and Temporal Visualization of Water Quality Data in a Three-Year Monitoring Project in the Lower Arkansas-Maumelle HUC-8 Watershed

Session: 37th Annual Undergraduate Research Exhibition Sponsored by Sigma Gamma Epsilon (Posters)

Presenting Author:

Authors:

Abstract:

The Lower Arkansas-Maumelle HUC-8 watershed serves nearly 500,000 people for drinking water, agriculture, and industry across 1,100 square miles in central Arkansas, including the state capitol, Little Rock. This three-year monitoring project establishes critical baseline water quality data across three contrasting subwatersheds. Each subwatershed represents different land use patterns and pollution pressures. The upper Maumelle River subwatershed occupies a more forested, less developed area but remains critically important as it feeds Lake Maumelle-the primary drinking water source for central Arkansas residents. Fourche Creek, an urban mid-basin subwatershed containing Little Rock, fails to meet Arkansas Water Quality Standards for dissolved oxygen, sediment/siltation, fecal coliform, copper, and zinc according to the Arkansas Division of Environmental Quality. Its urban location makes it vulnerable to further degradation from continued development. The lower Plum Bayou subwatershed has shared land use pressures in a more rural setting that contrasts significantly with both the upper and mid subwatersheds. 

University of Arkansas at Little Rock students conducted semimonthly field measurements and water sampling at 16 sites within the watershed. Field parameters included temperature, turbidity, pH, specific conductance, dissolved oxygen, and average flow velocity. The Arkansas Water Resources Center analyzed samples for total nitrogen, ammonia-N, nitrate+nitrite-N, total phosphorus, soluble reactive phosphorus, total dissolved solids, and total suspended solids. Quarterly analyses included biological oxygen demand, copper, E. coli, and total coliform. Alkalinity was measured on campus. Data visualization and analysis employed GIS software to create raster datasets for each parameter and sampling date, revealing temporal trends and spatial relationships. A web-based story map was developed for public outreach. Statistical analyses included Principal Component Analysis (PCA) and Analysis of Variance (ANOVA) to identify key drivers of water quality variation. Results will provide local policymakers and the public with clear visualizations of pollution sources and impacts across the watershed, enabling more targeted monitoring and remediation efforts. This baseline dataset helps support evidence-based decision making focused on protecting both urban and rural water resources in central Arkansas.

Geological Society of America Abstracts with Program. Vol. 57, No. 6, 2025

doi: 10.1130/abs/2025AM-11013

© Copyright 2025 The Geological Society of America (GSA), all rights reserved.