The Bellinge data set: open data and models for community-wide urban drainage systems research

Pedersen, Agnethe Nedergaard; Pedersen, Jonas Wied; Vigueras-Rodríguez, Antonio; Brink-Kjær, Annette; Borup, Morten; Mikkelsen, Peter Steen

doi:10.5194/essd-2021-8

Cited by 6 publications

(21 citation statements)

References 31 publications

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“…Future work to best demonstrate the full value of the proposed simulation approach would be to derive the reduced complexity CWSD model from network data only and validate by observed data rather than against a high‐fidelity simulation model. An open‐source case study that could explore the simulated flows at monitored locations could be performed using the data collected for the Bellinge urban water system (Pederson et al., 2021). The demonstration of our proposed approach without using parameters from the high‐fidelity model, Figures 6 and S23 in Supporting Information , show that simulations are surprisingly insensitive to runoff coefficient and roughness parameter choices.…”

Section: Discussionmentioning

confidence: 99%

A Reduced Complexity Model With Graph Partitioning for Rapid Hydraulic Assessment of Sewer Networks

Dobson

Watson‐Hill

Muhandes

et al. 2022

Water Resources Research

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Hydraulically based models are used to simulate how sewer networks of urban catchments will respond to precipitation events (Salvadore et al., 2015). These models enable planners to design interventions that might resolve current network issues, and to plan for changes in the urban catchment. However, the models also require the network and catchment to be represented at a high temporal resolution with a fixed spatial representation, resulting in accurate simulations but lengthy simulation times and a lack of flexibility in modeling options. As regulations, such as the UK's newly introduced "Drainage and Wastewater Management Planning," require more computationally expensive applications of sewer network models, such as optimization, real-time control, or scenario analysis to explore the impacts of, for example, changes in climate and land cover (Water, 2019), it is increasingly clear that alternative and more flexible approaches are needed to complement traditional high-fidelity sewer network modeling.

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Section: Discussionmentioning

confidence: 99%

A Reduced Complexity Model With Graph Partitioning for Rapid Hydraulic Assessment of Sewer Networks

Dobson

Watson‐Hill

Muhandes

et al. 2022

Water Resources Research

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“…Finally, site 3 is an We used one-minute model input and level observations for up to 10 years with the number of rain-induced events (events observed in the water level observations that are induced by rain events) calculated as indicated in Figure 4 for each site (143 events at site 1, 578 events at site 2, 345-357 events at site 3). Observation data were cleaned for outliers as proposed in Pedersen et al (2021b), but anomalies naturally occurring in urban drainage systems were not considered. Weather data (solar radiation, wind velocity, humidity and temperature) were extracted from the Danish Meteorological Institute's (DMI) open dataset for a weather station (Aarslev) 7 km away (DMI 2020).…”

Section: Case Studysystem Data and Modelmentioning

confidence: 99%

“…The applied simulation model is an integrated urban drainage model (see the section Urban drainage modeling and surrounding states) developed in the Mike Urban software by VCS Denmark. The model setup is described in the Bellinge open dataset (Pedersen et al 2021b). The surface runoff module is based on the time-area principle, and the pipe-flow module is the MOUSE hydraulic engine.…”

Section: Case Studysystem Data and Modelmentioning

confidence: 99%

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

Pedersen

Borup

et al. 2022

Water Science and Technology

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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.

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“…The UWNs' research community is moving the first steps in this direction. One example concerns the UDS of the Bellinge dataset (Pedersen et al., 2021), a suburb to the city of Odense, Denmark that is now available for “independent testing and replication of results from future scientific developments and innovation within urban hydrology and urban drainage system research”. This dataset includes 10 years of asset data (information from manholes and links), sensor data (level, flow, and power meters), rain data, hydrodynamic models (MIKE urban and EPA SWMM), and other information.…”

Section: Research Directionsmentioning

confidence: 99%

“…On the other hand, there is no consolidated set of benchmark networks for UDSs, let alone an entire structured database. This is attributable to factors such as the difficulty of taking measurements in sewer environments and, according to Pedersen et al (2021), the little interest of utility companies in making the datasets publicly available. Consequently, all the applications on UDSs were entirely developed for real cases, which is positive for the bridging between the theoretical approaches and the practice, but hampers the development of algorithms on the systems, due to the difficulty of comparison and the process of accounting for particularities of each system.…”

Section: Case Studies: Lack Of Benchmarking With Complex Networkmentioning

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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The Bellinge data set: open data and models for community-wide urban drainage systems research

Cited by 6 publications

References 31 publications

A Reduced Complexity Model With Graph Partitioning for Rapid Hydraulic Assessment of Sewer Networks

A Reduced Complexity Model With Graph Partitioning for Rapid Hydraulic Assessment of Sewer Networks

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

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

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