Automated screening of control potential with spatially explicit results to support dialogue about sewer overflow reduction and beyond.

For real-time control to become a standard measure for upgrading urban drainage systems, control potential screenings need to be easily integrated into the early planning processes that already take place. However, current screening methods are either not aligned with the present planning process, unrelatable for water managers or too time-consuming. We therefore developed an automated screening methodology through a co-design process with six Danish utilities. The process started out from a literature review, included interviews and workshops, and resulted in the control potential screening tool COPOTO. In the co-design process, utilities generally responded that indicators based solely on an assessment of static system attributes are insufficient. Thus, COPOTO instead post-processes the results of urban drainage simulation models that are commonly available. The decision context considered in initial planning phases was found to include environmental, economic, social and technical objectives that were highly case-dependent. When presenting CSO reduction potentials, the utilities therefore generally preferred interactive, spatially explicit visualisations that link the CSO reduction at a particular location to the storages and actuators that need to be activated. This enables water managers to discuss, for example, operational constraints of a considered control location. COPOTO provides such assessments with very limited manual and computational effort and thus facilitates the integration of real-time control into standard planning workflows of utilities.

Using multi-event hydrologic and hydraulic signatures from water level sensors to diagnose locations of uncertainty in integrated urban drainage models used in living digital twins.

Digital twins of urban drainage systems require simulation models that can adequately replicate the physical system. All models have their limitations, and it is important to investigate when and where simulation results are acceptable and to communicate the level of performance transparently to end users. This paper first defines a classification of four possible 'locations of uncertainty' in integrated urban drainage models. It then develops a structured framework for identifying and diagnosing various types of errors. This framework compares model outputs with in-sewer water level observations based on hydrologic and hydraulic signatures. The approach is applied on a real case study in Odense, Denmark, with examples from three different system sites: a typical manhole, a small flushing chamber, and an internal overflow structure. This allows diagnosing different model errors ranging from issues in the underlying asset database and missing hydrologic processes to limitations in the model software implementation. Structured use of signatures is promising for continuous, iterative improvements of integrated urban drainage models. It also provides a transparent way to communicate the level of model adequacy to end users.

Prioritize effluent quality, operational costs or global warming? - Using predictive control of wastewater aeration for flexible management of objectives in WRRFs.

This study presents a general model predictive control (MPC) algorithm for optimizing wastewater aeration in Water Resource Recovery Facilities (WRRF) under different management objectives. The flexibility of the MPC is demonstrated by controlling a WRRF under four management objectives, aiming at minimizing: (A) effluent concentrations, (B) electricity consumption, (C) total operations costs (sum electricity costs and discharge effluent tax) or (D) global warming potential (direct and indirect nitrous oxide emissions, and indirect from electricity production) . The MPC is tested with data from the alternating WRRF in Nørre Snede (Denmark) and from the Danish electricity grid. Results showed how the four control objectives resulted in important differences in aeration patterns and in the concentration dynamics over a day. Controls B and C showed similarities when looking at total costs, while similarities in global warming potential for controls A and D suggest that improving effluent quality also reduced greenhouse gasses emissions. The MPC flexibility in handling different objectives is shown by using a combined objective function, optimizing both cost and greenhouse emissions. This shows the trade-off between the two objectives, enabling the calculation of marginal costs and thus allowing WRRF operators to carefully evaluate prioritization of management objectives. The long-term MPC performance is evaluated over 51 days covering seasonal and inter-weekly variations. On a daily basis, control A was 9-30% cheaper on average compared to controls A, D and to the current rule-based control. Similarly, control D resulted on average in 35-43% lower greenhouse gasses daily emission compared to the other controls. Difference between control performance increased for days with greater inter-diurnal variations in electricity price or greenhouse emissions from electricity production, i.e. when MPC has greater possibilities for exploiting input variations. The flexibility of the proposed MPC can easily accommodate for additional control objectives, allowing WRRF operators to quickly adapt the plant operation to new management objectives and to face new performance requirements.

