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  <titleInfo>
    <title>UTILIZING SUSTAIN TO MODEL BEST MANAGEMENT PRACTICES FOR STORMWATER MANAGEMENT ON THE IIT CAMPUS</title>
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    <namePart>Miller, Patrick</namePart>
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    <namePart>Anderson, Paul R.</namePart>
    <affiliation authority="wikidata" authorityURI="https://www.wikidata.org" valueURI="https://www.wikidata.org/wiki/Q131720503">CAEE / Civil, Architectural, and Environmental Engineering</affiliation>
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  <abstract>As cities expand the amount of impervious surface area increases, which increases the amount of stormwater runoff generated. Urban stormwater runoff contributes to the degradation and poor biological conditions of rivers and streams throughout the United States (USEPA, 2013). Currently, there are several different tools (i.e. computer software and models) available for stormwater managers to assess the effectiveness of best management practices (BMPs) to meet stormwater quality and quantity goals. In an effort to a create a single model that allows stormwater managers to evaluate the effectiveness of BMPs and associated cost information, the U.S. Environmental Protection Agency developed System for Urban Stormwater Treatment and Analysis INtegration (SUSTAIN) (USEPA, 2009). In this study, SUSTAIN is used to determine what BMPs are necessary to meet the Illinois Institute of Technology (IIT) 2020 Sustainability Plan’s goal of achieving 100 percent capture and retention of all stormwater runoff on the IIT campus by the year 2020. Multiple BMPs were simulated in currently available green space and parking lots to evaluate the level of runoff reduction and associated cost of BMP installation. Although the simulations show that reductions in runoff are possible without affecting the current layout of the campus, 100 percent capture and retention is not possible for the entire IIT campus. While the 2020 goal of 100 percent reduction cannot be met for the entire campus, significant reductions in runoff can still be realized with the use of BMPs in different sections of campus with high associated costs.</abstract>
  <note type="provenance">Submitted by Liana Khananashvili (khananashvili@iit.edu) on 2013-10-10T15:18:04Z No. of bitstreams: 2 Miller_Thesis_Final.pdf: 2274239 bytes, checksum: 64d7a93569fc418de7002ae9d4af69fa (MD5) Miller_Thesis_Final_Signed_Title_Page.pdf: 15730 bytes, checksum: d828056a0756158e08ce663501c93631 (MD5)</note>
  <note type="provenance">Made available in DSpace on 2013-10-10T15:18:04Z (GMT). No. of bitstreams: 2 Miller_Thesis_Final.pdf: 2274239 bytes, checksum: 64d7a93569fc418de7002ae9d4af69fa (MD5) Miller_Thesis_Final_Signed_Title_Page.pdf: 15730 bytes, checksum: d828056a0756158e08ce663501c93631 (MD5) Previous issue date: 2013-05</note>
  <note type="thesis">M.S. in in Environmental Engineering, May 2013</note>
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    <dateCaptured>2013-05-15</dateCaptured>
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    <dateCreated keyDate="yes">2013-05</dateCreated>
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  <identifier type="hdl">http://hdl.handle.net/10560/3083</identifier>
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    <namePart>CAEE / Civil, Architectural, and Environmental Engineering</namePart>
    <affiliation>Illinois Institute of Technology</affiliation>
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