The importance of gully flow modelling to urban flood simulation

ABSTRACT

Urban flood simulation often ignores or simplifies the function of underground gully systems due to data and computational limitations. To discover the influence of gullies on urban flooding, a novel approach is proposed in this study, by fully-coupling a 1D gully flow model (GFM), a 1D sewer flow model (SFM), and a 2D overland flow model (OFM) to simultaneously simulate the flow exchanges between surface, gullies and sewer pipes. This fully-coupled approach is compared with a simplified approach which directly introduces surface water into sewer pipes without being via gullies. The validation results show that the fully-coupled approach considerably reduces the underestimation of flood extent by 27% compared with the simplified approach. Without considering the capacity of lateral tubes between gullies and sewer pipes, the simplified approach over-drains the surface water into sewer pipes. The modelling of gully flow is crucial for correctly evaluating the efficiency of drainage systems.     

Hydraulic design aspects for supercritical flow in vortex drop shafts

ABSTRACT

Vortex drop shafts, as special sewer manholes, operate optimally if an adequate energy dissipation is guaranteed and the integrity of the structural components is safeguarded. The results of an experimental study on a vortex drop shaft with supercritical inflow are discussed herein. The hydraulic behaviour of the spiral inlet, the vertical shaft and the dissipation chamber is described. Based on detailed flow observations, useful recommendations for designing these structures are provided. It is demonstrated that a relation adopted for supercritical bend flows provides a reliable estimation of the maximum wave height along the inlet. A procedure for predicting the rotational flow angles and the velocity distribution along vertical shafts with swirling flows is developed. Water levels and pressure measurements in the dissipation chamber are further analysed to identify maximum forces acting on the chamber invert and to derive preliminary design equations.     

Statistical comparison of the performance of data-based models for sewer condition modeling

Abstract

The present article proposes a methodology to consider the uncertainty intrinsic to data-based models when comparing their performance. The goal is to provide a quantification of the variability of this type of models due to the random nature of the calibration process and enable a statistical comparison of the models’ performance when attempting to identify the best. The methodology proposed doesn’t provide an alternative metric to determine the models’ performance, but it expands the traditional deterministic comparison to a stochastic comparison. The methodology builds on the current standard approach for developing data-based model and its application is demonstrated to model sewer condition using data from 4 trunk sewers of the SANEST – Saneamento da Costa do Estoril sewer system, corresponding to 25?km of sewer pipes. The data-based models were developed using artificial neural networks, support vector machines, bootstrapping aggregation and least squares support vector machines. For the case study, the highest and average misclassification performance records are similar for all models (23% to 24% and 31% to 33%, respectively) but the lowest performance varied more significantly (39% to 62%). This demonstrates that selecting a model based on its maximum single realisation performance alone may be misleading.     

Measuring surplus capacity for multiobjective optimal design of foul sewer systems

ABSTRACT

This paper proposes a new performance index of foul sewer systems, i.e. sewer conveyance capacity (SCC) index, to quantify the surplus capacity for multi-objective optimization design problems. The use of the new SCC index is demonstrated using a hypothetical network and a real-world foul sewer network. Results obtained show clear trade-offs between SCC and the other two objectives considered, i.e., capital and operational costs and greenhouse gas emissions. The results show that the upstream sewers in the system often have a relatively large surplus capacity, while the sewer mains operate close to the design capacity. Moreover, SCC is compared with three common indicators at both individual sewer and system-wide levels. Strong correlations between SCC and other indicators are revealed, implying that SCC is a good representation of system performance and can provide a more comprehensive picture of the foul sewer system performance.     

Quantifying costs and lengths of urban drainage systems with a simple static sewer infrastructure model

A generic model is introduced that is capable of quantitatively representing the combined sewer infrastructure of a settlement. It consists of a catchment area module, which calculates the length and size distribution of the needed sewer pipes on the basis of rain, housing densities and area size. These results are fed into the sewer construction costs module in order to estimate the combined sewer costs of the entire catchment area.

