Date of Award
2025-12-01
Degree Name
Master of Science
Department
Geological Sciences
Advisor(s)
Mark A. Engle
Abstract
Groundwater salinization is increasingly troublesome in aquifers in and around El Paso, Texas, where concern for available water resources has grown due to frequent droughts and increasing population. Both groundwater and surface water have experienced an increase in total dissolved solids (TDS), a trend that can pose future health and economic problems for residents who primarily rely on groundwater. To address this issue, this research focuses on the Hueco Bolson Aquifer and the Rio Grande Alluvial Aquifer within the Lower Valley area of El Paso, Texas, utilizing a multi-analysis approach to evaluate and determine solute sources and their possible end-members in groundwater. The first approach employs machine learning non-negative matrix factorization (NMF) source apportionment using major and minor ion data from pre-existing public geochemical datasets and this study’s new data. Recognizing that this approach can have difficulty in separating chemically similar sources, our second approach applies geochemical and isotopic tools (d11B, d2H, d18OH2O, d18OSO4, d34SSO4, 87Sr/86Sr, and 234U/238U) on collected samples to refine the NMF-derived end-member interpretations. From these methods, this study identified four dominant processes influencing groundwater TDS; 1) freshwater input from Rio Grande recharge, 2) evaporation-influenced high-TDS water with chemical weathering/agricultural inputs, 3) carbonate dissolution, and 4) surface Cl Na salt mobilization and/or halite dissolution. These findings clarify the effects of agricultural practices, groundwater-surface water interactions, and contaminant transport that will help guide future water management strategies. Such strategies could include over-pumping prevention to decrease vertical flow of deep, high saline water, and the use of flood irrigation alternatives, such as drip irrigation, that could prevent water-logging, reduce evaporation, and decrease irrigation return flow.
Language
en
Provenance
Received from ProQuest
Copyright Date
2025-12
File Size
101 p.
File Format
application/pdf
Rights Holder
Gloria A. Ortiz Gamboa
Recommended Citation
Ortiz Gamboa, Gloria A., "A Combined Multi-Isotope And Machine Learning Approach To Determine Groundwater Salinity And Solute Sources, Lower Valley Area, El Paso County, Texas" (2025). Open Access Theses & Dissertations. 4579.
https://scholarworks.utep.edu/open_etd/4579