Experimental study of rainfall spatial variability effect on peak flow variability using a data generation method

Shin, Mun-Ju

doi:10.3741/jkwra.2017.50.6.359

J. Korea Water Resour. Assoc

2017

DOI: 10.3741/jkwra.2017.50.6.359

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Experimental study of rainfall spatial variability effect on peak flow variability using a data generation method

Mun-Ju Shin¹

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2019

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Estimating Regional Maximum Floods using a Runoff Data Spatial Extension Method in Ungauged Watersheds

Kim¹,

Jung²

2019

J. Korean Soc. Hazard Mitig

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In this study, regional maximum floods for ungauged watersheds at the Choongju dam (CJD) were estimated using flood runoff data generated in storage function method (SFM) applications. The CJD watersheds were divided into smaller watersheds to generate runoff data for ungauged watersheds. The SFM optimized saturated rainfall (R sa) while keeping other parameters (k, p, Tl, and f 1) constant. Possible flood occurrences were estimated based on estimated runoff data and by analyzing the correlation between specific mean flooding events and regional maximum floods (Q RMF) at the CJD. Results show that, in terms of being able to estimate runoff data for CJD watersheds, the spatial extension method based on an SFM was suitable for estimating possible regional flood occurrences (NSE > 0.5). Furthermore, there are strong correlations between flood events and Q RMF (Pearson's r > 0.9); can be used to estimate regional maximum floods in the CJD watersheds.

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Estimating Regional Maximum Floods using a Runoff Data Spatial Extension Method in Ungauged Watersheds

Kim¹,

Jung²

2019

J. Korean Soc. Hazard Mitig

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show abstract

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Experimental study of rainfall spatial variability effect on peak flow variability using a data generation method

Cited by 1 publication

References 24 publications

Estimating Regional Maximum Floods using a Runoff Data Spatial Extension Method in Ungauged Watersheds

Estimating Regional Maximum Floods using a Runoff Data Spatial Extension Method in Ungauged Watersheds

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