A simplified empirical equation is developed for widespread prediction of dynamic catchment response time. This model allows for time‐to‐peak prediction to evolve from static, lumped models, thereby providing a single value for any storm within a given catchment, using a single set of input parameters, that can be applied to a dynamic model, thus accounting for the variability between storm sizes and catchment moisture conditions. These dynamic prediction methods are translated to North America for the first time. This allows the concepts and prediction methods for catchment response time prediction previously established for the United Kingdom (UK), to be translated to a simple empirical equation for use in North America, through the use of selected study areas in Canada and the United States. This reconfigured model is statistically successful in both the UK and North America and allows for a straightforward implementation of dynamic time‐to‐peak prediction. Further, the reconfigured model introduces the use of a runoff coefficient (R_c) to encompass historical catchment wetness, increasing the ease of incorporating antecedent moisture condition into predictions.

中文翻译：

---

动态预测模型

开发了一个简化的经验公式，用于动态预测流域响应时间。该模型允许从静态的集总模型演变为峰值时间预测，从而使用一组输入参数将给定流域内任何风暴的单个值提供给动态模型，从而进行核算风暴规模和集水区湿度条件之间的差异。这些动态预测方法首次被翻译成北美地区。这使得先前为英国（UK）建立的集水区响应时间预测的概念和预测方法，可以通过使用加拿大和美国的选定研究区域，转化为用于北美的简单经验方程式。这种重新配置的模型在英国和北美在统计上都是成功的，并且可以直接实施动态的峰值时间预测。此外，重新配置的模型引入了径流系数（R _c）涵盖了历史流域的湿度，从而增加了将先前的湿度条件纳入预测的难度。