Integrated model predictive control of water resource recovery facilities and sewer systems in a smart grid: example of full-scale implementation in Kolding.

An integrated model predictive control (MPC) strategy to control the power consumption and the effluent quality of a water resource recovery facility (WRRF) by utilizing the storage capacity from the sewer system was implemented and put into operation for a 7-day trial period. This price-based MPC reacted to electricity prices and forecasted pollutant loads 24 hours ahead. The large storage capacity available in the sewer system directly upstream from the plant was used to control the incoming loads and, indirectly, the power consumption of the WRRF during dry weather operations. The MPC balances electricity costs and treatment quality based on linear dynamical models and predictions of storage capacity and effluent concentrations. This article first shows the modelling results involved in the design of this MPC. Secondly, results from full-scale MPC operation of the WRRF are shown. The monetary savings of the MPC strategy for the specific plant were quantified around approximately 200 DKK per day when fully exploiting the allowed storage capacity. The developed MPC strategy provides a new option for linking WRRFs to smart grid electricity systems.

Evaluation of stormwater micropollutant source control and end-of-pipe control strategies using an uncertainty-calibrated integrated dynamic simulation model.

The estimation of micropollutant (MP) fluxes in stormwater systems is a fundamental prerequisite when preparing strategies to reduce stormwater MP discharges to natural waters. Dynamic integrated models can be important tools in this step, as they can be used to integrate the limited data provided by monitoring campaigns and to evaluate the performance of different strategies based on model simulation results. This study presents an example where six different control strategies, including both source-control and end-of-pipe treatment, were compared. The comparison focused on fluxes of heavy metals (copper, zinc) and organic compounds (fluoranthene). MP fluxes were estimated by using an integrated dynamic model, in combination with stormwater quality measurements. MP sources were identified by using GIS land usage data, runoff quality was simulated by using a conceptual accumulation/washoff model, and a stormwater retention pond was simulated by using a dynamic treatment model based on MP inherent properties. Uncertainty in the results was estimated with a pseudo-Bayesian method. Despite the great uncertainty in the MP fluxes estimated by the runoff quality model, it was possible to compare the six scenarios in terms of discharged MP fluxes, compliance with water quality criteria, and sediment accumulation. Source-control strategies obtained better results in terms of reduction of MP emissions, but all the simulated strategies failed in fulfilling the criteria based on emission limit values. The results presented in this study shows how the efficiency of MP pollution control strategies can be quantified by combining advanced modeling tools (integrated stormwater quality model, uncertainty calibration).

Aeration tank settling and real time control as a tool to improve the hydraulic capacity and treatment efficiency during wet weather: results from 7 years' full-scale operational data.

This paper investigates the aeration tank settling (ATS) operation in combination with real time control (RTC) as a tool for increasing the hydraulic capacity and improving the treatment efficiency of a wastewater treatment plant (WWTP) during wet weather flows. Results from 7 years' full-scale operational data at the Avedøre WWTP, Denmark, show that ATS operation in combination with RTC increases the hydraulic capacity of the treatment plant with up to 150 and 67% of the design capacity during winter and summer respectively. Compared to the conventional wet weather operation, the ATS in combination with RTC operation resulted in lower effluent concentrations for total phosphate (40-50%), suspended solids (30-60%) and chemical oxygen demand (30-50%), whereas no significant effect was observed on total nitrogen. Apart from the reduced effluent concentrations, the RTC resulted in economic savings in the form of reduced costs for electricity and green taxes. However, in very few cases the ATS operation in combination with RTC was not able to handle design capacity, and some overflows occurred at flows below the design capacity. The frequency of these overflows may increase in the future due to increased rain intensity resulting in shorter prediction time available for ATS.

A conceptual framework for addressing complexity and unfolding transition dynamics when developing sustainable adaptation strategies in urban water management.

