Journal of Advanced Informatics in Water, Soil, and Structure

Journal of Advanced Informatics in Water, Soil, and Structure

Generation of Hourly Precipitation Time Series Incorporating Extreme Values Under Data Limitations

Document Type : Research Article

Authors
1 Department of Civil Engineering, Payame Noor University, Tehran, Iran
2 School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
Abstract
To simulate floods in small basins, precipitation data with fine temporal resolution is necessary. Especially in assessing the impact of climate change on flooding, it is essential to have a continuous precipitation series in short time steps that includes extreme values. However, precipitation data is often recorded daily, and long-term hourly precipitation series are usually unavailable. In such cases, generating long-term precipitation series with small time steps that incorporate extreme values becomes critical. This study proposes and validates a method for generating long-term 6-hour precipitation series when the available 6-hour series is short, but long-term daily precipitation series is available. The proposed method utilizes an empirical relationship between hourly and daily precipitation statistics over a short-term period to estimate long-term hourly precipitation statistics from long-term daily statistics. Then, using the generated hourly precipitation statistics and the Neyman-Scott Rectangular Pulse (NSRP) stochastic point process model, hourly precipitation series of any desired length can be produced. Using this approach, a long-term 6-hour precipitation series incorporating extreme values was generated and validated with high accuracy based on a 5-year 6-hour precipitation series and a 19-year daily precipitation series
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Volume 1, Issue 1 - Serial Number 1
January 2025
Pages 164-173

  • Receive Date 22 January 2025
  • Revise Date 29 April 2025
  • Accept Date 12 May 2025
  • First Publish Date 14 May 2025
  • Publish Date 18 May 2025