Reference Time of Concentration Estimation for Ungauged Catchments

J. Perdikaris, Bahram Gharabaghi, R. Rudra
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引用次数: 23

Abstract

Accurate modelling of flood flow hydrographs in ungauged catchments is a challenging task due to large errors in the estimation of its response time using existing empirical equations. The time of concentration (Tc) is a key catchment response time parameter needed for forecasting of the peak discharge rate and the timing of the flood event. At least eight different definitions have been presented in the literature for the time of concentration. In this study, a new definition of “Reference Tc” is presented along with a practical procedure for its estimation using readily available basin catchment characteristic parameters with the aim of standardizing this key parameter for practitioners. Nine different empirical models were calibrated and tested on nine catchments of the Credit River watershed, Ontario, Canada to determine which method would provide the most accurate prediction of the Reference Tc. The NRCS velocity method (1986) proved once again to be the most reliable and an accurate method. This study shows that the main reason for the higher accuracy of the NRCS velocity method predictions compared to the empirical equations is attributed to the inclusion of the Manning's roughness coefficient.
未计量集水区浓度估计的参考时间
由于使用现有经验方程估计其响应时间的误差很大,因此对未测量集水区的洪水水流曲线进行精确建模是一项具有挑战性的任务。浓度时间(Tc)是预测洪峰流量和洪水发生时间所需的关键流域响应时间参数。至少有八种不同的定义已在文献中提出的时间集中。在本研究中,提出了“参考Tc”的新定义以及使用现成的流域集水区特征参数进行估计的实用程序,目的是为从业者标准化这一关键参数。在加拿大安大略省信贷河流域的九个集水区对九个不同的经验模型进行了校准和测试,以确定哪种方法可以提供最准确的参考Tc预测。1986年的NRCS速度法再次证明是最可靠、最准确的方法。研究表明,与经验方程相比,NRCS速度方法预测精度更高的主要原因是包含了曼宁粗糙度系数。
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