To achieve a successful and sustainable adaptation to climate change we need to transform the way we think about change. Much water management research has focused on technical innovation with a range of new solutions developed to achieve a 'more sustainable and integrated urban water management cycle'. But Danish municipalities and utility companies are struggling to bring such solutions into practice. 'Green infrastructure', for example, requires the consideration of a larger range of aspects related to the urban context than the traditional urban water system optimization. There is the need for standardized methods and guidelines to organize transdisciplinary processes where different types of knowledge and perspectives are taken into account. On the basis of the macro-meso-micro pattern inspired by complexity science and transition theory, we developed a conceptual framework to organize processes addressing the complexity characterizing urban water management in the context of climate change. In this paper the framework is used to organize a research process aiming at understanding and unfolding urban dynamics for sustainable transition. The final goal is to enable local authorities and utilities to create the basis for managing and catalysing the technical and organizational innovation necessary for a sustainable transition towards climate change adaptation in urban areas.

Quantification of uncertainty in modelled partitioning and removal of heavy metals (Cu, Zn) in a stormwater retention pond and a biofilter.

Strategies for reduction of micropollutant (MP) discharges from stormwater drainage systems require accurate estimation of the potential MP removal in stormwater treatment systems. However, the high uncertainty commonly affecting stormwater runoff quality modelling also influences stormwater treatment models. This study identified the major sources of uncertainty when estimating the removal of copper and zinc in a retention pond and a biofilter by using a conceptual dynamic model which estimates MP partitioning between the dissolved and particulate phases as well as environmental fate based on substance-inherent properties. The two systems differ in their main removal processes (settling and filtration/sorption, respectively) and in the time resolution of the available measurements (composite samples and pollutographs). The most sensitive model factors, identified by using Global Sensitivity Analysis (GSA), were related to the physical characteristics of the simulated systems (flow and water losses) and to the fate processes related to Total Suspended Solids (TSS). The model prediction bounds were estimated by using the Generalized Likelihood Uncertainty Estimation (GLUE) technique. Composite samples and pollutographs produced similar prediction bounds for the pond and the biofilter, suggesting a limited influence of the temporal resolution of samples on the model prediction bounds. GLUE highlighted model structural uncertainty when modelling the biofilter, due to disregard of plant-driven evapotranspiration, underestimation of sorption and neglect of oversaturation with respect to minerals/salts. The results of this study however illustrate the potential for the application of conceptual dynamic fate models base on substance-inherent properties, in combination with available datasets and statistical methods, to estimate the MP removal in different stormwater treatment systems and compare with environmental quality standards targeting the dissolved MP fraction.

Micropollutants in stormwater runoff and combined sewer overflow in the Copenhagen area, Denmark.

Stormwater runoff contains a broad range of micropollutants. In Europe a number of these substances are regulated through the Water Framework Directive, which establishes Environmental Quality Standards (EQSs) for surface waters. Knowledge about discharge of these substances through stormwater runoff and combined sewer overflows (CSOs) is essential to ensure compliance with the EQSs. Results from a screening campaign including more than 50 substances at four stormwater discharge locations and one CSO in Copenhagen are reported here. Heavy metal concentrations were detected at levels similar to earlier findings, e.g., with copper found at concentrations up to 13 times greater than the Danish standard for surface waters. The concentration of polyaromatic hydrocarbons (PAHs) exceeded the EQSs by factors up to 500 times for stormwater and 2,000 times for the CSO. Glyphosate was found in all samples whilst diuron, isoproturon, terbutylazine and MCPA were found only in some of the samples. Diethylhexylphthalate (DEHP) was also found at all five locations in concentrations exceeding the EQS. The results give a valuable background for designing further monitoring programmes focusing on the chemical status of surface waters in urban areas.

Water management in cities of the future using emission control strategies for priority hazardous substances.

