Stochastic Hydrology & Water Balance

This research area focuses on the development of analytical and stochastic models to describe hydrological processes such as soil moisture dynamics and runoff generation. Predicting flood risk starts with understanding how rainfall, soil, and basin geometry interact. Our research applies stochastic soil water balance modeling to derive probability functions of saturated areas and basin saturation — key indicators for water resource management in humid and semi-humid environments. Our derived flood frequency model, validated on Southern Italy basins, identifies two distinct runoff mechanisms: ordinary floods triggered by rainfall exceeding infiltration thresholds over small source areas, and extreme outlier events driven by storage-threshold exceedance across larger basin portions. Model parameters correlate directly with geomorphological descriptors, enabling application to ungauged catchments. A physically based, probabilistic toolkit for flood risk assessment and climate adaptation planning.

Key Contributions

  • Stochastic modeling of soil moisture
  • Probability distributions of hydrological variables
  • Flood frequency analysis based on physical processes

Why This Research Matters

Together, these models offer a physically based, probabilistic toolkit for flood risk assessment, basin hydrology, and climate adaptation planning. Whether you are designing stormwater infrastructure, calibrating hydrological models, or assessing environmental vulnerability, these approaches provide robust theoretical foundations supported by field-validated numerical simulations.

Key Publications

About the author

He is Full Professor of Hydrology and Hydraulic Constructions at the University of Naples Federico II. He is currently chair of the IAHS MOXXI working group. His research primarily centers on hydrological modeling and monitoring. Recognizing the challenges posed by the complexity and limitations of traditional hydrological observations, he actively explores advanced and alternative monitoring techniques, such as the utilization of Unmanned Aerial Systems (UAS) coupled with image processing.