Edwar Forero-Ortiz

There is an increasing demand to enhance infrastructure asset management within the drinking water sector. A key factor for achieving this is improving the accuracy of pipe failure prediction models. Machine learning-based models have emerged as a powerful tool in enhancing the predictive capabilities of water distribution network models. Extensive research has been conducted to explore the role of explanatory variables in optimizing model outputs. However, the underlying mechanisms of incorporating explanatory variable data into the models still need to be better understood. This review aims to expand our understanding of explanatory variables and their relationship with existing models through a comprehensive investigation of the explanatory variables employed in models over the past 15 years. The review underscores the importance of obtaining a substantial and reliable dataset directly from Water Utilities databases. Only with a sizeable dataset containing high-quality data can we better understand how all the variables interact, a crucial prerequisite before assessing the performance of pipe failure rate prediction models.

Dams are hydraulic infrastructure that have several purposes, such as irrigation, hydropower, water supply, flood control, recreation, fish breeding and navigation. However, their failure or malfunctioning can pose a threat to downstream communities, and thus, their safety is paramount to public protection and economic security. A variety of approaches to classify dams can be found in countries worldwide. Their classification allows to distinguish among those that are to be subject to safety regulation in each country. A common approach to classify them is according to their potential damage in case of failure. Roads are usually among the infrastructures that these approaches consider to be assessed in terms of the level of damage that can suffer. A new people-centred criterion is proposed in this paper to assess potential intangible damage (i.e. human lives) when roadways could be flooded due to a dam failure. This novel methodology is based on the Average Daily Traffic (ADT) of roadways and sets a maximum and a minimum number of vehicles expected in the area receiving the flood. To evaluate its appropriateness, it is verified from the results obtained after being applied to three existing ponds located in Catalonia (Spain).

Inferring the interactions between coupled oscillators is a significant open problem in complexity science, with multiple interdisciplinary applications. While the Kalman filter (KF) technique is a well-known tool, widely used for data assimilation and parameter estimation, to the best of our knowledge, it has not yet been used for inferring the connectivity of coupled chaotic oscillators. Here we demonstrate that KF allows reconstructing the interaction topology and the coupling strength of a network of mutually coupled Rössler-like chaotic oscillators. We show that the connectivity can be inferred by considering only the observed dynamics of a single variable of the three that define the phase space of each oscillator. We also show that both the coupling strength and the network architecture can be inferred even when the oscillators are close to synchronization. Simulation results are provided to show the effectiveness and applicability of the proposed method.

Once a wastewater treatment plant (WWTP) exceeds its capacity, it is necessary to discharge a proportion of the flow to watercourses through combined sewer overflow (CSO) structures. In coastal urban areas, CSO spills may occur in seawaters. The present study analyses the effects of these spills into urban coastal bathing areas, through a qualitative survey-based analysis in Badalona and Barcelona, focusing on stakeholders' reputation and image involved in the sewer system and beaches management (i.e. intangible damages) and the consequences for the economy (i.e. tangible damages). The direct relation between CSO spills and impacts on restaurants’ revenues is not observed since business owners in Badalona and Barcelona do not perceive any economic impact due to these events. Their main concern is the municipality’s image, which might affect the citizens’ view of the management of the responsible agents and indirectly, the tourist sector, especially in Barcelona. Residents perception in this matter is remarkably different in both cities. In Badalona, residents know the problem and even the body responsible for setting the red flag and the beaches closure (i.e. the municipality). In Barcelona, though, residents are quite confused about this. The complexity in terms of competencies in sewer systems management requires a better communication campaign for the citizens to avoid misunderstandings and unnecessary loss of trust in the City Council. Decision-makers and stakeholders should be interested in understanding the perception of affected users upon these events to take appropriate measures to enhance awareness programs or measures to reduce overflows.

The authors would like to make the following corrections about the published paper

The results of recent climate projections for the city of Barcelona show a relevant increment of the maximum rainfall intensities for the period 2071–2100. Considering the city as a system of systems, urban resilience is strictly linked to the proper functioning of urban services and the knowledge of the cascading effects that may occur in the case of the failure of one or more critical infrastructures of a particular strategic sector. In this context, the aim of this paper is to assess urban resilience through the analysis of the behavior of the main urban services in case of pluvial floods for current and future rainfall conditions due to climate change. A comprehensive flood risk assessment including direct, indirect, tangible and intangible impacts has been performed using cutting edge sectorial and integrated models to analyze the resilience of different urban services (urban drainage, traffic, electric and waste sectors) and their cascade effects. In addition, the paper shows how the information generated by these models can be employed to feed a more holistic analysis to provide a general overview of the city’s resilience in the case of extreme rainfall events. According to the obtained results, Barcelona could suffer a significant increase of socio-economic impacts due to climate change if adaptation measures are not adopted. In several cases, these impacts have been geographically distributed showing the specific situation of each district of the city for current and future scenarios. This information is essential for the justification and prioritization of the implementation of adaptation measures.

Flooding events can produce significant disturbances in underground transport systems within urban areas and lead to economic and socioenvironmental well-known consequences, which can be worsened by variations in the occurrence of weather and climate extremes. A better comprehension of these impacts and their conditions is consequently needed. Hence, this paper presents a state-of-the-art literature review on flood impact assessment in ‘metro’ systems, analysing their purposes and their shortcomings. This document shows the adaptation measures dealing with specific classes of pluvial flood damages, besides identifying prospective paths towards the application of suitable actions facing actual and projected hazards in metro systems worldwide.

Flooding events can produce significant disturbances in underground transport systems within urban areas and lead to economic and technical consequences, which can be worsened by variations in the occurrence of climate extremes. Within the framework of the European project RESCCUE (RESilience to cope with Climate Change in Urban arEas—a multi-sectorial approach focusing on water), climate projections for the city of Barcelona manifest meaningful increases in maximum rainfall intensities for the 2100 horizon. A better comprehension of these impacts and their conditions is consequently needed. A hydrodynamic modelling process was carried out on Barcelona Metro Line 3, as it was identified as vulnerable to pluvial flooding events. The Metro line and all its components are simulated in the urban drainage models as a system of computational link and nodes reproducing the main physical characteristics like slopes and cross-sections when embedded in the current 1D/2D hydrodynamic model of Barcelona used in the project RESCCUE. This study presents a risk analysis focused on ensuring transport service continuity in flood events. The results reveal that two of the 26 stations on Metro Line 3 are exposed to a high risk of flooding in current rainfall conditions, and 11 of the 26 stations on Metro Line 3 are exposed to a high risk of flooding in future rainfall conditions for a 20-year return period event, which affects Metro service in terms of increased risk. This research gives insights for stakeholders and policymakers to enhance urban flood risk management, as a reasonable approach to tackle this issue for Metro systems worldwide. This study provides a baseline for assessing potential flood outcomes in Metro systems and can be used to evaluate adaptation measures’ effectiveness.