João P. Leitão

Statistical failure models for water distribution pipes - A review from a unified perspective.

This review describes and compares statistical failure models for water distribution pipes in a systematic way and from a unified perspective. The way the comparison is structured provides the information needed by scientists and practitioners to choose a suitable failure model for their specific needs. The models are presented in a novel framework consisting of: 1) Clarification of model assumptions. The models originally formulated in different mathematical forms are all presented as failure rate. This enables to see differences and similarities across the models. Furthermore, we present a new conceptual failure rate that an optimal model would represent and to which the failure rate of each model can be compared. 2) Specification of the detailed data assumptions required for unbiased model calibration covering the structure and completeness of the data. 3) Presentation of the different types of probabilistic predictions available for each model. Nine different models and their variations or further developments are presented in this review. For every model an overview of its applications published in scientific journals and the available software implementations is provided. The unified view provides guidance to model selection. Furthermore, the model comparison presented herein enables to identify areas where further research is needed.

Comparative Study of Three Stochastic Models for Prediction of Pipe Failures in Water Supply Systems

The prediction of pipe failures in urban water systems is a complex process because the available failure records, originating in work orders, are often short and incomplete. To identify a robust and simple model with good failure prediction results using short data history, three existing models were compared in this study: the single-variate Poisson process, the Weibull accelerated lifetime model, and the linear-extended Yule process. This work also presents modifications to these models that enable them to produce more accurate predictions and overcome computational issues for practical software implementation. The three models, together with the improvements where applicable, were applied to water supply system data provided by a Portuguese water utility, and the results were comparatively analysed to assess the accuracy of each model. The Weibull accelerated lifetime model yielded the best results among the three models, accurately predicting failures and detecting pipes with high failure likelihood; however, it is based on Monte Carlo simulations, which can be time-consuming. The linear extended Yule process could also effectively detect pipes with higher failure likelihood; however, it presented a clear tendency to overestimate the number of future failures. The single-variate Poisson process is the simplest of the three models and produced failure prediction results of lower quality.

The influence of digital elevation model resolution on overland flow networks for modelling urban pluvial flooding.

This paper presents the developments towards the next generation of overland flow modelling of urban pluvial flooding. Using a detailed analysis of the Digital Elevation Model (DEM) the developed GIS tools can automatically generate surface drainage networks which consist of temporary ponds (floodable areas) and flow paths and link them with the underground network through inlets. For different commercially-available Rainfall-Runoff simulation models, the tool will generate the overland flow network needed to model the surface runoff and pluvial flooding accurately. In this paper the emphasis is placed on a sensitivity analysis of ponds and preferential overland flow paths creation. Different DEMs for three areas were considered in order to compare the results obtained. The DEMs considered were generated using different acquisition techniques and hence represent terrain with varying levels of resolution and accuracy. The results show that DEMs can be used to generate surface flow networks reliably. As expected, the quality of the surface network generated is highly dependent on the quality and resolution of the DEMs and successful representation of buildings and streets.

Methodology for qualitative urban flooding risk assessment

Pluvial or surface flooding can cause significant damage and disruption as it often affects highly urbanised areas. Therefore it is essential to accurately identify consequences and assess the risks associated with such phenomena. The aim of this study is to present the results and investigate the applicability of a qualitative flood risk assessment methodology in urban areas. This methodology benefits from recent developments in urban flood modelling, such as the dual-drainage modelling concept, namely one-dimensional automatic overland flow network delineation tools (e.g. AOFD) and 1D/1D models incorporating both surface and sewer drainage systems. To assess flood risk, the consequences can be estimated using hydraulic model results, such as water velocities and water depth results; the likelihood was estimated based on the return period of historical rainfall events. To test the methodology two rainfall events with return periods of 350 and 2 years observed in Alcântara (Lisbon, Portugal) were used and three consequence dimensions were considered: affected public transportation services, affected properties and pedestrian safety. The most affected areas in terms of flooding were easily identified; the presented methodology was shown to be easy to implement and effective to assess flooding risk in urban areas, despite the common difficulties in obtaining data.

Prioritization of rehabilitation interventions for urban water assets using multiple criteria decision-aid methods.

The aim of this paper is to compare sorting and ranking methods for prioritization of rehabilitation interventions of sewers, taking into account risk, performance and cost. For that purpose multiple criteria decision-aid (MCDA) methods such as ELECTRE TRI for sorting and ELECTRE III for ranking are applied in a real case-study and the results obtained are compared. The case study is a small sanitary sewer system from a Portuguese utility located in the metropolitan area of Lisbon. The problem to investigate is the prioritization of the sewer candidates for rehabilitation. The decision maker (a panel group of specialists) has chosen five assessment measures: water level and maximum flow velocity (hydraulic performance indices), sewer importance and failure repair cost (collapse-related consequences of failure) and the risk of collapse. The results show that the outcomes from ELECTRE III are easier to understand than those from ELECTRE TRI method. Two different sets of weights were used, and the sorting and ranking results from both methods were found to be sensitive to them. ELECTRE TRI method is not straightforward as it involves technical parameters that are difficult to define, such as reference profiles and cut levels.

