Sediment Deposits In Sewers Research Articles

Sewer sediment deposition prediction using a two-stage machine learning solution

ABSTRACT Sediment accumulation in the sewer is a source of cascading problems if left unattended and untreated, causing pipe failures, blockages, flooding, or odour problems. Good maintenance scheduling reduces dangerous incidents, but it also has financial and human costs. In this paper, we propose a predictive model to support the management of maintenance routines and reduce cost expenditure. The solution is based on an architecture composed of an autoencoder and a feedforward neural network that classifies the future sediment deposition. The autoencoder serves as a feature reduction component that receives the physical properties of a sewer section and reduces them into a smaller number of variables, which compress the most important information, reducing data uncertainty. Afterwards, the feedforward neural network receives this compressed information together with rain and maintenance data, using all of them to classify the sediment deposition in four thresholds: more than 5, 10, 15, and 20% sediment deposition. We use the architecture to train four different classification models, with the best score from the 5% threshold, being 82% accuracy, 70% precision, 76% specificity, and 88% sensitivity. By combining the classifications obtained with the four models, the solution delivers a final indicator that categorizes the deposited sediment into clearly defined ranges.

An investigation into the impacts of water demand management and decentralized water recycling on excess sewer sediment deposition

Sewers are a critical part of the urban water system and represent a considerable investment due to the presence of extensive networks in many cities. Consequently, excess sewer sediment deposition, from changed inflow conditions or lack of appropriate sewer infrastructure, can lead to significantly increased maintenance and operational costs. The main aim of this manuscript is to quantify the potential impacts of reduced inflow and increased sediment concentrations from the implementation of sustainable water practices, such as Decentralized Water Recycling and Water Demand Management, on excess sediment deposition in gravity sewers. Experiments in a sewer pilot plant, with municipal wastewater, and modelling using a comprehensive local-scale sewer sediment model were used in conjunction to address this aim. Results from both these methods indicated that a reduction in inflows from the moderate implementation of sustainable water practices had a large impact on the quantity of sediment deposited in gravity sewers. However, further modelling showed that the reduction in bed erosion during peak flows for the same implementations of sustainable water practices occurred more gradually. Overall, our findings showed that in existing gravity sewer mains with reasonable slope and flow velocities, a moderate decrease in peak flow velocity of around 15% due to the implementation of Decentralized Water Recycling and Water Demand Management was unlikely to result in a net increase of sediment deposition. Future work in this area could focus on confirming these findings through case studies in the field or on long-term pilot studies with detailed bed height and density measurements.

SewerSedFoam: A Model for Free Surface Flow, Sediment Transport, and Deposited Bed Morphology in Sewers

This paper aims to bridge the gap in the detailed modelling of flow and sediment process interactions in sewers through the development of a computational fluid dynamics (CFD) model. It draws on previous models developed for surface water sediment transport in the OpenFOAM CFD framework and builds on them to improve their suitability for sewer sediment processes. Three distinct sediment processes, suspended sediment transport, bedload transport, and deposited bed morphology, are incorporated into a free surface flow solver, interFoam. This sewer sediment model, called SewerSedFoam, models the impacts of sediment deposition and erosion on flow velocity by using dynamic mesh deformation to capture the movement of the deposited bed and its morphology. Further, three sediment classes, two suspended and one bedload sediment, can be modelled along with some bed stabilization and consolidation effects during deposition and erosion, respectively. The functionality of the overall model in modelling sewer sediment deposition and erosion is promising, although the validation of a large magnitude sediment erosion event has been limited by the availability of granular data in existing case studies.

Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques

Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated. For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers proposed an alternative method for sewer sediment accumulation calculation using predictive models harnessing multiple linear regression model (MLRM) and artificial neural network (ANN). AL-Thawra trunk sewer in Baghdad city is selected as a case study area; data from a survey done on this trunk is used in the modeling process. Results showed that MLRM is acceptable, with an adjusted coefficient of determination (adj. R2) in order of 89.55%. ANN model found to be practical with R2 of 82.3% and fit the data better throughout its range. Sensitivity analysis showed that the flow is the most influential parameter on the depth of sediment deposition.