The model could be successfully fitted to existing Swiss sewer systems, indicating that it can emulate their principal characteristics. It could also identify fundamental differences in sewer designs in cities with historic roots. The results confirm that there are economies of scale for combined sewer systems in Switzerland. The modelling approach proved to be an effective tool for understanding the factors underlying the cost structure for water network infrastructures.     

A Survival Analysis Model for Sewer Pipe Structural Deterioration

Abstract: The structural state of sewer systems is often quantified using condition classes. The classes are based on the severity of structural defects observed on individual pipes within the system. Here, a survival analysis model was developed to predict the overall structural state of a sewer network based on camera inspection data from a sample of pipes in the system. The convolution product was used to define the survival functions for cumulative staying times in each condition class. An original calibration procedure for the sewer deterioration model was developed to overcome the censored nature of data (left censored and right censored) available for the calibration of sewer deterioration models. The exponential and Weibull functions were used to represent the distribution of waiting times in each deterioration state. Cross‐validation tests showed that the Weibull function led to greater uncertainty than the exponential function for the simulated proportion of pipes that are in a deteriorated state. Using various sample sizes for model calibration, these cross‐validation tests also showed that the model's results are robust to smaller calibration sample sizes. This confirms the model's potential for predicting the overall state of deterioration of a sewer network when only a small proportion of the pipes have been inspected.     

Improved understanding of combined sewer systems using the Illinois Conveyance Analysis Program (ICAP)

Understanding the conveyance of sewer networks is vital, especially in cases of great variability in flow rates, such as in combined sanitary and storm sewer systems. Conventional conveyance studies in sewer systems often have extended computation times due to complexity of the solution, or alternatively make assumptions that ignore the water-surface profile within a pipe. In previous research, the hydraulic performance graph (HPG) was successfully used for open-channel capacity determination. The HPG summarizes the results of many backwater calculations for a reach so that these calculations do not need to be repeated. This article describes algorithms utilized by the Illinois Conveyance Analysis Program that uses the HPGs to describe the conveyance of a system, identify bottlenecks for varying conditions, conserve mass by tracking outflow and overflows under stepwise steady flow conditions. The software is freely available at https://github.com/obergshavefun/icap/wiki.     

Data co-synthesis in developing public product service systems

ABSTRACT

Design and research teams working on public product service systems (PPSS) are often confronted with large data sets, presented in a complex language. This paper presents a method for how designers may translate quantitative aggregated data with a toolkit that enables qualitative co-synthesis to generate novel PPSS proposals. The toolkit development and application is shown through a specific case study in Melbourne, Australia, that focused on reimagining a public transport bus service in light of emerging propulsion and information technologies. People affected by the service were able to assist in co-synthesising existing data from transport planning literature into emergent ideas for system upgrades or even complete overhauls. A variety of multi-faceted service interventions were developed through a series of workshops with different participant groups. Workshop outcome variations further support the notion of emergence in co-creation, and reinforce the importance of running multiple sessions due to their potential impact on project outcomes. This paper proposes that co-synthesising complex data with the help of a toolkit, which may be a powerful way to inform PPSS design. An application framework is presented to summarise this process and to generate discussion towards broader application and further refinement.     

Sewer asset management – state of the art and research needs

ABSTRACT

Sewer asset management gained momentum and importance in recent years due to economic considerations, since infrastructure maintenance and rehabilitation directly represent major investments. Because physical urban water infrastructure has life expectancies of up to 100 years or more, contemporary urban drainage systems are strongly influenced by historical decisions and implementations. The current decisions taken in sewer asset management will, therefore, have a long-lasting impact on the functionality and quality of future services provided by these networks. These decisions can be supported by different approaches ranging from various inspection techniques, deterioration models to assess the probability of failure or the technical service life, to sophisticated decision support systems crossing boundaries to other urban infrastructure. This paper presents the state of the art in sewer asset management in its manifold facets spanning a wide field of research and highlights existing research gaps while giving an outlook on future developments and research areas.     

Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques

Sanitary sewer systems are designed to collect and transport sanitary wastewater and stormwater. Pipe inspection is important in identifying both the type and location of pipe defects to maintain the normal sewer operations. Closed-circuit television (CCTV) has been commonly utilized for sewer pipe inspection. Currently, interpretation of the CCTV images is mostly conducted manually to identify the defect type and location, which is time-consuming, labor-intensive and inaccurate. Conventional computer vision techniques are explored for automated interpretation of CCTV images, but such process requires large amount of image pre-processing and the design of complex feature extractor for certain cases. In this study, an automated approach is developed for detecting sewer pipe defects based on a deep learning technique namely faster region-based convolutional neural network (faster R-CNN). The detection model is trained using 3000 images collected from CCTV inspection videos of sewer pipes. After training, the model is evaluated in terms of detection accuracy and computation cost using mean average precision (mAP), missing rate, detection speed and training time. The proposed approach is demonstrated to be applicable for detecting sewer pipe defects accurately with high accuracy and fast speed. In addition, a new model is constructed and several hyper-parameters are adjusted to study the influential factors of the proposed approach. The experiment results demonstrate that dataset size, initialization network type and training mode, and network hyper-parameters have influence on model performance. Specifically, the increase of dataset size and convolutional layers can improve the model accuracy. The adjustment of hyper-parameters such as filter dimensions or stride values contributes to higher detection accuracy, achieving an mAP of 83%. The study lays the foundation for applying deep learning techniques in sewer pipe defect detection as well as addressing similar issues for construction and facility management.     

Iron salts dosage for sulfide control in sewers induces chemical phosphorus removal during wastewater treatment

Chemical phosphorus (P) removal during aerobic wastewater treatment induced by iron salt addition in sewer systems for sulfide control is investigated. Aerobic batch tests with activated sludge fed with wastewater containing iron sulfide precipitates showed that iron sulfide was rapidly reoxidised in aerobic conditions, resulting in phosphate precipitation. The amount of P removed was proportional to the amount of iron salts added, and for the sludge used, ratios of 0.44 and 0.37 mgP/mgFe were obtained for ferric and ferrous dosages, respectively. The hydraulic retention time (HRT) of iron sulfide in sewers was found to have a crucial impact on the settling of iron sulfide precipitates during primary settling, with a shorter HRT resulting in a higher concentration of iron sulfide in the primary effluent and thus enabling higher P removal. A mathematical model was developed to describe iron sulfide oxidation in aerated activated sludge and the subsequent iron phosphate precipitation. The model was used to optimise FeCl₃ dosing in a real wastewater collection and treatment system. Simulation studies revealed that, by moving FeCl₃ dosing from the WWTP, which is the current practice, to a sewer location upstream of the plant, both sulfide control and phosphate removal could be achieved with the current ferric salt consumption. This work highlights the importance of integrated management of sewer networks and wastewater treatment plants.     

Removal of organic matter in stormwater ponds: a plug-flow model generalisation from waste stabilisation ponds to shallow rivers

ABSTRACT

This study investigates the effect of flow conditions on the organic matter concentration, removal efficiency, and reaction kinetics in a stormwater pond in Fortaleza, Brazil. As a result of unauthorized sewage discharges, BOD and COD concentrations were similar to those of combined sewer systems. The concentrations remained roughly the same during the rainy season, which was attributed to sewage network overflow. Removal efficiencies ranged from 70–90%, similar to primary facultative ponds. Fitting different hydraulic models to the field data, it was possible to obtain BOD and COD removal rates that could be described as functions of the Reynolds number. The best fit was achieved considering the plug-flow assumption, and a general BOD model including data reported in the literature for waste stabilisation ponds, stormwater ponds and shallow rivers was derived. Lastly, simulations with this general model were performed to assess the impact of remediation measures on the studied pond.     

