Modelling of metaldehyde concentrations in surface waters: A travel time based approach

Diffuse agricultural pollution is widely recognized as a significant threat to the quality of water resources. Metaldehyde is a soluble synthetic aldehyde pesticide used globally in agriculture which has caused recent concern due to high observed levels (exceeding the European and UK standards for pesticides in drinking water value of 0.1 µg/l) in surface waters utilized for potable water supply. This paper describes the development of a new travel time based physically distributed metaldehyde prediction model which aims to describe the short term fluctuations of metaldehyde concentrations in surface waters caused by rainfall runoff events. This will enable water infrastructure operators to consider informed control decisions in order to improve the quality of abstracted surface water. The methodology is developed and trailed within a case study catchment in the UK. The new approach integrates spatially and temporally disaggregated surface runoff generation, routing and build-up/wash-off concepts using a simple structure in a GIS environment to build a metaldehyde concentration prediction model. The use of 1 km 2 resolution radar rainfall data and identification of high risk areas in the catchment provide an approach which considers the spatio-temporal variations of pollutant generation and transport in the catchment. The model is calibrated and validated using available catchment flow and a new metaldehyde concentration dataset acquired using automatic samplers over four rainfall events. An average coefficient of determination and model efficiency of 0.75 and 0.46 respectively have been obtained for the rainfall events used to validate the model. This shows the capability of the model for the intended purpose of predicting the arrival of peak metaldehyde concentrations at surface water abstraction sites and informing abstraction decisions

Quantification of energy losses at a surcharging manhole

Hydraulic models of sewer systems are commonly used to predict the risk of urban flooding. However, suitable calibration datasets in flood conditions are scarce. The quantification of energy losses within manhole structures is a current source of uncertainty within such models. To address this gap, a scaled physical manhole model is used to quantify hydraulic energy losses during surcharging and non-surcharging conditions. Two different novel configurations were tested; (1) With and without the presence of a manhole lid; (2) With and without the presence of a shallow flow on the surface. Results showed that total head losses were found to increase in surcharging conditions. The presence of the lid also marginally increased total head losses. The datasets are used to assess the performance of a numerical urban flood model (SIPSON) and comparisons highlighted that SIPSON tends to overestimate energy losses in surcharging conditions

CFD modelling of the transport of soluble pollutants from sewer networks to surface flows during urban flood events

Surcharging urban drainage systems are a potential source of pathogenic contamination of floodwater. While a number of previous studies have investigated net sewer to surface hydraulic flow rates through manholes and gullies during flood events, an understanding of how pollutants move from sewer networks to surface flood water is currently lacking. This paper presents a 3D CFD model to quantify flow and solute mass exchange through hydraulic structures featuring complex interacting pipe and surface flows commonly associated with urban flood events. The model is compared against experimental datasets from a large-scale physical model designed to study pipe/surface interactions during flood simulations. Results show that the CFD model accurately describes pipe to surface flow partition and solute transport processes through the manhole in the experimental setup. After validation, the model is used to elucidate key timescales which describe mass flow rates entering surface flows from pipe networks. Numerical experiments show that following arrival of a well-mixed solute at the exchange structure, solute mass exchange to the surface grows asymptotically to a value equivalent to the ratio of flow partition, with associated timescales a function of the flow conditions and diffusive transport inside the manhole

Comparative study of instantaneous frequency based methods for leak detection in pipeline networks

Methods of pressure transient analysis can be seen as a promising, accurate and low-cost tool for leak and feature detection in pipelines. Various systems have been developed by several groups of researchers in recent years. Such techniques have been successfully demonstrated under laboratory conditions but are not yet established for use with real field test data. The current paper presents a comparative study of instantaneous frequency analysis techniques based on pressure transients recorded within a live distribution network. The instantaneous frequency of the signals are analysed using the Hilbert transform (HT), the Normalised Hilbert transform (NHT), Direct Quadrature (DQ), Teager Energy Operator (TEO) and Cepstrum. This work demonstrates the effectiveness of the instantaneous frequency analysis in detecting a leaks and other features within the network. NHT and DQ allowed for the identification of the approximate location of leaks. The performance TEO is moderate, with Cepstrum being the worst performing method. © 2011 Elsevier Ltd. All rights reserved

