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首页> 外文期刊>Journal of the American Water Resources Association >Empirical Estimation of Stream Discharge Using Channel Geometry in Low-Gradient, Sand-Bed Streams of the Southeastern Plains
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Empirical Estimation of Stream Discharge Using Channel Geometry in Low-Gradient, Sand-Bed Streams of the Southeastern Plains

机译:东南平原低坡度沙床河道利用流道几何学估算河道流量

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Manning's equation is used widely to predict stream discharge (Q) from hydraulic variables when logistics constrain empirical measurements of in-bank flow events. Uncertainty in Manning's roughness (n(M)) is the major source of error in natural channels, and sand-bed streams pose difficulties because flow resistance is affected by flow-dependent bed configuration. Our study was designed to develop and validate models for estimating Q from channel geometry easily derived from cross-sectional surveys and available GIS data. A database was compiled consisting of 484 Q measurements from 75 sand-bed streams in Alabama, Georgia, South Carolina, North Carolina (Southeastern Plains), and Florida (Southern Coastal Plain), with six New Zealand streams included to develop statistical models to predict Q from hydraulic variables. Model error characteristics were estimated with leave-one-site-out jackknifing. Independent data of 317 Q measurements from 55 Southeastern Plains streams indicated the model (Q=A(c)R(H)(0.6906)S(0.1216); where A(c) is the channel area, R-H is the hydraulic radius, and S is the bed slope) best predicted Q, based on Akaike's information criterion and root mean square error. Models also were developed from smaller Q range subsets to explore if subsets increased predictive ability, but error fit statistics suggested that these were not reasonable alternatives to the above equation. Thus, we recommend the above equation for predicting in-bank Q of unbraided, sandy streams of the Southeastern Plains.
机译:当物流限制银行内流量事件的实证测量时,曼宁方程被广泛用于根据水力变量预测流量(Q)。曼宁粗糙度(n(M))的不确定性是自然通道误差的主要来源,并且沙床流造成困难,因为流阻受与流量有关的床构造的影响。我们的研究旨在开发和验证模型,以根据可从横截面调查和可用GIS数据轻松得出的通道几何形状估算Q。汇编了一个数据库,其中包括来自阿拉巴马州,乔治亚州,南卡罗来纳州,北卡罗来纳州(东南平原)和佛罗里达州(南沿海平原)的75条砂层流的484 Q测量值,其中包括六个新西兰流以开发统计模型以进行预测Q来自水力变量。模型误差特征是通过留一站外的粗略估计来估计的。来自55个东南平原流的317个Q测量值的独立数据表明该模型(Q = A(c)R(H)(0.6906)S(0.1216);其中A(c)是通道面积,RH是水力半径,并且S是基于Akaike信息准则和均方根误差的最佳预测Q。还从较小的Q范围子集开发了模型,以探索子集是否增加了预测能力,但是误差拟合统计表明,这些不是上述方程式的合理替代方案。因此,我们建议使用上述方程式来预测东南平原未编织的沙质河流的岸上Q。

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