State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China; Key Laboratory of Yangtze River Water Environment (Ministry of Education), Tongji University, Shanghai 200092, PR China.
State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; Key Laboratory of Yangtze River Water Environment (Ministry of Education), Tongji University, Shanghai 200092, PR China.
Water Res. 2018 Nov 1;144:112-125. doi: 10.1016/j.watres.2018.07.022. Epub 2018 Jul 12.
Onsite runoff control is considered an important part of sustainable urban drainage schemes, but estimating the maximum runoff flow rate from a catchment with onsite runoff controls remains controversial. Runoff controls complicate the issue by dividing the catchment into several subcatchments that feed into individual runoff controls, which dynamically regulate the catchment imperviousness. Rational Method (RM) is the most-employed technique to determine maximum flow rates for designing urban drainage infrastructures, but it cannot handle such conditions. Nonetheless, it has advantages over alternative methods in terms of principle from the urban drainage design perspective. This work develops Rational Method Prime (RMP) that follows the basic principle of RM but instead recalculates catchment variables by taking into account runoff control effects and evaluates runoff control efficiencies by using two indices. RMP has three merits: (1) providing an integrated response of the whole catchment with runoff controls; (2) interpreting runoff control effects by plotting runoff flow rate-rainfall duration curves; (3) connecting the design of runoff controls and storm sewers that are based on different design principles and rainfall statistics. Case study results showed that runoff controls reduced peak flow rates by 5.83-91.6%, corresponding to reduction factors for return period of maximum flow rate from 0.04 to 0.76. Indeed, the original RM is based on four assumptions, which also cause its weakness, and there have been current methods to address 3 of them. RMP contributes to addressing the last assumption (i.e. constant catchment imperviousness), which finally allowing the evolution from RM 1.0 to 2.0.
就地径流控制被认为是可持续城市排水系统的重要组成部分，但估算具有就地径流控制的集水区的最大径流量仍然存在争议。径流控制通过将集水区划分为几个子流域来使问题复杂化，这些子流域流入各个径流控制装置，这些装置动态调节集水区的不透水率。理性方法（RM）是确定城市排水基础设施设计最大流量的最常用技术，但它无法处理这种情况。尽管如此，从城市排水设计的角度来看，它在原理上优于替代方法。这项工作开发了理性方法 Prime（RMP），它遵循 RM 的基本原理，但通过考虑径流控制效果重新计算集水区变量，并使用两个指数来评估径流控制效率。RMP 有三个优点：（1）提供了具有径流控制的整个集水区的综合响应；（2）通过绘制径流流量-降雨持续时间曲线来解释径流控制效果；（3）将基于不同设计原则和降雨统计数据的径流控制和雨水管道设计联系起来。案例研究结果表明，径流控制将峰值流量降低了 5.83-91.6%，相应的最大流量重现期的缩减系数为 0.04-0.76。实际上，原始 RM 基于四个假设，这也导致了它的弱点，并且已经有了当前的方法来解决其中的三个。RMP 有助于解决最后一个假设（即恒定集水区不透水率），最终允许 RM 1.0 到 2.0 的演变。
