Engineering Applications of Computational Fluid Mechanics

Numerical Simulation of Earth Surface Water Flows and Flood Disasters

Flood disasters represent the most pervasive natural threat to human societies and infrastructure globally. Accelerated climate change and expanding anthropogenic influence are intensifying their frequency and severity. Understanding and mitigating these risks necessitate precise predictive tools. Numerical simulation has thus become indispensable, providing a virtual laboratory to analyze complex earth surface water flows—from flash floods in mountainous catchments to expansive riverine and coastal inundations.

Advances in computational fluid dynamics (CFD) form the cornerstone, enabling detailed one- to three-dimensional modeling of hydrodynamics, often coupled with sediment transport. Furthermore, the integration of machine learning and data-driven techniques is revolutionizing the field, offering new avenues for handling complexity and accelerating computations. This research topic seeks to collate cutting-edge contributions on numerical techniques for simulating all flood typologies, aiming to enhance predictive accuracy and inform resilient flood risk management strategies worldwide.

This research is critically important because flood disasters cause catastrophic loss of life and immense economic damage globally. As climate change increases the frequency and intensity of extreme weather, the threat is escalating. Effective mitigation hinges on precise prediction. High-fidelity numerical simulation is the only tool that can unravel the complex physics of water flow across diverse landscapes—from urban streets to river valleys—allowing us to visualize inundation, assess risk, and test mitigation strategies before disasters strike.

By advancing these modeling techniques, particularly through the integration of traditional CFD with emerging machine learning, this work directly enables the development of more accurate early warning systems, smarter infrastructure, and evidence-based land-use policies. Ultimately, it translates complex science into actionable intelligence, safeguarding communities, economies, and ecosystems from one of humanity's most persistent and growing natural hazards.

Flooding is the world's most damaging natural disaster, a threat intensified by climate change and human activity. This research focuses on advancing numerical simulation to understand and manage diverse flood types: flash, riverine, urban, and coastal. It explores modeling techniques ranging from fundamental 1D/2D/3D computational fluid dynamics (CFD), including sediment transport, to innovative hybrid approaches integrating machine learning for enhanced speed and accuracy. The scope encompasses studies on water vapor transport, specific flood scenarios in various basins, and cutting-edge methodologies like CFD-DEM and data-driven models. This Article Collection aims to develop superior predictive tools for effective flood risk mitigation globally.

This Article Collection aims to solicit global contributions on modeling earth surface water flows, which will further enhance our understanding and management of flood disasters. The scope of this Article Collection focuses on numerical simulation techniques and broadly includes the following areas:

• Global, regional, and local water vapor transport
• Flash floods in small basins
• Urban floods
• Riverine floods and dam-related floods
• Estuarine and coastal floods
• Flood modeling using machine learning, data-driven, and CFD-DEM (Computational Fluid Dynamics-Discrete Element Method) approaches

Keywords: Flood disasters, Computational Fluid Dynamics, Hydrological modeling, Hydrodynamic modeling, Machine Learning

­­All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisor for this Collection will not be handling the manuscripts (unless they are an Editorial Board member).

Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is 06 November 2026.

Please contact Hang Ke at [email protected] with any queries and discount codes regarding this Article Collection.

Please be sure to select the appropriate Article Collection from the drop-down menu in the submission system.

Xiekang Wang is a professor at the State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan. He is the Winner of the Ministry of Education's New Century Excellent Talents Support Program. His research is engaged in characteristics and laws of water-sediment transport and geomorphological change in mountainous rivers and has recently focused on flash flood disaster modelling, monitoring, and mitigation.

Xudong Fu received his PhD degree from Tsinghua University in 2001, and became a full professor in the Department of Hydraulic Engineering, Tsinghua University in 2009. He is the Winner of the National Outstanding Youth Science Foundation Project, China; the Chairman of the Chinese National Commission for the International Association of Hydrological Sciences. His research interests mainly focus on sediment transport, flash floods, and geomorphology. He is an expert in the field of numerical methods in fluid mechanics and hydraulic engineering. He has published dozens of high-quality scientific papers on numerical algorithms and numerical simulations in turbulent flow, two-phase flow, and watershed modeling.

Xufeng Yan is an Associate Professor at the State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan. He is a Member of the Youth Committee of the Chinese National Commission for the International Association of Hydrological Sciences. He is the Winner of the Sichuan Tianfu Emei Plan Project. His interests are mountain river dynamics, vegetation-related hydraulics, sediment dynamics, and modeling techniques.