Jon Røstum

Assessing mechanical vulnerability in water distribution networks under multiple failures

Understanding mechanical vulnerability of water distribution networks (WDN) is of direct relevance for water utilities since it entails two different purposes. On the one hand, it might support the identification of severe failure scenarios due to external causes (e.g., natural or intentional events) which result into the most critical consequences on WDN supply capacity. On the other hand, it aims at figure out the WDN portions which are more prone to be affected by asset disruptions. The complexity of such analysis stems from the number of possible scenarios with single and multiple simultaneous shutdowns of asset elements leading to modifications of network topology and insufficient water supply to customers. In this work, the search for the most disruptive combinations of multiple asset failure events is formulated and solved as a multiobjective optimization problem. The higher vulnerability failure scenarios are detected as those causing the lower supplied demand due to the lower number of simultaneous failures. The automatic detection of WDN topology, subsequent to the detachments of failed elements, is combined with pressure-driven analysis. The methodology is demonstrated on a real water distribution network. Results show that, besides the failures causing the detachment of reservoirs, tanks, or pumps, there are other different topological modifications which may cause severe WDN service disruptions. Such information is of direct relevance to support planning asset enhancement works and improve the preparedness to extreme events.

Statistical analysis and definition of blockages-prediction formulae for the wastewater network of Oslo by evolutionary computing

Oslo Vann og Avløpsetaten (Oslo VAV)-the water/wastewater utility in the Norwegian capital city of Oslo-is assessing future strategies for selection of most reliable materials for wastewater networks, taking into account not only material technical performance but also material performance, regarding operational condition of the system.The research project undertaken by SINTEF Group, the largest research organisation in Scandinavia, NTNU (Norges Teknisk-Naturvitenskapelige Universitet) and Oslo VAV adopts several approaches to understand reasons for failures that may impact flow capacity, by analysing historical data for blockages in Oslo.The aim of the study was to understand whether there is a relationship between the performance of the pipeline and a number of specific attributes such as age, material, diameter, to name a few. This paper presents the characteristics of the data set available and discusses the results obtained by performing two different approaches: a traditional statistical analysis by segregating the pipes into classes, each of which with the same explanatory variables, and a Evolutionary Polynomial Regression model (EPR), developed by Technical University of Bari and University of Exeter, to identify possible influence of pipes attributes on the total amount of predicted blockages in a period of time.Starting from a detailed analysis of the available data for the blockage events, the most important variables are identified and a classification scheme is adopted.From the statistical analysis, it can be stated that age, size and function do seem to have a marked influence on the proneness of a pipeline to blockages, but, for the reduced sample available, it is difficult to say which variable it is more influencing. If we look at total number of blockages the oldest class seems to be the most prone to blockages, but looking at blockage rates (number of blockages per km per year), then it is the youngest class showing the highest blockage rate. EPR allowed identifying the relation between attitude to block and pipes attributes in order to understand what affects the possibility to have a blockage in the pipe. EPR provides formulae to compute the accumulated number of blockages for a pipe class at the end of a given period of time. Those formulae do not represent simply regression models but highlight those variables which affect the physical phenomenon in question.

Uncertainty modelling in multi-criteria analysis of water safety measures

Water utilities must assess risks and make decisions on safety measures in order to obtain a safe and sustainable drinking water supply. The World Health Organization emphasises preparation of water safety plans, in which risk ranking by means of risk matrices with discretised probability and consequence scales is commonly used. Risk ranking enables prioritisation of risks, but there is currently no common and structured way of performing uncertainty analysis and using risk ranking for evaluating and comparing water safety measures. To enable a proper prioritisation of safety measures and an efficient use of available resources for risk reduction, two alternative models linking risk ranking and multi-criteria decision analysis (MCDA) are presented and evaluated. The two models specifically enable uncertainty modelling in MCDA, and they differ in terms of how uncertainties in risk levels are considered. The need of formal handling of risk and uncertainty in MCDA is emphasised in the literature, and the suggested models provide innovations that are not dependent on the application domain. In the case study application presented here, possible safety measures are evaluated based on the benefit of estimated risk reduction, the cost of implementation and the probability of not achieving an acceptable risk level. Additional criteria such as environmental impact and consumer trust may also be included when applying the models. The case study shows how safety measures can be ranked based on preference scores or cost-effectiveness and how measures not reducing the risk enough can be identified and disqualified. Furthermore, the probability of each safety measure being ranked highest can be calculated. The two models provide a stepwise procedure for prioritising safety measures and enable a formalised handling of uncertainties in input data and results.

WASTEWATER NETWORK CHALLENGES AND SOLUTIONS

Sewer and storm water systems in cities worldwide suffer from ageing and inappropriate wastewater networks. This challenge has to be met by systematic upgrading and preventive maintenance. It is necessary to analyse the current performance of the wastewater networks, to determine the system bottlenecks that cause system vulnerability on floods in city areas and pollution of receiving waters. The next task is then to use this information for selecting and ranking upgrading projects to improve the situation. CARE-S is a computer based system developed to meet this challenge. It is designed for sewer and storm water network rehabilitation planning. It provides fundamental instruments for estimating the current and future condition of sewer networks, ______ * Sveinung Saegrov, SINTEF, Dept. Water and Wastewater, Klaebuveien 153, NO-7465 Trondheim, Norway, phone +47-73592349, fax +47 73592376, e-mail: sveinung.sagrov@sintef.no

RISK AND VULNERABILITY ASSESSMENT ("ROS-ANALYSIS") OF THE BERGEN WATER SUPPLY SYSTEM - A SOURCE TO TAP APPROACH

The paper provides an overview of the application and results of a risk and vulnerability analysis (in Norwegian: ROS-analyse) of Bergens water supply system covering all elements from source to tap (i.e. catchment, source, treatment plant, and distribution). The analysis gives an overview of the risk-picture for the water supply system. The main conclusion is that the flexible and redundant water system of Bergen, where five independent waterworks feed water into the same system, reduces the consequences from many of the undesired events which might happen. This puts Bergen in a unique situation compared to many other water companies in Norway. However, resulting from the analysis, we have identified new possible risk reducing measures for all elements in the water supply system which will improve the safety of the system to an even higher level. Within the project a new procedure for assessing the strength of the hygienic barriers represented by the water treatment step and the disinfection step has been developed. By using large datasets from the SCADA-system, long time-series of water quality data has been aggregated into easy understandable risk measures represented by duration curves. The risk analysis is organised and carried out within a database system, making it easy to update and improve the analysis at later stages.

Integrated Urban Water System

This chapter presents the challenges faced by the water utilities to provide safe, secure and reliable service to meet the Water Framework Directives 2000/60/EC and the water safety plan (WHO [16]). These directives among others will form framing conditions for the risk and vulnerability analysis to be conducted. The analysis approach follows standard methodology for risk and vulnerability described in Chap. 3 of this book. In order to structure the analysis, it is common to split the system into the various water cycle components. For each of these components, hazards and threats are identified, probability and consequences assessed, and finally, the total risk picture presented. Practical examples from the Oslo case study are presented to support the approach.