{"id":{"repo_id":"uno","oai_identifier":"oai:scholarworks.uno.edu:td-1532"},"canonical_url":"https://search.dev.ndltd.org/etd/uno/oai:scholarworks.uno.edu:td-1532","repository":{"repo_id":"uno","name":"University of New Orleans","base_url":"https://scholarworks.uno.edu/do/oai/"},"display":{"title":"Stormwater Runoff from Elevated Highways: Prediction of COD from Field Measurements and TSS","abstract":"This proposed research focused on the prediction and identification of chemical oxygen demand (COD) concentrations in storm water runoff from elevated roadways, which transports a significant load of contaminants. The objective of this research was to develop a mathematical model to relate COD concentration to different measurable parameters which are easily available and routinely measurable for elevated roadways. The test site for this research was selected at the intersection of the Interstate-10 and Interstate-610, Orleans Parish, New Orleans, Louisiana. Subsequently a research test site was developed and highway storm water runoff was collected. The developed model enables the user to predict COD concentrations within a prediction interval of 95 % confidence. The reliability of the model was verified by carrying out significant-difference tests for both sets of data, observed and predicted, for a 5% of significance level.","abstract_html":"This proposed research focused on the prediction and identification of chemical oxygen demand (COD) concentrations in storm water runoff from elevated roadways, which transports a significant load of contaminants. The objective of this research was to develop a mathematical model to relate COD concentration to different measurable parameters which are easily available and routinely measurable for elevated roadways. The test site for this research was selected at the intersection of the Interstate-10 and Interstate-610, Orleans Parish, New Orleans, Louisiana. Subsequently a research test site was developed and highway storm water runoff was collected. The developed model enables the user to predict COD concentrations within a prediction interval of 95 % confidence. The reliability of the model was verified by carrying out significant-difference tests for both sets of data, observed and predicted, for a 5% of significance level.","abstract_has_math":false,"creators":["L'Altrella, Claudio"],"institution":null,"degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil and Environmental Engineering","degree_department":null,"school":null,"contributors":["Tittelbaum, Marty","Kura, Bhaskar","Barbe, Donald"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2007,"date_issued":"2007-05-18T07:00:00Z","date_published":"2007-05-18T07:00:00Z","updated_at":"2026-07-24T05:28:36Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.uno.edu/td/532","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Tittelbaum, Marty","Kura, Bhaskar","Barbe, Donald"]},{"key":"dc:creator","label":"Author","values":["L'Altrella, Claudio"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil and Environmental Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.uno.edu/td/532"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This proposed research focused on the prediction and identification of chemical oxygen demand (COD) concentrations in storm water runoff from elevated roadways, which transports a significant load of contaminants. The objective of this research was to develop a mathematical model to relate COD concentration to different measurable parameters which are easily available and routinely measurable for elevated roadways. The test site for this research was selected at the intersection of the Interstate-10 and Interstate-610, Orleans Parish, New Orleans, Louisiana. Subsequently a research test site was developed and highway storm water runoff was collected. The developed model enables the user to predict COD concentrations within a prediction interval of 95 % confidence. The reliability of the model was verified by carrying out significant-difference tests for both sets of data, observed and predicted, for a 5% of significance level."]},{"key":"dc:title","label":"Title","values":["Stormwater Runoff from Elevated Highways: Prediction of COD from Field Measurements and TSS"]}]}],"canonical_facts":{"dc:contributor":["Tittelbaum, Marty","Kura, Bhaskar","Barbe, Donald"],"dc:creator":["L'Altrella, Claudio"],"dc:description.abstract":["This proposed research focused on the prediction and identification of chemical oxygen demand (COD) concentrations in storm water runoff from elevated roadways, which transports a significant load of contaminants. The objective of this research was to develop a mathematical model to relate COD concentration to different measurable parameters which are easily available and routinely measurable for elevated roadways. The test site for this research was selected at the intersection of the Interstate-10 and Interstate-610, Orleans Parish, New Orleans, Louisiana. Subsequently a research test site was developed and highway storm water runoff was collected. The developed model enables the user to predict COD concentrations within a prediction interval of 95 % confidence. The reliability of the model was verified by carrying out significant-difference tests for both sets of data, observed and predicted, for a 5% of significance level."],"dc:identifier":["https://scholarworks.uno.edu/td/532"],"dc:title":["Stormwater Runoff from Elevated Highways: Prediction of COD from Field Measurements and TSS"],"thesis:degree_discipline":["Civil and Environmental Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."]},"updated_at":"2026-07-24T05:28:36Z"}