Urban runoff index estimation, which has traditionally been a time-consuming and labor-intensive process, is a fundamental problem for modeling watershed runoff especially for growing cities that lack stream gages worldwide. The research developed and evaluated the composite runoff index (RIc) geographic model (© 2005-2006 Pravara Thanapura. Use with permission)—an area-weighted parameterization scheme-based remote sensing and GIS methodology—for efficiently and effectively estimating the critical input as required by the most widely used single-parameter rainfall-runoff techniques: the curve number (CN) for the Natural Resources Conservation Service Curve-Number (NRCS-CN) method and the runoff coefficient (C) for the rational method. The RIc geographic model, as developed using Sioux Falls, South Dakota, and demonstrated in Las Vegas, Nevada, provides an improved scheme for effective drainage design, analysis, and water management in urban ungaged areas. This, in turn, should help prevent uncertain local and downstream flooding during unusual rainfall events, and potentially reduce loss of life and damage to property, and thus could enhance public safety, economic development, and quality of life.
","abstract_html":"<p>Urban runoff index estimation, which has traditionally been a time-consuming and labor-intensive process, is a fundamental problem for modeling watershed runoff especially for growing cities that lack stream gages worldwide. The research developed and evaluated the composite runoff index (RIc) geographic model (© 2005-2006 Pravara Thanapura. Use with permission)—an area-weighted parameterization scheme-based remote sensing and GIS methodology—for efficiently and effectively estimating the critical input as required by the most widely used single-parameter rainfall-runoff techniques: the curve number (CN) for the Natural Resources Conservation Service Curve-Number (NRCS-CN) method and the runoff coefficient (C) for the rational method. The RIc geographic model, as developed using Sioux Falls, South Dakota, and demonstrated in Las Vegas, Nevada, provides an improved scheme for effective drainage design, analysis, and water management in urban ungaged areas. This, in turn, should help prevent uncertain local and downstream flooding during unusual rainfall events, and potentially reduce loss of life and damage to property, and thus could enhance public safety, economic development, and quality of life.</p>","abstract_has_math":false,"creators":["Thanapura, Pravara"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation - University Access Only","degree_discipline":"Agricultural and Biosystems Engineering","degree_department":null,"school":null,"contributors":["Edwin T. Engman"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-01-01T08:00:00Z","date_published":"2011-01-01T08:00:00Z","updated_at":"2026-07-24T04:28:11Z","subjects":["Bioresource and Agricultural Engineering"],"languages":["en"],"rights":["Copyright © 2011 Pravara Thanapura. All rights reserved"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://openprairie.sdstate.edu/etd/638","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Edwin T. Engman"]},{"key":"dc:creator","label":"Author","values":["Thanapura, Pravara"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural and Biosystems Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation - University Access Only"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Bioresource and Agricultural Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright © 2011 Pravara Thanapura. All rights reserved"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openprairie.sdstate.edu/etd/638"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Urban runoff index estimation, which has traditionally been a time-consuming and labor-intensive process, is a fundamental problem for modeling watershed runoff especially for growing cities that lack stream gages worldwide. The research developed and evaluated the composite runoff index (RIc) geographic model (© 2005-2006 Pravara Thanapura. Use with permission)—an area-weighted parameterization scheme-based remote sensing and GIS methodology—for efficiently and effectively estimating the critical input as required by the most widely used single-parameter rainfall-runoff techniques: the curve number (CN) for the Natural Resources Conservation Service Curve-Number (NRCS-CN) method and the runoff coefficient (C) for the rational method. The RIc geographic model, as developed using Sioux Falls, South Dakota, and demonstrated in Las Vegas, Nevada, provides an improved scheme for effective drainage design, analysis, and water management in urban ungaged areas. This, in turn, should help prevent uncertain local and downstream flooding during unusual rainfall events, and potentially reduce loss of life and damage to property, and thus could enhance public safety, economic development, and quality of life.
"]},{"key":"dc:title","label":"Title","values":["Developing and Evaluating the Composite Runoff Index Geographic Model for Urban Rainfall-Runoff Modeling"]}]}],"canonical_facts":{"dc:contributor":["Edwin T. Engman"],"dc:creator":["Thanapura, Pravara"],"dc:description.abstract":["Urban runoff index estimation, which has traditionally been a time-consuming and labor-intensive process, is a fundamental problem for modeling watershed runoff especially for growing cities that lack stream gages worldwide. The research developed and evaluated the composite runoff index (RIc) geographic model (© 2005-2006 Pravara Thanapura. Use with permission)—an area-weighted parameterization scheme-based remote sensing and GIS methodology—for efficiently and effectively estimating the critical input as required by the most widely used single-parameter rainfall-runoff techniques: the curve number (CN) for the Natural Resources Conservation Service Curve-Number (NRCS-CN) method and the runoff coefficient (C) for the rational method. The RIc geographic model, as developed using Sioux Falls, South Dakota, and demonstrated in Las Vegas, Nevada, provides an improved scheme for effective drainage design, analysis, and water management in urban ungaged areas. This, in turn, should help prevent uncertain local and downstream flooding during unusual rainfall events, and potentially reduce loss of life and damage to property, and thus could enhance public safety, economic development, and quality of life.
"],"dc:identifier":["https://openprairie.sdstate.edu/etd/638"],"dc:language":["en"],"dc:rights":["Copyright © 2011 Pravara Thanapura. All rights reserved"],"dc:subject":["Bioresource and Agricultural Engineering"],"dc:title":["Developing and Evaluating the Composite Runoff Index Geographic Model for Urban Rainfall-Runoff Modeling"],"thesis:degree_discipline":["Agricultural and Biosystems Engineering"],"thesis:degree_level":["Dissertation - University Access Only"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T04:28:11Z"}