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Multivariate frequency analysis of urban rainfall characteristics using three-dimensional copulas.

Chenglin Liu1, Yuwen Zhou2, Jun Sui3

  • 1College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China and Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering, Beijing 100124, China; Guangzhou Municipal Engineering Design & Research Insitute, Guangzhou 510060, China.

Water Science and Technology : a Journal of the International Association on Water Pollution Research
|April 27, 2018
PubMed
Summary

Urban flooding is hard to monitor, but rainfall data is available. This study uses a copula method to analyze rainfall events, improving urban flood control and drainage planning.

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Area of Science:

  • Hydrology
  • Urban Planning
  • Statistical Analysis

Background:

  • Urban runoff is a primary driver of urban flooding, posing monitoring challenges.
  • Current methods use design rainfall depth as a proxy for runoff, lacking coordination and failing to capture rainfall variability.
  • Long-term continuous rainfall data offers a viable alternative for hydrological analysis.

Purpose of the Study:

  • To develop a multivariate frequency analysis for rainfall characteristics using a copula-based approach.
  • To address the limitations of using design rainfall depth as a sole proxy for urban runoff.
  • To provide a more accurate method for assessing urban rainstorm characteristics and informing flood control strategies.

Main Methods:

  • Utilized a long-term (1961-2012) rainfall dataset from Guangzhou, China.
  • Divided continuous rainfall data into individual events using the rainfall intensity method.
  • Employed a three-dimensional copula to analyze multivariate joint and conditional probability distributions of rainfall characteristics (DRD, TRD, PRD).

Main Results:

  • The copula-based method effectively analyzes multivariate rainfall characteristics.
  • This approach provides a more accurate reflection of urban rainstorm variability compared to traditional methods.
  • The study demonstrated the ease of implementation and effectiveness of the copula method.

Conclusions:

  • The copula-based multivariate frequency analysis offers a robust framework for understanding urban rainfall characteristics.
  • This methodology improves upon traditional approaches that use design rainfall depth as a proxy for runoff.
  • The findings provide a valuable scientific reference for enhancing urban flood control and drainage planning.