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Peter Steen Mikkelsen
DTU Environment, DTU, Kgs. Lyngby, 2800, Denmark

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Preprint content
Published: 06 April 2021
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This paper describes a comprehensive and unique open-access data set for research within hydrological and hydraulic modelling of urban drainage systems. The data comes from a mainly combined urban drainage system covering a 1.7 km2 area in the town of Bellinge, a suburb to the city of Odense, Denmark. The data set consists of up to 10 years of observations (2010–2020) from 13 level meters, one flow meter, one position-sensor and four power sensors in the system, along with rainfall data from three rain gauges and two weather radars (X- and C-band), and meteorological data from a nearby weather station. The system characteristics of the urban drainage system (information about manholes, pipes etc.) can be found in the data set along with characteristics of the surface area (contour lines etc.). Two detailed hydrodynamic, distributed urban drainage models of the system are provided in the software systems Mike Urban and EPA SWMM. The two simulation models generally show similar responses, but systematic differences are present since the models have not been calibrated. With this data set we provide a useful case that enables independent testing and replication of results from future scientific developments and innovation within urban hydrology and urban drainage system research. The data set can be downloaded from https://doi.org/10.11583/DTU.c.5029124, (Pedersen et al., 2021a).

ACS Style

Agnethe Nedergaard Pedersen; Jonas Wied Pedersen; Antonio Vigueras-Rodriguez; Annette Brink-Kjær; Morten Borup; Peter Steen Mikkelsen. The Bellinge data set: open data and models for community-wide urban drainage systems research. 2021, 2021, 1 -28.

AMA Style

Agnethe Nedergaard Pedersen, Jonas Wied Pedersen, Antonio Vigueras-Rodriguez, Annette Brink-Kjær, Morten Borup, Peter Steen Mikkelsen. The Bellinge data set: open data and models for community-wide urban drainage systems research. . 2021; 2021 ():1-28.

Chicago/Turabian Style

Agnethe Nedergaard Pedersen; Jonas Wied Pedersen; Antonio Vigueras-Rodriguez; Annette Brink-Kjær; Morten Borup; Peter Steen Mikkelsen. 2021. "The Bellinge data set: open data and models for community-wide urban drainage systems research." 2021, no. : 1-28.

Journal article
Published: 26 February 2021 in Water Research
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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.

ACS Style

P.A. Stentoft; T. Munk-Nielsen; J.K. Møller; H. Madsen; B. Valverde-Pérez; P.S. Mikkelsen; L. Vezzaro. Prioritize effluent quality, operational costs or global warming? – Using predictive control of wastewater aeration for flexible management of objectives in WRRFs. Water Research 2021, 196, 116960 .

AMA Style

P.A. Stentoft, T. Munk-Nielsen, J.K. Møller, H. Madsen, B. Valverde-Pérez, P.S. Mikkelsen, L. Vezzaro. Prioritize effluent quality, operational costs or global warming? – Using predictive control of wastewater aeration for flexible management of objectives in WRRFs. Water Research. 2021; 196 ():116960.

Chicago/Turabian Style

P.A. Stentoft; T. Munk-Nielsen; J.K. Møller; H. Madsen; B. Valverde-Pérez; P.S. Mikkelsen; L. Vezzaro. 2021. "Prioritize effluent quality, operational costs or global warming? – Using predictive control of wastewater aeration for flexible management of objectives in WRRFs." Water Research 196, no. : 116960.

Journal article
Published: 25 February 2021 in Water
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In this paper, we review the emerging concept of digital twins (DTs) for urban water systems (UWS) based on the literature, stakeholder interviews and analyzing the current DT implementation process in the utility company VCS Denmark (VCS). Here, DTs for UWS are placed in the context of DTs at the component, unit process/operation or hydraulic structure, treatment plant, system, city, and societal levels. A UWS DT is characterized as a systematic virtual representation of the elements and dynamics of the physical system, organized in a star-structure with a set of features connected by data links that are based on standards for open data. This allows the overall functionality to be broken down into smaller, tangible units (features), enabling microservices that communicate via data links to emerge (the most central feature), facilitated by application programing interfaces (APIs). Coupled to the physical system, simulation models and advanced analytics are among the most important features. We propose distinguishing between living and prototyping DTs, where the term “living” refers to coupling observations from an ever-changing physical twin (which may change with, e.g., urban growth) with a simulation model, through a data link connecting the two. A living DT is thus a near real-time representation of an UWS and can be used for operational and control purposes. A prototyping DT represents a scenario for the system without direct coupling to real-time observations, which can be used for design or planning. By acknowledging that different DTs exist, it is possible to identify the value-creation from DTs achieved by different end-users inside and outside a utility organization. Analyzing the DT workflow in VCS shows that a DT must be multifunctional, updateable, and adjustable to support potential value creation across the utility company. This study helps clarify key DT terminology for UWS and identifies steps to create a DT by building upon digital ecosystems (DEs) and open standards for data.

ACS Style

Agnethe Pedersen; Morten Borup; Annette Brink-Kjær; Lasse Christiansen; Peter Mikkelsen. Living and Prototyping Digital Twins for Urban Water Systems: Towards Multi-Purpose Value Creation Using Models and Sensors. Water 2021, 13, 592 .

