Remote sensing (RS) and geographic information system (GIS) data is increasingly used in urban stormwater modeling. The undirected use of such data may waste economic and human resources. In order to provide guidance for practitioners to efficiently use different data collection resources, as well as give a reference for future works, this paper aims to assess the effects of using free access G...

A unique methodology for the optimal specification of sewer rehabilitation investment is presented in this paper. By accounting for the critical risk of asset failure, this methodology builds on previously successful work which explored the application of multi-objective optimisation tools to assist engineers with the specification of optimal rehabilitation strategies. The conventional sewerage...

Recently, “smart” urban infrastructure has been suggested as a strategy to mitigate social and economic risks posed by extreme weather events and to improve the sustainability of urban centers. Smart infrastructure is enabled by real-time sensing, modeling, optimization, and actuation, which permit the infrastructure to reason about the world around it and to autonomously reconfigure in order t...

This paper presents a new and alternative method (in the context of urban drainage) for probabilistic hydrodynamical analysis of drainage systems in general and especially prediction of combined sewer overflow. Using a probabilistic shell it is possible to implement both input and parameter uncertainties on an application of the commercial urban drainage model MOUSE combined with the probabilis...

In this paper a multijoint robot f o r sewer inspection tasks i s presented. In order t o increase the operating scope the robot has been made able t o run round or over obstacles, to follow sewage branches and is aimed t o work wirelessly unlike mos t other sewer inspection robots. A s a result of the wireless approach the robot has to carry an energy resource and mus t be able to act autonomo...

This paper describes the application of Artificial Neural Networks (ANNs) as Data Driven Models (DDMs) to predict urban flooding in real-time based on weather radar and/or raingauge rainfall data. A 123manhole combined sewer sub-network from Keighley, West Yorkshire, UK is used to demonstrate the methodology. An ANN is configured for prediction of flooding at manholes based on rainfall input. I...

The ADRICOSM project was launched in October 2001, and ended in March 2005, with the main objective of demonstrating the feasibility of a near real time operational marine monitoring and forecasting system at the shelf and coastal scales, with connections to river basin runoff and coastal town sewer systems. The basic system consisted of an efficient network for the collection of marine data su...

Sustainable Urban Drainage Systems (SuDS) constitute an alternative to conventional drainage when managing stormwater in cities, reducing the impact of urbanization by decreasing the amount of runoff generated by a rainfall event. This paper shows the potential benefits of installing different types of SuDS in preventing flooding in comparison with the common urban drainage strategies consistin...

Urban drainage systems are frequently analysed using hydraulic modelling software packages such as InfoWorks CS or MIKE-Urban. The use of such modelling tools allows the evaluation of sewer capacity and the likelihood and impact of pluvial flood events. Models can also be used to plan major investments such as increasing storage capacity or the implementation of sustainable urban drainage syste...