An analysis of shear stress distribution in circular channels with sediment deposition based on Gene Expression Programming

Knowledge of the boundary shear stress distribution in channels is important because it is a key factor affecting on erosion and sedimentation rates. The presence of sediment deposits in sewers is often reported during operation, and circular channels are frequently used in sewer networks. Gene expression programming (GEP) is applied in this study to determine an equation for evaluating the shear stress distribution along the wetted perimeter of a circular channel with a flat bed, because of the presence of sediment on the bed. In view of the parameters affecting the shear stress distribution, five dimensionless parameters are applied to develop six GEP models to be used with 905 experimental data. The impact of the shear stress parameters is studied using the six GEP models and by dividing the wetted perimeter into wall and bed sections. Two equations are extracted from the GEP models’ output to estimate wall and bed shear stresses. The best model results are compared with a well-known equation based on the entropy concept. The GEP model predictions of wall and bed shear stresses are very similar to the experimental outcomes, whereas the entropy-based model overestimates the shear stress distribution. The proposed GEP models demonstrate superior performance in estimating the shear stress distribution with a mean absolute percentage error (MAPE) of 3.79% compared to an existing equation with MAPE of 9.52%.

Different erosion characteristics of sediment deposits in combined and storm sewers.

To investigate the different erosion patterns of sediments in combined and storm sewers, sediments from three separate sewer systems and two combined sewer systems in urban Shanghai were collected for the flushing experiments. These experiments were conducted with different consolidation periods and shear velocities. As the consolidation period increases, dissolved oxygen exhibits a positive effect on the microbial transformations of organic substrates. Potential structural changes and separations of the surface and bottom layers of sediments are observed. The results also reveal that the organic matter, particle size and moisture have different effects on the erosion resistance of sediments. Furthermore, illicit connections behaved as an important factor affecting the viscosity and static friction force of particles, which directly alter the erosion resistance of sewer sediments.

Modes of Bed-Load Movement on a Smooth Rigid Surface

Sediment grains transported as supply-limited bed load on a rigid surface move either discretely or collectively as bed forms, with significantly different effective grain speeds and active storage volumes. The adopted mode has implications for sediment sorting and heavy mineral placer formation, dispersal of grain-associated pollutants, and accumulation and flushing of sediment deposits in unlined canals and sewers. The threshold condition between the two modes has been established for a smooth surface from flume experiments with different sediment types, flow conditions, and sediment supply rates. This is expressed in terms of a relationship between the sediment movability number, a dimensionless bed load parameter, and a grain shear Reynolds number.

Effect of temperature on the substrate utilization profiles of microbial communities in different sewer sediments

Sewer systems represent an essential component of modern society. They have a major impact on our quality of life by preventing serious illnesses caused by waterborne diseases, by protecting the environment, and by enabling economic and social development through reducing flood risk. In the UK, systems are normally large and complex and, because of the long lifespan of these assets, their performance and hence their management are influenced by long‐term environmental and urban changes. Recent work has focussed on the long‐term changes in the hydraulic performance of these systems in response to climate change, e.g. rainfall and economic development. One climate‐related driver that has received little attention is temperature, which may in itself have a complex dependence on factors such as rainfall. This study uses Biolog EcoPlates™ to investigate the effect of different temperatures (4 °C, 24 °C and 30 °C) on the carbon substrate utilization profiles of bacterial communities within sewer sediment deposits. Distinct differences in the metabolic profiles across the different temperatures were observed. Increasing temperature resulted in a shift in biological activity with an increase in the number of different carbon sources that can be utilized. Certain carboxylic and amino acids, however, did not support growth, regardless of temperature. Distinct differences in carbon utilization profiles were also found within sewers that have similar inputs. Therefore, this study has demonstrated that the carbon utilization profile for microbial communities found within sewer sediment deposits is dependent on both temperature and spatial variations.

Modelling sewer sediment deposition, erosion, and transport processes to predict acute influent and reduce combined sewer overflows and CO2 emissions

Understanding of solids deposition, erosion, and transport processes in sewer systems has improved considerably in the past decade. This has provided guidance for controlling sewer solids and associated acute pollutants to protect the environment and improve the operation of wastewater systems. Although measures to decrease combined sewer overflow (CSO) events have reduced the amount of discharged pollution, overflows continue to occur during rainy weather in combined sewer systems. The solution lies in the amount of water allotted to various processes in an effluent treatment system, in impact evaluation of water quality and prediction technology, and in stressing the importance of developing a control technology. Extremely contaminated inflow has been a serious research subject, especially in connection with the influence of rainy weather on nitrogen and organic matter removal efficiency in wastewater treatment plants (WWTP). An intensive investigation of an extremely polluted inflow load to WWTP during rainy weather was conducted in the city of Matsuyama, the region used for the present research on total suspended solid (TSS) concentration. Since the inflow during rainy weather can be as much as 400 times that in dry weather, almost all sewers are unsettled and overflowing when a rain event is more than moderate. Another concern is the energy consumed by wastewater treatment; this problem has become important from the viewpoint of reducing CO(2) emissions and overall costs. Therefore, while establishing a prediction technology for the inflow water quality characteristics of a sewage disposal plant is an important priority, the development of a management/control method for an effluent treatment system that minimises energy consumption and CO(2) emissions due to water disposal is also a pressing research topic with regards to the quality of treated water. The procedure to improve water quality must make use of not only water quality and biotic criteria, but also modelling systems to enable the user to link the effect of changes in urban sewage systems with specific quality, energy consumption, CO(2) emission, and ecological improvements of the receiving water.

