RESUMEN
Enhancing sediment accumulation monitoring techniques in sewers will enable a better understanding of the build-up processes to develop improved cleaning strategies. Thermal sensors provide a solution to sediment depth estimation by passively monitoring temperature fluctuations in the wastewater and sediment beds, which allows evaluation of the heat-transfer processes in sewer pipes. This study analyses the influence of the flow conditions on heat-transfer processes at the water-sediment interface during dry weather flow conditions. For this purpose, an experimental campaign was performed by establishing different flow, temperature patterns, and sediment depth conditions in an annular flume, which ensured steady flow and room-temperature conditions. Numerical simulations were also performed to assess the impact of flow conditions on the relationships between sediment depth and harmonic parameters derived from wastewater and sediment-bed temperature patterns. Results show that heat transfer between water and sediment occurred instantaneously for velocities greater than 0.1 m/s, and that sediment depth estimations using temperature-based systems were barely sensitive to velocities between 0.1 and 0.4 m/s. A depth estimation accuracy of ±7 mm was achieved. This confirms the ability of using temperature sensors to monitor sediment build-up in sewers under dry weather conditions, without the need for flow monitoring.
Asunto(s)
Aguas del Alcantarillado , Temperatura , Sedimentos Geológicos , Monitoreo del Ambiente/métodos , Monitoreo del Ambiente/instrumentación , Movimientos del Agua , Eliminación de Residuos Líquidos/métodosRESUMEN
Combined sewer overflows (CSOs) may represent a significant source of pollution, but they are difficult to quantify at a large scale (e.g. regional or national), due to a lack of accessible data. In the present study, we use a large scale, 6-parameter, lumped hydrological model to perform a screening level assessment of different CSO management scenarios for the European Union and United Kingdom, considering prevention and treatment strategies. For each scenario we quantify the potential reduction of CSO volumes and duration, and estimate costs and benefits. A comparison of scenarios shows that treating CSOs before discharge in the receiving water body (e.g. by constructed wetlands) is more cost-effective than preventing CSOs. Among prevention strategies, urban greening has a benefit/cost ratio one order of magnitude higher than grey solutions, due to the several additional benefits it entails. We also estimate that real time control may bring on average a CSO volume reduction of just above 20%. In general, the design of appropriate CSO management strategies requires consideration of context-specific conditions, and is best made in the context of an integrated urban water management plan taking into account factors such as other ongoing initiatives in urban greening, the possibility to disconnect impervious surfaces from combined drainage systems, and the availability of space for grey or nature-based solutions.
Asunto(s)
Hidrología , Aguas del Alcantarillado , Análisis Costo-Beneficio , Reino UnidoRESUMEN
Uncertainty in urban drainage modelling studies presents challenges to decision makers with limited investment resources attempting to achieve regulatory compliance for intermittent discharges from Combined Sewer Overflows. This paper presents the development of a new decision-making approach to address two key challenges encountered when attempting to manage sewer overflows, these are (i) the implications of different risk preferences of individuals for investment decisions; and (ii) how to utilize information on uncertainties in system performance predictions due to input or parameter uncertainty while comparing decision alternatives. The developed decision-making approach uses a multi-objective decision formulation to analyse the trade-off between investment and predicted system performance under uncertainty while accounting for risk preferences of the individual decision maker. The proposed uncertainty based decision-making approach is able to incorporate any threshold-based regulatory criteria for intermittent sewer overflows and is illustrated using a case study catchment in Luxembourg. The results from this case study highlight the significant impact of individuals' risk preferences on the level of investment recommended to comply with threshold-based regulatory criteria. It was demonstrated that differing levels of risk-averseness can result in a substantial increase in investment cost for solutions that are regulatory compliant. This paper demonstrates the need for water companies to rigorously define a corporate risk preference strategy to ensure consistent investment decisions across their operations; otherwise, individual preferences may cause significant over-investment to meet the same regulatory goals.