AMA Style

Agnethe Pedersen, Morten Borup, Annette Brink-Kjær, Lasse Christiansen, Peter Mikkelsen. Living and Prototyping Digital Twins for Urban Water Systems: Towards Multi-Purpose Value Creation Using Models and Sensors. Water. 2021; 13 (5):592.

Chicago/Turabian Style

Agnethe Pedersen; Morten Borup; Annette Brink-Kjær; Lasse Christiansen; Peter Mikkelsen. 2021. "Living and Prototyping Digital Twins for Urban Water Systems: Towards Multi-Purpose Value Creation Using Models and Sensors." Water 13, no. 5: 592.

Journal article
Published: 05 February 2021 in Journal of Hydro-environment Research
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Information and communication technologies combined with in-situ sensors are increasingly being used in the management of urban drainage systems. The large amount of data collected in these systems can be used to train a data-driven soft sensor, which can supplement the physical sensor. Artificial Neural Networks have long been used for time series forecasting given their ability to recognize patterns in the data. Long Short-Term Memory (LSTM) neural networks are equipped with memory gates to help them learn time dependencies in a data series and have been proven to outperform other type of networks in predicting water levels in urban drainage systems. When used for soft sensing, neural networks typically receive antecedent observations as input, as these are good predictors of the current value. However, the antecedent observations may be missing due to transmission errors or deemed anomalous due to errors that are not easily explained. This study quantifies and compares the predictive accuracy of LSTM networks in scenarios of limited or missing antecedent observations. We applied these scenarios to an 11-month observation series from a combined sewer overflow chamber in Copenhagen, Denmark. We observed that i) LSTM predictions generally displayed large variability across training runs, which may be reduced by improving the selection of hyperparameters (non-trainable parameters); ii) when the most recent observations were known, adding information on the past did not improve the prediction accuracy; iii) when gaps were introduced in the antecedent water depth observations, LSTM networks were capable of compensating for the missing information with the other available input features (time of the day and rainfall intensity); iv) LSTM networks trained without antecedent water depth observations yielded larger prediction errors, but still comparable with other scenarios and captured both dry and wet weather behaviors. Therefore, we concluded that LSTM neural network may be trained to act as soft sensors in urban drainage systems even when observations from the physical sensors are missing.

ACS Style

Rocco Palmitessa; Peter Steen Mikkelsen; Morten Borup; Adrian W.K. Law. Soft sensing of water depth in combined sewers using LSTM neural networks with missing observations. Journal of Hydro-environment Research 2021, 1 .

AMA Style

Rocco Palmitessa, Peter Steen Mikkelsen, Morten Borup, Adrian W.K. Law. Soft sensing of water depth in combined sewers using LSTM neural networks with missing observations. Journal of Hydro-environment Research. 2021; ():1.

Chicago/Turabian Style

Rocco Palmitessa; Peter Steen Mikkelsen; Morten Borup; Adrian W.K. Law. 2021. "Soft sensing of water depth in combined sewers using LSTM neural networks with missing observations." Journal of Hydro-environment Research , no. : 1.

Journal article
Published: 20 August 2020 in Water Resources Research
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Combined sewer overflows (CSO) of mixed stormwater and wastewater pollute nearby receiving surface waters and pose a risk to the environment and human health. We use ‘integrated stormwater inflow control’ to mitigate CSO by dynamically controlling the inflow of stormwater to the combined sewer system in real‐time, expanding the physical space of traditional real‐time control. This control is carried out with model predictive control (MPC), which we base on convex optimization including a linear internal surrogate model of the controllable above‐ and belowground infrastructure. A detailed hydrodynamic model is used to evaluate the results and recursively initialize the surrogate model. MPC dynamically decides when to let stormwater enter the sewer system and when to store and convey excess stormwater in the above‐ground infrastructure otherwise intended for passive cloudburst management. The performance was quantified in a simulation study in Copenhagen, Denmark, using a 1D distributed hydrodynamic model and 32 rain events from 2016, of which 18 caused CSO in the situation without control. Four of the 18 CSO events were avoided with MPC, and the total CSO volume was reduced by 98.4% of the potential reducible volume. For one event, stormwater was unnecessarily kept on the surface because the surrogate model wrongly predicted a CSO. The computational cost was in all cases compatible with an operational implementation. With the invention of proper actuators for control of stormwater inflows, we show that MPC of stormwater inflows may be a viable supplement to more traditional passive ways of managing stormwater in urban areas.

ACS Style

N. S. V. Lund; M. Borup; H. Madsen; O. Mark; P. S. Mikkelsen. CSO Reduction by Integrated Model Predictive Control of Stormwater Inflows: A Simulated Proof of Concept Using Linear Surrogate Models. Water Resources Research 2020, 56, 1 .

AMA Style

N. S. V. Lund, M. Borup, H. Madsen, O. Mark, P. S. Mikkelsen. CSO Reduction by Integrated Model Predictive Control of Stormwater Inflows: A Simulated Proof of Concept Using Linear Surrogate Models. Water Resources Research. 2020; 56 (8):1.

Chicago/Turabian Style

N. S. V. Lund; M. Borup; H. Madsen; O. Mark; P. S. Mikkelsen. 2020. "CSO Reduction by Integrated Model Predictive Control of Stormwater Inflows: A Simulated Proof of Concept Using Linear Surrogate Models." Water Resources Research 56, no. 8: 1.