Laboratory Experiments and Numerical Modelling of the Scouring Effects of Flushing Waves on Sediment Beds

This paper presents an investigation on the scouring effects of flushing waves on sewer sediment deposits in order to derive guidelines on the design and set-up of flushing devices in sewer systems and in stormwater storage tanks. The investigation comprises both laboratory experiments and numerical modelling. The experimental campaign was carried out on a channel at the laboratory of the Department of Hydraulic and Environmental Engineering of the University of Pavia adopting a simple flushing device. The first set of experiments is carried out without sediment and the water levels during the flushing processes are monitored by a digital video-camera. The second set of tests is carried out with uniform layers of sediment at the bottom of the channel and the effects on sediment beds produced by flushes are analysed. The numerical model solves the De Saint Venant equations describing unsteady flow in open channel and the continuity equation of Exner for the conservation of the sediment mass. For this purpose, the MacCormack explicit finite difference scheme is introduced. A sediment erosion relationship linking the rate of erosion to an excess of shear stress at the bottom is included in the model. The comparison between the experimental and computed water depths shows good agreement for different flushing conditions and longitudinal slopes of the channel. The tests with different sediment beds allow the calibration of the parameters that globally describe the erosion process produced by flushes.

Estimation of Uncertainty in Long-Term Sewer Sediment Predictions Using a Response Database

Regulations require U.K. water companies to reduce the number of properties at risk of sewer flooding. One of the potential causes of sewer flooding is the presence of persistent sediment deposits in sewers, such deposits are a common problem in many combined sewers. Although the regulations are risk based, there is a gap in the current knowledge on how the risk assessment is affected by the uncertainty in sewer sediment transport prediction. This paper describes the development of a methodology for estimating uncertainty in sewer sediment deposit depth predictions using existing empirically calibrated sediment load equations and Monte Carlo simulations combined with a response database. This methodology has been used to estimate the range of uncertainty of in-pipe deposit build-up predictions for a U.K. combined sewer system that suffered persistent deposition problems.

Estimation of uncertainty in long term combined sewer sediment behaviour predictions, a UK case study

There are regulatory driven requirements for UK water companies to reduce the number of properties at risk of sewer flooding. One of the potential causes of sewer flooding is the presence of persistent sediment deposits in sewers. This is a common problem in many combined sewers. Although the regulation is risk based, there is a gap in current knowledge on how risk assessment is affected by the uncertainty in sewer solids behaviour prediction. This paper describes a UK case study exploring the possibility of estimating uncertainty in sewer sediment deposit level predictions, using Monte Carlo simulations combined with a response database.

The erosion behaviour of biologically active sewer sediment deposits: Observations from a laboratory study

The erosion behaviour of various fine-grained sediment deposits has been investigated in laboratory experiments. This work mainly focused on tests using sewer sediment in which strong biochemical reactions were observed during the deposit formation period. A small number of initial tests were conducted in which the deposits were made from mixtures of “clean” mineral and organic sediments. The erosion behaviour observed in these tests was compared with the erosion characteristics for sediments taken from deposits in a sewer. The impact of the biological processes on physical properties such as bulk density, water content, deposit structure and the erosive behaviour as a function of bed shear stress are quantified and discussed. Based on these observations it is believed that bio-processes weaken the strength of the in-pipe sediment deposits. A significantly weaker sediment surface layer was observed during deposition under quiescent oxygen-rich conditions. This resulted in a deposit with low shear strength which may be a cause of a first foul flush of suspended sediment when flow rates were increased. Comparison between tests with sewer sediments and the artificial representative surrogates suggested that the deposits of the later did not correctly simulate the depositional development and the resultant erosion patterns observed with the more bio-active sewer sediment.

