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Infrastructures
Special Issues
Preserving Life Through Dams
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Preserving Life Through Dams

A special issue of Infrastructures (ISSN 2412-3811).

Deadline for manuscript submissions: closed (31 October 2025) | Viewed by 3495

Special Issue Editors

Dr. Laura Caldeira

E-Mail Website
Guest Editor
National Laboratory for Civil Engineering, LNEC, Av. do Brasil 101, 1700-066 Lisbon, Portugal
Interests: geotechnical engineering; embankment dams; risk management; seismic risk; constitutive models; laboratorial an in situ characterization of soils; observation and behaviour of geotechnical structure
Dr. Carlos Pina

E-Mail Website
Guest Editor
National Laboratory for Civil Engineering, LNEC, Av. do Brasil 101, 1700-066 Lisbon, Portugal
Interests: concrete dams; computational mechanics; physical modeling; mechanical behavior of concrete; structural health monitoring; earthquake engineering; rock mechanics
Prof. Dr. Teresa Viseu

E-Mail Website
Guest Editor
National Laboratory for Civil Engineering, LNEC, Av. do Brasil 101, 1700-066 Lisbon, Portugal
Interests: dam hydraulics; dam appurtenant structures; dam hydraulic safety; dam failure; emergency action plans

Special Issue Information

Dear Colleagues,

We are delighted to introduce this Special Issue of Infrastructures, dedicated to showcasing the latest advancements in dam engineering. This issue compiles a selection of high-quality papers presented at the Fifth International DAM WORLD Conference, which took place in Lisbon from April 13 to 17, 2025.

The DAM WORLD Conference brought together leading experts, researchers, and practitioners from around the globe to exchange knowledge, discuss challenges, and present innovations in the field of dam engineering. The conference covered a broad spectrum of themes, including the following:

- Concrete and masonry dams;
- Embankment dams and levees;
- Hydraulics for dams;
- Tailings dams;
- Environmental and social issues;
- Regulation and governance;
- Dams and climate.

The conference provided a platform for lively discussions on the latest research findings, technological innovations, and best practices. The presentations and discussions focused on both traditional dam structures and emerging challenges such as climate change, sustainability, and environmental and social considerations. By addressing these crucial topics, the conference helped pave the way for future advancements in dam safety, design, and management.

This Special Issue includes a selection of papers that reflect the diversity and depth of the discussions at the conference. From advanced analytical techniques for assessing dam safety to case studies highlighting innovative design solutions, these papers offer valuable insights for professionals and academics alike. We are confident that this collection will serve as a reference point for the ongoing development of safer, more efficient, and environmentally conscious dam infrastructure.

We hope this Special Issue will inspire further research and collaboration in the field of dam engineering, building on the foundation laid during the Fifth International DAM WORLD Conference.

Dr. Laura Caldeira
Dr. Carlos Pina
Prof. Dr. Teresa Viseu
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Infrastructures 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

  • dams
  • concrete
  • embankment
  • levees
  • tailings dams
  • hydraulic
  • hydrology
  • foundation
  • geology
  • design
  • models
  • safety
  • seismic analysis
  • instrumentation
  • monitoring
  • construction
  • rehabilitation
  • operation
  • maintenance
  • deterioration
  • decommissioning
  • dam management
  • new technologies
  • risk assessment
  • emergency action plans
  • dam failure
  • sedimentation in reservoirs
  • climate change

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

Published Papers (4 papers)