Multiobjective optimisation algorithm for sewer network rehabilitation

Understanding of deterioration mechanisms in sewers helps asset managers in developing prediction models for estimating whether or not sewer collapse is likely. Effective utilisation of deterioration prediction models along with the development and use of life cycle maintenance cost analysis contribute to reducing operation and maintenance costs in sewer systems. This article presents a model for life-cycle maintenance planning of deteriorating sewer network as a multi-objective optimisation problem that treats the sewer network condition and service life as well as life-cycle maintenance cost (LCMC) as separate objective functions. The developed model utilises Markov chain model for the prediction of the deterioration of the network. A multi-objective genetic algorithm is used to automatically locate an appropriate maintenance scenario that exhibits an optimised tradeoff among conflicting objectives. Monte Carlo simulation is used to account for LCMC uncertainties. The optimisation algorithm provides an improved opportunity for asset managers to actively select near-optimum maintenance scenario that balances life-cycle maintenance cost, condition and service life of deteriorating sewer network. A case study is used to demonstrate the practical features of developed methodology.     

Optimal planning of decentralised storage tanks to reduce combined sewer overflow spills using particle swarm optimisation

The present study suggests an optimised method for planning multiple decentralised storage tanks which are designed to reduce combined sewer overflow (CSO) spills. Particle swarm optimisation (PSO) was applied for the optimal planning of the storage tanks in terms of location distribution and sizing. The framework for the storage optimal planning suggested in this study includes developing a simplified mathematical model that is, along with the PSO algorithm, for optimisation. In order to reduce the computational burden of PSO’s inherent iterative solution-searching process a simplified mathematical model was developed to simulate the complex hydraulic flows of a sewer network. Then, the optimisation model with the PSO algorithm was connected interactively with the mathematical model. A case study network was simulated to analyse its application in the planning of distributed CSO storage tanks, and the best available scenarios were suggested.     

Key control handles in integrated urban wastewater systems for improving receiving water quality

ABSTRACT

There is an increasing interest in modelling and control of integrated urban wastewater systems (UWS). Nevertheless, given the multiple interactions between the sub-systems – catchment, sewer system, wastewater treatment plant (WWTP) and receiving water system – the selection of effective control handles for improving receiving water quality is a major challenge. In this paper, a systematic study to identify the most important control handles in an UWS is presented. The Benchmark Simulation Model for Urban Wastewater Systems (BSM-UWS) is selected as a virtual case-study. Morris screening is used to perform global sensitivity analysis. Results indicate that, for the BSM-UWS layout, while river dissolved oxygen quality (T_exc,DO) is influenced by multiple control handles both in the sewer system and WWTP, river un-ionized ammonia quality (T_exc,NH3) is mainly influenced by WWTP control handles. The study highlights the need to perform simulations for at least 1 year when determining key control handles for UWS.     

Development of a model for assessing methane formation in rising main sewers

Significant methane formation in sewers has been reported recently, which may contribute significantly to the overall greenhouse gas emission from wastewater systems. The understanding of the biological conversions occurring in sewers, particularly the competition between methanogenic and sulfate-reducing populations for electron donors, is an essential step for minimising methane emissions from sewers. This work proposes an extension to the current state-of-the-art models characterising biological and physicochemical processes in sewers. This extended model includes the competitive interactions of sulfate-reducing bacteria and methanogenic archaea in sewers for various substrates available. The most relevant parameters of the model were calibrated with lab-scale experimental data. The calibrated model described field data reasonably well. The model was then used to investigate the effect of several key sewer design and operational parameters on methane formation. The simulation results showed that methane production was highly correlated with the hydraulic residence time (HRT) and pipe area to volume (A/V) ratio showing higher methane concentrations at a long HRT or a larger A/V ratio.     

