We present a knowledge‐guided machine learning framework for operational hydrologic forecasting at the catchment scale. Our approach, a Factorized Hierarchical Neural Network (FHNN), has two main ...

A comprehensive, modular Python automation system for HEC-RAS flood analysis workflows. This professional-grade tool demonstrates advanced hydraulic modeling capabilities, Python integration, and ...

Abstract: Extreme rainfall and flood events increasingly threaten urban transportation networks, yet conventional resilience evaluations fail to capture the dynamic interplay between flooding, traffic ...

Abstract: Mountain flood water levels exhibit high variability and complexity, making them challenging to predict, and gathering long-term data of disaster-causing factors is difficult in small ...

MANVILLE, N.J.—Richard Onderko said he will never forget the terrifying Saturday morning back in 1971 when the water rose so swiftly at his childhood home here that he and his brother had to be ...