Off-campus South Dakota State University users: To download campus access theses, please use the following link to log into our proxy server with your South Dakota State University ID and password.

Non-South Dakota State University users: Please talk to your librarian about requesting this thesis through interlibrary loan.

Document Type

Dissertation - University Access Only

Award Date


Degree Name

Doctor of Philosophy (PhD)


Agricultural and Biosystems Engineering

First Advisor

Edwin T. Engman


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.

Library of Congress Subject Headings

urban runoff
mathematical models
urban hydrology


Includes bibliographical references (293-309)



Number of Pages



South Dakota State University


Copyright © 2011 Pravara Thanapura. All rights reserved