{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/127388"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/127388","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Assessing interactions between streamflow and reservoir storage: Integrated modeling of hydrological drought propagation to water supply","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01","abstract_has_math":false,"creators":["Li, Donghui"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Cai, Ximing","Konar, Megan","Zhang, Zhenxing","Mishra, Ashok"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-12-05","date_published":"2024-12-05","updated_at":"2026-07-22T22:25:04Z","subjects":["Drought","Hydrological Modeling","Reservoir Operation"],"languages":["en","eng"],"rights":["Copyright 2024 Donghui Li"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/127388","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Cai, Ximing","Konar, Megan","Zhang, Zhenxing","Mishra, Ashok"]},{"key":"dc:creator","label":"Author","values":["Li, Donghui"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-12-05","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":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"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":["Drought","Hydrological Modeling","Reservoir Operation"]}]},{"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 Donghui Li"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/127388"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01","The student, Donghui Li, accepted the attached license on 2024-12-03 at 09:11.","The student, Donghui Li, submitted this Dissertation for approval on 2024-12-03 at 09:23.","This Dissertation was approved for publication on 2024-12-05 at 14:30.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21467 on 2025-03-28 at 14:44:31","Drought, which can be as serious as a billion-dollar natural disaster, propagates from meteorological to hydrological drought, ultimately ending with severe socioeconomic consequences. In the Anthropocene era, drought propagation and impact have become increasingly complex due to intensive interactions between hydrological and human systems. This dissertation addresses this complexity by examining the relationship among hydrological drought, reservoir storage condition (a major human interference to streamflow), and water supply drought in river basins with significant storage regulation, employing an integrated hydrological and water management modeling approach. The dissertation is structured in three interconnected parts. The first part develops a novel machine learning model to extract real-world reservoir operation rules, which provides a realistic reservoir representation for large-scale hydrological simulation at the river basin scale. The transparent model structure uncovers real-world water management patterns for major reservoirs across the contiguous United States (CONUS). The derived empirical operation rules are shown to effectively capture real-world reservoir operations for over 450 large reservoirs with diverse purposes across the CONUS. These rules provide ready-to-implement “if-then” conditions that can be seamlessly integrated into hydrological models. Furthermore, our analysis identifies five typical operation schemes and their spatially heterogeneous patterns of application and transition, providing valuable insights for constructing reservoir operation rules in data-scarce regions. Building on this data-driven reservoir operation model, the second part establishes an integrated modeling framework to simulate the role of reservoir operation in drought propagation from hydrological drought to water supply drought across CONUS river basins. A key finding reveals the trade-off impacts of reservoir operation on hydrological droughts: while reservoirs regulation generally reduces downstream drought frequency and intensity, they tend to increase drought duration and accumulated severity. However, spatially heterogeneous impacts are observed, with some regions exhibiting opposite trade-off effects, reflecting regional drought mitigation strategies and varied roles of reservoir operation in drought management. Furthermore, this part identifies four distinct types of basins with respect to drought propagation from hydrological to water supply drought. These include basins with abundant water availability, where hydrological droughts do not lead to water supply stress or reservoir storage depletion; basins where reservoirs successfully prevent water supply deficits during hydrological droughts, but at the cost of significantly declining reservoir storage levels; basins with slow drought propagation, where reservoirs effectively mitigate most hydrological droughts, allowing only occasional, short-lived water supply deficits; and basins experiencing rapid drought propagation, where hydrological droughts consistently lead to water supply shortages despite intensive reservoir regulation. Based on these insights, a new water supply drought index is developed, incorporating both streamflow and reservoir storage levels via a power-law relation. The third part investigates individual drought events, examining the dynamic interaction between hydrological drought and reservoir storage drought. This analysis reveals the following four typical patterns of interaction between these critical variables. These include 1) isolated hydrological droughts, where events occur without triggering reservoir drought; 2) simultaneous hydrological and reservoir droughts, characterized by reservoir drought quickly following hydrological drought; 3) decoupled hydrological and reservoir drought, where reservoir drought occurs without a synchronous link to hydrological drought; and 4) lagged hydrological and reservoir drought, featuring considerable time lags between the onset of hydrological drought and its propagation to reservoir drought. The spatial distribution of these four drought patterns across the CONUS and their temporal evolution underscore the complex dynamics between hydrological drought and reservoir storage drought, highlighting the need for adaptive, region-specific approaches for effective drought monitoring and preparation. With improved representation of the human dimension in drought propagation through realistic representation of reservoir in large-scale hydrologic modeling, this dissertation bridges a critical gap in our understanding of how anthropogenic factors modulate natural drought processes. The research establishes a coupled hydrological and water management modeling framework, fusing data-driven reservoir operation modeling with process-based hydrological modeling. This integrated approach enhances our ability to understand, predict, and manage water supply droughts in the context of complex human-natural systems."