Joint probability and design storms at the crossroads
Joint probability and design storms at the crossroads
复制标题
十字路口的联合概率与设计风暴
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
P. Coombes
中科院分区：
文献类型：
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作者：
G. Kuczera;M. Lambert;T. Heneker;S. Jennings;A. Frost;P. Coombes
摘要洪水估算中的联合概率问题是一个复杂的问题。尽管设计风暴法有着悠久的传统，但它缺乏联合概率分析的基本严谨性。如果输入的变化以线性方式影响峰值流量密度，则可以从联合概率的角度对降雨强度和持续时间以外的随机输入使用平均值。然而，初始条件的平均值的分配是有问题的。一个涉及滞留盆地的案例研究表明，在对体积敏感的系统中，初始条件的错误指定会产生很大的偏差。建议当前修订的ARR需要阐明设计风暴方法的不足之处，确定确保关闭的校准策略，并就其在不同应用中的可靠性提供指导。展望未来，ARR需要转向以严格的联合概率框架为基础的事件和总联合概率方法。连续模拟正在成为一种实用的工具，并且仍然是可用的最严格的工具。基于蒙特卡罗模拟的事件联合概率方法在计算上要求较低，但需要指定初始条件的概率分布。随机降雨模型即将用于蒙特卡罗方法的实际应用。
Abstract The joint probability problem inherent in flood estimation is complex. Although the design storm approach has a long tradition it lacks the fundamental rigour of joint probability analysis. The use of average values for random inputs other than rainfall intensity and duration can be justified from a joint probability perspective provided variations in the input affect the peak flow density in a linear fashion. However, the assignment of the average value for initial conditions is problematic. A case study involving a detention basin demonstrates large biases arising from mis-specification of initial conditions in volume-sensitive systems. It is suggested that the current revision of ARR needs to articulate the shortcomings of the design storm approach, identify calibration strategies that ensure closure and give guidance about its reliability in different applications. Looking to the future, ARR needs to move towards event and total joint probability approaches that are underpinned by a rigorous joint probability framework. Continuous simulation is emerging as a practical tool and remains the most rigorous tool available. Event joint probability methods based on Monte Carlo simulation are computationally less demanding but require specification of the probability distribution of initial conditions. Stochastic rainfall models are on the verge of practical application to service Monte Carlo methods.