Impact-based integrated real-time control for improvement of the Dommel River water quality

Langeveld, Jeroen; Benedetti, Lorenzo; Klein, J.J.M. de; Nieuwenhuijzen, A. van; Flameling, Tony; Zanten, Oscar van; Weijers, Stefan

doi:10.2175/193864712811710056

Cited by 3 publications

(5 citation statements)

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“…Consequently, these applications suffer from the already mentioned drawbacks for optimization with MLSMs. For UDS, real‐time applications concern Real‐Time Control (RTC), where operation and validation relies on real data (Beeneken et al., 2013; Langeveld et al., 2013; Lund et al., 2018). This is an issue since the usual targets are infrequent events, that is, outflows and flooding; therefore, the availability of records may be scarce or nonexistent.…”

Section: Review—current Status Of Machine Learning Surrogate Models I...mentioning

confidence: 99%

Machine Learning‐Based Surrogate Modeling for Urban Water Networks: Review and Future Research Directions

Garzón

Kapelan

Langeveld

et al. 2022

Water Resources Research

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Urban water networks (UWNs) comprise drinking water distribution and urban drainage systems (WDS and UDS). The former are responsible for supplying drinking water to cities and the latter for evacuating wastewater and stormwater runoff. These infrastructures are a fundamental part of the city and are directly linked to its development (Brown et al., 2009). Each of these systems faces challenges to improve and maintain quality service in a dynamic urban environment under a widening range of climatic conditions; especially, in a climate-changing situation. Designing, optimizing, and intervening in these systems requires approximating their hydraulic behavior. Many models have been developed in the past years for simulating UWNs, for example, SOBEK (Deltares, n.d.), WaterCAD (Bentley®, n.d.), EPA-SWMM (Rossman, 2010), among others. Traditional modeling approaches are either based on accurate description of the physical processes (e.g., EPANET;Rossman et al., 2000) or rely on simplified conceptual models (e.g., SIMPOL;Dempsey et al., 1997); nonetheless, the former usually entail computationally expensive calculations while the latter lack fidelity, that is, level of detail. Applications such as optimization, real-time modeling, and uncertainty analysis need efficient models for evaluating the performance

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Section: Review—current Status Of Machine Learning Surrogate Models I...mentioning

confidence: 99%

Machine Learning‐Based Surrogate Modeling for Urban Water Networks: Review and Future Research Directions

Garzón

Kapelan

Langeveld

et al. 2022

Water Resources Research

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“…The fully integrated model was implemented in the platform WEST (DHI). Further detail in the model and system characteristics can be found at Langeveld et al (2013b) and Moreno-Rodenas et al (2017a). Figure 14 (Annex A) depicts the model structure scheme.…”

Section: The Integrated Catchment Modelmentioning

confidence: 99%

Parametric emulation and inference in computationally expensive integrated urban water quality simulators

Moreno-Rodenas

Langeveld

Clemens

2019

Environ Sci Pollut Res

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Water quality environmental assessment often requires the joint simulation of several subsystems (e.g. wastewater treatment processes, urban drainage and receiving water bodies). The complexity of these integrated catchment models grows fast, leading to potentially over-parameterised and computationally expensive models. The receiving water body physical and biochemical parameters are often a dominant source of uncertainty when simulating dissolved oxygen depletion processes. Thus, the use of system observations to refine prior knowledge (from experts or literature) is usually required. Unfortunately, simulating realworld scale water quality processes results in a significant computational burden, for which the use of sampling intensive applications (e.g. parametric inference) is severely hampered. Data-driven emulation aims at creating an interpolation map between the parametric and output multidimensional spaces of a dynamic simulator, thus providing a fast approximation of the model response. In this study a large-scale integrated urban water quality model is used to simulate dissolved oxygen depletion processes in a sensitive river. A polynomial expansion emulator was proposed to approximate the link between four and eight river physical and biochemical river parameters and the dynamics of river flow and dissolved oxygen concentration during one year (at hourly frequency). The emulator scheme was used to perform a sensitivity analysis and a formal parametric inference using local system observations. The effect of different likelihood assumptions (e.g. heteroscedasticity, normality and autocorrelation) during the inference of dissolved oxygen processes is also discussed. This study shows how the use of datadriven emulators can facilitate the integration of formal uncertainty analysis schemes in the hydrological and water quality modelling community.

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“…The processes in the river model with DO and ammonium as state variables include BOD decay, reaeration, plant production and respiration, nitrification, and settling of particulate organic matter. 5 The equations of the implemented model are described by ordinary differential equations and are solved with the use of the numerical variable step size VODE solver included in WEST. For each of the measures and the base case, the integrated model is simulating the climatic and influent variability occurring in the system for the duration of ten years.…”

Section: ■ Case Studymentioning

confidence: 99%

“…For each of the measures and the base case, the integrated model is simulating the climatic and influent variability occurring in the system for the duration of ten years. 5 The ten-year time series was developed using monitoring data of precipitation, sewer water levels and flow, and water quality. A description of the development and calibration of the integrated UWS model and the monitoring data used is provided in extensive detail by .…”

Section: ■ Case Studymentioning

confidence: 99%

“…A description of the development and calibration of the integrated UWS model and the monitoring data used is provided in extensive detail by . 5 The outputs to water are the net loads released to the environment at the end of the studied reach from the WWTP and CSOs. In this manner, the purification capacity of the receiving water is taken into account in the estimated emissions.…”

Section: ■ Case Studymentioning

confidence: 99%

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Assessing Urban Wastewater System Upgrades Using Integrated Modeling, Life Cycle Analysis, and Shadow Pricing

Hadjimichael

Morera

Benedetti

et al. 2016

Environ. Sci. Technol.

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This study assesses the environmental impacts of four measures proposed for upgrading of the urban wastewater system of Eindhoven and the Dommel River in The Netherlands, against the base case, “do-nothing” option. The measures aim to reduce the overall environmental impact of the Eindhoven urban wastewater system (UWS) by targeting river dissolved oxygen depletion and ammonia peaks, reducing combined sewer overflows, and enhancing nutrient removal. The measures are evaluated using a life cycle analysis with the boundaries including the receiving river section by means of an integrated model of the UWS. An uncertainty analysis of the estimated impacts has been performed to support the outcomes. The study also uses the economic concept of shadow prices to assign relative weights of socio-economic importance to the estimated life cycle impacts. This novel integration of tools complements the assessments of this UWS with the inclusion of long-term global environmental impacts and the investigation of trade-offs between different environmental impacts through a single monetary unit. The results support the selection of deeper clarifiers as the most environmentally beneficial measure for upgradeThe authors would like to acknowledge the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007−2013 under REA agreement 289193 (SANITAS ITN). The authors thank the Spanish Ministry of Science and Innovation (Ramon y Cajal RYC-2013-14595 and CTM 2015-66892-R) and the European Union (Marie Curie Career Integration Grant PCIG9-GA-2011-293535). The authors also acknowledge support from the Economy and Knowledge Department of the Catalan Government through the Consolidated Research Group (2014-SGR- 1168)-LEQUIA-University of Girona and (2014 SGR 291)- Catalan Institute for Water Researc

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Impact-based integrated real-time control for improvement of the Dommel River water quality

Cited by 3 publications

References 0 publications

Machine Learning‐Based Surrogate Modeling for Urban Water Networks: Review and Future Research Directions

Machine Learning‐Based Surrogate Modeling for Urban Water Networks: Review and Future Research Directions

Parametric emulation and inference in computationally expensive integrated urban water quality simulators

Assessing Urban Wastewater System Upgrades Using Integrated Modeling, Life Cycle Analysis, and Shadow Pricing

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