Evaluation of data-driven and process-based real-time flow forecasting techniques for informing operation of surface water abstraction

This paper presents an approach to managing surface water abstraction utilizing real-time flow forecasting and control techniques. To evaluate the effectiveness of alternative data-driven and process-based methods, flow forecasts at a case study site (River Dove, UK) using (1) a probability-distributed rainfall-runoff model (PDM), (2) PDM coupled with an autoregressive integrated moving average (ARIMA) error predictor, and (3) a long short-term memory (LSTM) neural network are integrated into a water resources management model coupled with genetic algorithm optimization to simulate and compare water abstractions, reservoir storage, downstream river flows, and pumping energy costs. When compared to historical data, results show that both PDM plus ARIMA and LSTM forecasts led to improved water abstraction operations, i.e., increased water abstraction volumes during dry periods while maintaining river environmental flows, as well as reduced pumping costs. Cost savings were found to be sensitive to the accuracy of the forecasting technique only within specific flow ranges. This study demonstrates the water resource benefits of real-time flow forecasting in supporting flexible water pumping schedules and further discusses the benefits of alternative modeling approaches in the specific context of controlling water abstraction

Surface to sewer flow exchange through circular inlets during urban flood conditions

Accurately quantifying the capacity of sewer inlets (such as manhole lids and gullies) to transfer water is important for many hydraulic flood modelling tools. The large range of inlet types and grate designs used in practice makes the representation of flow through and around such inlets challenging. This study uses a physical scale model to quantify flow conditions through a circular inlet during shallow steady state surface flow conditions. Ten different inlet grate designs have been tested over a range of surface flow depths. The resulting datasets have been used (i) to quantify weir and orifice discharge coefficients for commonly used flood modelling surface-sewer linking equations and (ii) to validate a 2D finite difference model in terms of simulated water depths around the inlet. Calibrated weir and orifice coefficients were observed to be in the range 0.115-0.372 and 0.349-2.038, respectively, and a relationship with grate geometrical parameters was observed. The results show an agreement between experimentally observed and numerically modelled flow depths but with larger discrepancies at higher flow exchange rates. Despite some discrepancies, the results provide improved confidence regarding the reliability of the numerical method to model surface to sewer flow under steady state hydraulic conditions

Quantifying the impact of uncertainty within the longitudinal dispersion coefficient on concentration dynamics and regulatory compliance in rivers

The one‐dimensional advection dispersion equation (1D ADE) is commonly used in practice to simulate pollutant transport processes for assessment and improvement of water quality conditions in rivers. Various studies have shown that the longitudinal dispersion coefficient used within the 1D ADE is influenced by a range of hydraulic and geomorphological conditions. This study aims to quantify the impact and importance of the parameter uncertainty associated with the longitudinal dispersion coefficient on modeled pollutant time‐concentration profiles and its implications for meeting compliance with water quality regulations. Six regression equations for estimating longitudinal dispersion coefficients are evaluated, and commonly used evaluation criteria were assessed for their suitability. A statistical evaluation of the regression equations based on their original calibration data sets resulted in percent bias (PBIAS) values between −47.01% and 20.78%. For a case study, uncertainty associated with the longitudinal dispersion coefficient was propagated to time‐concentration profiles using 1D ADE and Monte Carlo simulations, and 75% confidence interval bands of the pollutant concentration versus time profiles were derived. For two studied equations, the measured peak concentration values were above the simulated 87.5th percentile, and for the other four equations it was close to the 87.5th percentile. Subsequent uncertainty propagation analysis of four diverse rivers show the potential considerable impact on concentration‐duration‐frequency‐based water quality studies, with 1D ADE modeling producing predictions of quality standard compliance which varied over hundreds of kilometers