Cities of the future face challenges with respect to the quantity and quality of water resources, and multiple managerial options need to be considered in order to safeguard urban surface water quality. In a recently completed project on 'Source control options for reducing emissions of Priority Pollutants' (ScorePP), seven emission control strategies (ECSs) were developed and tested within a semi-hypothetical case city (SHCC) to evaluate their potential to reduce the emission of selected European priority hazardous substances (PHSs) to surface waters. The ECSs included (1) business-as-usual, (2) full implementation of relevant European (EU) directives, (3) ECS2 in combination with voluntary options for household, municipalities and industry, (4) ECS2 combined with industrial treatment and best available technologies (BAT), (5) ECS2 in combination with stormwater and combined sewer overflow treatment, (6) ECS2 in combination with advanced wastewater treatment, and (7) combinations of ECS3-6. The SHCC approach was chosen to facilitate transparency, to allow compensating for data gaps and to decrease the level of uncertainty in the results. The selected PHSs: cadmium (Cd), hexachlorobenzene (HCB), nonylphenol (NP) and pentabromodiphenyl ether (PBDE) differ in their uses and environmental fate and therefore accumulate in surface waters to differing extents in response to the application of alternative ECS. To achieve the required reduction in PHS levels in urban waters the full implementation of existing EU regulation is prioritised and feasible combinations of managerial and technological options (source control and treatment) can be highly relevant for mitigating releases.

Evaluation of two stormwater infiltration trenches in central Copenhagen after 15 years of operation.

Two stormwater infiltration trenches were installed in 1993 in an area in central Copenhagen. The system was monitored continuously for almost three years after establishment, and a small reduction in performance over that time, possibly due to clogging, was noted. A new study was conducted in 2009 to see whether the reduction in performance has continued and to determine how the system performs today. Water levels in the trenches were monitored for almost 4 months, and from this period seven events were selected to analyse the infiltration rate. A comparison with similar analyses on storm sequences from the first 3 years of operation shows that the infiltration has decreased since the establishment of the system 15 years ago. The decrease is statistically significant (p<0.01). A clogging model was fitted to the data and predictions were made for future performance. The results show that the system will discharge around 10 times more annual overflow to the sewers after 100 years of operation compared to the initial volumes, if clogging continues at current rates. This corresponds to 60% of the total runoff from the area. The results show that clogging and proper maintenance are important factors to consider when implementing stormwater infiltration trenches.

Uncertainty-based calibration and prediction with a stormwater surface accumulation-washoff model based on coverage of sampled Zn, Cu, Pb and Cd field data.

A dynamic conceptual and lumped accumulation wash-off model (SEWSYS) is uncertainty-calibrated with Zn, Cu, Pb and Cd field data from an intensive, detailed monitoring campaign. We use the generalized linear uncertainty estimation (GLUE) technique in combination with the Metropolis algorithm, which allows identifying a range of behavioral model parameter sets. The small catchment size and nearness of the rain gauge justified excluding the hydrological model parameters from the uncertainty assessment. Uniform, closed prior distributions were heuristically specified for the dry and wet removal parameters, which allowed using an open not specified uniform prior for the dry deposition parameter. We used an exponential likelihood function based on the sum of squared errors between observed and simulated event masses and adjusted a scaling factor to cover 95% of the observations within the empirical 95% model prediction bounds. A positive correlation between the dry deposition and the dry (wind) removal rates was revealed as well as a negative correlation between the wet removal (wash-off) rate and the ratio between the dry deposition and wind removal rates, which determines the maximum pool of accumulated metal available on the conceptual catchment surface. Forward Monte Carlo analysis based on the posterior parameter sets covered 95% of the observed event mean concentrations, and 95% prediction quantiles for site mean concentrations were estimated to 470 µg/l ± 20% for Zn, 295 µg/l ± 40% for Cu, 20 µg/l ± 80% for Pb and 0.6 µg/l ± 35% for Cd. This uncertainty-based calibration procedure adequately describes the prediction uncertainty conditioned on the used model and data, but seasonal and site-to-site variation is not considered, i.e. predicting metal concentrations in stormwater runoff from gauged as well as ungauged catchments with the SEWSYS model is generally more uncertain than the indicated numbers.

Combining multimedia models with integrated urban water system models for micropollutants.