Journal article
Published: 05 August 2020 in Sustainability
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Climate changes and urbanization push cities to redesign their drainage systems, which may increase separate stormwater discharges to local recipients. In the EU, regulation of these is governed by the Water Framework Directive (WFD) and the Floods Directive, but national implementation varies and is often supplemented with local non-legislative guidelines. By reviewing trends and discrepancies in the Danish regulation practice for separated stormwater discharges, this article investigates how the directives are put into effect. A legislative gap for separate stormwater discharges introduces uncertainty in the discharge permit conditions, which especially affect conditions targeting water quality. We point to several topics to be addressed, e.g., the level at which the regulation of separate stormwater discharges takes place, opportunities for coordination with flood risk and climate change adaptation initiatives, as well as uncertainties regarding the application of Best Available Techniques. Working with these issues would elevate the regulation practice and aid regulators in reaching a more holistic and consistent approach, thus improving chances of reaching the desired recipient status before or after the WFD deadline in 2027. This could be undertaken at river basin, river basin district or national level, but there is also potential for harvesting mutual benefits by addressing these challenges internationally.

ACS Style

Ditte Jensen; Anja Thomsen; Torben Larsen; Sara Egemose; Peter Mikkelsen. From EU Directives to Local Stormwater Discharge Permits: A Study of Regulatory Uncertainty and Practice Gaps in Denmark. Sustainability 2020, 12, 6317 .

AMA Style

Ditte Jensen, Anja Thomsen, Torben Larsen, Sara Egemose, Peter Mikkelsen. From EU Directives to Local Stormwater Discharge Permits: A Study of Regulatory Uncertainty and Practice Gaps in Denmark. Sustainability. 2020; 12 (16):6317.

Chicago/Turabian Style

Ditte Jensen; Anja Thomsen; Torben Larsen; Sara Egemose; Peter Mikkelsen. 2020. "From EU Directives to Local Stormwater Discharge Permits: A Study of Regulatory Uncertainty and Practice Gaps in Denmark." Sustainability 12, no. 16: 6317.

Perspective
Published: 14 October 2019 in Nature Sustainability
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Cities increasingly use real-time control of combined sewer systems and green infrastructure to decrease emissions to surface waters, and incorporate infrastructure into the urban landscape to reduce flooding from short, intense rainfall events called cloudbursts, which can cause flash flooding. Inspired by the ‘smart cities’ agenda, we propose the use of integrated stormwater inflow control to dynamically activate cloudburst conveyance infrastructure in the urban landscape as well as green storage elements more often than originally intended. This control facilitates synergy between sewers, green infrastructure and the urban landscape, and has lower environmental impacts than isolated control approaches. A simulated, yet realistic, case study in Copenhagen, Denmark, shows that combined sewage emissions can be eliminated or reduced substantially in this manner. Other potential benefits include increasing amenity value and educating citizens, for example. The results suggest that the proposed control concept potentially provides a viable path towards more resilient, liveable and sustainable cities.

ACS Style

Nadia Schou Vorndran Lund; Morten Borup; Henrik Madsen; Ole Mark; Karsten Arnbjerg-Nielsen; Peter Steen Mikkelsen. Integrated stormwater inflow control for sewers and green structures in urban landscapes. Nature Sustainability 2019, 2, 1003 -1010.

AMA Style

Nadia Schou Vorndran Lund, Morten Borup, Henrik Madsen, Ole Mark, Karsten Arnbjerg-Nielsen, Peter Steen Mikkelsen. Integrated stormwater inflow control for sewers and green structures in urban landscapes. Nature Sustainability. 2019; 2 (11):1003-1010.

Chicago/Turabian Style

Nadia Schou Vorndran Lund; Morten Borup; Henrik Madsen; Ole Mark; Karsten Arnbjerg-Nielsen; Peter Steen Mikkelsen. 2019. "Integrated stormwater inflow control for sewers and green structures in urban landscapes." Nature Sustainability 2, no. 11: 1003-1010.

Journal article
Published: 28 December 2018 in Water Science and Technology
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Online model predictive control (MPC) of water resource recovery facilities (WRRFs) requires simple and fast models to improve the operation of energy-demanding processes, such as aeration for nitrogen removal. Selected elements of the activated sludge model number 1 modelling framework for ammonium and nitrate removal were included in discretely observed stochastic differential equations in which online data are assimilated to update the model states. This allows us to produce model-based predictions including uncertainty in real time while it also reduces the number of parameters compared to many detailed models. It introduces only a small residual error when used to predict ammonium and nitrate concentrations in a small recirculating WRRF facility. The error when predicting 2 min ahead corresponds to the uncertainty from the sensors. When predicting 24 hours ahead the mean relative residual error increases to ∼10% and ∼20% for ammonium and nitrate concentrations respectively. Consequently this is considered a first step towards stochastic MPC of the aeration process. Ultimately this can reduce electricity demand and cost for water resource recovery, allowing the prioritization of aeration during periods of cheaper electricity.

ACS Style

Peter Alexander Stentoft; Thomas Munk-Nielsen; Luca Vezzaro; Henrik Madsen; Peter Steen Mikkelsen; Jan Kloppenborg Møller. Towards model predictive control: online predictions of ammonium and nitrate removal by using a stochastic ASM. Water Science and Technology 2018, 79, 51 -62.

