Alma Schellart

Towards quantification of uncertainty in predicting water quality failures in integrated catchment model studies.

This paper describes the development and application of a method for estimating uncertainty in the prediction of sewer flow quantity and quality and how this may impact on the prediction of water quality failures in integrated catchment modelling (ICM) studies. The method is generic and readily adaptable for use with different flow quality prediction models that are used in ICM studies. Use is made of the elicitation concept, whereby expert knowledge combined with a limited amount of data are translated into probability distributions describing the level of uncertainty of various input and model variables. This type of approach can be used even if little or no site specific data is available. Integrated catchment modelling studies often use complex deterministic models. To apply the results of elicitation in a case study, a computational reduction method has been developed in order to determine levels of uncertainty in model outputs with a reasonably practical level of computational effort. This approach was applied to determine the level of uncertainty in the number of water quality failures predicted by an ICM study, due to uncertainty associated with input and model parameters of the urban drainage model component of the ICM. For a small case study catchment in the UK, it was shown that the predicted number of water quality failures in the receiving water could vary by around 45% of the number predicted without consideration of model uncertainty for dissolved oxygen and around 32% for unionised ammonia. It was concluded that the potential overall levels of uncertainty in the ICM outputs could be significant. Any solutions designed using modelling approaches that do not consider uncertainty associated with model input and model parameters may be significantly over-dimensioned or under-dimensioned. With changing external inputs, such as rainfall and river flows due to climate change, better accounting for uncertainty is required.

Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area

Abstract Due to the relatively small spatial scale, as well as rapid response, of urban drainage systems, the use of quantitative rainfall forecasts for providing quantitative flow and depth predictions is a challenging task. Such predictions are important when consideration is given to urban pluvial flooding and receiving water quality, and it is worthwhile to investigate the potential for improved forecasting. In this study, three quantitative precipitation forecast methods of increasing complexity were compared and used to create quantitative forecasts of sewer flows 0–3 h ahead in the centre of a small town in the north of England. The HyRaTrac radar nowcast model was employed, as well as two different versions of the more complex STEPS model. The STEPS model was used as a deterministic nowcasting system, and was also blended with the Numerical Weather Prediction (NWP) model MM5 to investigate the potential of increasing forecast lead-times (LTs) using high-resolution NWP. Predictive LTs between 15 and 90 min gave acceptable results, but were a function of the event type. It was concluded that higher resolution rainfall estimation as well as nowcasts are needed for prediction of both local pluvial flooding and combined sewer overflow spill events. Editor D. Koutsoyiannis; Guest editor R.J. Moore Citation Schellart, A., Liguori, S., Krämer, S., Saul, A., and Rico-Ramirez, M.A., 2014. Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area. Hydrological Sciences Journal, 59 (7), 1418–1436. http://dx.doi.org/10.1080/02626667.2014.920505

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.

Modelling the viability of heat recovery from combined sewers.

Modelling of wastewater temperatures along a sewer pipe using energy balance equations and assuming steady-state conditions was achieved. Modelling error was calculated, by comparing the predicted temperature drop to measured ones in three combined sewers, and was found to have an overall root mean squared error of 0.37 K. Downstream measured wastewater temperature was plotted against modelled values; their line gradients were found to be within the range of 0.9995-1.0012. The ultimate aim of the modelling is to assess the viability of recovering heat from sewer pipes. This is done by evaluating an appropriate location for a heat exchanger within a sewer network that can recover heat without impacting negatively on the downstream wastewater treatment plant (WWTP). Long sewers may prove to be more viable for heat recovery, as heat lost can be reclaimed before wastewater reaching the WWTP.

Erosion resistance and behaviour of highly organic in-sewer sediment.

