The expansion of urban areas is a threat to wildlife because it fragments habitat and reduces the access to resources. Consequently, there is a need to improve the quality of urban habitats by increasing connectivity between habitats and resources. For volant species like bats, birds, and flying invertebrates, linear features such as tree-lines and/or connected canopies can create corridors that allow these wildlife to move along. In an urban environment, the structure of the urban forest (essentially all the trees in an urban area) can provide connectivity, if appropriate, thereby increasing access to resources and landscape permeability. Thus, in this study we used behavioral observation and acoustics surveys to monitor the commuting activity of bats in Fort Worth, Texas along 15 potential commuting routes. At each route, we measured tree height, percent canopy cover, gap distance, number of gaps, and rugosity or ruggedness of the canopy edge to identify what tree canopy features aided bat movement. Using GLM, we found that routes surrounded with more linear canopy cover and less gap distance resulted in more bats commuting. Moreover, we found that an increase in rugosity negatively influenced route use, as undulating tree canopies increased obstacles that created an inefficient commuting route (i.e., straight lines save energy). Our study demonstrates that the urban environment can be managed to increase connectivity and we provide recommendations on how to better manage the urban forest to increase commuting corridors for bats in this landscape.

Currently over 1,400 households use the Roubidoux Aquifer in Northeastern Oklahoma as their main source of drinking water. Additionally, the total water demand is projected to increase 56% from 2010 to 2060. This increase in water demand is concerning due to the Boone and Roubidoux aquifers being highly susceptible to surface contamination, containing elements such as lead and zinc, from the Tar Creek Superfund site located (TCSS) in Picher, OK. This study seeks to determine, using spatial analysis tools in GIS, the contamination susceptibility of the Boone and Roubidoux aquifer recharge zones as a result of direct surface contaminants and processes that facilitate their propagation.

Flood is a major threat to many communities worldwide, despite many areas lacking flood hazard mapping due to data scarcity. Under such a scenario, remote sensing and GIS-based approaches could be a promising solution for assessing and characterizing flood hazard risk. Therefore, the objectives of this research project are to develop a flood hazard risk map for Rowlett Creek Watershed using remote sensing data and GIS (Geographic Information Systems) techniques to identify and evaluate flood risk areas over the study site. The research will involve development of complied flood hazard index (FHI) using GIS software based on flood causative factors such as slope, flow accumulation, drainage network density, distance from drainage channel, geology, land use/cover, soil moisture and rainfall intensity. Filed data of geology will be obtained from SSURGO and other data will be extracted from remote sensing product such as SRTM, NLCD, CROPCASMA and PERSIAN. The expected outcome of the research is the development of flood hazard risk thematic map and further verify it with the inundation area of a historical flood events in the study area, which will help to purpose proper mitigation and management strategies in flood-prone area. This research looks over a remote sensing and GIS-based approach for characterizing flood hazard risk, which will provide valuable information for policymakers, disaster management agencies, and other stakeholders working towards reducing the impact of floods even in data-scarce areas.

Water represents one of the required resources for wildlife to live and thrive in an area. Due to urbanization, we have seen an increase in the transformation of natural water sources (i.e. lakes, streams, and rivers) to semi-natural (i.e. retention ponds, reservoirs, and drainage ditches), for which we create for the urban infrastructure and for animals. The objective of the following study was to assess whether water quality influences the direct use of water sources by terrestrial wildlife in an urban environment utilizing bats as our indicator species. We, therefore, hypothesize that water sources with higher water quality will have an abundant and diverse community of bats using them (i.e., foraging and drinking), while lower quality water sources will have little to no bat activity and lower species diversity. We conducted this study using thermal cameras and acoustic monitoring to determine whether water quality has discernible influences for water resource use by bats at water sources across six urban parks and greenspaces in Fort Worth, Texas. We observed increased bat activity at water sources that were listed as areas with higher water quality standards with very slow moving water, and little activity in areas that have been known to have lower water quality. Understanding how the water quality of urban sources impacts bats, may not only be used as an indicator of water availability for other wildlife species in urban areas, but also provide insights into the environmental health of local parks and surrounding neighborhoods.

Sinkhole hazards pose a major threat to key infrastructure and human lives in Taylor and Jones counties in West Central Texas. These counties are underlain by soluble evaporite and carbonate rocks. In this study, a data fusion approach was adopted in which multi-source datasets and techniques were combined to detect and map the spatial distribution of sinkholes, quantify their displacement rates, and identify the processes and factors controlling their occurrence. Preliminary results indicate: (a) there is a spatial correspondence between depressions (area: 625 m2 - 2500 m2) identified using Light Detection and Ranging (LIDAR) datasets and previously- mapped sinkholes; (b) deformation rates over the mapped depressions derived using Persistent Scatterer Interferometry technique applied on 53 level-1 Sentinel-1 images (2016 – 2021) and calibrated using long-term (2006 – 2021) GNSS data indicate an average and peak subsidence rates of -6 mm/yr and +5 mm/yr, respectively; (c) clusters of high subsidence rates were noted over areas underlain by evaporites belonging to the Clear Fork Group; (d) efforts to validate the accuracy of the sinkhole detection techniques are currently underway using 2D Electrical Resistivity Tomography (ERT) surveys carried out on the identified subsiding depressions. In addition, groundwater level and discharge time series and other relevant datasets are being integrated to assess the processes and factors that induce the formation of these features. Results of this study could be used to develop an early warning system to implement mitigation strategies to curtail the impacts of the sinkhole hazards in Texas and other parts of the globe.