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Development and Evaluation of Technologies and Social Science Methods Supporting Collective Action Toward Climate Resilient Water Resource Management
Development and Evaluation of Technologies and Social Science Methods Supporting Collective Action Toward Climate Resilient Water Resource Management
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260311091513.5
- ISBN
- 9798315703112
- DDC
- 628.1
- 서명/저자
- Development and Evaluation of Technologies and Social Science Methods Supporting Collective Action Toward Climate Resilient Water Resource Management / Katherine Demaree
- 발행사항
- [Sl] : University of Colorado at Boulder, 2025
- 형태사항
- 1 electronic resource (113 pages)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-11, Section: A.
- 주기사항
- Advisors: Thomas, Evan Committee members: Gooseff, Mike; Salvinelli, Carlo; Andersson, Krister; Ross, Matt.
- 학위논문주기
- - Ph.D. : University of Colorado at Boulder, 2025.
- 초록/해제
- 요약This work explores innovative approaches toward sustainable water management in the Western United States, focusing on the integration of behavioral economics, nature-based solutions, and sensor technology to address challenges posed by climate change and shifting hydrology in rural and agricultural communities. Developing and evaluating a digital behavioral economics game simulating groundwater conservation in Colorado's San Luis Valley, the initial study introduces a novel tool enabling policymakers to explore institutional innovations for preventing overexploitation of renewable resources. Results demonstrate that financial incentives significantly influence crop choices and water use patterns, while fostering collaborative behaviors among stakeholders. This game proves effective in informing and empowering communities to engage in collaborative problem-solving, leading to improved water conservation efforts. Barriers and opportunities for implementing nature-based solutions to enhance water quality form the focus of the subsequent investigation. Employing a mixed-methods approach, including key informant interviews, focus groups, and surveys, the research identifies regulatory hurdles, funding challenges, and the need for robust water quality monitoring systems as primary obstacles. Regulatory constraints emerge as a critical barrier, highlighting the necessity for policy reforms to facilitate nature-based solution implementation. The study emphasizes the importance of new financing models and incentive-based programs to overcome funding limitations. In the concluding study, a novel approach to predicting Total Organic Carbon (TOC) and nutrients in the Yampa River watershed using high-frequency sensor data and machine learning techniques is presented. A Gradient Boosting Machine model, trained on lab-analyzed TOC and TN samples and in situ sensor measurements, achieves high accuracy in predicting TOC concentrations (RMSE 0.9 mg/L) and binary classification (above/below 0.3 mg/L) of TN with an accuracy of 80%. The study also reveals significant discrepancies between traditional and high-resolution land cover data, highlighting the importance of accurate land use assessment in water quality monitoring. This approach offers a cost-effective method for continuous water quality monitoring, enabling more responsive watershed management strategies. The integration of these diverse studies demonstrates the potential of integrating technological tools, stakeholder engagement, and innovative methodologies to develop locally-tailored solutions for water resource conservation and protection. By addressing both water quantity and quality concerns, this research provides valuable insights for policymakers, water managers, and communities facing water security challenges in the changing climate of the Western United States.
- 언어주기
- English
- 일반주제명
- Sustainability
- 키워드
- Groundwater
- 키워드
- Policy
- 키워드
- Water management
- 키워드
- Water quality
- 기타저자
- University of Colorado at Boulder Civil Environmental and Architectural Engineering
- 기본자료저록
- Dissertations Abstracts International. 86-11A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■006m o d
■007cr|nu||||||||
■020 ▼a9798315703112
■040 ▼aMiAaPQD▼beng▼cMiAaPQD▼erda
■082 ▼a628.1
■1001 ▼aDemaree, Katherine▼eauthor.▼0(orcid)0000-0001-7287-2439
■24510▼aDevelopment and Evaluation of Technologies and Social Science Methods Supporting Collective Action Toward Climate Resilient Water Resource Management ▼cKatherine Demaree
■260 ▼a[Sl]▼bUniversity of Colorado at Boulder▼c2025
■264 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a1 electronic resource (113 pages)
■336 ▼atext▼btxt▼2rdacontent
■337 ▼acomputer▼bc▼2rdamedia
■338 ▼aonline resource▼bcr▼2rdacarrier
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-11, Section: A.
■500 ▼aAdvisors: Thomas, Evan Committee members: Gooseff, Mike; Salvinelli, Carlo; Andersson, Krister; Ross, Matt.
■5021 ▼bPh.D.▼cUniversity of Colorado at Boulder▼d2025.
■520 ▼aThis work explores innovative approaches toward sustainable water management in the Western United States, focusing on the integration of behavioral economics, nature-based solutions, and sensor technology to address challenges posed by climate change and shifting hydrology in rural and agricultural communities. Developing and evaluating a digital behavioral economics game simulating groundwater conservation in Colorado's San Luis Valley, the initial study introduces a novel tool enabling policymakers to explore institutional innovations for preventing overexploitation of renewable resources. Results demonstrate that financial incentives significantly influence crop choices and water use patterns, while fostering collaborative behaviors among stakeholders. This game proves effective in informing and empowering communities to engage in collaborative problem-solving, leading to improved water conservation efforts. Barriers and opportunities for implementing nature-based solutions to enhance water quality form the focus of the subsequent investigation. Employing a mixed-methods approach, including key informant interviews, focus groups, and surveys, the research identifies regulatory hurdles, funding challenges, and the need for robust water quality monitoring systems as primary obstacles. Regulatory constraints emerge as a critical barrier, highlighting the necessity for policy reforms to facilitate nature-based solution implementation. The study emphasizes the importance of new financing models and incentive-based programs to overcome funding limitations. In the concluding study, a novel approach to predicting Total Organic Carbon (TOC) and nutrients in the Yampa River watershed using high-frequency sensor data and machine learning techniques is presented. A Gradient Boosting Machine model, trained on lab-analyzed TOC and TN samples and in situ sensor measurements, achieves high accuracy in predicting TOC concentrations (RMSE 0.9 mg/L) and binary classification (above/below 0.3 mg/L) of TN with an accuracy of 80%. The study also reveals significant discrepancies between traditional and high-resolution land cover data, highlighting the importance of accurate land use assessment in water quality monitoring. This approach offers a cost-effective method for continuous water quality monitoring, enabling more responsive watershed management strategies. The integration of these diverse studies demonstrates the potential of integrating technological tools, stakeholder engagement, and innovative methodologies to develop locally-tailored solutions for water resource conservation and protection. By addressing both water quantity and quality concerns, this research provides valuable insights for policymakers, water managers, and communities facing water security challenges in the changing climate of the Western United States.
■546 ▼aEnglish
■590 ▼aSchool code: 0051
■650 4▼aEnvironmental engineering
■650 4▼aSustainability
■650 4▼aWater resources management
■653 ▼aCollective action
■653 ▼aGroundwater
■653 ▼aPolicy
■653 ▼aWater management
■653 ▼aWater quality
■7102 ▼aUniversity of Colorado at Boulder▼bCivil, Environmental, and Architectural Engineering.▼edegree granting institution.
■7201 ▼aThomas, Evan▼edegree supervisor.
■7730 ▼tDissertations Abstracts International▼g86-11A.
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17357080▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