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Assessing interactions between streamflow and reservoir storage: Integrated modeling of hydrological drought propagation to water supply"]}]}],"canonical_facts":{"dc:contributor":["Cai, Ximing","Konar, Megan","Zhang, Zhenxing","Mishra, Ashok"],"dc:creator":["Li, Donghui"],"dc:date":["2024-12-05","2024-12"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01","The student, Donghui Li, accepted the attached license on 2024-12-03 at 09:11.","The student, Donghui Li, submitted this Dissertation for approval on 2024-12-03 at 09:23.","This Dissertation was approved for publication on 2024-12-05 at 14:30.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21467 on 2025-03-28 at 14:44:31","Drought, which can be as serious as a billion-dollar natural disaster, propagates from meteorological to hydrological drought, ultimately ending with severe socioeconomic consequences. In the Anthropocene era, drought propagation and impact have become increasingly complex due to intensive interactions between hydrological and human systems. This dissertation addresses this complexity by examining the relationship among hydrological drought, reservoir storage condition (a major human interference to streamflow), and water supply drought in river basins with significant storage regulation, employing an integrated hydrological and water management modeling approach. The dissertation is structured in three interconnected parts. The first part develops a novel machine learning model to extract real-world reservoir operation rules, which provides a realistic reservoir representation for large-scale hydrological simulation at the river basin scale. The transparent model structure uncovers real-world water management patterns for major reservoirs across the contiguous United States (CONUS). The derived empirical operation rules are shown to effectively capture real-world reservoir operations for over 450 large reservoirs with diverse purposes across the CONUS. These rules provide ready-to-implement “if-then” conditions that can be seamlessly integrated into hydrological models. Furthermore, our analysis identifies five typical operation schemes and their spatially heterogeneous patterns of application and transition, providing valuable insights for constructing reservoir operation rules in data-scarce regions. Building on this data-driven reservoir operation model, the second part establishes an integrated modeling framework to simulate the role of reservoir operation in drought propagation from hydrological drought to water supply drought across CONUS river basins. A key finding reveals the trade-off impacts of reservoir operation on hydrological droughts: while reservoirs regulation generally reduces downstream drought frequency and intensity, they tend to increase drought duration and accumulated severity. However, spatially heterogeneous impacts are observed, with some regions exhibiting opposite trade-off effects, reflecting regional drought mitigation strategies and varied roles of reservoir operation in drought management. Furthermore, this part identifies four distinct types of basins with respect to drought propagation from hydrological to water supply drought. These include basins with abundant water availability, where hydrological droughts do not lead to water supply stress or reservoir storage depletion; basins where reservoirs successfully prevent water supply deficits during hydrological droughts, but at the cost of significantly declining reservoir storage levels; basins with slow drought propagation, where reservoirs effectively mitigate most hydrological droughts, allowing only occasional, short-lived water supply deficits; and basins experiencing rapid drought propagation, where hydrological droughts consistently lead to water supply shortages despite intensive reservoir regulation. Based on these insights, a new water supply drought index is developed, incorporating both streamflow and reservoir storage levels via a power-law relation. The third part investigates individual drought events, examining the dynamic interaction between hydrological drought and reservoir storage drought. This analysis reveals the following four typical patterns of interaction between these critical variables. These include 1) isolated hydrological droughts, where events occur without triggering reservoir drought; 2) simultaneous hydrological and reservoir droughts, characterized by reservoir drought quickly following hydrological drought; 3) decoupled hydrological and reservoir drought, where reservoir drought occurs without a synchronous link to hydrological drought; and 4) lagged hydrological and reservoir drought, featuring considerable time lags between the onset of hydrological drought and its propagation to reservoir drought. The spatial distribution of these four drought patterns across the CONUS and their temporal evolution underscore the complex dynamics between hydrological drought and reservoir storage drought, highlighting the need for adaptive, region-specific approaches for effective drought monitoring and preparation. With improved representation of the human dimension in drought propagation through realistic representation of reservoir in large-scale hydrologic modeling, this dissertation bridges a critical gap in our understanding of how anthropogenic factors modulate natural drought processes. The research establishes a coupled hydrological and water management modeling framework, fusing data-driven reservoir operation modeling with process-based hydrological modeling. This integrated approach enhances our ability to understand, predict, and manage water supply droughts in the context of complex human-natural systems."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/127388"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Donghui Li"],"dc:subject":["Drought","Hydrological Modeling","Reservoir Operation"],"dc:title":["Assessing interactions between streamflow and reservoir storage: Integrated modeling of hydrological drought propagation to water supply"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:04Z"}