{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/17779"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/17779","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"Delineating contributing areas for karst springs using NEXRAD data and cross-correlation analysis","abstract":"The use of cross-correlation analysis on spring discharge and precipitation data in karst aquifer basins has been used for many years to develop a conceptual understanding of an aquifer and estimate aquifer properties. However, to this point, the application of these processes has relied on gaged precipitation at discrete locations. The use of spatially varying precipitation data and cross-correlation analysis provides a means of spatially characterizing recharge locations on a karst aquifer. NEXRAD provides a spatial estimate of precipitation based by combining reflectivity measurements from radar stations and traditional precipitation gages. This study combines NEXRAD precipitation data with spring discharge data to develop maps of contributing areas for two karst springs in Central Texas. By calculating the cross-correlation of each NEXRAD measurement to spring flow data for the same period of time a map showing the locations hydraulically connected to the spring can be developed. Both numerical experiments and field applications were conducted as part of the study. The numerical experiments conducted by Padilla and Pulido-Bosch are revisited using the numerical groundwater model MODFLOW. This allowed the introduction of spatially varying parameters into the model. The results show that spatially varying parameters can be inferred based on the results cross-correlation of spatially varying precipitation with respect to a single spring discharge location. Also, contributing area maps are prepared for both Barton Springs and Jacob’s Well. Barton Springs has a precise estimate of the recharge area. The current map of the recharge area and the NEXRAD derived map show good agreement with the cross-correlation results. Conversely, Jacob’s Well has not been sufficiently studied to delineate a contributing area map. This study provides an preliminary estimate of the area contributing to flow at Jacob’s Well. Finally, the development of these maps can also be applied to the construction of regional groundwater models. An application of this methodology with the groundwater availability model for the Barton Springs portion of the Edward’s aquifer is introduced. The application of spatial cross-correlation analysis to constrain recharge in the model showed a reduction in the objective function with respect to discharge at Barton Springs of 15%.","abstract_html":"The use of cross-correlation analysis on spring discharge and precipitation data in karst aquifer basins has been used for many years to develop a conceptual understanding of an aquifer and estimate aquifer properties. However, to this point, the application of these processes has relied on gaged precipitation at discrete locations. The use of spatially varying precipitation data and cross-correlation analysis provides a means of spatially characterizing recharge locations on a karst aquifer. NEXRAD provides a spatial estimate of precipitation based by combining reflectivity measurements from radar stations and traditional precipitation gages. This study combines NEXRAD precipitation data with spring discharge data to develop maps of contributing areas for two karst springs in Central Texas. By calculating the cross-correlation of each NEXRAD measurement to spring flow data for the same period of time a map showing the locations hydraulically connected to the spring can be developed. Both numerical experiments and field applications were conducted as part of the study. The numerical experiments conducted by Padilla and Pulido-Bosch are revisited using the numerical groundwater model MODFLOW. This allowed the introduction of spatially varying parameters into the model. The results show that spatially varying parameters can be inferred based on the results cross-correlation of spatially varying precipitation with respect to a single spring discharge location. Also, contributing area maps are prepared for both Barton Springs and Jacob’s Well. Barton Springs has a precise estimate of the recharge area. The current map of the recharge area and the NEXRAD derived map show good agreement with the cross-correlation results. Conversely, Jacob’s Well has not been sufficiently studied to delineate a contributing area map. This study provides an preliminary estimate of the area contributing to flow at Jacob’s Well. Finally, the development of these maps can also be applied to the construction of regional groundwater models. An application of this methodology with the groundwater availability model for the Barton Springs portion of the Edward’s aquifer is introduced. The application of spatial cross-correlation analysis to constrain recharge in the model showed a reduction in the objective function with respect to discharge at Barton Springs of 15%.","abstract_has_math":false,"creators":["Budge, Trevor Jones, 1974-"],"institution":"The University of Texas at Austin","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Geological Sciences","degree_department":null,"school":null,"contributors":[],"advisors":["Sharp, John Malcolm, 1944-"],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008-08","date_published":"2008-08","updated_at":"2026-07-24T05:01:10Z","subjects":[],"languages":["eng"],"rights":["Copyright is held by the author. Presentation of this material on the Libraries&apos; web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2152/17779","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Sharp, John Malcolm, 1944-"]},{"key":"dc:creator","label":"Author","values":["Budge, Trevor Jones, 1974-"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2012-09-06T17:25:35Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2012-09-06T17:25:35Z"]},{"key":"dc:date.issued","label":"Date","values":["2008-08"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geological Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Texas at