{"id":{"repo_id":"texas-state","oai_identifier":"oai:digital.library.txst.edu:10877/23611"},"canonical_url":"https://search.dev.ndltd.org/etd/texas-state/oai:digital.library.txst.edu:10877/23611","repository":{"repo_id":"texas-state","name":"Texas State University","base_url":"https://digital.library.txst.edu/server/oai/request"},"display":{"title":"Dynamic Sensing of a Dynamic System: Mobile Water Quality Monitoring at Spring Lake, San Marcos, Texas","abstract":"This study uses a boat-mounted continuous monitoring device to collect real-time water-quality data, providing insight into the patterns and drivers of variability in Spring Lake and comparable karst systems. From June 22, 2022, to June 11, 2023, a solar-powered continuous monitoring device mounted by Spring Lake staff on the stern of the 1953 glass-bottom tour boat automatically collected water-quality measurements every 15 seconds. Over the monitoring period, the device recorded more than 35,000 individual data points for total dissolved solids and temperature, providing high-resolution coverage of water-quality conditions in Spring Lake. I applied data-quality control procedures to remove incomplete or anomalous measurements and uploaded the cleaned dataset into a geographic information system to support detailed spatial mapping and analysis of water-quality patterns within the lake. I performed statistical analyses that show periods of low spring flow coincide with reduced total dissolved solids and slightly lower temperatures. I also identified greater variability in both measures during transitional months, highlighting the influence of shifting spring sources on water quality. Through spatial analysis, I documented clear gradients, with higher total dissolved solids in downstream areas and lower values in the upstream headwaters. I found that the temperature remains generally uniform but stays warmer and more stable in central areas and slightly cooler along the lake margins. These results demonstrate the sensitivity of Spring Lake to changes in spring flow and show how groundwater mixing processes shape the lake’s chemical and thermal conditions. The high-frequency dataset generated by the mobile monitoring device allowed me to identify these fine-scale spatial and temporal patterns, underscoring the value of real-time, boat-based sensing for improving water-quality monitoring in surface water systems.","abstract_html":"This study uses a boat-mounted continuous monitoring device to collect real-time water-quality data, providing insight into the patterns and drivers of variability in Spring Lake and comparable karst systems. From June 22, 2022, to June 11, 2023, a solar-powered continuous monitoring device mounted by Spring Lake staff on the stern of the 1953 glass-bottom tour boat automatically collected water-quality measurements every 15 seconds. Over the monitoring period, the device recorded more than 35,000 individual data points for total dissolved solids and temperature, providing high-resolution coverage of water-quality conditions in Spring Lake. I applied data-quality control procedures to remove incomplete or anomalous measurements and uploaded the cleaned dataset into a geographic information system to support detailed spatial mapping and analysis of water-quality patterns within the lake. I performed statistical analyses that show periods of low spring flow coincide with reduced total dissolved solids and slightly lower temperatures. I also identified greater variability in both measures during transitional months, highlighting the influence of shifting spring sources on water quality. Through spatial analysis, I documented clear gradients, with higher total dissolved solids in downstream areas and lower values in the upstream headwaters. I found that the temperature remains generally uniform but stays warmer and more stable in central areas and slightly cooler along the lake margins. These results demonstrate the sensitivity of Spring Lake to changes in spring flow and show how groundwater mixing processes shape the lake’s chemical and thermal conditions. The high-frequency dataset generated by the mobile monitoring device allowed me to identify these fine-scale spatial and temporal patterns, underscoring the value of real-time, boat-based sensing for improving water-quality monitoring in surface water systems.","abstract_has_math":false,"creators":["Willrich, Tiffany"],"institution":"Texas State University","degree_name":"Masters of Applied Geography","degree_level":"Masters","degree_discipline":"Natural Resources and Environmental Studies","degree_department":null,"school":null,"contributors":[],"advisors":["Mace, Robert E."],"committee_chairs":[],"committee_members":["Meitzen, Kimberly"],"year":2025,"date_issued":"2025-12","date_published":"2025-12","updated_at":"2026-07-27T21:22:45Z","subjects":["Spring Lake water quality","continuous water quality monitoring device","water quality"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10877/23611","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Mace, Robert E."