Understanding, Forecasting and Control of Flooding and Pollution in the Urban Environment: The 10th Anniversary of Hydrology

A special issue of Hydrology (ISSN 2306-5338).

Deadline for manuscript submissions: 31 March 2025 | Viewed by 4673

Special Issue Editors


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Water Resources Engineering, Newcastle University, Newcastle, UK
Interests: hydrological modelling; hydrology and water resources management; climate change impact assessment; flood risk estimation and management; rainfall modelling; earth systems engineering

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Guest Editor
Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy
Interests: river hydraulics and hydro-morphology; bed-load sediment transport; scour processes; river morphology; sediment yield from mountain catchments; flood risk
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Guest Editor
Biological and Environmental Engineering, Cornell University, Ithaca, NY 14850, USA
Interests: watershed management; catchment processes; agricultural water management erosion; best management practices; groundwater quality; vadose zone transport; preferential flow
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National Research Council of Italy, Research Institute for Geo-Hydrological Protection (CNR-IRPI), 87036 Rende, CS, Italy
Interests: hydrology; climatology; climate change; natural hazards; land use change; forest ecology
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Italian Hydrological Society, Piazza di Porta San Donato 1, 40126 Bologna, Italy
Interests: hydrological modeling; real-time flood forecasting; predictive uncertainty assessment; Kalman filters; Bayesian statistics and decision; water resources management
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Special Issue Information

Dear Colleagues,

In 2024, we are celebrating the 10th anniversary of the journal Hydrology (ISSN 2306-5338). Since 2014, when the inaugural issue of Hydrology was launched, we have already published more than 1000 papers from over 3800 authors. Nearly 2200 reviewers have submitted at least one review report. In 2023, Hydrology received its first Impact Factor of 3.2 in Web of Science. Our sincerest thanks go to our readers, innumerable authors, anonymous peer reviewers, editors, and all the people working for the journal in some way who have contributed their efforts over the years. These achievements would not have been made without your participation.

To mark this significant milestone, a Special Issue entitled “Understanding, Forecasting and Control of Flooding and Pollution in the Urban Environment: The 10th Anniversary of Hydrology” is being launched.

In 2024, major floods have led to extensive loss of life and economic damage in both developed and developing countries: e.g., Spain, Italy, Nepal, Sudan, and Brazil, to name but a few. In the aftermaths, it is usually reported that the citizens did not receive warnings, or the warnings were too late, despite the advances that have been made in flood forecasting and warning and IT communication in recent decades. In many cases, the water levels rise very rapidly; are the forecasting models able to predict this? Is there a lack of investment/reliance on out-of-date methods/a failure for research advances to be translated into practice?  Are there institutional failings/a lack of connectivity between the emergency agencies? These flood disaster events, exacerbated by wild urbanization and population growth, are increasing across the world, and are largely attributed to anthropogenic climate change by the media. But there is also large underlying natural climatic variability that is not always recognised. Do we have the balance right between investment in anthropogenic climate change mitigation and adaptation? After flooding disasters, climate scientists report on attribution to the effects increasing greenhouse gases, calling for more investment to reduce them, but is government investment in flood defence infrastructure given sufficient priority in the face of the increasing flood hazards?  Why is there continued building on flood plains despite the recurring disasters? Cities in many countries are expanding due to inward migration, increasing vulnerability.

There is also the problem of pluvial flooding in towns and cities due to intense rainfall, the frequency and magnitude of which have increased with climate change, overwhelming drainage networks and leading to repeated economic damage. This also, in some countries, has led to combined sewer overflow discharges which pollute rivers, lakes, and coastal areas with sewage, as has happened throughout the UK. This leads to health hazards for bathing, degraded water environments with loss of biodiversity, and loss of amenities. Urban and population growth are major drivers in this regard, and there is a lack of investment in the necessary drainage infrastructure in response. Pollution sources are frequently disputed between different polluters, so reliable attribution is needed if the ‘polluter pays’ principle is to be applied.

This Special Issue invites high-quality papers within the scope explained above and/or under the following specific headings. Contributions to a Discussion Forum (https://sciprofiles.com/discussion-groups/1680) are also invited under the same headings.

Understanding: From intense rainfall deluges to steep flood waves, what are the key triggers/mechanisms? What are the roles of topography/drainage network configuration/slope/land use in generating flood hazards? How do major floods become major loss-of-life disasters? How can the sources of pollution in urban areas be identified using attribution methods?

Modelling and forecasting: Coupling of meteorological and hydrological models; nowcasting using radar rainfall; forecasting of steep flood waves due to intense downpours. Inundation modelling in urban areas due to fluvial and pluvial flooding. Coupling of hydrological and sewer system models; modelling of sewer flooding, combined sewer overflows and associated pollution loads; forecasting of pollution incidents; attribution of pollution sources.

Performance of early warning systems: Evaluation of deterministic and probabilistic forecasts. Operational performance of flood warning systems: the forecast–warning–intervention chain and the decision-making procedures. The use of modern AI and IT technologies in dissemination, e.g., mobile phones/social media and drones; increasing public awareness; flood disaster rehearsals/gaming.

