{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/86100"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/86100","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Tile -Drained Watershed Scs-Curve Number Model","abstract":"Tile flow can be quantified using the altered SCS-CN method. Through theory analogy, a procedure similar to the traditional SCS-CN method was developed to estimate tile flow from rainfall. However, the relationship between initial abstractions and potential maximum retention was redefined. Curve number was obtained from observed rainfall and tile flow by assuming that initial abstractions were a portion of potential maximum retention. The curve number was sensitive to the ratio of initial abstractions/potential maximum retention. Additionally, curve number varied with rainfall amount, date and previous rainfall condition. Therefore, multiple regression was performed based on curve number and date, rainfall amount, and previous rainfall conditions. Regression results were used to obtain a curve number for each individual rainfall event. Flow was predicted based on the curve number obtained from regression. Comparisons were made between observed flow and predicted flow for five tile monitoring stations in Little Vermilion River watershed in east central Illinois. The method was successful in estimating tile flow regardless of whether the tile drain system is regular or irregular.","abstract_html":"Tile flow can be quantified using the altered SCS-CN method. Through theory analogy, a procedure similar to the traditional SCS-CN method was developed to estimate tile flow from rainfall. However, the relationship between initial abstractions and potential maximum retention was redefined. Curve number was obtained from observed rainfall and tile flow by assuming that initial abstractions were a portion of potential maximum retention. The curve number was sensitive to the ratio of initial abstractions/potential maximum retention. Additionally, curve number varied with rainfall amount, date and previous rainfall condition. Therefore, multiple regression was performed based on curve number and date, rainfall amount, and previous rainfall conditions. Regression results were used to obtain a curve number for each individual rainfall event. Flow was predicted based on the curve number obtained from regression. Comparisons were made between observed flow and predicted flow for five tile monitoring stations in Little Vermilion River watershed in east central Illinois. The method was successful in estimating tile flow regardless of whether the tile drain system is regular or irregular.","abstract_has_math":false,"creators":["Yuan, Yongping"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Agricultural Engineering","degree_department":null,"school":null,"contributors":["Mitchell, J. Kent"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-28T14:53:57Z","date_published":"2015-09-28T14:53:57Z","updated_at":"2026-07-22T22:26:26Z","subjects":["Agriculture, Soil Science"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI9955685"],"render_values":[{"text":"(MiAaPQ)AAI9955685","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/86100","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mitchell, J. 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Through theory analogy, a procedure similar to the traditional SCS-CN method was developed to estimate tile flow from rainfall. However, the relationship between initial abstractions and potential maximum retention was redefined. Curve number was obtained from observed rainfall and tile flow by assuming that initial abstractions were a portion of potential maximum retention. The curve number was sensitive to the ratio of initial abstractions/potential maximum retention. Additionally, curve number varied with rainfall amount, date and previous rainfall condition. Therefore, multiple regression was performed based on curve number and date, rainfall amount, and previous rainfall conditions. Regression results were used to obtain a curve number for each individual rainfall event. Flow was predicted based on the curve number obtained from regression. Comparisons were made between observed flow and predicted flow for five tile monitoring stations in Little Vermilion River watershed in east central Illinois. The method was successful in estimating tile flow regardless of whether the tile drain system is regular or irregular.","Made available in DSpace on 2015-09-28T14:53:57Z (GMT). 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However, the relationship between initial abstractions and potential maximum retention was redefined. Curve number was obtained from observed rainfall and tile flow by assuming that initial abstractions were a portion of potential maximum retention. The curve number was sensitive to the ratio of initial abstractions/potential maximum retention. Additionally, curve number varied with rainfall amount, date and previous rainfall condition. Therefore, multiple regression was performed based on curve number and date, rainfall amount, and previous rainfall conditions. Regression results were used to obtain a curve number for each individual rainfall event. Flow was predicted based on the curve number obtained from regression. Comparisons were made between observed flow and predicted flow for five tile monitoring stations in Little Vermilion River watershed in east central Illinois. 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