Experimental and numerical analysis of the scouring effects of flushing waves on sediment deposits

In the management of urban drainage networks, great interest has been recently addressed to the removal of sediment deposits from sewer collectors. In particular, sewer cleansing can be carried out by flushing devices able to discharge a great volume of water during a short period of time. In this paper an experimental and numerical investigation on the scouring effects of flushing waves on sewer sediment deposits is presented. Experiments were carried out on a laboratory channel adopting a simple flushing device and considering different flushing conditions. Accurate measurements on the evolution of mobile-bed deposits and on sediment transported during the flushing operations were carried out. Subsequently, a numerical model was specifically developed for the analysis of the flushing wave propagation and for the description of the sediment scouring on mobile-bed channels. The model is based on the semi-coupled solution of the complete De Saint Venant equations for the water flow and of the Exner equation for the sediment continuity. Numerical results were compared with the experimental measurements in order to derive indications on the scouring processes consequent to flushing operations.

Effect of environmental conditions on the erosional resistance of cohesive sediment deposits in sewers

The potential to adjust sewer network operation in order to control the level of transported sediment in sewage so as to enhance the performance of end-of-pipe treatment works is now being investigated. However for this to become a practical management option there is a need to be able to understand the processes which control the movement of sediments that are found in many combined sewers. Crucial to this understanding is an ability to predict how sediments from in-sewer deposits, are released by the action of vigorous flows. This paper reports on a laboratory investigation that aimed to investigate the effect that the environmental conditions during deposit formation can have on the ability of fine-grained organic sediment within in-sewer deposits to resist erosion and subsequent release into transport.

A conceptual CSO emission model: SEWSIM

CSO emission is widely considered a significant pollution source to receiving waters in urban areas. The existing deterministic sewer models are not able to predict CSO emission effectively. In this study, a conceptual CSO emission model SEWSIM has been developed using a powerful programming package MATLAB and SIMULINK. A sewer system consisting of an impervious catchment and a sewer network is schematised as two linear dynamic reservoirs. The following physical processes are conceptually modelled: rainfall-runoff; surface solids buildup and washoff; sewer sediment erosion and deposition. The model is suitable for both event-based and continuous simulations. Some simulation results demonstrate that SEWSIM predicts pollution load of CSO emission more effectively than deterministic models.

A conceptual CSO emission model: SEWSIM

CSO emission is widely considered a significant pollution source to receiving waters in urban areas. The existing deterministic sewer models are not able to predict CSO emission effectively. In this study, a conceptual CSO emission model SEWSIM has been developed using a powerful programming package MATLAB and SIMULINK. A sewer system consisting of an impervious catchment and a sewer network is schematised as two linear dynamic reservoirs. The following physical processes are conceptually modelled: rainfall-runoff; surface solids buildup and washoff; sewer sediment erosion and deposition. The model is suitable for both event-based and continuous simulations. Some simulation results demonstrate that SEWSIM predicts pollution load of CSO emission more effectively than deterministic models.

Prediction of locations with sediment deposits in sewers

The present paper presents an application of MOUSE ST, a general deterministic sediment transport model for sewer systems. MOUSE ST is used to predict the locations subjected to sedimentation in the sewer system of Ljubljana, Slovenia. The prediction is made by means of a sediment transport model with a movable bed. This model is run in parallel with the hydrodynamic MOUSE model. The results, in terms of locations with sediment deposits, are compared with field data from the sewer system in Ljubljana. Further, the model is used to predict the effect of the removal of the sediment deposits on the combined sewer overflows.

Prediction of locations with sediment deposits in sewers

The present paper presents an application of MOUSE ST, a general deterministic sediment transport model for sewer systems. MOUSE ST is used to predict the locations subjected to sedimentation in the sewer system of Ljubljana, Slovenia. The prediction is made by means of a sediment transport model with a movable bed. This model is run in parallel with the hydrodynamic MOUSE model. The results, in terms of locations with sediment deposits, are compared with field data from the sewer system in Ljubljana. Further, the model is used to predict the effect of the removal of the sediment deposits on the combined sewer overflows.

The transfer of solids in combined sewer networks

Suspended solids are the main vectors of pollution in combined sewer wet weather flows. In spite of being very fine, they decant rather quickly except in the case of light rainfall events rich in organic matter. The part originating from sewer sediment deposits provides a large proportion of organic matter mass. By analysing the content and the volume of sewer deposits at different points from upstream to downstream, it emerges that the main source of this contribution is probably located in man-entry sewers. In one of these, sewer trunk no. 13 in Marseilles, five hundred metres of which were monitored continuously for sediment build-up over three years, the deposit volume grows mainly during certain rainfall events and its surface slope tends to an equilibrium with the (millimetric) particle size. Theoretical bed-load and suspension thresholds have been validated, then analysed for various situations and sections. A typology of the vulnerable areas, in several networks, has been drawn up, as well as a study of shear stress variations during a rainfall event. The sediment deposits seem to occur in particular hydraulic discontinuity zones where transport capacities can drop sharply.