Reliable prediction of time-varying pollutant loads in combined sewer systems during storm periods can aid better management of the release of pollution into natural environments as well as enhancing storage tank design. Better understanding of the behaviour of sewer sediments is crucial for the development of models that adequately describe the transport of in-sewer solids and accurately predict the changes in pollutant concentration within combined sewers during storm events. This paper reports on the results of a test programme to examine the erosion of highly organic sewer sediment under the application of time-varying shear stress. The tests were carried out with and without supplying oxygen, and varying simulated dry-weather periods. The aim was to investigate the behaviour of real in-sewer sediment with a high organic content (around 80%) in an attempt to improve prediction of the transport rates under the particular Mediterranean conditions of long dry-period/build-up and intense rainfall/wash-off, and understand how this environment affects the erosional resistance and subsequent sediment release. Results have been compared with previous work on lower organic content sewer sediments and artificial organic sediment.

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.

A comparative study of manhole hydraulics using stereoscopic PIV and different RANS models

Flows in manholes are complex and may include swirling and recirculation flow with significant turbulence and vorticity. However, how these complex 3D flow patterns could generate different energy losses and so affect flow quantity in the wider sewer network is unknown. In this work, 2D3C stereo Particle Image Velocimetry measurements are made in a surcharged scaled circular manhole. A computational fluid dynamics (CFD) model in OpenFOAM® with four different Reynolds Averaged Navier Stokes (RANS) turbulence model is constructed using a volume of fluid model, to represent flows in this manhole. Velocity profiles and pressure distributions from the models are compared with the experimental data in view of finding the best modelling approach. It was found among four different RANS models that the re-normalization group (RNG) k-ɛ and k-ω shear stress transport (SST) gave a better approximation for velocity and pressure.

Modelling the potential for multi-location in-sewer heat recovery at a city scale under different seasonal scenarios

A computational network heat transfer model was utilised to model the potential of heat energy recovery at multiple locations from a city scale combined sewer network. The uniqueness of this network model lies in its whole system validation and implementation for seasonal scenarios in a large sewer network. The network model was developed, on the basis of a previous single pipe heat transfer model, to make it suitable for application in large sewer networks and its performance was validated in this study by predicting the wastewater temperature variation across the network. Since heat energy recovery in sewers may impact negatively on wastewater treatment processes, the viability of large scale heat recovery was assessed by examining the distribution of the wastewater temperatures throughout a 3000 pipe network, serving a population equivalent of 79500, and at the wastewater treatment plant inlet. Three scenarios; winter, spring and summer were modelled to reflect seasonal variations. The model was run on an hourly basis during dry weather. The modelling results indicated that potential heat energy recovery of around 116, 160 & 207 MWh/day may be obtained in January, March and May respectively, without causing wastewater temperature either in the network or at the inlet of the wastewater treatment plant to reach a level that was unacceptable to the water utility.

Prediction of organic combined sewer sediment release and transport

AbstractAccurate predictions of sediment loads released by sewer overflow discharges are important for being able to provide protection to vulnerable receiving waters. These predictions are sensiti...

Thermal and Hydraulic Properties of Sandy Soils during Drying and Wetting Cycles

There is an increasing interest in the use of Ground Source Heat Pumps (GSHPs) as a source of renewable energy in temperate countries. GSHPs coupled with buried heat collectors can harness the thermal energy from near-surface soils to provide the heating required for domestic properties. The performance of a GSHP system depends greatly on the thermal conductivity of the surrounding soils. Near-surface soils undergo cycles of drying and wetting due to, for example, the infiltration of rain water and/or fluctuations of the ground water table. Several parameters - including the properties of soil, suction head and saturation history - affect the thermal properties as well as the retention and flow of water. This paper presents results from a comprehensive laboratory investigation on sand samples with markedly different grain size distribution. Simultaneous measurements of thermal and hydraulic properties of the sands were taken under incremental increase/decrease in the suction head values to simulate cycles of drying and wetting. The results clearly suggest that the thermal conductivity is better expressed as a function of the matric suction head so as to reflect the saturation history. There has been almost five-fold increase in the measured value of thermal conductivity when the soil was wetted to a residual degree of saturation from being dry.