Integrated urban water system (IUWS) modeling aims at assessing the quality of the surface water receiving the urban emissions through sewage treatment plants, combined sewer overflows (CSOs) and stormwater drainage systems. However, some micropollutants tend to appear in more than one environmental medium (air, water, sediment, soil, groundwater, etc.). In this work, a multimedia fate and transport model (MFTM) is "wrapped around" a dynamic IUWS model for organic micropollutants to enable integrated environmental assessment. The combined model was tested on a hypothetical catchment using two scenarios: on the one hand a reference scenario with a combined sewerage system and on the other hand a stormwater infiltration pond scenario, as an example of a sustainable urban drainage system (SUDS). A case for Bis(2-ethylhexyl) phthalate (DEHP) was simulated and resulted in reduced surface water concentrations for the latter scenario. However, the model also showed that this was at the expense of increased fluxes to air, groundwater and infiltration pond soil. The latter effects are generally not included in IUWS models, whereas MTFMs usually do not consider dynamic surface water concentrations,; hence the combined model approach provides a better basis for integrated environmental assessment of micropollutants' fate in urban environments.

Dynamic stormwater treatment unit model for micropollutants (STUMP) based on substance inherent properties.

Modelling the removal of micropollutants (MPs) in stormwater treatment systems is essential in a context that is characterized by a general lack of measurements. This paper presents an innovative dynamic model for the prediction of the removal of MPs in stormwater treatment systems (Stormwater Treatment Unit model for Micro Pollutants--STUMP). The model, based on a conceptual model of two-compartment (water and sediment) serial Continuous Stirred-Tank Reactors (CSTRs), can predict the fate of MPs based on their inherent properties, which are often the only information available regarding this kind of substances. The flexible structure of the model can be applied to a wide range of treatment units and substances. Based on the most relevant removal processes (settling, volatilization, sorption, biodegradation, and abiotic degradation), the model allows the dynamic simulation of the MP behaviour in the different compartments of stormwater treatment systems. The model was tested for heavy metals (copper and zinc) and organic substances (benzene and di(2-ethylhexyl)phthalate). The results show that volatilization plays a big role for removal of benzene while the removal of substances with high sorption capacity is mainly driven by settling. The model was proven to be able to predict the importance of the various fate processes for selected substances with different inherent properties. A thorough assessment of the influence of the various fate process parameters will allow a reliable assessment of the treatment performances for a wide range of MPs.

Potential future increase in extreme one-hour precipitation events over Europe due to climate change.

In this study the potential increase of extreme precipitation in a future warmer European climate has been examined. Output from the regional climate model (RCM) HIRHAM4 covering Europe has been analysed for two periods, a control period 1961-1990 and a scenario 2071-2100, the latter following the IPCC scenario A2. The model has a resolution of about 12 km, which is unique compared with existing RCM studies that typically operate at 25-50 km scale, and make the results relevant to hydrological phenomena occurring at the spatial scale of the infrastructure designed to drain off rainfall in large urban areas. Extreme events with one- and 24-hour duration were extracted using the Partial Duration Series approach, a Generalized Pareto Distribution was fitted to the data and T-year events for return periods from 2 to 100 years were calculated for the control and scenario period in model cells across Europe. The analysis shows that there will be an increase of the intensity of extreme events generally in Europe; Scandinavia will experience the highest increase and southern Europe the lowest. A 20 year 1-hour precipitation event will for example become a 4 year event in Sweden and a 10 year event in Spain. Intensities for short durations and high return periods will increase the most, which implies that European urban drainage systems will be challenged in the future.

How uncertain is model-based prediction of copper loads in stormwater runoff?

In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation-washout model and a total of 57 measurements during one month, the total predicted copper masses can be predicted within a range of +/-50% of the median value. The message is that this relatively large uncertainty should be acknowledged in connection with posting statements about micropollutant loads as estimated from dynamic models, even when calibrated with on-site concentration data.

Comparative uncertainty analysis of copper loads in stormwater systems using GLUE and grey-box modeling.

