The role of hyetograph shape and designer subjectivity in the design of an urban drainage system.

Even though it has been established that a hyetograph's shape affects the results of hydrological simulations, common engineering practice does not always account for this fact. Instead, a single design storm is often considered sufficient for designing a urban drainage system. This study examines the impact that this design paradigm, combined with the uncertainty introduced by subjective choices made during the design process, has on the robustness of a designed system.

Hotspot analysis for integrated multi-infrastructure asset management.

Urban infrastructure, important for societal functioning, faces challenges from aging assets and increasing service demands. Traditional asset management practices, often conducted in silos, fail to address the interconnected nature of these systems, leading to inefficiencies and heightened system failure risks. This article combines the spatial and temporal aspects of sewer, water, and road networks to facilitate integrated interventions and enable informed decision-making among diverse stakeholders.

Embracing epistemic uncertainty: a risk evaluation method for pollutants in stormwater.

In this study, we show that pollutants of emerging concern are, by nature, prone to the emergence of epistemic uncertainty. We also show that the current uncertainty quantification methods used for pollutant modelling rely almost exclusively on parameter uncertainty, which is not adequate to tackle epistemic uncertainty affecting the model structure. We, therefore, suggest a paradigm shift in the current pollutant modelling approaches by adding a term explicitly accounting for epistemic uncertainties.

Metrics to quantify the degree of co-location of urban water infrastructure.

Co-located infrastructure networks such as road, water, and sewer in theory offer the possibility for integrated multi-infrastructure interventions. However, how closely these networks are aligned in space and time determines the practical extent to which such coordinated interventions can be realized. This study quantifies the spatial alignment of the aforementioned infrastructure networks and demonstrates its application for integrated interventions and potential cost savings.

Towards transferable metamodels for water distribution systems with edge-based graph neural networks.

Data-driven metamodels reproduce the input-output mapping of physics-based models while significantly reducing simulation times. Such techniques are widely used in the design, control, and optimization of water distribution systems. Recent research highlights the potential of metamodels based on Graph Neural Networks as they efficiently leverage graph-structured characteristics of water distribution systems.

A deep dive into green infrastructure failures using fault tree analysis.

Green Infrastructure has transformed traditional urban stormwater management systems by fostering a wide range of service functions. Despite their popularity, green infrastructure's performance can deteriorate over their lifecycle, leading to operational failures. The operation of green infrastructure has predominantly relied on reactive maintenance strategies.

Uncertainty analysis in a large-scale water quality integrated catchment modelling study.

Receiving water quality simulation in highly urbanised areas requires the integration of several processes occurring at different space-time scales. These integrated catchment models deliver results with a significant uncertainty level associated. Still, uncertainty analysis is seldom applied in practice and the relative contribution of the individual model elements is poorly understood.

What can we learn from a 500-year event? Experiences from urban drainage in Austria.

Urban drainage systems are designed to capture the runoff for a certain return period of a design rainfall event. Typically, numerical models are used, which are calibrated by comparing model response and measured system performance. The applicability of such models to predict the system behaviour under extreme events is unclear, as usually then no data are available.

Lost in calibration: why people still do not calibrate their models, and why they still should - a case study from urban drainage modelling.

From a scientific point of view, it is unquestioned that numerical models for technical systems need to be calibrated. However, in sufficiently calibrated models are still used in engineering practice. Case studies in the scientific literature that deal with urban water management are mostly large cities, while little attention is paid to the differing boundary conditions of smaller municipalities.

Adaptation of sewer networks using integrated rehabilitation management.

The urban water structure is aging and in need of rehabilitation. Further, the need to address future challenges (climate change, urban development) also arise lines. This study investigates if it is possible to combine rehabilitation and adaptation measures.

Integrated planning of rehabilitation strategies for sewers.

Building measures in sewer systems are increasingly driven by rehabilitation/retrofitting and adaptation needs. Aging infrastructure together with changing boundary conditions (due to climate change, land-use change, demographic change) and also changing design standards and legislation require a prospective design to preserve the functionality of urban drainage systems not only today, but also in a long-term perspective. To improve a prospective design of urban water infrastructure, the Austrian Research Promotion Agency funded the research project 'REHAB - Integrated planning of rehabilitation strategies of urban infrastructure systems'.