Sensitivity analysis of surface runoff generation in urban flood forecasting

Reliable flood forecasting requires hydraulic models capable to estimate pluvial flooding fast enough in order to enable successful operational responses. Increased computational speed can be achieved by using a 1D/1D model, since 2D models are too computationally demanding. Further changes can be made by simplifying 1D network models, removing and by changing some secondary elements. The Urban Water Research Group (UWRG) of Imperial College London developed a tool that automatically analyses, quantifies and generates 1D overland flow network. The overland flow network features (ponds and flow pathways) generated by this methodology are dependent on the number of sewer network manholes and sewer inlets, as some of the overland flow pathways start at manholes (or sewer inlets) locations. Thus, if a simplified version of the sewer network has less manholes (or sewer inlets) than the original one, the overland flow network will be consequently different. This paper compares different overland flow networks generated with different levels of sewer network skeletonisation. Sensitivity analysis is carried out in one catchment area in Coimbra, Portugal, in order to evaluate overland flow network characteristics.

Stochastic evaluation of the impact of sewer inlets’ hydraulic capacity on urban pluvial flooding

Sewer inlet structures are vital components of urban drainage systems and their operational conditions can largely affect the overall performance of the system. However, their hydraulic behaviour and the way in which it is affected by clogging is often overlooked in urban drainage models, thus leading to misrepresentation of system performance and, in particular, of flooding occurrence. In the present paper, a novel methodology is proposed to stochastically model stormwater urban drainage systems, taking the impact of sewer inlet operational conditions (e.g. clogging due to debris accumulation) on urban pluvial flooding into account. The proposed methodology comprises three main steps: (i) identification of sewer inlets most prone to clogging based upon a spatial analysis of their proximity to trees and evaluation of sewer inlet locations; (ii) Monte Carlo simulation of the capacity of inlets prone to clogging and subsequent simulation of flooding for each sewer inlet capacity scenario, and (iii) delineation of stochastic flood hazard maps. The proposed methodology was demonstrated using as case study design storms as well as two real storm events observed in the city of Coimbra (Portugal), which reportedly led to flooding in different areas of the catchment. The results show that sewer inlet capacity can indeed have a large impact on the occurrence of urban pluvial flooding and that it is essential to account for variations in sewer inlet capacity in urban drainage models. Overall, the stochastic methodology proposed in this study constitutes a useful tool for dealing with uncertainties in sewer inlet operational conditions and, as compared to more traditional deterministic approaches, it allows a more comprehensive assessment of urban pluvial flood hazard, which in turn enables better-informed flood risk assessment and management decisions.

Urban pluvial flooding in Jakarta: applying state-of-the-art technology in a data scarce environment.

Available data relating to major pluvial flooding events in Jakarta, Indonesia were used to investigate the suitability of two different levels of sophistication in urban modelling tools for modelling these events. InfoWorks CS v9.0 was employed to build 1D and 1D/2D models of a 541 ha area of inner city Ciliwung River catchment which has a history of being particularly badly affected by flooding during heavy rainfall events. The study demonstrated that a 1D model was sufficient to simulate the flood extent of a major event using the limited data available. While the 1D/2D model also performed well, more data and time would have been required to match the 1D models simulation of flood extent. Much more detailed data would have been required to produce reliable results in the 1D/2D model and to enable any kind of verification or calibration of the two models beyond visual comparison with crude flood extent maps.

Stochastic data mining tools for pipe blockage failure prediction

Abstract Failure prediction plays an important role in the management of urban water systems infrastructures. An accurate description of the deterioration of urban drainage systems is essential for optimal investment and rehabilitation planning. In the study presented in this paper, a new method to predict sewer pipe failure based on robust decision trees is proposed. Five other different stochastic failure prediction models – the non-homogeneous Poisson process, the zero-inflated non-homogeneous Poisson process, classical decision tress (CART and Random Forest algorithms), the Weibull accelerated lifetime model and the linear extended Yule process – are also implemented and explored in order to identify models that combine good failure prediction results with robustness. The six models were tested on the asset register and pipe failure register of a large US wastewater utility; only pipe blockage failures were considered in this study. The linear extended Yule process and the zero-inflated non-homogeneous Poisson process presented the overall best results throughout the models’ comparison, showing a good ability to detect pipes with high likelihood of blockage failure. Decision trees based on robust random forests only detected pipes with high likelihood of failure when considering a short-term prediction window; the accuracy of the predictions was one of the best when using the robust decision tree model. The Weibull accelerated lifetime model provided some of the best medium-term predictions but performed less well for shorter prediction windows.

Moving urban water infrastructure asset management from science into practice

iGPI, the National Initiative for Infrastructure Asset Management is a Portuguese collaborative project led by LNEC (National Civil Engineering Laboratory, Portugal) through which 19 water utilities develop their own infrastructure asset management (IAM) systems and plans in a joint training and capacitation programme. Technical assistance to the participating utilities is ensured by LNEC, IST (Technical University of Lisbon) and Addition, a software development company. The water utilities get collective as well as one-on-one support and specific training. They benefit from networking with the other utilities in a common and simultaneous process, with similar difficulties and challenges, leading to an effective sharing of solutions. The developed products, including training materials, templates and guidelines for developing strategic and tactical IAM plans, are available to the general public. This project has greatly contributed to the establishment of reference methodologies and standards for IAM planning, in a range of utilities of widely diverse size and context, effectively defining an accepted best practice. This paper discusses the projects format and its advantages, and goes on to describe the main outcomes, including selected cases and final products.