Development of a Method to Compare Storm Water Best Management Practices at The University of Toledo

Storm water runoff has become a concern in urban environments. Urban environments have a very large percentage of impermeable area, creating large amounts of surface runoff. This surface runoff carries contaminants (nutrients, sediments, pathogens, oils and greases) into storm water collection systems, which drain directly into natural waters. These contaminants degrade water quality, harming human health and aquatic life. In order to address these concerns, storm water best management practices (BMPs) have been developed to reduce flow rates and improve water quality. However, many sites that require the use of the BMPs have no means of deciding which BMP is the best fit for the site in question. To address this problem, a Storm Water BMP Model was developed to analyze three different BMPs (porous pavement, bioswales, and rain gardens) for effectiveness. A comparison is made using input parameters including water quality information and permeable/impermeable areas, and potential. BMPs are ranked based on flow quantity reduction, pollutant reduction, and payback period. The payback period includes capital costs associated with constructing the BMP as well as monetary values associated with environmental gains from implementing the BMP. This model provides the opportunity to see a side by side comparison of BMPs in a retrofit situation and to evaluate their implementation based on cost and performance.

Name thesis:degree_name

Master of Science in Civil Engineering

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Civil Engineering

Grantor dc:publisher

University of Toledo

Year dc:date

2012

Author dc:creator

• Wancata, Christopher Michael

Contributors dc:contributor

• Gruden, Cyndee

• Civil Engineering
• storm water
• best management practices
• comparison analysis

Statement dc:rights

• 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.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=toledo1353085450

OAI identifier oai:identifier

oai:etd.ohiolink.edu:toledo1353085450