AMA Style

Peter Alexander Stentoft, Thomas Munk-Nielsen, Luca Vezzaro, Henrik Madsen, Peter Steen Mikkelsen, Jan Kloppenborg Møller. Towards model predictive control: online predictions of ammonium and nitrate removal by using a stochastic ASM. Water Science and Technology. 2018; 79 (1):51-62.

Chicago/Turabian Style

Peter Alexander Stentoft; Thomas Munk-Nielsen; Luca Vezzaro; Henrik Madsen; Peter Steen Mikkelsen; Jan Kloppenborg Møller. 2018. "Towards model predictive control: online predictions of ammonium and nitrate removal by using a stochastic ASM." Water Science and Technology 79, no. 1: 51-62.

Technical note
Published: 13 November 2018 in Geosciences
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To prevent online models diverging from reality they need to be updated to current conditions using observations and data assimilation techniques. A way of doing this for distributed hydrodynamic urban drainage models is to use the Ensemble Kalman Filter (EnKF), but this requires running an ensemble of models online, which is computationally demanding. This can be circumvented by calculating the Kalman gain, which is the governing matrix of the updating, offline if the gain is approximately constant in time. Here, we show in a synthetic experiment that the Kalman gain can vary by several orders of magnitude in a non-uniform and time-dynamic manner during surcharge conditions caused by backwater when updating a hydrodynamic model of a simple sewer system with the EnKF. This implies that constant gain updating is not suitable for distributed hydrodynamic urban drainage models and that the full EnKF is in fact required.

ACS Style

Morten Borup; Henrik Madsen; Morten Grum; Peter Steen Mikkelsen. Technical Note on the Dynamic Changes in Kalman Gain when Updating Hydrodynamic Urban Drainage Models. Geosciences 2018, 8, 416 .

AMA Style

Morten Borup, Henrik Madsen, Morten Grum, Peter Steen Mikkelsen. Technical Note on the Dynamic Changes in Kalman Gain when Updating Hydrodynamic Urban Drainage Models. Geosciences. 2018; 8 (11):416.

Chicago/Turabian Style

Morten Borup; Henrik Madsen; Morten Grum; Peter Steen Mikkelsen. 2018. "Technical Note on the Dynamic Changes in Kalman Gain when Updating Hydrodynamic Urban Drainage Models." Geosciences 8, no. 11: 416.

Journal article
Published: 11 July 2018 in Water Research
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We examine how core professional and institutional actors in the innovation system conceptualize climate change adaptation in regards to pluvial flooding—and how this influences innovation. We do this through a qualitative case study in Copenhagen with interconnected research rounds, including 32 semi-structured interviews, to strengthen the interpretation and analysis of qualitative data. We find that the term “climate change adaptation” currently has no clearly agreed definition in Copenhagen; instead, different actors use different conceptualizations of climate change adaptation according to the characteristics of their specific innovation and implementation projects. However, there is convergence among actors towards a new cognitive paradigm, whereby economic goals and multifunctionality are linked with cost-benefit analyses for adapting to extreme rain events on a surface water catchment scale. Differences in definitions can lead to both successful innovation and to conflict, and thus they affect the city's capacity for change. Our empirical work suggests that climate change adaptation can be characterized according to three attributes: event magnitudes (everyday, design, and extreme), spatial scales (small/local, medium/urban, and large/national-international), and (a wide range of) goals, thereby resulting in different technology choices.

ACS Style

Herle Mo Madsen; Maj Munch Andersen; Martin Rygaard; Peter Steen Mikkelsen. Definitions of event magnitudes, spatial scales, and goals for climate change adaptation and their importance for innovation and implementation. Water Research 2018, 144, 192 -203.

AMA Style

Herle Mo Madsen, Maj Munch Andersen, Martin Rygaard, Peter Steen Mikkelsen. Definitions of event magnitudes, spatial scales, and goals for climate change adaptation and their importance for innovation and implementation. Water Research. 2018; 144 ():192-203.

Chicago/Turabian Style

Herle Mo Madsen; Maj Munch Andersen; Martin Rygaard; Peter Steen Mikkelsen. 2018. "Definitions of event magnitudes, spatial scales, and goals for climate change adaptation and their importance for innovation and implementation." Water Research 144, no. : 192-203.

Review
Published: 01 February 2018 in Critical Reviews in Environmental Science and Technology
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Model predictive control (MPC) can be used to manage combined urban drainage systems more efficiently for protection of human health and the environment, but examples of operational implementations are rare. This paper reviews more than 30 years of partly heterogeneous research on the topic. We propose a terminology for MPC of urban drainage systems and a hierarchical categorization where we emphasize four overall components: the “receding horizon principle”, the “optimization model”, the “optimization solver”, and the “internal MPC model”. Most of the reported optimization models share the trait of a multiobjective optimization based on a conceptual internal MPC model. However, there is a large variety of both convex and non-linear optimization models and optimization solvers as well as constructions of the internal MPC model. Furthermore, literature disagrees about the optimal length of the components in the receding horizon principle. The large number of MPC formulations and evaluation approaches makes it problematic to compare different MPC methods. This review highlights methods, challenges, and research gaps in order to make MPC of urban drainage systems accessible for researchers and practitioners from different disciplines. This will pave the way for shared understanding and further development within the field, and eventually lead to more operational implementations.

ACS Style

Nadia Schou Vorndran Lund; Anne Katrine Vinther Falk; Morten Borup; Henrik Madsen; Peter Steen Mikkelsen. Model predictive control of urban drainage systems: A review and perspective towards smart real-time water management. Critical Reviews in Environmental Science and Technology 2018, 48, 279 -339.

AMA Style

Nadia Schou Vorndran Lund, Anne Katrine Vinther Falk, Morten Borup, Henrik Madsen, Peter Steen Mikkelsen. Model predictive control of urban drainage systems: A review and perspective towards smart real-time water management. Critical Reviews in Environmental Science and Technology. 2018; 48 (3):279-339.

Chicago/Turabian Style

Nadia Schou Vorndran Lund; Anne Katrine Vinther Falk; Morten Borup; Henrik Madsen; Peter Steen Mikkelsen. 2018. "Model predictive control of urban drainage systems: A review and perspective towards smart real-time water management." Critical Reviews in Environmental Science and Technology 48, no. 3: 279-339.

Journal article
Published: 16 January 2018 in Water
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The environmental benefits of combining traditional infrastructure solutions for urban drainage (increasing storage volume) with real time control (RTC) strategies were investigated in the Lundofte catchment in Denmark, where an expensive traditional infrastructure expansion is planned to comply with environmental requirements. A coordinating, rule-based RTC strategy and a global, system-wide risk-based dynamic optimization strategy (model predictive control), were compared using a detailed hydrodynamic model. RTC allowed a reduction of the planned storage volume by 21% while improving the system performance in terms of combined sewer overflow (CSO) volumes, environmental impacts, and utility costs, which were reduced by up to 10%. The risk-based optimization strategy provided slightly better performance in terms of reducing CSO volumes, with evident improvements in environmental impacts and utility costs, due to its ability to prioritize among the environmental sensitivity of different recipients. A method for extrapolating annual statistics from a limited number of events over a time interval was developed and applied to estimate yearly performance, based on the simulation of 46 events over a five-year period. This study illustrates that including RTC during the planning stages reduces the infrastructural costs while offering better environmental protection, and that dynamic risk-based optimisation allows prioritising environmental impact reduction for particularly sensitive locations.

ACS Style

Elbys Jose Meneses; Marion Gaussens; Carsten Jakobsen; Peter Steen Mikkelsen; Morten Grum; Luca Vezzaro. Coordinating Rule-Based and System-Wide Model Predictive Control Strategies to Reduce Storage Expansion of Combined Urban Drainage Systems: The Case Study of Lundtofte, Denmark. Water 2018, 10, 76 .

AMA Style

Elbys Jose Meneses, Marion Gaussens, Carsten Jakobsen, Peter Steen Mikkelsen, Morten Grum, Luca Vezzaro. Coordinating Rule-Based and System-Wide Model Predictive Control Strategies to Reduce Storage Expansion of Combined Urban Drainage Systems: The Case Study of Lundtofte, Denmark. Water. 2018; 10 (1):76.

Chicago/Turabian Style

Elbys Jose Meneses; Marion Gaussens; Carsten Jakobsen; Peter Steen Mikkelsen; Morten Grum; Luca Vezzaro. 2018. "Coordinating Rule-Based and System-Wide Model Predictive Control Strategies to Reduce Storage Expansion of Combined Urban Drainage Systems: The Case Study of Lundtofte, Denmark." Water 10, no. 1: 76.

Journal article
Published: 01 January 2018 in Journal of Hydrology
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Precipitation constitutes a major contribution to the flow in urban storm- and wastewater systems. Forecasts of the anticipated runoff flows, created from radar extrapolation and/or numerical weather predictions, can potentially be used to optimize operation in both wet and dry weather periods. However, flow forecasts are inevitably uncertain and their use will ultimately require a trade-off between the value of knowing what will happen in the future and the probability and consequence of being wrong. In this study we examine how ensemble forecasts from the HIRLAM-DMI-S05 numerical weather prediction (NWP) model subject to three different ensemble post-processing approaches can be used to forecast flow exceedance in a combined sewer for a wide range of ratios between the probability of detection (POD) and the probability of false detection (POFD). We use a hydrological rainfall-runoff model to transform the forecasted rainfall into forecasted flow series and evaluate three different approaches to establishing the relative operating characteristics (ROC) diagram of the forecast, which is a plot of POD against POFD for each fraction of concordant ensemble members and can be used to select the weight of evidence that matches the desired trade-off between POD and POFD. In the first approach, the rainfall input to the model is calculated for each of 25 ensemble members as a weighted average of rainfall from the NWP cells over the catchment where the weights are proportional to the areal intersection between the catchment and the NWP cells. In the second approach, a total of 2825 flow ensembles are generated using rainfall input from the neighbouring NWP cells up to approximately 6 cells in all directions from the catchment. In the third approach, the first approach is extended spatially by successively increasing the area covered and for each spatial increase and each time step selecting only the cell with the highest intensity resulting in a total of 175 ensemble members. While the first and second approaches have the disadvantage of not covering the full range of the ROC diagram and being computationally heavy, respectively, the third approach leads to both a broad coverage of the ROC diagram range at a relatively low computational cost. A broad coverage of the ROC diagram offers a larger selection of prediction skill to choose from to best match to the prediction purpose. The study distinguishes itself from earlier research in being the first application to urban hydrology, with fast runoff and small catchments that are highly sensitive to local extremes. Furthermore, no earlier reference has been found on the highly efficient third approach using only neighbouring cells with the highest threat to expand the range of the ROC diagram. This study provides an efficient and robust approach to using ensemble rainfall forecasts affected by bias and misplacement errors for predicting flow threshold exceedance in urban drainage systems.

