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For pluvial flood risk assessment in urban areas it is important to be able to calculate how often a specific area is at risk of flooding. This is especially evident in urban areas subject to contribution from multiple sources, e.g. surcharging drainage system, surface runoff, overflowing rivers, etc. In this study extreme event statistics are assessed by simulation of rainfall impact and consecutive statistics of flood response in order to estimate return periods of flooding. The model applied is an integrated hydraulic model which includes relevant hydrological processes that contribute to urban flooding. The setup is analysed based on a small urban catchment in Aalborg Denmark. Results show that it is possible to estimate return periods of flood volume, flood extent and local water levels based on simulation and that rainfall and hydrological conditions critical to flooding can be identified.

Determining the load bearing capacity of a deteriorated sewer is one of the important aspects to assess the overall condition of the sewer pipe system. Current indicators to achieve an impression of the residual bearing strength of the pipe are the age of the pipe and footage obtained by camera inspection (CCTV). However, these indicators have proven not to be very accurate, which makes the need for a reliable method to estimate the load bearing capacity of sewers high. The finite element method (FEM) is a suitable analysis tool for gaining a detailed understanding of the load bearing capacity of in-situ sewer pipes. The load bearing capacity does not only depend on the geometrical and material parameters of the pipe itself, but also on the deformation and failure behaviour of the soil structure supporting the pipe. The present contribution discusses the numerical implementation of an advanced soil model that can be used in a finite element analysis of a sewer pipe-soil system, which is a first step in the development of a computational model that is able to accurately predict the overall failure response of sewer pipe systems under arbitrary in-situ conditions.

The concentration of domestic slurry has two advantages, it promotes resource recovery (nutrients and biomass) and saves water. But the design of a relevant sewerage requires a clear understanding of the frictional losses incurred during the transport of the slurry. This abstracts describes numerical & CFD-based methods to estimate losses while the concentrated slurry flows through circular pipes in a fully-turbulent flow. To model turbulent flows through circular pipes, one can rely on either the Newtonian Moody Charts appropriate for engineering applications or a computational fluid dynamics (CFD)-based analysis, made possible through the Newtonian universal law of the wall. However, our studies reveal that concentrated domestic slurry behaves like a non-Newtonian fluid, of the Herschel-Bulkley type. Therefore, the analysis of such a slurry would require modifications to both, existing engineering models and CFD methods. This abstract summarises a modified law of the wall suitable for Herschel-Bulkley fluids, which has been validated against experiments on concentrated domestic slurry. It further details possible non-Newtonian numerical engineering models that could be modified to assess frictional losses incurred by Herschel-Bulkley fluids. The latter will be a quicker and perhaps reliable alternative to computationally expensive CFD-analyses.

Due to the ageing of our underground wastewater infrastructure, leakage of sewers and pressure mains and subsequent infiltration or exfiltration are becoming an increasingly important issue. Herein, we present a novel method to detect and potentially quantify exfiltration from sewer systems under variable flow conditions; the DEST method. The DEST method is based on the principle of setting up a mass balance of a tracer substance. At an upstream point a tracer is injected in a sewer with a constant rate for a certain period, subsequently downstream high frequent time discrete grab samples are combined with discharge measurements to complete the mass balance. The method is applied on a sewer section in Loenen (NL) to investigate its feasibility. Two different tracers are used; Lithium chloride and Deuterium. Preliminary results indicate that both tracers show similar behaviour at the downstream measurement point. Final lab results are expected at the end of March, allowing in depth analysis of the experimental results with a focus on the measurement uncertainty.

Integrated urban drainage systems (IUDS) (i.e., sewer systems, wastewater treatment plants and receiving water bodies) contribute to climate change being sources of greenhouse gas emissions (GHG). This paper, produced by the International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, reviews the state-of-the-art and the recently developed modelling tools used to understand and manage GHG emissions from IUDS. Further, open problems and research gaps are discussed, while proposing a framework for handling GHG from IUDS. The literature review reveals that there is a need to strengthen and partially adequate already available mathematical models for IUDS to take GHG into account.

The aim of the present study was to investigate the nitrous oxide (N2O) emissions from a University of Cape Town (UCT) moving bed membrane bioreactor pilot plant. An experimental campaign was carried out during 60 days with three different sludge retention time (SRT). The pilot plant reactor was provided of funnel shape covers that guaranteed gas accumulation in the headspace. The results highlighted that N2O concentrations significantly increased when the biofilm concentrations increased within the aerobic and anoxic compartments. Furthermore, results have shown an increase of N2O with the decrease of SRT. Moreover, the MBR tank resulted the key emission source (up to 70% of the total N2O emission during SRT=∞ period) whereas the highest N2O production occurred in the anoxic reactor. Moreover, N2O concentrations measured in the permeate flow were not negligible, thus highlighting its potential detrimental contribution for the receiving water body.

The paper reports the main results of a respirometric experimental survey carried out on several membrane bioreactor pilot plants, characterized by different pilot plant layouts as well as operational conditions. The main aim was to assess the influence of specific conditions on biokinetic/stoichiometric parameters. In particular, the respirometric tests were specifically aimed at investigating the activity of both heterotrophic and autotrophic bacterial species. The achieved results showed that the plant configuration and the features of the feeding wastewater and operational conditions determine significant variation of the kinetic coefficients. The respirometric analysis was confirmed to be a simple and effective tool for the evaluation of the actual biomass kinetic parameters, to be used in mathematical models for the design phase as well as for monitoring the biomass viability during plant operations.

The paper presents the sensitivity analysis of an integrated urban water quality system by means of the global sensitivity analysis (GSA). Specifically, an home-made integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole - SMX). The model takes into account also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and the receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Five scenarios each characterized by different combinations of sub-systems (i.e., SS, WWTP and RWB) have been considered applying the Extended-FAST method in order to select the key factors affecting the RWB quality and to design a reliable/useful experimental campaign. Results demonstrated that GSA is a powerful tool for increasing operator confidence in the modelling results; the approach can be used for blocking some non-identifiable parameters thus wisely modifying the structure of the model and reducing the related uncertainty. The model factors related to the SS have been found to be the most relevant factors affecting the SMX modeling