Prediction of Typhoon-Induced Flood Flows at Ungauged Catchments Using Simple Regression and Generalized Estimating Equation Approaches

Hyosang Lee,Joungyoun Kim,Sunggu Kim,Neil Mcintyre,Hojin Lee

doi:10.3390/w10050647

Hyosang Lee, Joungyoun Kim + Show 3 more

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https://doi.org/10.3390/w10050647

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Journal: Water	Publication Date: May 16, 2018
Citations: 4	License type: CC BY 4.0

Affiliation: Chungbuk National University, University of Queensland

Abstract

Typhoons are the main type of natural disaster in Korea, and accurately predicting typhoon-induced flood flows at gauged and ungauged locations remains an important challenge. Flood flows caused by six typhoons since 2002 (typhoons Rusa, Maemi, Nari, Dienmu, Kompasu and Bolaven) are modeled at the outlets of 24 Geum River catchments using the Probability Distributed Moisture model. The Monte Carlo Analysis Toolbox is applied with the Nash Sutcliffe Efficiency as the criterion for model parameter estimation. Linear regression relationships between the parameters of the Probability Distributed Moisture model and catchment characteristics are developed for the purpose of generalizing the parameter estimates to ungauged locations. These generalized parameter estimates are tested in terms of ability to predict the flood hydrographs over the 24 catchments using a leave-one-out validation approach. We then test the hypothesis that a more complex generalization approach, the Generalized Estimating Equation, which includes properties of the typhoons as well as catchment characteristics as predictors of PDM model parameters, will provide more accurate predictions. The results show that the predictions of Generalized Estimating Equation are comparable to those of the simpler, conventional regression. The simpler approach is therefore recommended for practical applications; however, further refinements of the Generalized Estimating Equation approach may be explored.

Highlights

Typhoons are the main natural disaster in Korea
The aim of this study is to develop a method for prediction of typhoon-induced flood hydrographs for ungauged catchments, using a case study of six typhoon flood events in 24 Geum River catchments, Korea
Conventional regression and Generalized Estimating Equations (GEEs), are used to regionalize the Probability Distributed Moisture (PDM) model parameters, so that typhoon-induced flows can be simulated at ungauged locations within the same region

Summary

Introduction

Typhoons are the main natural disaster in Korea. The maximum annual flood peak historically is often caused by heavy rainfall in the wet season (“Changma”) as well as typhoons; since 2002, typhoons are perceived to have become the main source of flood risk, while the Changma has become less influential in Korea. Estimation of typhoon-induced flood hydrographs and associated flood peaks is considered to be increasingly important for engineering applications, such as design of civil engineering structures, stabilization of river banks and flood warning and management. Gauged flood hydrographs are not available for most of the medium to small-sized catchments in. The need to predict flows at locations where observed flows do not exist for model calibration and validation, i.e., the ungauged catchment problem, is common [3].

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