Contribution of different sources to the pollution of wet weather flows in combined sewers

Experiments performed on "Marais" catchment, in central Paris, aimed to follow up the quality of wet weather flows from the entry to the exit of a combined sewer network. SS, VSS, COD, BOD5, Cd, Cu, Pb, Zn concentrations were measured for an important number of rain events in roof, yard, street runoff, as well as in dry and wet weather flows at the catchment outlet. Mass entry-exit totals, at the scale of the catchment, were calculated over 31 rain events in order to evaluate the contribution of different types of runoff, of sanitary sewage and of sewer sediments to the total wet weather pollutant loads at the catchment outlet. The erosion of in-sewer pollutant stocks was found to be the main source of particles and of organic matter in wet weather flows, whereas heavy metal loads mainly originated from roof runoff, due to the corrosion of metallic roofs. Particles eroded inside the sewer during rain events were found to be quite different from the particles constituting the main part of sewer sediments: they are organic and biodegradable, with rather important settling velocities and seem to accumulate during dry weather periods. A change of the chemical form of heavy metals was noticed during the transport in the sewer and it is suspected that a fraction of the dissolved metals from the runoff is adsorbed on sewer sediments.     

Electrochemical sulfide removal from synthetic and real domestic wastewater at high current densities

Hydrogen sulfide generation is the key cause of sewer pipe corrosion, one of the major issues in water infrastructure. Current abatement strategies typically involve addition of various types of chemicals to the wastewater, which incurs large operational costs. The transport, storage and application of these chemicals also constitute occupational and safety hazards. In this study, we investigated high rate electrochemical oxidation of sulfide at Ir/Ta mixed metal oxide (MMO) coated titanium electrodes as a means to remove sulfide from wastewater. Both synthetic and real wastewaters were used in the experiments. Electrochemical sulfide oxidation by means of indirect oxidation with in-situ produced oxygen appeared to be the main reaction mechanism at Ir/Ta MMO coated titanium electrodes. The maximum obtained sulfide removal rate was 11.8 ± 1.7 g S m⁻² projected anode surface h⁻¹ using domestic wastewater at sulfide concentrations of ≥30 mg L⁻¹ or higher. The final products of the oxidation were sulfate, thiosulfate and elemental sulfur. Chloride and acetate concentrations did not entail differences in sulfide removal, nor were the latter two components affected by the electrochemical oxidation. Hence, the use of electrodes to generate oxygen in sewer systems may constitute a promising method for reagent-free removal of sulfide from wastewater.     

Production and transport of urban wet weather pollution in combined sewer systems: the “Marais” experimental urban catchment in Paris

An experimental catchment area was set up in the centre of Paris (France) so as to follow up the quality of wet weather flows from the entry to the exit of a combined sewer network. The distinctive characteristic of this site is its location in a town centre and the extent of the equipment used to monitor the water pollution over the whole length of its course through the catchment area. The results obtained show a change in quality between the runoff entering the sewer network and the combined storm water flow at the sewer's outlet, which cannot be explained only by the mixture with domestic wastewater. In particular, an increase was observed in the concentrations of suspended solids (SS), VSS, COD, BOD and Cu, in the proportion of pollutants linked to particles and in the characteristics of the particles. A calculation of the total masses going in and out of the sewer network during a rainfall event shows that the erosion of in-sewer pollution stocks is the main source of particles and of organic matter in wet weather flows, whereas heavy metals loads originated from roof runoff, due to the corrosion of metallic roofs. Particles eroded from the sewer sediments during rain events were found to be quite different from the particles of type A deposits and organic biofilms. Nevertheless, they have mean organic and metallic loads that are of the same order of magnitude as the particles of the organic layer at water sediment interface. A change in the chemical form of heavy metals was noticed during the transport in the sewer and it is suspected that a fraction of the dissolved metals from the runoff is adsorbed on sewer sediments.