Groundwater Modeling
![Columbia Northern Plains Superfund Research Program Project 1](https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_200/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=mnRRnK3n 200w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_260/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=kK3T0MMF 260w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_320/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=7XUQmaXn 320w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_400/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=f87gm1f8 400w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_520/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=f1OjBkgO 520w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_640/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=o19DVN6H 640w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_1600/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=5vvuWDMW 782w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_800/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=4kuERY41 800w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_1040/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=5NLM6Yoi 1040w, https://www.publichealth.columbia.edu/sites/default/files/styles/cola_media_1280/public/media/images/2023-03/columbia_superfund_project_1.jpg?itok=1ieDMRNS 1280w)
High-resolution Models of Groundwater Metal Exposure
There is a lack of groundwater data in Northern Plains Native American tribal communities despite groundwater being the most likely source of exposure contributing to high urinary arsenic and uranium levels in these communities. Project 1 will merge new measurements of drinking water quality with existing spatial datasets to develop process-based models that predict contaminant concentrations at the household scale across Northern Plains tribal sites. The results, together with evaluations of temporal changes in drinking water concentrations from prior policy interventions and development of drinking water exposure profiles for the study cohort, will enable the development and establishment of effective interventions to reduce these potentially hazardous exposures to contaminated drinking water in the Northern Plains and beyond.