Control systems: How can flooding and pollution in urban areas be better controlled? Real-time control of flood gates, sluices, and diversion channels; use of smart sensors and AI for the control of flooding; smart sewer systems; model-based control algorithms.

Flood resilience: Smart design at various scales using resilient materials and construction techniques; blue-green infrastructure; sustainable urban drainage systems (SuDSs); flood proofing; limiting construction in flood-prone areas.

The human dimension: Institutional structures and their functioning/fitness for providing and disseminating warnings, organising evacuations, etc.; successes and failures in early warning dissemination; human judgement/decision-making in issuing flood warnings; agent-based modelling of human responses. Flood defence investment strategies under a changing climate—how are the decisions taken?

Prof. Dr. Enda O'Connell
Dr. Alessio Radice
Prof. Dr. Tammo Steenhuis
Dr. Tommaso Caloiero
Prof. Dr. Ezio Todini
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. 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

  • global hydrology
  • water quality
  • water management
  • ecohydrology
  • hydrological cycle

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Published Papers (2 papers)

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19 pages, 2946 KiB  
Article
Determination of Environmental Flow Using a Holistic Methodology in Three River Paths in the Tempisque River Basin, Costa Rica
by Laura Chavarría-Pizarro, Fernando Watson-Hernández, Francisco Quesada-Alvarado, Valeria Serrano-Núñez, Ana Lucía Bustos-Vásquez, Karina Fernández-Chévez, Jendry Chacón-Gutierrez and Isabel Guzmán-Arias
Hydrology 2024, 11(10), 159; https://doi.org/10.3390/hydrology11100159 - 27 Sep 2024
Viewed by 935
Abstract
The study of environmental flow has garnered significant scientific interest due to the considerable degradation caused by human activities on aquatic ecosystem dynamics. Environmental flow is defined as the quantity, timing, and quality of water flow required to sustain freshwater and estuarine ecosystems [...] Read more.
The study of environmental flow has garnered significant scientific interest due to the considerable degradation caused by human activities on aquatic ecosystem dynamics. Environmental flow is defined as the quantity, timing, and quality of water flow required to sustain freshwater and estuarine ecosystems while meeting human demands. Research in riverine ecosystems can generate the critical scientific knowledge needed to determine an adequate environmental flow that balances the requirements of both aquatic organisms and human populations. This study is part of a series of investigations aimed at field-testing different methodologies to determine appropriate environmental flow levels for rivers with specific characteristics. In particular, we adapted and validated a holistic methodology for calculating the environmental flow regime in the Tempisque River basin in Costa Rica. This research involved analyzing hydrological parameters, hydraulic conditions, the presence of flow bioindicators, and various anthropogenic uses of the river (such as human consumption, productive, recreational, and cultural activities) to estimate environmental flow requirements throughout the year. The findings indicate that the lower and upper limits of the environmental flow for the studied section of the Tempisque River correspond to the monthly excesses of 95.00% and 64.00%, respectively. These results provide a reliable annual flow regime that can inform decision-making by authorities in water resource management, particularly in regions where there is a high demand for water across different human activities. Full article
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22 pages, 2747 KiB  
Article
Utilizing Hybrid Machine Learning Techniques and Gridded Precipitation Data for Advanced Discharge Simulation in Under-Monitored River Basins
by Reza Morovati and Ozgur Kisi
Hydrology 2024, 11(4), 48; https://doi.org/10.3390/hydrology11040048 - 4 Apr 2024
Cited by 2 | Viewed by 2189
Abstract
This study addresses the challenge of utilizing incomplete long-term discharge data when using gridded precipitation datasets and data-driven modeling in Iran’s Karkheh basin. The Multilayer Perceptron Neural Network (MLPNN), a rainfall-runoff (R-R) model, was applied, leveraging precipitation data from the Asian Precipitation—Highly Resolved [...] Read more.
This study addresses the challenge of utilizing incomplete long-term discharge data when using gridded precipitation datasets and data-driven modeling in Iran’s Karkheh basin. The Multilayer Perceptron Neural Network (MLPNN), a rainfall-runoff (R-R) model, was applied, leveraging precipitation data from the Asian Precipitation—Highly Resolved Observational Data Integration Toward Evaluation (APHRODITE), Global Precipitation Climatology Center (GPCC), and Climatic Research Unit (CRU). The MLPNN was trained using the Levenberg–Marquardt algorithm and optimized with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Input data were pre-processed through principal component analysis (PCA) and singular value decomposition (SVD). This study explored two scenarios: Scenario 1 (S1) used in situ data for calibration and gridded dataset data for testing, while Scenario 2 (S2) involved separate calibrations and tests for each dataset. The findings reveal that APHRODITE outperformed in S1, with all datasets showing improved results in S2. The best results were achieved with hybrid applications of the S2-PCA-NSGA-II for APHRODITE and S2-SVD-NSGA-II for GPCC and CRU. This study concludes that gridded precipitation datasets, when properly calibrated, significantly enhance runoff simulation accuracy, highlighting the importance of bias correction in rainfall-runoff modeling. It is important to emphasize that this modeling approach may not be suitable in situations where a catchment is undergoing significant changes, whether due to development interventions or the impacts of anthropogenic climate change. This limitation highlights the need for dynamic modeling approaches that can adapt to changing catchment conditions. Full article
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