Detention-based Green/Gray Infrastructure Framework to Control Combined Sewer Overflows
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| Language: | English |
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University of Cincinnati / OhioLINK
2015
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439307033 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-ucin1439307033 |
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| record_format |
oai_dc |
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NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Water Resource Management Combined Sewer Overflows Green gray infrastructure Storm water Management Optimal operation Geographical Information Systems quasi real time control operation |
| spellingShingle |
Water Resource Management Combined Sewer Overflows Green gray infrastructure Storm water Management Optimal operation Geographical Information Systems quasi real time control operation Mancipe Muñoz, Nestor Alonso Detention-based Green/Gray Infrastructure Framework to Control Combined Sewer Overflows |
| author |
Mancipe Muñoz, Nestor Alonso |
| author_facet |
Mancipe Muñoz, Nestor Alonso |
| author_sort |
Mancipe Muñoz, Nestor Alonso |
| title |
Detention-based Green/Gray Infrastructure Framework to Control Combined Sewer Overflows |
| title_short |
Detention-based Green/Gray Infrastructure Framework to Control Combined Sewer Overflows |
| title_full |
Detention-based Green/Gray Infrastructure Framework to Control Combined Sewer Overflows |
| title_fullStr |
Detention-based Green/Gray Infrastructure Framework to Control Combined Sewer Overflows |
| title_full_unstemmed |
Detention-based Green/Gray Infrastructure Framework to Control Combined Sewer Overflows |
| title_sort |
detention-based green/gray infrastructure framework to control combined sewer overflows |
| publisher |
University of Cincinnati / OhioLINK |
| publishDate |
2015 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439307033 |
| work_keys_str_mv |
AT mancipemunoznestoralonso detentionbasedgreengrayinfrastructureframeworktocontrolcombinedseweroverflows |
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1719438879511019520 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-ucin14393070332021-08-03T06:32:47Z Detention-based Green/Gray Infrastructure Framework to Control Combined Sewer Overflows Mancipe Muñoz, Nestor Alonso Water Resource Management Combined Sewer Overflows Green gray infrastructure Storm water Management Optimal operation Geographical Information Systems quasi real time control operation Combined sewer overflows (CSO) are uncontrolled discharges of rainfall-runoff and untreated sewage into nearby streams that occur when the capacity of the combined sewer system (CSS) or the treatment facility is exceeded during heavy rainfall or snowmelt events. Resilient and affordable solutions are needed to control CSO and help manage urban flooding. Typically, gray infrastructure (i.e. treatment facilities, etc.) are proposed to mitigate CSO impacts. A more environmentally friendly approach called green infrastructure (i.e. ponds, rain-gardens, etc.) is being considered to help solve this problem. Individually each approach would achieve a desired CSO control/reduction goal. Interest has grown in using a combination of “green” and “gray” infrastructure because it not only mitigates CSO, but also maximizes social, economic, and environmental benefits for its service communities. The present work demonstrates the technical and economic feasibility of using an innovative decentralized detention-based green/gray infrastructure (DBGI) system to mitigate impacts of CSO in urban communities. A cascading network of DBGI (i.e. short storm-sewers and small detention ponds), strategically placed throughout a sewershed, is studied to intercept and temporarily detain rainfall-runoff during a storm event. During and after a storm, the network of ponds makes constant controlled releases of runoff into the existing CSS. The releases are carefully managed to not exceed the conveyance capacity of the CSS and, hence, to avoid causing a CSO. The proposed framework combines state-of-the-art mathematical modeling complemented with Geographical Information Systems (GIS). The framework has four components: first, a reliable calibration approach for a physically-based semidistributed rainfall-runoff model is presented using the storm water management model (SWMM5). The calibrated SWMM5 is used to simulate both the existing CSS (pre-DBGI) and the DBGI alternative (Post-DBGI) scenarios. Second, an efficient GIS-based algorithm based on terrain analysis is developed and implemented in ArcGIS10 to identify, screen, and size competing DBGI sites. Third, a unique optimal control-operation method is developed for the DBGI system. It is hypothesized that the DBGI’s optimal operation is a “synchronized inhale then exhale strategy” (SITES). Under the SITES, all ponds fill and release in unison so that the instantaneous fraction of total storage occupied by runoff is similar in all ponds at all times. Fourth, a DBGI quasi real-time control-operation strategy (RTC-SITES) is developed and verified with an analogous search approach that uses SITES, quantitative precipitation forecast (QPF), and historical rainfall events. The framework is tested for a study area in Cincinnati, OH as a proof-of-concept of the DBGI alternative.Simulation results indicate that strategic deployment of a network of DBGI operated by RTC-SITES can meet required CSO federal consent decrees in urbanized areas at a much lower cost than a conventional “gray” alternative. These findings are significant not only for the study area, but also for any of the hundreds of metropolitan urban regions in US that are struggling under regulatory decrees to fix CSO problems. This framework provides a promising and useful tool for evaluating the effectiveness, feasibility, and operational control of this approach to control CSO in urbanized areas. 2015-10-19 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439307033 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439307033 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |