Sriwastava, A.K., Tait, S., Schellart, A. et al. (4 more authors) (2018) Quantifying uncertainty in simulation of sewer overflow volume. Journal of Environmental Engineering, 144 (7). 04018050. ISSN 0733-9372
Abstract
Environmental regulators frequently stipulate the modeling approaches required for water utilities managing sewer networks to demonstrate regulatory compliance. The performance of drainage systems with regard to combined sewer overflow (CSO) discharges is required to be assessed using urban drainage models to prove compliance before large investments can be authorized. However, as far as the authors are aware, the modeling approaches to demonstrate regulatory compliance currently provide no opportunity for considering model uncertainty. This paper therefore addresses a knowledge gap in the role of model uncertainty in environmental compliance studies by describing an objective uncertainty quantification process that enables the water utilities to evaluate and report the uncertainty in their modeling predictions and that is also transparent enough to satisfy regulators. The sewer network was modeled in InfoWorks CS software using a design storm defined by the regulator to test the performance of CSOs. Uncertainty in the model and input parameters was propagated using Monte Carlo simulations with Latin hypercube sampling, and the results were presented to show the trade-off between the infrastructure investment and the risk of spilling.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © ASCE 2018. This work is made available under the terms of the Creative Commons Attribution 4.0 International license, http://creativecommons.org/licenses/by/4.0/. |
Keywords: | Environmental protection; Model uncertainty; Regulatory compliance; Sewer overflows; Uncertainty propagation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Jun 2018 11:03 |
Last Modified: | 19 Jun 2018 11:03 |
Published Version: | https://doi.org/10.1061/(ASCE)EE.1943-7870.0001392 |
Status: | Published |
Publisher: | American Society of Civil Engineers |
Refereed: | Yes |
Identification Number: | 10.1061/(ASCE)EE.1943-7870.0001392 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:131905 |