Abderraman Brandão is a Brazilian researcher who investigates unresolved questions about how catchments function, from typical conditions to hydrological extremes. Originally from Minas Gerais, Brazil, he holds a bachelor’s degree in Civil Engineering from the Federal University of Viçosa, a master’s degree in Hydraulic Engineering and Sanitation, and an MBA in Data Science and Analytics from the University of São Paulo.

His research examines how hydrological processes studied at the local scale manifest across large samples of catchments and how interactions between the atmosphere and components of the hydrosphere influence these processes. By comparing hundreds of catchments, he seeks to understand which mechanisms are shared and which depend on regional characteristics. His work combines observations, machine learning, and explainable artificial intelligence to investigate relationships that remain poorly understood. This knowledge can help transfer hydrological insights to ungauged regions, improve modeling under nonstationary conditions, estimate water availability, and anticipate hydrological extremes.

His goal is to improve our understanding of the processes that govern the water cycle and develop modeling tools that support water management and preparedness for extreme events. His research relates to SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action), with a focus on water availability and adaptation to hydrological extremes.