Dealing with Uncertainty in Water Distribution System Models: A Framework for Real-Time Modeling and Data Assimilation

Hutton, Christopher; Kapelan, Zoran; Vamvakeridou-Lyroudia, Lydia; Savić, Dragan

doi:10.1061/(asce)wr.1943-5452.0000325

Cited by 110 publications

(60 citation statements)

References 124 publications

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“…Except for the groundwater remediation design examples already noted, the approach has also been used extensively in water distribution system optimisation applications (e.g. Behzadian et al, 2009;Broad et al, 2005;Broad et al, 2010) and in real-time control (Hutton et al, 2014).…”

Section: Current Statusmentioning

confidence: 99%

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Maier

Kapelan

Kasprzyk

et al. 2014

Environmental Modelling & Software

530

317

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In all cases accepted manuscripts should:  link to the formal publication via its DOI  bear a CC-BY-NC-ND license -this is easy to do, click here to find out how  if aggregated with other manuscripts, for example in a repository or other site, be shared in alignment with our hosting policy  not be added to or enhanced in any way to appear more like, or to substitute for, the published journal article AbstractThe development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g., model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.

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Section: Current Statusmentioning

confidence: 99%

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Maier

Kapelan

Kasprzyk

et al. 2014

Environmental Modelling & Software

530

317

View full text Add to dashboard Cite

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“…In hydraulic modeling as well as in measuring hydraulic parameters one has to face several sources of uncertainty (Hutton et al 2014). We therefore assume that these effects should be taken into account in OSP algorithms.…”

Section: Introductionmentioning

confidence: 99%

Efficient Sensor Placement for Leak Localization Considering Uncertainties

Steffelbauer

Fuchs-Hanusch

2016

Water Resour Manage

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Losses in water distribution systems can be between several percent in well maintained systems up to more than 50 percent in developing countries. Most of the losses originate from leaks. Therefore, a fast detection and localization of leaks is crucial for effectively reducing this losses in water distribution networks. Model-based leak localization has become increasingly popular in recent years. Certainly, the performance of these methods is linked to 1) the measurement locations in the system and 2) uncertainties at these locations. This paper provides a methodology that incorporates uncertainties of different types and sources in the optimal sensor placement problem for leak localization shown by the example of the effect of demand uncertainties on potential pressure measurement points. The problem is solved for different numbers of sensors and different strengths of uncertainties are taken into account. Additionally, to describe the relation between the number of sensors and the leak localization quality, a cost-benefit function is derived based on the different sensor placement results and GoF statistics. It was found that the function follows a power law. Results show that incorporating uncertainties leads to other optimal positions than without uncertainties, but the power law behavior still stays true. Additionally, more sensors are needed than without uncertainties.

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“…This leakage can be a burst or any event that induce similar abnormal pressure/flow variations at the district metered area (DMA) level. Goulet et al (2013) assessed that the most important uncertainty sources are demands and model simplifications, but uncertainty also originates from measurement errors, incorrect boundary conditions, inherent model structural errors or unknown status of valves [(Hutton et al 2014), (Walski et al 2014)]. The calibration in this work focuses on demands due to their daily variability and continuous evolution depending generally on social and climate factors comparing to the more stable evolution of roughness.…”

Section: Introductionmentioning

confidence: 99%

Leak Detection and Localization through Demand Components Calibration

Sanz

Pérez

Kapelan

et al. 2016

J. Water Resour. Plann. Manage.

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The success in the application of any model-based methodology (e.g. design, control, supervision) highly depends on the availability of a well calibrated model. The calibration in water distribution networks needs to be performed online due to the continuous evolution of demands. During the calibration process, background leakages or bursts can be unintentionally incorporated to the demand model and treated as a system evolution (change in demands). This work proposes a leak detection and localization approach to be coupled with a calibration methodology that identifies geographically distributed parameters. The approach proposed consists in comparing the calibrated parameters with their historical values to assess if changes in these parameters are caused by a system evolution or by the effect of leakage. The geographical distribution allows to associate an unexpected behavior of the calibrated parameters (e.g. abrupt changes, trends, etc.) to a specific zone in the network. The performance of the methodology proposed is tested on a real water distribution network using synthetic data. Tested scenarios include leaks occurring at different locations and ranging from 2.5% to 13% of the total consumption. Leakage is represented as pressure-dependent demand simulated as emitter flows at the network nodes. Results show that even considering a low number of sensors, leaks with an effect on parameters higher than the parameters' uncertainty can be correctly detected and located within 200 meters.

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Dealing with Uncertainty in Water Distribution System Models: A Framework for Real-Time Modeling and Data Assimilation

Cited by 110 publications

References 124 publications

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Efficient Sensor Placement for Leak Localization Considering Uncertainties

Leak Detection and Localization through Demand Components Calibration

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