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Hydrology
Special Issues
Urban Hydrology and Hydroclimate Resilience for Climate Change Adaptation
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Urban Hydrology and Hydroclimate Resilience for Climate Change Adaptation

A Special Issue of Hydrology (ISSN 2306-5338) belonging to the section "Hydrology–Climate Interactions".

Deadline for manuscript submissions: 30 November 2026 | Viewed by 1569

Editors

Dr. Qijie Li

E-Mail Website
Guest Editor
Planning Building Environment, Technische Universität Berlin, Berlin, Germany
Interests: hydro-environmental systems; resilient urban built environments; urban resilience and multi-hazard risk reduction; flood modelling and risk management in underground space; intelligent hydro-informatic systems for sustainable cities and society
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Reinhard Hinkelmann

E-Mail Website
Guest Editor
Chair of Water Resources Management and Modeling of Hydrosystems, Technische Universität Berlin, Gustav-Meyer-Allee 25, 13355 Berlin, Germany
Interests: modeling of flow and transport processes in surface waters; modeling of flow and transport processes in subsurface systems; model development and hydro-informatics
Prof. Dr. Dongfang Liang

E-Mail Website
Guest Editor
Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK
Interests: fluid mechanics; hydrodynamics; sediment transport; granular flow; pollutant transport; water quality; computational methods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Global warming, exacerbated by rapid urbanization, is driving an upward trend in extreme weather. Urban hydrological systems are undergoing unprecedented stress due to the dual pressures of climate change and rapid urbanization. The increasing intensity and frequency of extreme precipitation events have exposed vulnerabilities in aging urban drainage infrastructures, leading to more frequent surface flooding, combined sewer overflows, and critical disruptions to underground facilities. Advances in hydrological and hydraulic modelling, including physically based distributed models, data-driven methods, and hybrid approaches, have become indispensable tools for understanding and predicting urban flood dynamics under future climate scenarios. Coupled with real-time monitoring, GIS-based spatial analysis, and scenario-based simulations, these models provide critical insights into system performance and potential adaptation pathways. By focusing on interdisciplinary and computationally advanced methodologies, this Special Issue seeks to support the development of resilient and adaptive urban water systems aligned with sustainable development and climate resilience objectives.

The goal of this Special Issue is to present papers (original research articles and review papers) that give comprehensive insights into urban hydro-system modelling and urban resilience, exploring how cities and communities respond to climate change, and how these responses align with the Sustainable Development Goals.

This Special Issue will welcome manuscripts that link the following themes:

  • Modelling of urban flood processes;
  • Climate adaptation in urban water systems;
  • Risk mapping and early warning systems;
  • Urban resilience quantification and optimization;
  • Systems-based approaches to multi-hazard risk reduction;
  • Real-time flood modelling and risk management;
  • AI-based hydroinformatics modelling;
  • Adaptive resilience of infrastructure for climate change adaptation.

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

Dr. Qijie Li
Prof. Dr. Reinhard Hinkelmann
Prof. Dr. Dongfang Liang
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.

Keywords

  • urban hydrology
  • urban resilience
  • climate change adaption
  • hydrological and hydrodynamic modelling
  • risk assessment
  • multi-hazard risk reduction

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

16 pages, 14487 KB  
Article
Modeling the Potential of a Roadside Two-Stage Ditch to Reduce Flooding and Erosion Risks
by Keith E. Schilling, Elliot S. Anderson, Ingrid Cintura, Betret Stanley Eustace and Antonio Arenas Amado
Hydrology 2026, 13(8), 220; https://doi.org/10.3390/hydrology13080220 - 17 Aug 2026
Viewed by 379
Abstract
Recent efforts to address flooding have explored incorporating flow-reduction capabilities into existing infrastructure. Roadside ditches have historically been viewed as an underutilized component of flood reduction, and a two-stage design has been proposed that modifies a conventional trapezoidal ditch by incorporating bench insets [...] Read more.
Recent efforts to address flooding have explored incorporating flow-reduction capabilities into existing infrastructure. Roadside ditches have historically been viewed as an underutilized component of flood reduction, and a two-stage design has been proposed that modifies a conventional trapezoidal ditch by incorporating bench insets along the main channel. While it is expected that this second stage becomes inundated during storm events, resulting in flow attenuation, the exact impacts of this design are unknown. This study quantified the impact of the two-stage design by modeling a roadside ditch corridor in eastern Iowa. An existing single-stage ditch was converted to a two-stage design, and a HEC-RAS model was constructed to investigate the ditch’s impacts for four design storms (1-year, 2-year, 5-year, and 10-year). In the modeled results, peak flow rates were reduced by 22%, 21%, 7.5%, and 4.3%, respectively, while water volume reductions were near 6%. Maximum velocities throughout the ditch corridor also decreased, with reductions spanning 32% (1-year)–45% (10-year). These results indicate that increased travel times and infiltration associated with the two-stage design provide hydrologic and hydraulic benefits by lessening flood and erosion risk. While further study is needed to verify this behavior through monitoring and modeling at other locations, our findings suggest that two-stage ditches can be a useful best management practice for the transportation community. Full article
(This article belongs to the Special Issue Urban Hydrology and Hydroclimate Resilience for Climate Change Adaptation)
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24 pages, 16916 KB  
Article
Deciphering Urban Flood Drivers: An Explainable Machine Learning Approach to Vulnerability Assessment in Indonesian Catchments
by Ahyahudin Sodri, Geovanny Branchiny Imasuly, Nuraeni Nuraeni and Annisa Layyina Ihsani
Hydrology 2026, 13(7), 184; https://doi.org/10.3390/hydrology13070184 - 11 Jul 2026
Viewed by 466
Abstract
Flooding is one of the most frequent and damaging natural disasters, accounting for nearly half of global disasters and posing a major challenge in Indonesia, where floods represent approximately 77% of all nationally recorded disaster events. Rapid urbanisation, land-use change, and climate-induced extreme [...] Read more.
Flooding is one of the most frequent and damaging natural disasters, accounting for nearly half of global disasters and posing a major challenge in Indonesia, where floods represent approximately 77% of all nationally recorded disaster events. Rapid urbanisation, land-use change, and climate-induced extreme rainfall have intensified flood risks nationwide. However, existing vulnerability assessments remain fragmented and localised, limiting their relevance for national-scale adaptation planning. This study develops a measurable and explainable framework for assessing urban flood vulnerability across Indonesia using cloud-based geospatial data and interpretable machine learning. The approach integrates CEMS-GLOFAS (flood hazard), WorldPop (population exposure), SRTM (topography), and ESA WorldCover (land cover) datasets within Google Earth Engine (GEE). Flood vulnerability is quantified through a modified Flood Vulnerability Index (FVI) combining hazard, exposure, and physical vulnerability components. The Extreme Gradient Boosting (XGBoost) model predicts FVI values, while SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs) enhance model transparency and identify the influence of key variables such as flood depth, population density, and elevation. The model achieved high predictive accuracy (R2 = 0.89; RMSE = 0.04728 FVI units, dimensionless) and revealed substantial spatial heterogeneity across 514 districts, with the highest FVI (0.75–0.85) in Banda Aceh, Mojokerto, Pasuruan, Samarinda, and Merauke. The integration of GEE and explainable AI offers a transparent, scalable framework to support data-driven flood risk mitigation and urban climate resilience in Indonesia. Full article
(This article belongs to the Special Issue Urban Hydrology and Hydroclimate Resilience for Climate Change Adaptation)
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