Austin"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright is held by the author. Presentation of this material on the Libraries&apos; web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/2152/17779"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["text"]},{"key":"dc:description.abstract","label":"Abstract","values":["The use of cross-correlation analysis on spring discharge and precipitation data in karst aquifer basins has been used for many years to develop a conceptual understanding of an aquifer and estimate aquifer properties. However, to this point, the application of these processes has relied on gaged precipitation at discrete locations. The use of spatially varying precipitation data and cross-correlation analysis provides a means of spatially characterizing recharge locations on a karst aquifer. NEXRAD provides a spatial estimate of precipitation based by combining reflectivity measurements from radar stations and traditional precipitation gages. This study combines NEXRAD precipitation data with spring discharge data to develop maps of contributing areas for two karst springs in Central Texas. By calculating the cross-correlation of each NEXRAD measurement to spring flow data for the same period of time a map showing the locations hydraulically connected to the spring can be developed. Both numerical experiments and field applications were conducted as part of the study. The numerical experiments conducted by Padilla and Pulido-Bosch are revisited using the numerical groundwater model MODFLOW. This allowed the introduction of spatially varying parameters into the model. The results show that spatially varying parameters can be inferred based on the results cross-correlation of spatially varying precipitation with respect to a single spring discharge location. Also, contributing area maps are prepared for both Barton Springs and Jacob’s Well. Barton Springs has a precise estimate of the recharge area. The current map of the recharge area and the NEXRAD derived map show good agreement with the cross-correlation results. Conversely, Jacob’s Well has not been sufficiently studied to delineate a contributing area map. This study provides an preliminary estimate of the area contributing to flow at Jacob’s Well. Finally, the development of these maps can also be applied to the construction of regional groundwater models. An application of this methodology with the groundwater availability model for the Barton Springs portion of the Edward’s aquifer is introduced. The application of spatial cross-correlation analysis to constrain recharge in the model showed a reduction in the objective function with respect to discharge at Barton Springs of 15%."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["electronic"]},{"key":"dc:title","label":"Title","values":["Delineating contributing areas for karst springs using NEXRAD data and cross-correlation analysis"]}]}],"canonical_facts":{"dc:contributor.advisor":["Sharp, John Malcolm, 1944-"],"dc:creator":["Budge, Trevor Jones, 1974-"],"dc:date.accessioned":["2012-09-06T17:25:35Z"],"dc:date.available":["2012-09-06T17:25:35Z"],"dc:date.issued":["2008-08"],"dc:description":["text"],"dc:description.abstract":["The use of cross-correlation analysis on spring discharge and precipitation data in karst aquifer basins has been used for many years to develop a conceptual understanding of an aquifer and estimate aquifer properties. However, to this point, the application of these processes has relied on gaged precipitation at discrete locations. The use of spatially varying precipitation data and cross-correlation analysis provides a means of spatially characterizing recharge locations on a karst aquifer. NEXRAD provides a spatial estimate of precipitation based by combining reflectivity measurements from radar stations and traditional precipitation gages. This study combines NEXRAD precipitation data with spring discharge data to develop maps of contributing areas for two karst springs in Central Texas. By calculating the cross-correlation of each NEXRAD measurement to spring flow data for the same period of time a map showing the locations hydraulically connected to the spring can be developed. Both numerical experiments and field applications were conducted as part of the study. The numerical experiments conducted by Padilla and Pulido-Bosch are revisited using the numerical groundwater model MODFLOW. This allowed the introduction of spatially varying parameters into the model. The results show that spatially varying parameters can be inferred based on the results cross-correlation of spatially varying precipitation with respect to a single spring discharge location. Also, contributing area maps are prepared for both Barton Springs and Jacob’s Well. Barton Springs has a precise estimate of the recharge area. The current map of the recharge area and the NEXRAD derived map show good agreement with the cross-correlation results. Conversely, Jacob’s Well has not been sufficiently studied to delineate a contributing area map. This study provides an preliminary estimate of the area contributing to flow at Jacob’s Well. Finally, the development of these maps can also be applied to the construction of regional groundwater models. An application of this methodology with the groundwater availability model for the Barton Springs portion of the Edward’s aquifer is introduced. The application of spatial cross-correlation analysis to constrain recharge in the model showed a reduction in the objective function with respect to discharge at Barton Springs of 15%."],"dc:format.medium":["electronic"],"dc:identifier.uri":["http://hdl.handle.net/2152/17779"],"dc:language.iso":["eng"],"dc:rights":["Copyright is held by the author. Presentation of this material on the Libraries&apos; web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works."],"dc:title":["Delineating contributing areas for karst springs using NEXRAD data and cross-correlation analysis"],"thesis:degree_discipline":["Geological Sciences"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["The University of Texas at Austin"]},"updated_at":"2026-07-24T05:01:10Z"}