Franz Tscheikner-Gratl

Integrated rehabilitation planning of urban infrastructure systems using a street section priority model

Abstract Due to the changes in water management, from the construction of new systems to the rehabilitation of existing networks, integrated strategic rehabilitation management has become more and more important. Consequently, this paper shows a method that considers sewer and water distribution networks against environmental factors (e.g. street network and connected buildings) in a priority model. This approach aids in not only identifying areas where rehabilitation is technically necessary but also economically recommendable (e.g. completely depreciated). This is achieved by implementing factors of structural resiliency, vulnerability of the network, capital value and other network components (e.g. manholes, house connections). This model is applied to a medium sized case study in which the rehabilitation areas identified by the developed model are compared to the actual rehabilitation plans of the water and sewage companies. Results also show the application of the estimated ranking for rehabilitation planning with a fixed budget.

Enhancement of limited water supply network data for deterioration modelling and determination of rehabilitation rate

In the past decades, the main focus of water supply management has moved from construction of new water supply networks to rehabilitation and adaptation of the existing infrastructure. The decision-making process for the rehabilitation management relies heavily on the quality of the applied deterioration model. A recurring problem in the application of such models relates to the quality and availability of network data. These data are often incomplete or unreliable because building measures and damages are only documented properly recently and the recovery of older data is difficult and expensive. A key point in rehabilitation planning is therefore data collection and data reconstruction. Consequently, the aim of this paper is to present a methodology for the enhancement of the available data of water supply networks and the prognosis of the necessary rehabilitation rates under limited data availability. Results indicate that the presented data reconstruction technique has advantages as compared to traditional data extrapolation. It also allows the reconstruction of fragmentary data about existing water supply and wastewater collection systems for the operating utilities. However, it cannot be used for reconstructing failure types as well as the whole information on pipes (e.g. more than two missing information).

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. To do so, we combined an urban development model, an urban drainage model and a rehabilitation model. A case study of a medium-sized alpine city with a sewer length of 228 km and a population of 125,431 was used to develop and apply this method. A priority model to pinpoint the structures in need of replacement was used. This model considered a deterioration model, vulnerability estimation and other influences. Further different rehabilitation rates and methods were examined. The urban development model used is a simplistic approach specifically tailored for the field of urban infrastructure management. Climate change is considered in terms of climate change factors. All these different influences together create scenarios for which the construction costs and the flooding volume are estimated and compared. Consequently the aim of this paper was to test to which degree it is possible to reduce urban flooding by adapting those parts of the network which require rehabilitation anyway. In our case study it could be reduced by 5%.

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. This paper describes the analysis of an extreme rainfall event in the year 2016. The event is characterized by a very short duration and very high rainfall intensities. The maximum-recorded rainfall peak was 47.1 mm rainfall within 10 min, which corresponds to a return period of 500 years. The event caused local flooding on streets, interruptions of traffic and damages in buildings. In order to improve the flood resilience of the city, the event was analysed with an existing 1D hydrodynamic model of the sewer system. Model results were compared to water level measurements in the drainage system and citizen observations of surface flooding (gathered from social media and citizen reports). Although the hydrodynamic model could reproduce water level measurements in parts of the system, the plausibility check using descriptive data showed that the model failed to predict flooding in some areas.

Decision Support for Adaptation Planning of Urban Drainage Systems

AbstractUrban drainage networks are under constant pressure caused by a permanently changing environment. For proactive planning, management, and adaptation of urban water infrastructure, a robust ...

Pipe failure modelling for water distribution networks using boosted decision trees

Abstract Pipe failure modelling is an important tool for strategic rehabilitation planning of urban water distribution infrastructure. Rehabilitation predictions are mostly based on existing network data and historical failure records, both of varying quality. This paper presents a framework for the extraction and processing of such data to use it for training of decision tree-based machine learning methods. The performance of trained models for predicting pipe failures is evaluated for simple as well as more advanced, ensemble-based, decision tree methods. Bootstrap aggregation and boosting techniques are used to improve the accuracy of the models. The models are trained on 50% of the available data and their performance is evaluated using confusion matrices and receiver operating characteristic curves. While all models show very good performance, the boosted decision tree approach using random undersampling turns out to have the best performance and thus is applied to a real world case study. The applicability of decision tree methods for practical rehabilitation planning is demonstrated for the pipe network of a medium sized city.

Integrated Rehabilitation Management by Prioritization of Rehabilitation Areas for Small and Medium Sized Municipalities

The lifespan of urban water networks (e.g. water supply and sewer) and other infrastructure systems (gas distribution, streets, etc.) is limited. While for networks in larger municipalities (>50,000 inhabitants) various rehabilitation models exist, rehabilitation management of networks in small municipalities (water supply, sewer, gas supply, etc.) usually depends mainly on expert knowledge and the experience of engineers, as models and reliable data for these networks are often missing. To analyze this problem, we investigated the integrated rehabilitation of infrastructure networks of a small municipality (13,100 inhabitants). Since, water supply, sewer and gas distribution network and condition/failure data were available, an integrated, multi-utility approach is enabled. For rehabilitation management a prioritization of street sections containing all available infrastructure was applied. Jointly with the priority of each network an overall priority of the areas is estimated for an integrated rehabilitation management.

Selecting a series of storm events for a model-based assessment of combined sewer overflows

ABSTRACT The hydraulic verification of combined sewer systems as well as the assessment of combined sewer overflows (CSOs) can be conducted using a hydrodynamic model. Unfortunately, long-term simulations with hydrodynamic models for the assessment of CSOs can cause unacceptably long computation times. Using only a series of storm events instead of a precipitation continuum can reduce this time and enables parallel simulation of single storm events. We introduce a method to select this series of storm events. The method’s parameters have been optimized to replicate the overflow volume of the continuous simulation and to minimize the overall computation time. This optimization revealed a generally applicable parameter set that results in series of storm events that are shorter than the precipitation continuum by 86.2–95.2% for the investigated cases. Additionally, the deviation of overflow volume between continuous simulation and series simulation ranges between only 0.1% and 4.1%.