{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/78586"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/78586","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Automatic Calibration of Storm Water Management Model (SWMM) with Multi-objective Optimization","abstract":"M.S.","abstract_html":"M.S.","abstract_has_math":false,"creators":["Shahed Behrouz, Mina"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Zhu, Zhenduo","Civil, Structural and Environmental Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-10-26T02:56:03Z","date_published":"2018-10-26T02:56:03Z","updated_at":"2026-07-27T19:05:12Z","subjects":["environmental engineering","water resources management"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/78586","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhu, Zhenduo","Civil, Structural and Environmental Engineering"]},{"key":"dc:creator","label":"Author","values":["Shahed Behrouz, Mina"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-10-26T02:56:03Z","2018","2018-08-09 10:57:54"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["environmental engineering","water resources management"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/78586"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["M.S.","Among various hydrologic models that are available to simulate urban runoff, the Storm Water Management Model (SWMM) is the most widely used numerical model. A typical SWMM project has about hundreds or thousands of sub-catchments and for each sub-catchment, there are more than 20 parameters associated with six different physical processes. Estimating all of these parameters are practically impossible, so model calibration is a challenging task. Manual calibration is used mostly but requires significant efforts and stops once simulation results are “satisfactory”. Some studies have adopted automatic calibration using a single objective optimization. However, an optimal parameter set obtained for one objective (e.g. peak flow) may perform poorly for another objective (e.g. average or low flow). In this study, SWMM was integrated with OSTRICH (Optimization Software Tool for Research Involving Computational Heuristics) to perform automatic multi-objective calibration. A sub-catchment within Buffalo, NY was selected as a case study. Automatic calibration using single and multiple objectives were conducted and compared. OSTRICH-SWMM is proved to be a useful tool for calibrating SWMM models. This study shows multi-objective calibration provides a more robust parameter set than any single objectives. A Pareto front is obtained in multi-objective calibration so an optimal solution can be selected according to trade-off. Moreover, this study highlights the importance of determining and considering time delay between simulated and observed values in model calibration."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Automatic Calibration of Storm Water Management Model (SWMM) with Multi-objective Optimization"]}]}],"canonical_facts":{"dc:contributor":["Zhu, Zhenduo","Civil, Structural and Environmental Engineering"],"dc:creator":["Shahed Behrouz, Mina"],"dc:date":["2018-10-26T02:56:03Z","2018","2018-08-09 10:57:54"],"dc:description":["M.S.","Among various hydrologic models that are available to simulate urban runoff, the Storm Water Management Model (SWMM) is the most widely used numerical model. A typical SWMM project has about hundreds or thousands of sub-catchments and for each sub-catchment, there are more than 20 parameters associated with six different physical processes. Estimating all of these parameters are practically impossible, so model calibration is a challenging task. Manual calibration is used mostly but requires significant efforts and stops once simulation results are “satisfactory”. Some studies have adopted automatic calibration using a single objective optimization. However, an optimal parameter set obtained for one objective (e.g. peak flow) may perform poorly for another objective (e.g. average or low flow). In this study, SWMM was integrated with OSTRICH (Optimization Software Tool for Research Involving Computational Heuristics) to perform automatic multi-objective calibration. A sub-catchment within Buffalo, NY was selected as a case study. Automatic calibration using single and multiple objectives were conducted and compared. OSTRICH-SWMM is proved to be a useful tool for calibrating SWMM models. This study shows multi-objective calibration provides a more robust parameter set than any single objectives. A Pareto front is obtained in multi-objective calibration so an optimal solution can be selected according to trade-off. Moreover, this study highlights the importance of determining and considering time delay between simulated and observed values in model calibration."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/78586"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["environmental engineering","water resources management"],"dc:title":["Automatic Calibration of Storm Water Management Model (SWMM) with Multi-objective Optimization"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T19:05:12Z"}