Coastal wetlands are critical ecosystems located at the dynamic interface between terrestrial and marine environments, shaped by interactions among sediment transport and deposition, geomorphology, hydrodynamics, and biogeochemical processes. They provide essential ecosystem services, including protection against storm surge flooding and attenuation of cyclone-induced wind and wave energy. However, coastal freshwater wetlands are increasingly threatened by both natural and anthropogenic stressors, particularly sea level rise and land subsidence. Subsidence, together with saltwater intrusion largely driven by unsustainable groundwater extraction, contributes to soil salinization and a marked decline in the spatial extent of freshwater wetlands, thereby reducing their ecosystem functions. These challenges are especially pronounced along the Texas Gulf Coast, where frequent cyclone events result in significant environmental and socioeconomic impacts. This study adopts an integrated framework combining deep learning-based GeoAI approaches applied to remote sensing data, , and field-based geophysical methods to quantify spatiotemporal wetland dynamics, evaluate their driving factors, and assess implications for coastal hazard mitigation capacity.

The Dockum Group is of palaeontologic and sedimentary significance due to the fossils and preserved sedimentary structures. The units contain a vast variety of Late Triassic vertebrates ranging from aquatic and amphibian to early mammals and dinosaurs, and in addition the Dockum Group contains preserved upper-flow-regime structures. Early result from initial samples collected from an outcrop of a preserved lake have yielded potential bone fragments and teeth. The opportunity to study how upper flow regimes and fossil assemblages are related to preservation makes the Dockum group a unique study area.

Our project will focus on the evaluation of how the introduction of invasive fire ant species has affected horned lizard populations. The fire ant species is not native to the greater Texas area and, when introduced, preyed on the Texas horned lizard’s primary food source, the harvester ant. This has greatly reduced the lizard’s range, as it consumes few other insects. Its status as the university mascot further highlights its vulnerability to the TCU community. This study examines the impact of invasive fire ants on horned lizard populations in Texas. We will accomplish this through two approaches in the ArcGIS environment: first, by comparing maps of the lizard’s historical and current ranges, and second, by analyzing the temporal distribution of fire ant populations to determine whether a correlation exists with changes in the lizard’s range.

Coastal aquifers around the Galveston Bay System, located along the Texas Gulf Coast, have been experiencing saltwater contamination for the past few decades. This is driven by extensive groundwater use, land subsidence as a result of groundwater pumping, and rising sea levels in both the short term (through storm surge from cyclones) and long-term (relative sea level rise). This study leverages multitemporal groundwater quality data from wells located proximal to the coast and further inland to assess the spatial distribution and propagation of key saltwater contamination indicators (TDS, Chloride, etc.). This is accomplished through cluster mapping to identify contaminant hotspots and their progression over time, as well as by assessing the extent of contamination through evaluating the relationship between distance from the coast and inland contamination. The key objective is to provide insights of the modes of aquifer contamination, identify susceptible areas, and determine key drivers that may contribute to this accelerating contamination.

The Fort Worth metropolitan area faces increasing roadway congestion, automobile dependency, and growing accessibility challenges for households with limited vehicle and physical access. Although Tarrant County contains several rail assets, much of the regions' transit network remains limited in coverage and connectivity compared to neighboring systems in Dallas. Rather than proposing new infrastructure, this study aims to evaluate the existing rail corridors within Tarrant County to identify where improvements could generate the greatest mobility, equity, and connectivity benefits.

Using ArcGIS Pro, a weighted multi-criteria analysis is applied to three existing corridors where freight lines are already present: a south-to-north line dubbed the “Green Line”, with termini in Burleson and Keller, a west-to-east line dubbed the “Blue Line”, with termini in Benbrook and Arlington, and a southwest-to-northeast line dubbed the “Purple Line”, with termini in Crowley and Euless/Grapevine. Each corridor meets at Fort Worth T&P / Central stations and stops in significant population/economic centers. Buffers surrounding each corridor are analyzed to evaluate demographic demand, transportation efficiency, connectivity, and physical feasibility. Key variables include the percentage of households without vehicles, median income, senior and disability populations, highway congestion proximity, risk factors, and major destinations served.

By integrating demographic vulnerability indicators with transportation demand and physical constraints, this study identifies which existing retail corridors demonstrate greatest need and potential for targeted improvements. The results provide a GIS-based framework for prioritizing transit investments in automobile-dependent metropolitan regions and offer data-driven guidance for improving rail accessibility and connectivity across Tarrant County.