John L. Sabo
Professor
Education & Affiliations
Biography
John L. Sabo, Ph.D. (University of California, Berkeley) is Executive Director of the ByWater Institute for Climate Adaptation and Professor in the Department of River and Coastal Science and Engineering at Tulane University. His research focuses on climate adaptation, water resources, and the role of hydrology in shaping ecological systems, food security, and human well-being. Trained as an ecologist working at the interface of hydrology and ecosystems, Dr. Sabo studies how river flows, groundwater, and climate variability influence freshwater ecosystems, fisheries, and agricultural systems across large river basins.
At Tulane, his work integrates natural and built infrastructure, data science, and hydrologic modeling to support climate adaptation strategies for rivers, deltas, and coastal landscapes. His research frequently combines ecological theory, stochastic hydrology, and emerging data and AI tools to design water management strategies that improve resilience of both ecosystems and human communities.
A central theme of his work is understanding how hydrologic change—from dams, groundwater extraction, and climate variability—affects food systems and freshwater biodiversity, particularly in large river basins such as the Mississippi and Mekong.
Dr. Sabo is also active in public communication on water and climate adaptation. He hosts the Audacious Water podcast and writes widely about water policy and climate resilience through his Substack newsletter and as a contributor to Forbes, helping translate scientific insights into practical ideas for policymakers, businesses, and the public.
Courses
Contributions
This paper shows how hydrologic variability influences ecological structure in river ecosystems. By linking river discharge dynamics with food web structure across watersheds, the study demonstrates that hydrology constrains food chain length in rivers, highlighting the importance of flow regimes for biodiversity, ecosystem stability, and river management.
This methodological paper provides a framework for distinguishing different types of environmental variability—periodic, stochastic, and catastrophic—in ecological systems. The approach helps researchers and managers understand how environmental variability shapes ecosystem dynamics and improves forecasting of ecological responses to hydrologic change and climate variability.
This study demonstrates how river management can shape regional food security. By linking hydrologic models with fisheries production across the Mekong Basin, the research shows how dam operations influence fish harvests that support millions of people, illustrating how water management decisions can balance energy generation, ecosystem health, and food security.
This synthesis examines water sustainability challenges in the arid western United States, highlighting interactions among groundwater depletion, climate variability, and river regulation. The paper calls for integrated management approaches that combine hydrologic science, ecological understanding, and institutional reform to sustain freshwater ecosystems and human water supplies.
This research introduces a framework linking hydrologic modeling with economic risk analysis to evaluate investments in both natural and engineered water infrastructure. The work demonstrates how coordinated management of wetlands, floodplains, levees, and reservoirs can reduce climate risk and improve the resilience of water systems.
This paper develops causal machine-learning approaches to improve streamflow forecasting. By identifying causal relationships within hydrologic systems rather than relying solely on statistical correlations, the framework enhances prediction under nonstationary climate conditions and supports data-driven water management and climate adaptation planning.