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Meitzen, Kimberly"]},{"key":"dc:creator","label":"Author","values":["Willrich, Tiffany"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-01-14T18:00:08Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-12"]},{"key":"dc:type","label":"Dc Type","values":["Research Project"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Natural Resources and Environmental Studies"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Masters of Applied Geography"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Texas State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Spring Lake water quality","continuous water quality monitoring device","water quality"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10877/23611"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Applied Geography Directed Research"]},{"key":"dc:description.abstract","label":"Abstract","values":["This study uses a boat-mounted continuous monitoring device to collect real-time water-quality data, providing insight into the patterns and drivers of variability in Spring Lake and comparable karst systems. From June 22, 2022, to June 11, 2023, a solar-powered continuous monitoring device mounted by Spring Lake staff on the stern of the 1953 glass-bottom tour boat automatically collected water-quality measurements every 15 seconds. Over the monitoring period, the device recorded more than 35,000 individual data points for total dissolved solids and temperature, providing high-resolution coverage of water-quality conditions in Spring Lake. I applied data-quality control procedures to remove incomplete or anomalous measurements and uploaded the cleaned dataset into a geographic information system to support detailed spatial mapping and analysis of water-quality patterns within the lake. I performed statistical analyses that show periods of low spring flow coincide with reduced total dissolved solids and slightly lower temperatures. I also identified greater variability in both measures during transitional months, highlighting the influence of shifting spring sources on water quality. Through spatial analysis, I documented clear gradients, with higher total dissolved solids in downstream areas and lower values in the upstream headwaters. I found that the temperature remains generally uniform but stays warmer and more stable in central areas and slightly cooler along the lake margins. These results demonstrate the sensitivity of Spring Lake to changes in spring flow and show how groundwater mixing processes shape the lake’s chemical and thermal conditions. The high-frequency dataset generated by the mobile monitoring device allowed me to identify these fine-scale spatial and temporal patterns, underscoring the value of real-time, boat-based sensing for improving water-quality monitoring in surface water systems."]},{"key":"dc:format","label":"Dc Format","values":["Text"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["1 file (.pdf)"]},{"key":"dc:title","label":"Title","values":["Dynamic Sensing of a Dynamic System: Mobile Water Quality Monitoring at Spring Lake, San Marcos, Texas"]}]}],"canonical_facts":{"dc:contributor.advisor":["Mace, Robert E."],"dc:contributor.committeemember":["Meitzen, Kimberly"],"dc:creator":["Willrich, Tiffany"],"dc:date.accessioned":["2026-01-14T18:00:08Z"],"dc:date.issued":["2025-12"],"dc:description":["Applied Geography Directed Research"],"dc:description.abstract":["This study uses a boat-mounted continuous monitoring device to collect real-time water-quality data, providing insight into the patterns and drivers of variability in Spring Lake and comparable karst systems. From June 22, 2022, to June 11, 2023, a solar-powered continuous monitoring device mounted by Spring Lake staff on the stern of the 1953 glass-bottom tour boat automatically collected water-quality measurements every 15 seconds. Over the monitoring period, the device recorded more than 35,000 individual data points for total dissolved solids and temperature, providing high-resolution coverage of water-quality conditions in Spring Lake. I applied data-quality control procedures to remove incomplete or anomalous measurements and uploaded the cleaned dataset into a geographic information system to support detailed spatial mapping and analysis of water-quality patterns within the lake. I performed statistical analyses that show periods of low spring flow coincide with reduced total dissolved solids and slightly lower temperatures. I also identified greater variability in both measures during transitional months, highlighting the influence of shifting spring sources on water quality. Through spatial analysis, I documented clear gradients, with higher total dissolved solids in downstream areas and lower values in the upstream headwaters. I found that the temperature remains generally uniform but stays warmer and more stable in central areas and slightly cooler along the lake margins. These results demonstrate the sensitivity of Spring Lake to changes in spring flow and show how groundwater mixing processes shape the lake’s chemical and thermal conditions. The high-frequency dataset generated by the mobile monitoring device allowed me to identify these fine-scale spatial and temporal patterns, underscoring the value of real-time, boat-based sensing for improving water-quality monitoring in surface water systems."],"dc:format":["Text"],"dc:format.medium":["1 file (.pdf)"],"dc:identifier.uri":["https://hdl.handle.net/10877/23611"],"dc:language.iso":["en"],"dc:subject":["Spring Lake water quality","continuous water quality monitoring device","water quality"],"dc:title":["Dynamic Sensing of a Dynamic System: Mobile Water Quality Monitoring at Spring Lake, San Marcos, Texas"],"dc:type":["Research Project"],"thesis:degree_discipline":["Natural Resources and Environmental Studies"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Masters of Applied Geography"],"thesis:institution_name":["Texas State University"]},"updated_at":"2026-07-27T21:22:45Z"}