H152
Water and Society: Emerging Digital Solutions to Transform Governance of Coupled Human-Water Systems and interconnected urban infrastructure in the Anthropocene
Session ID#: 250109
Session Description:
Rethinking management strategies for coupled human-water systems and interconnected infrastructure is key for meeting future demands under changing socio-economic and climate conditions and urban development. Modeling water, energy, and human networks, and their interconnections across scales and heterogeneous future scenarios is essential to inform systems governance and adaptive planning and management. A growing body of work aims to capture these elements by analyzing the role of data analytics to inform policies in coupled human-water systems, relying on high-resolution data, emerging technologies, and modeling techniques. This session provides an active forum to discuss the frameworks, methods, risk assessment, and technologies for analysis and governance of human-water systems and interconnected networks. Topics of interest include supply and demand management using big-data analytics, artificial intelligence (including large language models and physics-informed machine learning), individual and aggregate consumer behavior, risk-based decision-making, water-energy nexus, regulations, and multi-sector and/or multi-scale system resilience within the urban metabolism.
Index Terms:
1848 Monitoring networks [HYDROLOGY]
1880 Water management [HYDROLOGY]
1884 Water supply [HYDROLOGY]
1910 Data assimilation, integration and fusion [INFORMATICS]
Primary Convener: Marta Zaniolo, Duke University, Durham, NC, United States
Conveners: Newsha K Ajami, Lawrence Berkeley National Laboratory, Berkeley, United States, Alvar Escriva-Bou, University of California Davis, Civil and Environmental Engineering, Davis, CA, United States and Andrea Cominola, Technische Universität Berlin, Chair of Smart Water Networks, Berlin, Germany; Einstein Center Digital Future, Berlin, Germany
Student/Early Career Convener: Marie Philine Gross, Technical University of Berlin, Einstein Center Digital Future, Berlin, Germany
Quantifying the Impact of Climate Change on Household Water Use in Mega Cities: A Case Study of Beijing, China (1846783)
Yubo Zhang1, Yongnan Zhu1, Haihong Li1, Lichuan Wang2, Longlong Zhang1, Haokai Ding1 and Hao Wang1, (1)State Key Laboratory of Water Cycle and Water Security, China Institute of Water Resources and Hydropower Research, Beijing, China, (2)State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China
Expecting the Unexpected: Hydro-Economic Multi-Sector Modeling for Resilience Against Emerging Rural-Urban Water Scarcity Risks (Invited) (1863247)
Christian J. A. Klassert1, Taís Carvalho2, Jim Yoon3, Ankun Wang4, Jasmin Heilemann1, Simon Werner1, Mansi Nagpal1, Bernd Klauer1, Erik Gawel1 and Steven M. Gorelick4, (1)Helmholtz Centre for Environmental Research UFZ Leipzig, Department of Economics, Leipzig, Germany, (2)Helmholtz Centre for Environmental Research UFZ Leipzig, Department of Urban and Environmental Sociology, Leipzig, Germany, (3)Pacific Northwest National Laboratory, Energy and Environment Directorate, Richland, United States, (4)Stanford University, Earth System Science, Stanford, United States
Quantifying Discretionary Authority in United States Water Reservoir Management: A Comparative Analysis by Agency, Climate, and Reservoir Purpose (1871619)
Peter Wasswa, Duke University, Nicholas School of the Environment, Durham, United States and Martin Doyle, Duke University, Nicholas School of the Environment, Durham, NC, United States
Explainable AI Reveals Time-Varying Effects of Media Coverage on Household Water Savings During a Drought (1889621)
Eunmi Lee1, Seunghui Choi1, Sangeun Lee2, Hyeoncheol Yoon3, Newsha K Ajami4, Xiaogang He5 and Jonghun Kam1, (1)Pohang University of Science and Technology, Division of Environmental Science and Engineering, Pohang, South Korea, (2)KRIHS Korea Research Institute for Human Settlements, Sejong-si, South Korea, (3)National Disaster Management Research Institute, Ulsan, South Korea, (4)Lawrence Berkeley National Laboratory, Berkeley, United States, (5)National University of Singapore, Department of Civil and Environmental Engineering, Singapore, Singapore
A Bayesian hierarchical framework for utility water demand reconstruction (1921172)
Cameron Moore1, Mark E Borsuk1, Ben Rachunok2 and Marta Zaniolo1, (1)Duke University, Civil and Environmental Engineering, Durham, United States, (2)North Carolina State University Raleigh, Edward P. Fitts Department of Industrial & Systems Engineering, Raleigh, United States
Validation of an Agent-based Model for Price and Income Elasticity of Demand Simulation (1982217)
Brent Vizanko, University of Kentucky, Lexington, KY, United States, Adam Shelley, Kentucky Water Research Institute, Lexington, United States and Lindell Ormsbee, University of Kentucky, Civil Engineering, Lexington, United States
Dynamic Failure Mapping: Integrating System Dynamics Modeling and Fault Tree Analysis for Drinking Water System Resilience and Public Health Risk Assessment (1988527)
Shima Kheirinejad, University of New Hampshire Main Campus, Durham, NH, United States, Taler Bixler, University of New Hampshire Main Campus, Civil and Environmental Engineering, Durham, United States and Weiwei Mo, University of New Hampshire, Civil and Environmental Engineering, Durham, United States
