Advances in Urban Flood Modeling, Forecasting and Early Warning

Dear Colleagues,

Urban flooding has emerged as one of the most pressing challenges in contemporary hydrology due to rapid urban expansion, increasing imperviousness, drainage network modifications, and land-use change fundamentally altering the hydrological cycle in cities, accelerating runoff generation, reducing infiltration capacity, and amplifying peak discharges. At the same time, climate change is intensifying short-duration, high-intensity precipitation events, thereby increasing the frequency and magnitude of pluvial and compound flooding in densely populated areas. These interacting drivers demand a rethinking of conventional hydrological modeling frameworks. Conventional flood modeling was centered on riverine processes at basin scales, often relying on lumped or semi-distributed approaches. However, urban environments require high-resolution, physically consistent, and computationally efficient models capable of representing fine-scale topography, sewer–surface interactions, hydraulic structures, and multi-pathway flow dynamics. Recent advances in remote sensing, radar rainfall products, IoT-based monitoring systems, data assimilation techniques, and high-performance computing have enabled the development of integrated hydrological–hydrodynamic models operating in near real time. Furthermore, machine learning and hybrid physics-informed approaches are transforming forecasting methodologies, offering improved predictive skill under data scarcity and non-stationary climate conditions. Despite these advancements, significant scientific and operational challenges persist, including uncertainty propagation across coupled models, integration of heterogeneous data sources, scalability to large urban regions, and the translation of forecasts into actionable early warning systems and decision-support tools. Addressing these gaps is essential for strengthening urban resilience, enhancing adaptive capacity, and supporting sustainable water governance in the face of accelerating environmental change.

The goal of this Special Issue is to collect original research articles and review papers that provide new insights into urban flood modeling, forecasting systems, and early warning strategies. This topic aligns closely with the scope of Hydrology, particularly in areas related to surface hydrology, hydrological processes, extreme events, and water management in urban systems.

This Special Issue welcomes manuscripts that link the following themes:

• Physically based and data-driven urban flood models;
• Coupled hydrological–hydrodynamic modeling;
• Real-time flood forecasting systems;
• Machine learning and AI in flood prediction;
• Urban drainage and stormwater management;
• Climate change impacts on urban flooding;
• Uncertainty analysis and statistical models;
• Early warning systems and decision-support tools;
• Case studies and comparative analyses;
• Review papers on emerging methodologies.

We look forward to receiving your original research articles and reviews.

Dr. Omayma Amellah
Prof. Dr. Carmen Maftei
Dr. Romulus Costache
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• urban flooding
• hydrological modeling
• flood forecasting
• early warning systems
• urban drainage
• machine learning
• climate change
• hydrodynamic modeling