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Urban Flood Risk Assessment and Management
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Urban Flood Risk Assessment and Management

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 28 October 2026 | Viewed by 1379

Special Issue Editors

Prof. Dr. Matjaž Mikoš

E-Mail Website
Guest Editor
Research Institute on Geo- and Hydro-Threats (RIGHT), Faculty of Civil and Geodetic Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia
Interests: hydrology; natural hazards; torrent control; erosion and sedimentation cycle; sediment transport; soil erosion
Dr. Damir Bekić

E-Mail Website
Guest Editor Assistant
Faculty of Civil Engineering, University of Zagreb, Fra Andrije Kačića-Miošića 26, 10 000 Zagreb, Croatia
Interests: hydrology; flooding; remote sensing; modelling; evapotranspiration

Special Issue Information

Dear Colleagues,

Floods are among the most frequent and devastating natural disasters, accounting for 44% of all disaster events worldwide and affecting 1.6 billion people between 2000 and 2019. Rapid urbanization is intensifying this challenge. Today, more people live in cities than in rural areas, and by 2050, an estimated 70% of the global population will be urban residents. As cities expand—often without adequate planning, infrastructure, or sustainable development practices, particularly in developing regions—drainage systems and urban infrastructure face mounting stress.

Climate change further compounds these issues. Increasingly frequent and intense rainfall events, combined with growing areas of impervious surfaces and aging drainage systems, are elevating peak discharges and overwhelming urban infrastructure. The pace of drainage system improvements often lags behind urban growth, heightening the vulnerability of densely populated areas to flooding. Consequently, urban floods now represent one of the most widespread and damaging hazards for cities worldwide, threatening lives, assets, and economic activities. To address these challenges, city leaders and municipal agencies must adopt forward-looking strategies, integrating climate adaptation and sustainable, risk-informed investments into urban planning.

This Special Issue seeks contributions that advance understanding and practice in the assessment and management of urban flood risk in the context of climate change and socioeconomic development. We welcome the following:

  • Original research on integrated urban flood assessments,
  • Innovative approaches to urban flood risk management,
  • Case studies and recent experiences from diverse contexts, and
  • Comprehensive reviews synthesizing current knowledge and future directions.

By sharing contemporary insights and innovative solutions, we aim to contribute to shaping more resilient and sustainable urban futures.

We look forward to your valuable contributions.

Prof. Dr. Matjaž Mikoš
Guest Editor

Dr. Damir Bekić
Guest Editor Assistant

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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly 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 2600 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.

Keywords

  • urban flooding
  • flood risk assessment
  • integrated flood risk management
  • drainage system
  • low-impact development
  • nature-based solutions
  • green infrastructure
  • surface water
  • ground water
  • rainfall–runoff mod-eling
  • spatial planning
  • stakeholder engagement

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Published Papers (2 papers)

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Research

31 pages, 5049 KB  
Article
Loss of Life in River and Flash Floods in Europe: Evaluation of Deterministic Approaches and Implications for Risk Assessment
by Damir Bekić
Water 2026, 18(9), 1011; https://doi.org/10.3390/w18091011 - 23 Apr 2026
Viewed by 564
Abstract
This study evaluates deterministic flood fatality models using a harmonised dataset of river and flash flood events in Europe (1980–2024). The objective is to quantify differences across data sources and critically assess the applicability of commonly used prediction models for hydrological floods, with [...] Read more.
This study evaluates deterministic flood fatality models using a harmonised dataset of river and flash flood events in Europe (1980–2024). The objective is to quantify differences across data sources and critically assess the applicability of commonly used prediction models for hydrological floods, with particular emphasis on flash floods, which remain poorly represented in existing methodologies. The analysis integrates large-scale databases on flood fatalities (HANZE, EM-DAT) with detailed event-based studies containing hazard and other indicators, enabling a combined evaluation from different sources. Three model groups are assessed by comparing predicted and observed fatalities: Damage–Fatality, Depth–Fatality, and Depth–Velocity–Fatality approaches. Results confirm discrepancy between exposure and mortality: river floods dominate in terms of affected population (87%) and economic losses (71%), whereas flash floods account for nearly half of all fatalities despite affecting only 13% of people. All evaluated models show significant limitations for prediction of flash floods fatalities; single-parameter approaches perform poorly, while multi-parameter models remain highly sensitive to uncertain hydraulic inputs. The study demonstrates that current methods are not transferable to flash flood conditions and highlights the need for integrated, multi-variable approaches supported by consistent and high-quality datasets. The main contributions of the study are the first systematic validation of widely used models against historical river and flash flood events, revealing their uncertainties, and a comprehensive assessment of their robustness and sensitivity to key input indicators. Full article
(This article belongs to the Special Issue Urban Flood Risk Assessment and Management)
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34 pages, 8819 KB  
Article
Mitigating Overfitting and Physical Inconsistency in Flood Susceptibility Mapping: A Physics-Constrained Evolutionary Machine Learning Framework for Ungauged Alpine Basins
by Chuanjie Yan, Lingling Wu, Peng Huang, Jiajia Yue, Haowen Li, Chun Zhou, Congxiang Fan, Yinan Guo and Li Zhou
Water 2026, 18(7), 882; https://doi.org/10.3390/w18070882 - 7 Apr 2026
Viewed by 478
Abstract
Flood susceptibility mapping in high-altitude ungauged basins faces a structural dichotomy: physically based models often suffer from systematic biases due to uncertain satellite precipitation, whereas data-driven models are prone to overfitting and lack physical consistency in data-scarce regions. To resolve this, this study [...] Read more.
Flood susceptibility mapping in high-altitude ungauged basins faces a structural dichotomy: physically based models often suffer from systematic biases due to uncertain satellite precipitation, whereas data-driven models are prone to overfitting and lack physical consistency in data-scarce regions. To resolve this, this study proposes a Physically constrained Particle Swarm Optimization–Random Forest (P-PDRF) framework, validated in the Lhasa River Basin. The core innovation lies in coupling a hydrological model with statistical learning by utilizing the maximum daily runoff depth as a “Relative Hydraulic Intensity Index.” This approach leverages the topological correctness of physical simulations to circumvent absolute forcing errors. Furthermore, a Physiographically Constrained Negative Sampling (PCNS) strategy and a PSO-optimized “Shallow Tree” configuration are introduced to enforce structural regularization against stochastic noise. Empirical results demonstrate that P-PDRF achieves superior generalization (AUC = 0.942), significantly outperforming standard Random Forest, Support Vector Machine, and Analytic Hierarchy Process models. Ablation studies confirm that the dynamic index outweighs the static Topographic Wetness Index in feature importance, effectively correcting topographic artifacts where static models misclassify arid depressions as high-risk zones. This study offers a scalable Physics-Informed Machine Learning solution for the global “Prediction in Ungauged Basins” initiative. Full article
(This article belongs to the Special Issue Urban Flood Risk Assessment and Management)
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