ACS Style

Vianney Courdent; Morten Grum; Peter Steen Mikkelsen. Distinguishing high and low flow domains in urban drainage systems 2 days ahead using numerical weather prediction ensembles. Journal of Hydrology 2018, 556, 1013 -1025.

AMA Style

Vianney Courdent, Morten Grum, Peter Steen Mikkelsen. Distinguishing high and low flow domains in urban drainage systems 2 days ahead using numerical weather prediction ensembles. Journal of Hydrology. 2018; 556 ():1013-1025.

Chicago/Turabian Style

Vianney Courdent; Morten Grum; Peter Steen Mikkelsen. 2018. "Distinguishing high and low flow domains in urban drainage systems 2 days ahead using numerical weather prediction ensembles." Journal of Hydrology 556, no. : 1013-1025.

Journal article
Published: 22 May 2017 in Hydrology and Earth System Sciences
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Precipitation is the cause of major perturbation to the flow in urban drainage and wastewater systems. Flow forecasts, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimize the operation of integrated urban drainage–wastewater systems (IUDWSs) during both wet and dry weather periods. Numerical weather prediction (NWP) models have significantly improved in recent years, having increased their spatial and temporal resolution. Finer resolution NWP are suitable for urban-catchment-scale applications, providing longer lead time than radar extrapolation. However, forecasts are inevitably uncertain, and fine resolution is especially challenging for NWP. This uncertainty is commonly addressed in meteorology with ensemble prediction systems (EPSs). Handling uncertainty is challenging for decision makers and hence tools are necessary to provide insight on ensemble forecast usage and to support the rationality of decisions (i.e. forecasts are uncertain and therefore errors will be made; decision makers need tools to justify their choices, demonstrating that these choices are beneficial in the long run). This study presents an economic framework to support the decision-making process by providing information on when acting on the forecast is beneficial and how to handle the EPS. The relative economic value (REV) approach associates economic values with the potential outcomes and determines the preferential use of the EPS forecast. The envelope curve of the REV diagram combines the results from each probability forecast to provide the highest relative economic value for a given gain–loss ratio. This approach is traditionally used at larger scales to assess mitigation measures for adverse events (i.e. the actions are taken when events are forecast). The specificity of this study is to optimize the energy consumption in IUDWS during low-flow periods by exploiting the electrical smart grid market (i.e. the actions are taken when no events are forecast). Furthermore, the results demonstrate the benefit of NWP neighbourhood post-processing methods to enhance the forecast skill and increase the range of beneficial uses.

ACS Style

Vianney Courdent; Morten Grum; Thomas Munk-Nielsen; Peter Steen Mikkelsen. A gain–loss framework based on ensemble flow forecasts to switch the urban drainage–wastewater system management towards energy optimization during dry periods. Hydrology and Earth System Sciences 2017, 21, 2531 -2544.

AMA Style

Vianney Courdent, Morten Grum, Thomas Munk-Nielsen, Peter Steen Mikkelsen. A gain–loss framework based on ensemble flow forecasts to switch the urban drainage–wastewater system management towards energy optimization during dry periods. Hydrology and Earth System Sciences. 2017; 21 (5):2531-2544.

Chicago/Turabian Style

Vianney Courdent; Morten Grum; Thomas Munk-Nielsen; Peter Steen Mikkelsen. 2017. "A gain–loss framework based on ensemble flow forecasts to switch the urban drainage–wastewater system management towards energy optimization during dry periods." Hydrology and Earth System Sciences 21, no. 5: 2531-2544.

Journal article
Published: 01 February 2017 in Technological Forecasting and Social Change
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ACS Style

Herle Mo Madsen; Rebekah Brown; Morten Elle; Peter Steen Mikkelsen. Social construction of stormwater control measures in Melbourne and Copenhagen: A discourse analysis of technological change, embedded meanings and potential mainstreaming. Technological Forecasting and Social Change 2017, 115, 198 -209.

AMA Style

Herle Mo Madsen, Rebekah Brown, Morten Elle, Peter Steen Mikkelsen. Social construction of stormwater control measures in Melbourne and Copenhagen: A discourse analysis of technological change, embedded meanings and potential mainstreaming. Technological Forecasting and Social Change. 2017; 115 ():198-209.

Chicago/Turabian Style

Herle Mo Madsen; Rebekah Brown; Morten Elle; Peter Steen Mikkelsen. 2017. "Social construction of stormwater control measures in Melbourne and Copenhagen: A discourse analysis of technological change, embedded meanings and potential mainstreaming." Technological Forecasting and Social Change 115, no. : 198-209.

Journal article
Published: 01 January 2017 in Journal of Hydrology
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Luca Locatelli; Ole Mark; Peter Steen Mikkelsen; Karsten Arnbjerg-Nielsen; Ana Deletic; Maria Roldin; Philip John Binning. Hydrologic impact of urbanization with extensive stormwater infiltration. Journal of Hydrology 2017, 544, 524 -537.

