{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/127416"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/127416","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Using GIS and RS-PRODUCTS to develop a geo-referenced inventory for reservoirs in the CONUS","abstract":"DSpace SAF Submission Ingestion Package generated from Vireo submission #21591 on 2025-03-28 at 14:45:05","abstract_html":"DSpace SAF Submission Ingestion Package generated from Vireo submission #21591 on 2025-03-28 at 14:45:05","abstract_has_math":false,"creators":["Zhang, Linshui"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Cai, Ximing"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-12-13","date_published":"2024-12-13","updated_at":"2026-07-22T22:25:04Z","subjects":["Gis","Rs-products","Hydrological Modeling","Reservoir Inflow And Outflow Simulation"],"languages":["en","eng"],"rights":["Copyright 2024 Linshui Zhang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/127416","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Cai, Ximing"]},{"key":"dc:creator","label":"Author","values":["Zhang, Linshui"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-12-13","2024-12"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Gis","Rs-products","Hydrological Modeling","Reservoir Inflow And Outflow Simulation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Linshui Zhang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/127416"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["DSpace SAF Submission Ingestion Package generated from Vireo submission #21591 on 2025-03-28 at 14:45:05","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01","The student, Linshui Zhang, accepted the attached license on 2024-12-12 at 20:57.","The student, Linshui Zhang, submitted this Thesis for approval on 2024-12-12 at 21:13.","This Thesis was approved for publication on 2024-12-13 at 12:58.","Reservoir operation models have evolved to address diverse hydrological conditions, yet challenges persist for reservoirs with limited or no historical data. This study extends the Generic Data-Driven Reservoir Operation Model (GDROM) to improve its scalability and applicability for data-limited and no-data reservoirs. By leveraging streamflow data from upstream and downstream gauge stations of a reservoir, the proposed method adopts a geospatial matching algorithm to identify the inflow and outflow of a reservoir and develop data inventory for many reservoirs with limited historical operation records. Historical records from data-rich reservoirs are used to validate the framework's robustness. For no-data reservoirs, spatially matched streamflow data and proxy-based methods provide a scalable solution to estimate reservoir inflow and outflow for reservoirs with limited data or no data. The results of this work will enable the simulation of reservoir operation dynamics and effective integration reservoirs into large-scale hydrological models. The framework’s adaptability across diverse operational scales and flow regimes enhances the application of GDROMs across the CONUS regions."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Using GIS and RS-PRODUCTS to develop a geo-referenced inventory for reservoirs in the CONUS"]}]}],"canonical_facts":{"dc:contributor":["Cai, Ximing"],"dc:creator":["Zhang, Linshui"],"dc:date":["2024-12-13","2024-12"],"dc:description":["DSpace SAF Submission Ingestion Package generated from Vireo submission #21591 on 2025-03-28 at 14:45:05","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01","The student, Linshui Zhang, accepted the attached license on 2024-12-12 at 20:57.","The student, Linshui Zhang, submitted this Thesis for approval on 2024-12-12 at 21:13.","This Thesis was approved for publication on 2024-12-13 at 12:58.","Reservoir operation models have evolved to address diverse hydrological conditions, yet challenges persist for reservoirs with limited or no historical data. This study extends the Generic Data-Driven Reservoir Operation Model (GDROM) to improve its scalability and applicability for data-limited and no-data reservoirs. By leveraging streamflow data from upstream and downstream gauge stations of a reservoir, the proposed method adopts a geospatial matching algorithm to identify the inflow and outflow of a reservoir and develop data inventory for many reservoirs with limited historical operation records. Historical records from data-rich reservoirs are used to validate the framework's robustness. For no-data reservoirs, spatially matched streamflow data and proxy-based methods provide a scalable solution to estimate reservoir inflow and outflow for reservoirs with limited data or no data. The results of this work will enable the simulation of reservoir operation dynamics and effective integration reservoirs into large-scale hydrological models. The framework’s adaptability across diverse operational scales and flow regimes enhances the application of GDROMs across the CONUS regions."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/127416"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Linshui Zhang"],"dc:subject":["Gis","Rs-products","Hydrological Modeling","Reservoir Inflow And Outflow Simulation"],"dc:title":["Using GIS and RS-PRODUCTS to develop a geo-referenced inventory for reservoirs in the CONUS"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:04Z"}