An Analytical Method of Stage- Discharge Rating and Its Associated Uncertainties

博士 === 國立交通大學 === 土木工程系所 === 96 === This thesis presents an analytical method for establishing stage-fall-discharge rating using hydraulic performance graph (HPG). The theoretical rating (steady reachwise approximated normal flow) curves derived from the HPG are used as the basis to establish the fu...

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Bibliographic Details
Main Authors: Reuy-Bean Wu, 吳瑞濱
Other Authors: Jinn-Chuang Yang、Yeou-Koung Tung
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/eqb82w
Description
Summary:博士 === 國立交通大學 === 土木工程系所 === 96 === This thesis presents an analytical method for establishing stage-fall-discharge rating using hydraulic performance graph (HPG). The theoretical rating (steady reachwise approximated normal flow) curves derived from the HPG are used as the basis to establish the functional relation of stage, fall and discharge through regression analysis following the USGS procedure. In doing so, the conventional trial-and-error process can be avoided and the associated uncertainties involved may be reduced. For illustration, the proposed analytical method is applied to establish stage-fall-discharge relations for the Keelung River and Kaoping River in Taiwan for examining its accuracy and applicability in natural rivers. Based on the data extracted from the HPG for the Keelung River and the Kaoping River, one can establish a stage-fall-discharge relation that is more accurate than the one by the conventionally used relation; the associated uncertainties can be analyzed. The uncertainty analysis shows that the channel geometry and channel bed roughness should be the significant factors to affect the functional relation of stage, fall, and discharge. Furthermore, the discharges obtained from the proposed rating method are verified through backwater analysis for measured high water level events. The results indicate that the analytical stage-fall-discharge rating method is capable of circumventing the shortcomings of those based on single-station data and, consequently, enhancing the reliability of flood estimation and forecasting.