AMA Style

Luca Locatelli, Ole Mark, Peter Steen Mikkelsen, Karsten Arnbjerg-Nielsen, Ana Deletic, Maria Roldin, Philip John Binning. Hydrologic impact of urbanization with extensive stormwater infiltration. Journal of Hydrology. 2017; 544 ():524-537.

Chicago/Turabian Style

Luca Locatelli; Ole Mark; Peter Steen Mikkelsen; Karsten Arnbjerg-Nielsen; Ana Deletic; Maria Roldin; Philip John Binning. 2017. "Hydrologic impact of urbanization with extensive stormwater infiltration." Journal of Hydrology 544, no. : 524-537.

Journal article
Published: 15 November 2016 in SpringerPlus
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This study investigated the potential effect of climate changes on stormwater pollution runoff characteristics and the treatment efficiency of a stormwater retention pond in a 95 ha catchment in Denmark. An integrated dynamic stormwater runoff quality and treatment model was used to simulate two scenarios: one representing the current climate and another representing a future climate scenario with increased intensity of extreme rainfall events and longer dry weather periods. 100-year long high-resolution rainfall time series downscaled from regional climate model projections were used as input. The collected data showed that total suspended solids (TSS) and total copper (Cu) concentrations in stormwater runoff were related to flow, rainfall intensity and antecedent dry period. Extreme peak intensities resulted in high particulate concentrations and high loads but did not affect dissolved Cu concentrations. The future climate simulations showed an increased frequency of higher flows and increased total concentrations discharged from the catchment. The effect on the outlet from the pond was an increase in the total concentrations (TSS and Cu), whereas no major effect was observed on dissolved Cu concentrations. Similar results are expected for other particle bound pollutants including metals and slowly biodegradable organic substances such as PAH. Acute toxicity impacts to downstream surface waters seem to be only slightly affected. A minor increase in yearly loads of sediments and particle-bound pollutants is expected, mainly caused by large events disrupting the settling process. This may be important to consider for the many stormwater retention ponds existing in Denmark and across the world.

ACS Style

Anitha Kumari Sharma; Luca Vezzaro; Heidi Birch; Karsten Arnbjerg-Nielsen; Peter Steen Mikkelsen. Effect of climate change on stormwater runoff characteristics and treatment efficiencies of stormwater retention ponds: a case study from Denmark using TSS and Cu as indicator pollutants. SpringerPlus 2016, 5, 1 -12.

AMA Style

Anitha Kumari Sharma, Luca Vezzaro, Heidi Birch, Karsten Arnbjerg-Nielsen, Peter Steen Mikkelsen. Effect of climate change on stormwater runoff characteristics and treatment efficiencies of stormwater retention ponds: a case study from Denmark using TSS and Cu as indicator pollutants. SpringerPlus. 2016; 5 (1):1-12.

Chicago/Turabian Style

Anitha Kumari Sharma; Luca Vezzaro; Heidi Birch; Karsten Arnbjerg-Nielsen; Peter Steen Mikkelsen. 2016. "Effect of climate change on stormwater runoff characteristics and treatment efficiencies of stormwater retention ponds: a case study from Denmark using TSS and Cu as indicator pollutants." SpringerPlus 5, no. 1: 1-12.

Preprint content
Published: 17 October 2016
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Precipitation is the major perturbation to the flow in urban drainage and wastewater systems. Flow forecast, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimise the operation of Integrated Urban Drainage–Wastewater Systems (IUDWS) during both wet and dry weather periods. Numerical Weather Prediction (NWP) models have significantly improved in recent years; increasing their spatial and temporal resolution. Finer resolution NWP are suitable for urban catchment scale applications, providing longer lead time than radar extrapolation. However, forecasts are inevitably uncertain and fine resolution is especially challenging for NWP. This uncertainty is commonly addressed in meteorology with Ensemble Prediction Systems (EPS). Handling uncertainty is challenging for decision makers and hence tools are necessary to provide insight on ensemble forecast usage and to support the rationality of decisions (i.e. forecasts are uncertain therefore errors will be made, decision makers need tools to justify their choices, demonstrating that these choices are beneficial in the long run). This study presents an economic framework to support the decision making process by providing information on when acting on the forecast is beneficial and how to handle the EPS. The Relative Economic Value (REV) approach associates economic values to the potential outcomes and determines the preferential use of the EPS forecast. The envelope curve of the REV diagram combines the results from each probability forecast to provide the highest relative economic value for a given gain-loss ratio. This approach is traditionally used at larger scales to assess mitigation measures for adverse events (i.e. the actions are taken when events are forecasted). The specificity of this study is to optimise the energy consumption in IUDWS during low flow periods by exploiting the electrical smart grid market (i.e. the actions are taken when no events are forecasted). Furthermore, the results demonstrate the benefit of NWP neighbourhood post-processing methods to enhance the forecast skill and increase the range of beneficial use.

ACS Style

Vianney Courdent; Morten Grum; Thomas Munk-Nielsen; Peter S. Mikkelsen. Coupling urban drainage–wastewater systems and electric smart grids during dry periods: a gain/loss framework using the relative economic value with ensemble flow forecasts to predict the switch between management objectives. 2016, 2016, 1 -24.

AMA Style

Vianney Courdent, Morten Grum, Thomas Munk-Nielsen, Peter S. Mikkelsen. Coupling urban drainage–wastewater systems and electric smart grids during dry periods: a gain/loss framework using the relative economic value with ensemble flow forecasts to predict the switch between management objectives. . 2016; 2016 ():1-24.

