As part of a research collaboration with the Fendorf Lab at Stanford University, I investigated the relationship between redox conditions and arsenic contamination in water supply in the San Luis, Valley in Colorado.
This work was conducted as part of a larger goal to create a prediction algorithm that could determine the likelihood of As contamination in a given location using numerous variables. In my work, I considered % clay fines and measurement depth as proxies for redox conditions, known to play a significant role in As mobilization in groundwater.
I found a small but significant relationship between my variables of interest and As concentrations, contributing to the robustness of the resulting model.
I conducted data analysis through RStudio and ArcGIS Pro and presented this work at a poster session at the AGU conference 2023
American Geophysical Union (AGU) Poster:
Abstract: https://ui.adsabs.harvard.edu/abs/2023AGUFM.H41T2043S/abstract