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Research

19 pages, 4731 KB  
Article
In Situ Estimation of Breach Outflow Hydrographs from Fluvial Dike Failures: A Methodology Integrating Real-Time Monitoring and Physical Modelling
by Ricardo Jónatas, Sílvia Amaral, Rui Aleixo, João Bilé Serra and Rui M. L. Ferreira
Infrastructures 2025, 10(12), 335; https://doi.org/10.3390/infrastructures10120335 - 5 Dec 2025
Viewed by 160
Abstract
Embankment structures in civil engineering, such as earth dams and fluvial dikes, have a crucial role in society. These structures, often used for water storage and mining tailing containment, are cost-effective due to their reliance on locally sourced materials. While the failure of [...] Read more.
Embankment structures in civil engineering, such as earth dams and fluvial dikes, have a crucial role in society. These structures, often used for water storage and mining tailing containment, are cost-effective due to their reliance on locally sourced materials. While the failure of concrete structures is not so frequent but often lead to severe consequences, embankment structures, particularly fluvial dikes, are more prone to breach and the consequences vary from mild to catastrophic, depending on the proximity to human populations. Worldwide, some fluvial dike failures have resulted in catastrophic outcomes for human lives, the local economy and the environment. This paper aims to develop a methodology to calculate in situ breach outflow hydrographs, resorting to real-time, non-intrusive and friendly access technology. The goal is to provide a practical platform for developing and testing integrated systems applicable to prototype failure cases. An accurate, real-time hydrograph estimation capacity improves risk assessment. The proposed methodology deploys, in a medium-scale experimental facility, common technology and data processing techniques to characterize the evolution of a fluvial dike failure. The morphodynamic and hydrodynamic components influencing the in situ breach outflow hydrograph are assessed by characterizing, in real-time, the breach morphology at the surface and underwater, the surface velocity maps and the corresponding cartesian coordinates. Full article
(This article belongs to the Special Issue Preserving Life Through Dams)
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17 pages, 4362 KB  
Article
Developing Statistical and Multilayer Perceptron Neural Network Models for a Concrete Dam Dynamic Behaviour Interpretation
by Andrés Mauricio Guzmán Sejas, Sérgio Pereira, Juan Mata and Álvaro Cunha
Infrastructures 2025, 10(11), 301; https://doi.org/10.3390/infrastructures10110301 - 9 Nov 2025
Viewed by 1224
Abstract
This work focuses on the dynamic monitoring behaviour of concrete dams, with a specific emphasis on the Baixo Sabor dam as a case study. The main objective of the dynamic monitoring is to continuously observe the dam’s behaviour, ensuring it remains within expected [...] Read more.
This work focuses on the dynamic monitoring behaviour of concrete dams, with a specific emphasis on the Baixo Sabor dam as a case study. The main objective of the dynamic monitoring is to continuously observe the dam’s behaviour, ensuring it remains within expected patterns and issuing alerts if deviations occur. The monitoring process relies on on-site instruments and behaviour models that use pattern recognition, thereby avoiding explicit dependence on mechanical principles. The undertaken work aimed to develop, calibrate, and compare statistical and machine learning models to aid in interpreting the observed dynamic behaviour of a concrete dam. The methodology included several key steps: operational modal analysis of acceleration time series, characterisation of the temporal evolution of observed magnitudes and influential environmental and operational variables, construction and calibration of predictive models using both statistical and machine learning methods, and the comparison of their effectiveness. Both Multiple Linear Regression (MLR) and Multilayer Perceptron Neural Network (MLP-NN) models were developed and tested. This work emphasised the development of several MLP-NN architectures. MLP-NN models with one and two hidden layers, and with one or more outputs in the output layer, were performed. The aim of this work is to assess the performance of MLP-NN models with different numbers of units in the output layer, in order to understand the advantages and disadvantages of having multiple models that characterise the observed behaviour of a single quantity or a single MLP-NN model that simultaneously learns and characterises the observed behaviour for multiple quantities. The results showed that while both MLR and MLP-NN models effectively captured and predicted the dam’s behaviour, the neural network slightly outperformed the regression model in prediction accuracy. However, the linear regression model is easier to interpret. In conclusion, both methods of linear regression and neural network models are suitable for the analysis and interpretation of monitored dynamic behaviour, but there are advantages in adopting a single model that considers all quantities simultaneously. For large-scale projects like the Baixo Sabor dam, Multilayer Perceptron Neural Networks offer significant advantages in handling intricate data relationships, thus providing better insights into the dam’s dynamic behaviour. Full article
