Urban drainage modeling and evolutionary multiobjective optimization for combined sewer overflows prediction and control

Morales, Viviana Maria

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https://hdl.handle.net/2142/90720 Copy

Description

Title

Urban drainage modeling and evolutionary multiobjective optimization for combined sewer overflows prediction and control

Author(s)

Morales, Viviana Maria

Issue Date

2016-02-22

Director of Research (if dissertation) or Advisor (if thesis)

Garcia, Marcelo H.

Doctoral Committee Chair(s)

Garcia, Marcelo H.

Committee Member(s)

• Cai, Ximing
• Schmidt, Arthur R.
• Markus, Momcilo

Department of Study

Civil & Environmental Eng

Discipline

Civil Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Hydrologic Modeling
• Combined Sewer Overflow
• Flooding
• Optimization

Abstract

As urbanization rapidly expands and climate change appears to contribute to more extreme rainfall events, the stress on urban wastewater systems increases. In particular, urban flooding and river water quality degradation due to combined sewer over flows (CSOs) are prevailing problems in urban areas worldwide. In this study we have developed an integrated hydrologic-hydraulic and water quality modeling framework coupled with an evolutionary multiobjective optimization algorithm to provide decision support for the minimization of both the pollutant load of CSOs and the risk of basement and street flooding. We first implemented a computationally efficient model that predicts the volume, frequency, and duration of CSOs. The model uses an existing probabilistic approach to simulate the hydrologic response of the combined sewer system in combination with a developed surrogate hydraulic model that solves the flow through the dropshafts, the deep tunnel, and outfall structures. We used this probabilistic framework to develop a model capable of simulating the fate and transport of non-conservative constituents in highly urbanized areas. This novel approach reproduces the same outcomes as deterministic models yet it reduces the computational time, requires less information and has the ability to track uncertainty in the predicted response. This framework is then utilized to perform a holistic analysis that involves not only water volume but also water quality through a multiobjective optimization. The optimization model is applied in a section of the Chicago combined sewer and tunnel system. We found that adaptive management for the operation of the sluice gate was successful in alleviating the pollutant load to the river by giving priority to the most polluted water to be stored in the tunnel system. However, the operation of the gate did not have a major effect on the risk of basement and street flooding. We examined the effect of climate change on the operation of the system and found that more storage capacity was needed in the tunnel to maintain similar constituent loads at the outfall, in response to more extreme rainfall events. Results from this research are useful for both scientists and managers to improve the understanding of constituent transport in urban watersheds, and to enhance decision making for the management of urban drainage systems.

Graduation Semester

2016-05

Type of Resource

text

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http://hdl.handle.net/2142/90720

Copyright and License Information

Copyright 2016 Viviana Morales

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