A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments

Yanchen Zheng, Gemma Coxon, Ross Woods, Jianzhu Li*, Ping Feng

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

4 Citations (Scopus)

Abstract

The derived distribution method is a promising approach for flood estimation in ungauged catchments. In this approach, event runoff coefficient (ERC) is often adopted to behave as the runoff generation component since the behavior of ERC is closely related to flood generation mechanisms and its distribution reflects catchment climatological and landscape characteristics. However, there is a lack of understanding of how to transfer the information on ERC characteristics from gauged to ungauged catchments at catchment scale. Hence, here, we propose a generalized framework to estimate the probability distribution of ERC for ungauged catchments based on knowledge of the spatial and temporal controls on ERC from gauged catchments. Key components of the framework include cluster analysis based on ERC characteristics, linking clusters with catchment attributes, and constructing typical probability distribution of ERC conditioned on its temporal indicators. A total of 290,743 rainfall-runoff events observed in 431 GB catchments during the period 1990–2014 have been employed to verify the framework. Good estimations are obtained with the median value of coefficient of determination (R2) reaching 0.85 across all test catchments. The results indicate that similar pre-event catchment conditions may cause distinct runoff response in different catchments, thus predicting the correct spatial cluster is crucial to the estimation accuracy. This work sheds light on constructing a stochastic generator model of ERC according to its spatial pattern and temporal dynamic, facilitating a new alternative for flood estimation method in ungauged catchments.

Original languageEnglish
Article numbere2022WR033227
JournalWater Resources Research
Volume59
Issue number1
Early online date3 Jan 2023
DOIs
Publication statusPublished - Jan 2023

Bibliographical note

Funding Information:
This work was supported by a studentship funded by the China Scholarship Council (No. 202006250090) for Y. Zheng. Our great thanks go to Giulia Giani for helping us identifying rainfall‐runoff events. G. Coxon was supported by a UKRI Future Leaders Fellowship Award [MR/V022857/1]. P. Feng was funded by the National Natural Science Foundation of China (Grant 52079086).

Publisher Copyright:
© 2022. The Authors.

Research Groups and Themes

  • Water and Environmental Engineering

Keywords

  • catchment attributes
  • event runoff coefficient
  • flood estimation
  • probability distribution
  • regionalization
  • ungauged catchments

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