Chicago/Turabian Style

Vianney Courdent; Morten Grum; Thomas Munk-Nielsen; Peter S. Mikkelsen. 2016. "Coupling urban drainage–wastewater systems and electric smart grids during dry periods: a gain/loss framework using the relative economic value with ensemble flow forecasts to predict the switch between management objectives." 2016, no. : 1-24.

Journal article
Published: 01 October 2016 in Science of The Total Environment
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The effect of contact time, solution pH, and the presence of humic acid (HA) on the combined removal of As, Cd, Cr, Cu, Ni and Zn is investigated in batch tests using alumina, granulated activated carbon (GAC), and bauxsol coated sand (BCS) as sorbents. It is found that the equilibrium time for Cd, Cu, Ni and Zn is about 4h, while no clear equilibrium is observed for As and Cr. It is also found that increasing the pH until pH~8 enhanced Cd, Cu, Ni and Zn removal, but increasing the pH above this point had no major effect. In the cases of As and Cr, higher pH values (i.e. >7) decreased their removal. The presence of both 20 and 100mg/L HA suppressed the heavy metal removal except for Cr, and the suppression was higher at the higher HA concentration. Geochemical simulations suggest that this is due to the formation of dissolved HA-metal complexes preventing effective metal sorption. In the case of Cr, the presence of HA increased the removal when using alumina or BCS, while hindering the removal when using GAC. The findings show that the pH-value of the stormwater to be treated must be in the range of 6-7 in order to achieve removal of the full spectrum of metals. The results also show that natural organic matter may severely influence the removal efficiency, such that, for most metals the removal was reduced to the half, while for Cr it was increased to the double for alumina and BCS. Consequently, a properly working filter set up may not work properly anymore when receiving high loads of natural organic acids during the pollen season in spring or during defoliation in autumn and early winter, and during mixing of runoff with snowmelt having a low pH.

ACS Style

Hülya Genç-Fuhrman; Peter Steen Mikkelsen; Anna Ledin. Simultaneous removal of As, Cd, Cr, Cu, Ni and Zn from stormwater using high-efficiency industrial sorbents: Effect of pH, contact time and humic acid. Science of The Total Environment 2016, 566-567, 76 -85.

AMA Style

Hülya Genç-Fuhrman, Peter Steen Mikkelsen, Anna Ledin. Simultaneous removal of As, Cd, Cr, Cu, Ni and Zn from stormwater using high-efficiency industrial sorbents: Effect of pH, contact time and humic acid. Science of The Total Environment. 2016; 566-567 ():76-85.

Chicago/Turabian Style

Hülya Genç-Fuhrman; Peter Steen Mikkelsen; Anna Ledin. 2016. "Simultaneous removal of As, Cd, Cr, Cu, Ni and Zn from stormwater using high-efficiency industrial sorbents: Effect of pH, contact time and humic acid." Science of The Total Environment 566-567, no. : 76-85.

Journal article
Published: 06 September 2016 in Water
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High quality on-line flow forecasts are useful for real-time operation of urban drainage systems and wastewater treatment plants. This requires computationally efficient models, which are continuously updated with observed data to provide good initial conditions for the forecasts. This paper presents a way of updating conceptual rainfall-runoff models using Maximum a Posteriori estimation to determine the most likely parameter constellation at the current point in time. This is done by combining information from prior parameter distributions and the model goodness of fit over a predefined period of time that precedes the forecast. The method is illustrated for an urban catchment, where flow forecasts of 0–4 h are generated by applying a lumped linear reservoir model with three cascading reservoirs. Radar rainfall observations are used as input to the model. The effects of different prior standard deviations and lengths of the auto-calibration period on the resulting flow forecast performance are evaluated. We were able to demonstrate that, if properly tuned, the method leads to a significant increase in forecasting performance compared to a model without continuous auto-calibration. Delayed responses and erratic behaviour in the parameter variations are, however, observed and the choice of prior distributions and length of auto-calibration period is not straightforward.

ACS Style

Jonas Wied Pedersen; Nadia S. V. Lund; Morten Borup; Roland Löwe; Troels S. Poulsen; Peter Steen Mikkelsen; Morten Grum. Evaluation of Maximum a Posteriori Estimation as Data Assimilation Method for Forecasting Infiltration-Inflow Affected Urban Runoff with Radar Rainfall Input. Water 2016, 8, 381 .

AMA Style

Jonas Wied Pedersen, Nadia S. V. Lund, Morten Borup, Roland Löwe, Troels S. Poulsen, Peter Steen Mikkelsen, Morten Grum. Evaluation of Maximum a Posteriori Estimation as Data Assimilation Method for Forecasting Infiltration-Inflow Affected Urban Runoff with Radar Rainfall Input. Water. 2016; 8 (9):381.

Chicago/Turabian Style

Jonas Wied Pedersen; Nadia S. V. Lund; Morten Borup; Roland Löwe; Troels S. Poulsen; Peter Steen Mikkelsen; Morten Grum. 2016. "Evaluation of Maximum a Posteriori Estimation as Data Assimilation Method for Forecasting Infiltration-Inflow Affected Urban Runoff with Radar Rainfall Input." Water 8, no. 9: 381.