Marta Zaniolo

Research Themes

Hydrology & Fluid Dynamics, Risk & Resilient Systems

Research Interests

Water resources planning and management, drought modeling and control, flexible climate change adaptation, conceptual and data-driven systems modeling, reinforcement learning for water systems, multi-objective control, feature extraction.

Bio

Marta Zaniolo joined Duke CEE as an assistant professor in January 2024. Her research addresses timely water sustainability challenges including how to ensure reliable and affordable access to water resources in the face of scarcity, competing demands, and a changing climate. She combines the fields of hydrology and water resources modeling with machine learning and data mining techniques to enable more informed decision-making about water use at scales large and small. Zaniolo holds a BS and MS degree in Environmental Engineering and a PhD in Information Technology earned in the Environmental Intelligence lab at Politecnico di Milano. Prior to joining Duke, she was a postdoctoral researcher in the CEE department at Stanford University.Learn more here: https://zeddlab.weebly.com/ 

Education

• B.S. Politecnico di Milano (Italy), 2014
• M.S. Politecnico di Milano (Italy), 2017
• Ph.D. Politecnico di Milano (Italy), 2020

Positions

• Assistant Professor of Civil and Environmental Engineering

Courses Taught

• CEE 690: Advanced Topics in Civil and Environmental Engineering
• CEE 493: Research Independent Study in Civil and Environmental Engineering

Publications

• Jordan SM, Quinn JD, Zaniolo M, Giuliani M, Castelletti A. Dam Reoperation to Mitigate Changing Climate Extremes in the Omo River Basin, Ethiopia. Journal of Water Resources Planning and Management. 2024 Nov 1;150(11).
• Zaniolo M, Fletcher S, Mauter MS. Quantifying the Value of Technology and Policy Innovation in Water Resource Portfolios. Earth’s Future. 2024 May 1;12(5).
• Willebrand K, Zaniolo M, Skerker J, Fletcher S. Valuing Combinations of Flexible Planning, Design, and Operations in Water Supply Infrastructure. Water Resources Research. 2024 Mar 1;60(3).
• Zaniolo M, Fletcher S, Mauter M. FIND: A Synthetic weather generator to control drought Frequency, Intensity, and Duration. Environmental Modelling and Software. 2024 Jan 1;172.
• Fletcher S, Zaniolo M, Zhang M, Lickley M. Climate oscillation impacts on water supply augmentation planning. Proceedings of the National Academy of Sciences of the United States of America. 2023 Aug;120(35):e2215681120.
• Skerker JB, Zaniolo M, Willebrand K, Lickley M, Fletcher SM. Quantifying the Value of Learning for Flexible Water Infrastructure Planning. Water Resources Research. 2023 Jun 1;59(6).
• Zaniolo M, Fletcher S, Mauter MS. Multi-scale planning model for robust urban drought response. Environmental Research Letters. 2023 May 1;18(5).
• Jordan S, Quinn J, Zaniolo M, Giuliani M, Castelletti A. Advancing reservoir operations modelling in SWAT to reduce socio-ecological tradeoffs. Environmental Modelling and Software. 2022 Nov 1;157.
• Zaniolo M, Giuliani M, Castelletti A. Neuro-Evolutionary Direct Policy Search for Multiobjective Optimal Control. IEEE transactions on neural networks and learning systems. 2022 Oct;33(10):5926–38.
• Giuliani M, Zaniolo M, Sinclair S, Micotti M, Van Orshoven J, Burlando P, et al. Participatory design of robust and sustainable development pathways in the Omo-Turkana river basin. Journal of Hydrology: Regional Studies. 2022 Jun 1;41.
• Zaniolo M, Giuliani M, Castelletti A. Policy Representation Learning for Multiobjective Reservoir Policy Design With Different Objective Dynamics. Water Resources Research. 2021 Dec 1;57(12).
• Zaniolo M, Giuliani M, Sinclair S, Burlando P, Castelletti A. When timing matters-misdesigned dam filling impacts hydropower sustainability. Nature communications. 2021 May;12(1):3056.
• Giuliani M, Zaniolo M, Block P, Castelletti A. Data-driven control of water reservoirs using an emulator of the climate system. In: IFAC-PapersOnLine. 2020. p. 16531–6.
• Giuliani M, Zaniolo M, Castelletti A, Davoli G, Block P. Detecting the State of the Climate System via Artificial Intelligence to Improve Seasonal Forecasts and Inform Reservoir Operations. Water Resources Research. 2019 Nov 1;55(11):9133–47.
• Zaniolo M, Giuliani M, Castelletti A. Data-driven modeling and control of droughts. In: IFAC-PapersOnLine. 2019. p. 54–60.
• Zaniolo M, Giuliani M, Castelletti AF, Pulido-Velazquez M. Automatic design of basin-specific drought indexes for highly regulated water systems. Hydrology and Earth System Sciences. 2018 Apr 20;22(4):2409–24.