A dynamic prediction model for time-to-peak |
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| Authors: | Mistaya Langridge Ed McBean Hossein Bonakdari Bahram Gharabaghi |
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| Institution: | 1. School of Engineering, University of Guelph, Guelph, Ontario, Canada;2. Department of Soils and Agri-Food Engineering, Laval University, Québec, Canada |
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| Abstract: | 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 (Rc) to encompass historical catchment wetness, increasing the ease of incorporating antecedent moisture condition into predictions. |
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| Keywords: | catchment response time peak flow runoff coefficient soil moisture time-to-peak water resources |
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