(This article belongs to the Special Issue Preserving Life Through Dams)
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17 pages, 3043 KB  
Article
3D Effects on the Stability of Upstream-Raised Tailings Dams in Narrow Valleys
by Raul Conceição, Gonçalo Ferreira, Henrique Lopes and João Camões Lourenço
Infrastructures 2025, 10(10), 277; https://doi.org/10.3390/infrastructures10100277 - 15 Oct 2025
Viewed by 481
Abstract
Tailings dams are unique structures due to the materials they store and the methods applied in their construction, often resulting in complex three-dimensional (3D) problems. Most current slope-stability analyses neglect the 3D effects without significant consequences. However, certain conditions, such as the valley [...] Read more.
Tailings dams are unique structures due to the materials they store and the methods applied in their construction, often resulting in complex three-dimensional (3D) problems. Most current slope-stability analyses neglect the 3D effects without significant consequences. However, certain conditions, such as the valley shape, the spatial variability of the tailings’ resistance, and the presence of internal dikes, may render the 2D simplification inadequate. For translational slides, the sliding-mass width-to-height ratio (W/H) is a reliable estimator of the 3D effects. However, it is unclear whether this geometric ratio is the most suitable for rotational slides, where the width of the sliding mass varies along its height. This paper presents a parametric study of the 3D effects of the dam’s height (HM) and the valley shape, namely the abutments’ slope angle with the horizontal (β) and the thalweg width (LM), on the overall stability of a tailings dam raised by the upstream method, by means of 2D and 3D Limit Equilibrium (LE) analyses. The study evaluates the dam stability using a straightforward and practical methodology, specifically the FS3D to FS2D ratio (R3D/2D), to compare the results of the 3D and 2D analyses, adapting current state-of-the-art techniques originally for translational slides, focused on pre-defined, closed-form slip-surface geometry, to rotational ones where the main focus is the geometry of the whole structure as a physical constraint for the sliding mass. The results show that the model average width-to-height ratio (WM,avr/HM), developed in this study, may be a better estimator of the 3D effects for rotational slides than the W/H ratio. Full article
(This article belongs to the Special Issue Preserving Life Through Dams)
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20 pages, 7094 KB  
Article
Adaptive Warning Thresholds for Dam Safety: A KDE-Based Approach
by Nathalia Silva-Cancino, Fernando Salazar, Joaquín Irazábal and Juan Mata
Infrastructures 2025, 10(7), 158; https://doi.org/10.3390/infrastructures10070158 - 26 Jun 2025
Cited by 1 | Viewed by 988
Abstract
Dams are critical infrastructures that provide essential services such as water supply, hydroelectric power generation, and flood control. As many dams age, the risk of structural failure increases, making safety assurance more urgent than ever. Traditional monitoring systems typically employ predictive models—based on [...] Read more.
Dams are critical infrastructures that provide essential services such as water supply, hydroelectric power generation, and flood control. As many dams age, the risk of structural failure increases, making safety assurance more urgent than ever. Traditional monitoring systems typically employ predictive models—based on techniques such as the finite element method (FEM) or machine learning (ML)—to compare real-time data against expected performance. However, these models often rely on static warning thresholds, which fail to reflect the dynamic conditions affecting dam behavior, including fluctuating water levels, temperature variations, and extreme weather events. This study introduces an adaptive warning threshold methodology for dam safety based on kernel density estimation (KDE). The approach incorporates a boosted regression tree (BRT) model for predictive analysis, identifying influential variables such as reservoir levels and ambient temperatures. KDE is then used to estimate the density of historical data, allowing for dynamic calibration of warning thresholds. In regions of low data density—where prediction uncertainty is higher—the thresholds are widened to reduce false alarms, while in high-density regions, stricter thresholds are maintained to preserve sensitivity. The methodology was validated using data from an arch dam, demonstrating improved anomaly detection capabilities. It successfully reduced false positives in data-sparse conditions while maintaining high sensitivity to true anomalies in denser data regions. These results confirm that the proposed methodology successfully meets the goals of enhancing reliability and adaptability in dam safety monitoring. This adaptive framework offers a robust enhancement to dam safety monitoring systems, enabling more reliable detection of structural issues under variable operating conditions. Full article
(This article belongs to the Special Issue Preserving Life Through Dams)
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