In this paper two attempts to assess the uncertainty involved with model predictions of copper loads from stormwater systems are made. In the first attempt, the GLUE methodology is applied to derive model parameter sets that result in model outputs encompassing a significant number of the measurements. In the second attempt the conceptual model is reformulated to a grey-box model followed by parameter estimation. Given data from an extensive measurement campaign, the two methods suggest that the output of the stormwater pollution model is associated with significant uncertainty. With the proposed model and input data, the GLUE analysis show that the total sampled copper mass can be predicted within a range of +/-50% of the median value (385 g), whereas the grey-box analysis showed a prediction uncertainty of less than +/-30%. Future work will clarify the pros and cons of the two methods and furthermore explore to what extent the estimation can be improved by modifying the underlying accumulation-washout model.

Selected stormwater priority pollutants: a European perspective.

The chemical characteristics of stormwater are dependent on the nature of surfaces (roads, roofs etc.) with which it comes into contact during the runoff process as well as natural processes and anthropogenic activities in the catchments. The different types of pollutants may cause problems during utilisation, detention or discharge of stormwater to the environment and may pose specific demands to decentralised treatment. This paper proposes a scientifically justifiable list of selected stormwater priority pollutants (SSPP) to be used, e.g., for evaluation of the chemical risks occurring in different handling strategies. The SSPP-list consists of 25 pollutant parameters including eight of the priority pollutants currently identified in the European Water Framework Directive. It contains general water quality parameters (organic and suspended matter, nutrients and pH); metals (Cd, Cr, Cu, Ni, Pb, Pt and Zn); PAH (naphthalene, pyrene and benzo[a]pyrene); herbicides (pendimethalin, phenmedipham, glyphosate and terbutylazine); and other representative industrially derived compounds (nonylphenol ethoxylates, pentachlorophenol, di(2-ethylhexyl)phthalate, PCB-28 and methyl tert-butyl ether). Tools for flux modelling, enabling calculation of predicted environmental concentrations (PECs), and for ranking the susceptibility of a pollutant to removal within a range of structural stormwater treatment systems or best management practices (BMPs) have been developed, but further work is required to allow all SSPPs to be addressed in the development of future stormwater pollution control measures. In addition, the identified SSPPs should be considered for inclusion in stormwater related monitoring campaigns.

Integrated modelling of two xenobiotic organic compounds.

This paper presents a dynamic mathematical model that describes the fate and transport of two selected xenobiotic organic compounds (XOCs) in a simplified representation of an integrated urban wastewater system. A simulation study, where the xenobiotics bisphenol A and pyrene are used as reference compounds, is carried out. Sorption and specific biological degradation processes are integrated with standardised water process models to model the fate of both compounds. Simulated mass flows of the two compounds during one dry weather day and one wet weather day are compared for realistic influent flow rate and concentration profiles. The wet weather day induces resuspension of stored sediments, which increases the pollutant load on the downstream system. The potential of the model to elucidate important phenomena related to origin and fate of the model compounds is demonstrated.

Transfer of hydrophobic contaminants in urban runoff particles to benthic organisms estimated by an in vitro bioaccessibility test.

An in vitro bioaccessibility test was applied for assessing the transfer of polycyclic aromatic hydrocarbons (PAHs) present in road dust, into benthic organisms living in a receiving water body. The road dust is supposed to be urban runoff particles under wet weather conditions. Sodium dodecyl sulfate (SDS) solution was used as a hypothetical gut fluid. Pyrene, fluoranthene and phenanthrene were the main PAH species in the SDS extractable fraction of road dust, as well as the whole extract. Benzo(ghi)perylene showed relatively low concentrations in the SDS extract in spite of a high concentration in the original dust. The PAH composition in benthic organisms (polychaetes) did not correspond with that of the surrounding sediment and the PAHs detected were also detected in high concentrations in the SDS extract of road dust. When testing the toxicity of the extracted contaminants by a standardised algal toxicity test, SDS extracts of a detention pond sediment showed higher toxicity than the pore water of the corresponding sediment. Sediment suspension showed a comparative toxicity with 0.1% SDS extract. From the results, the in vitro bioaccessibility test seems more suitable to evaluate the exposed contaminants than the traditional organic solvent extraction method and the SDS extracted fraction is applicable to toxicity tests reflecting the digestive process.