Hydraulic optimisation of multiple flow control locations for the design of local real time control systems

Local real-time control (RTC) represents a potentially cost-effective solution for stormwater management in urban drainage systems. Existing methodologies to select the location of flow control devices (FCDs) are limited to single gate systems and are based on analysis of activated storage volume capacity, without considering hydrodynamic processes or rainfall characteristics. In this paper, a new genetic algorithm (GA)–based methodology is developed to determine the optimal location of multiple FCDs in urban drainage networks, when assessing RTC performance through hydraulic analysis. The methodology is tested on a case study network, where a high number of possible FCD location arrangements are tested and compared, and the RTC effectiveness in reducing combined sewer overflows has been evaluated over a range of design storm events. Results demonstrate the capability of the proposed method in selecting robust FCD placement strategies, for example when designing local RTC systems to meet specific performance criteria

Exchange between drainage systems and surface flows during urban flooding: Quasi-steady and dynamic modelling in unsteady flow conditions

The accurate modelling of urban flooding constitutes an integral part of flood risk assessment and management in residential and industrial areas. Interactions between drainage networks and surface runoff flows are commonly modelled based on weir/orifice equations; however, this approach has not been satisfactorily validated in unsteady flow conditions due to uncertainties in estimating the discharge coefficients and associated head losses. This study utilises experimental data of flow exchange between the sewer flow and the floodplain through a manhole without a lid to develop two alternate approaches that simulate this interaction and describe the associated exchange flow. A quasi-steady model links the exchange flow to the total head in the sewer pipe and the head losses in the sewer and the manhole, whilst a dynamic model takes also into account the evolution of the water level within the manhole at discrete time steps. The developed numerical models are subsequently validated against large-scale experimental data for unsteady sewer flow conditions, featuring variable exchange to the surface. Results confirmed that both models can accurately replicate experimental conditions, with improved performance when compared to existing methodologies based only on weir or orifice equations

Importance of partial barriers and temporal variation in flow when modelling connectivity in fragmented river systems

(1) The potential for catchment-scale connectivity modelling to help plan the restoration of connectivity in fragmented river systems is not yet well understood. In the present study the importance of two interrelated aspects of such modelling in determining predictions of connectivity are explored: (1) uncertainty in the passability of partial barriers (such as fish passes) and how the passabilities of series of partial barriers combine, and (2) temporal variation in connectivity due to flow. (2) Connectivity for Atlantic salmon (Salmo salar L.) and European perch (Perca fluviatilis L.) are modelled under alternative restoration strategies in the heavily impounded Don Catchment UK using two different methods for simulating the combined passability of series of partial barriers. Catchment-scale hydraulic and connectivity modelling were integrated using a novel method to account for the effect of flow on connectivity, achieved by consideration of flow-fish pass efficiency relationships and the treatment of gaps between habitat patches as partial barrier. (3) Modelled connectivity is very sensitive to uncertainty in barrier passability and the method used to simulate the combined passability of series of partial barriers. Flow also has a strong and complex effect on connectivity, with predicted temporal patterns being particularly dependent on how the combined impact of series of barriers is modelled. The sensitivity of the modelling constrains its capacity to predict the outcome of alternative connectivity restoration strategies. Nevertheless it does serve as a tool to think critically about connectivity restoration. If applied thoughtfully in full awareness of its limitations it can still be used assist in the planning and appraisal of alternative restoration options. (4) The modelling also provides a number of important practical insights. It shows that series of fish passes may be ineffective unless they operate at very high efficiencies. Small changes to flow-fish pass efficiency relationships can have a large effect on temporal patterns in connectivity. Overall fish pass efficiency is comprised of attraction and passage efficiencies which may differ in the extent to which they are determined by random processes. This likely has significant implications for the nature of the combined passability of series of fish passes