Asunto(s)
Incertidumbre , Humanos , LuxemburgoRESUMEN
Heat recovery from combined sewers has a significant potential for practical renewable energy provision as sources of heat demand and sewer pipes are spread across urban areas. Sewers are continuously recharged with relatively hot wastewater, as well as interacting with heat sources from surrounding air and soil. However, the potential effects of modifying sewage temperature on in-sewer processes have received little attention. The deposition of fats, oils and greases (FOGs) and hydrogen sulphide formation are biochemical processes and are thus influenced by temperature. This paper utilises a case study approach to simulate anticipated temperature reductions in a sewer network due to heat recovery. A laboratory investigation into the formation of FOG deposits at temperatures varying between 5 °C and 20 °C provided mixed results, with only a weak temperature influence, highlighting the need for more research to fully understand the influence of the wastewater composition as well as temperature on FOG deposit formation. A separate modelling investigation into the formation of hydrogen sulphide when inflow temperature is varied between 5 °C and 20 °C showed considerable reductions in hydrogen sulphide formation. Hence, heat extraction from sewers could be a promising method for managing some in-sewer processes, combined with traditional methods such as chemical dosing.
Asunto(s)
Calor , Aguas del Alcantarillado , Grasas , Aceites , Aguas ResidualesRESUMEN
This paper aims to stimulate discussion based on the experiences derived from the QUICS project (Quantifying Uncertainty in Integrated Catchment Studies). First it briefly discusses the current state of knowledge on uncertainties in sub-models of integrated catchment models and the existing frameworks for analysing uncertainty. Furthermore, it compares the relative approaches of both building and calibrating fully integrated models or linking separate sub-models. It also discusses the implications of model linkage on overall uncertainty and how to define an acceptable level of model complexity. This discussion includes, whether we should shift our attention from uncertainties due to linkage, when using linked models, to uncertainties in model structure by necessary simplification or by using more parameters. This discussion attempts to address the question as to whether there is an increase in uncertainty by linking these models or if a compensation effect could take place and that overall uncertainty in key water quality parameters actually decreases. Finally, challenges in the application of uncertainty analysis in integrated catchment water quality modelling, as encountered in this project, are discussed and recommendations for future research areas are highlighted.
Asunto(s)
Modelos Teóricos , Calidad del Agua , IncertidumbreRESUMEN
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 & 207â¯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.
Asunto(s)
Calor , Aguas del Alcantarillado , Ciudades , Modelos Teóricos , Estaciones del Año , Aguas ResidualesRESUMEN
Exponential wash-off models are the most widely used method to predict sediment wash-off from urban surfaces. In spite of many studies, there is still a lack of knowledge on the effect of external drivers such as rainfall intensity and surface slope on wash-off predictions. In this study, a more physically realistic "structure" is added to the original exponential wash-off model (OEM) by replacing the invariant parameters with functions of rainfall intensity and catchment surface slope, so that the model can better represent catchment and rainfall conditions without the need for lookup tables and interpolation/extrapolation. In the proposed new exponential model (NEM), two such functions are introduced. One function describes the maximum fraction of the initial load that can be washed off by a rainfall event for a given slope and the other function describes the wash-off rate during a rainfall event for a given slope. The parameters of these functions are estimated using data collected from a series of laboratory experiments carried out using an artificial rainfall generator, a 1â¯m2 bituminous road surface and a continuous wash-off measuring system. These experimental data contain high temporal resolution measurements of wash-off fractions for combinations of five rainfall intensities ranging from 33 to 155â¯mm/h and three catchment slopes ranging from 2 to 8%. Bayesian inference, which allows the incorporation of prior knowledge, is implemented to estimate parameter values. Explicitly accounting for model bias and measurement errors, a likelihood function representative of the wash-off process is formulated, and the uncertainty in the prediction of the NEM is quantified. The results of this study show: 1) even when the OEM is calibrated for every experimental condition, the NEM's performance, with parameter values defined by functions, is comparable to the OEM. 2) Verification indices for estimates of uncertainty associated with the NEM suggest that the error model used in this study is able to capture the uncertainty well.
Asunto(s)
Modelos Teóricos , Lluvia , Teorema de Bayes , Calibración , Monitoreo del Ambiente/métodos , Sedimentos Geológicos , Incertidumbre , Movimientos del AguaRESUMEN
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-É and k-ω shear stress transport (SST) gave a better approximation for velocity and pressure.