Date of Award
Master of Science
Bankfull hydraulic characteristics, i.e., bankfull discharge (Qbf), bankfull width (Wbf), bankfull mean depth (Dbf), and bankfull cross-section area (Abf) are important design factors in stream restoration projects. Regional curves are widely accepted as a useful tool for estimating bankfull hydraulic characteristics at ungaged sites. Nevertheless regional curves are developed using only one independent variable, drainage area (Ada), to predict Qbf and bankfull hydraulic geometry (Wbf, Dbf, and Abf). Wilkerson (2008) has demonstrated that regression equations for predicting Qbf can be improved by including the two-year recurrence interval flood flow (Q2) as an explanatory variable. This paper explores the potential for improving predictions of bankfull hydraulic geometry by using Q2 as an independent variable in regression models. For this study, bankfull hydraulic geometry data, and Ada and Q2 estimates were obtained for 29 hydrologic regions (regions with similar hydrology or peak flow response) across 14 states. The data span a wide range of geologic, hydrologic, and climatic conditions. By comparing statistical measures (root mean squared error, coefficient of determination, and Akaike's information criterion), we determined that Q2 has significant utility for improving predictions of bankfull hydraulic geometry. Without considering dataset size and compared to Ada, Q2 is shown to be a better predictor of Wbf, Dbf, and Abf, respectively, in 71%, 54%, and 64% of the cases we evaluated. When minimum dataset size requirements are set, these numbers increase.
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