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深度相关水力粗糙度及其对水击评估的影响。

Depth-dependent hydraulic roughness and its impact on the assessment of hydropeaking.

机构信息

sje - Ecohydraulic Engineering GmbH, Viereichenweg 12, 70569 Stuttgart, Germany.

sje - Ecohydraulic Engineering GmbH, Viereichenweg 12, 70569 Stuttgart, Germany; Centre for Biorobotics, Tallinn University of Technology, Akadeemia tee 15A-111, 12618 Tallinn, Estonia.

出版信息

Sci Total Environ. 2017 Jan 1;575:1597-1605. doi: 10.1016/j.scitotenv.2016.10.110. Epub 2016 Oct 30.

DOI:10.1016/j.scitotenv.2016.10.110
PMID:27802885
Abstract

Hydrodynamic river models in combination with physical habitat modelling serve as the basis for a wide spectrum of environmental studies. Larvae, juvenile and spawning fish, redds and benthic invertebrates belong to the biological groups most heavily affected by rapid flow variations as a consequence of peaking energy production, or "hydropeaking". As these species find their preferential habitat to a great extent in shallow regions, high prediction accuracy for these areas is essential to substantiate the use of hydrodynamic models. In this paper, a new formulation for the depth-dependent roughness originating from the boundary layer theory is derived. The modelling approach is based on the concept of a dynamic, spatio-temporal Manning's roughness which allows for considerable improvement in the accuracy of stationary and highly transient hydrodynamic simulations in shallow river areas. In addition, the approach facilitates more effective model calibration, as it allows for the preservation of the roughness sublayer thickness as a single calibration parameter for the entire range of hydropeaking discharges. The approach is tested and validated on a 7.5km long stretch of a middle-size gravel river affected by hydropeaking. Model results using conventional constant roughness and the proposed dynamic roughness approaches are compared. The implications for the stationary habitat assessment and calculation of dynamic hydropeaking parameters are analysed as well.

摘要

水动力河流模型与物理栖息地建模相结合,为广泛的环境研究提供了基础。幼虫、幼鱼和产卵鱼、产卵床和底栖无脊椎动物属于受因峰值能源生产而产生的快速水流变化影响最大的生物群体,即“水力高峰”。由于这些物种在很大程度上在浅水区寻找其首选栖息地,因此对这些区域进行高精度预测对于证实水动力模型的使用至关重要。在本文中,提出了一种新的基于边界层理论的深度相关糙率的公式。该建模方法基于动态时空曼宁糙率的概念,允许对浅水区域的稳态和高度瞬态水动力模拟的精度进行相当大的改进。此外,该方法还促进了更有效的模型校准,因为它允许将糙率次层厚度作为整个水力高峰排放范围内的单个校准参数来保留。该方法在受水力高峰影响的一条 7.5 公里长的中型砾石河流上进行了测试和验证。比较了使用常规恒定糙率和所提出的动态糙率方法的模型结果。还分析了对静态栖息地评估和动态水力高峰参数计算的影响。

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