Naresh Devineni

Naresh Devineni is a Professor in the Department of Civil Engineering at the City College of New York (CUNY), with affiliations to the CUNY-CREST Institute, Earth System Science and Environmental Engineering, and NOAA-CESSRST. His research focuses on hydrology, machine learning, and risk management, particularly in water resource management and climate change impacts. He advises PhD students like Arun Ravindranath (crop water stress modeling) and Nasser Najibi (global flood trends analysis). His work integrates statistical modeling, environmental data analysis, and interdisciplinary collaboration to address challenges in flood risk, water scarcity, and climate adaptation. Recent studies include forecasting monsoon-induced agricultural risks in India and analyzing global flood frequency trends using satellite data.

Research highlights include developing the Cumulative Deficit Index (CDI) for crop water stress and analyzing flood duration changes via Earth System Dynamics. He collaborates with institutions like the Dartmouth Flood Observatory and Harvard Dataverse for data-driven insights. His research emphasizes probabilistic forecasting, uncertainty quantification, and actionable policy frameworks for sustainable water management.

Key areas of contribution include:

• Climate-informed seasonal forecasts for agriculture
• Urban flood resilience in NYC post-Hurricane Ida
• Global flood pattern analysis using historical datasets
• Machine learning applications for risk assessment

Publications span journals like Hydrology and Earth System Sciences and Earth System Dynamics, with a focus on bridging theoretical models and real-world decision-making.