Estimation of areal reduction factors using a mixed gamma distribution

Chulsang Yoo; Kyoungjun Kim; Hung S. Kim; Moo J. Park

doi:10.1016/j.jhydrol.2006.11.026

Estimation of areal reduction factors using a mixed gamma distribution

Chulsang Yoo, Kyoungjun Kim, Hung S. Kim, Moo J. Park

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

Abstract

This study proposes a methodology to estimate the areal reduction factor (ARF) using mixed probability density functions. In practice, ARFs are estimated by using contemporaneous rainfall data from a high density rain gauge network over the basin, which are rarely available. The methodology proposed in this study uses all rainfall data available, whether or not they are concurrent with others. A mixed probability density function is introduced to explain both the rainfall intermittency and variability, and is applied to both point rainfall and areal average rainfall, which are compared to estimate the ARFs. In this study, a mixed gamma distribution was applied for the Geum river basin, Korea, to estimate the ARFs of a one-day (or, 24 h) rainfall as an example. The new method was easier to apply and provided similar results with those of other studies.

Original language	English
Pages (from-to)	271-284
Number of pages	14
Journal	Journal of Hydrology
Volume	335
Issue number	3-4
DOIs	https://doi.org/10.1016/j.jhydrol.2006.11.026
Publication status	Published - 2007 Mar 15

Bibliographical note

Funding Information:
This work was supported by a grant (R01-2003-000-10046-0) from the Basic Research Program of the Korea Science and Engineering Foundation. This contribution is gratefully acknowledged.

Keywords

Areal reduction factor
Mixed gamma distribution
Rainfall

ASJC Scopus subject areas

Water Science and Technology

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10.1016/j.jhydrol.2006.11.026

Cite this

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title = "Estimation of areal reduction factors using a mixed gamma distribution",

abstract = "This study proposes a methodology to estimate the areal reduction factor (ARF) using mixed probability density functions. In practice, ARFs are estimated by using contemporaneous rainfall data from a high density rain gauge network over the basin, which are rarely available. The methodology proposed in this study uses all rainfall data available, whether or not they are concurrent with others. A mixed probability density function is introduced to explain both the rainfall intermittency and variability, and is applied to both point rainfall and areal average rainfall, which are compared to estimate the ARFs. In this study, a mixed gamma distribution was applied for the Geum river basin, Korea, to estimate the ARFs of a one-day (or, 24 h) rainfall as an example. The new method was easier to apply and provided similar results with those of other studies.",

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note = "Funding Information: This work was supported by a grant (R01-2003-000-10046-0) from the Basic Research Program of the Korea Science and Engineering Foundation. This contribution is gratefully acknowledged. ",

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AU - Yoo, Chulsang

AU - Kim, Kyoungjun

AU - Kim, Hung S.

AU - Park, Moo J.

N1 - Funding Information: This work was supported by a grant (R01-2003-000-10046-0) from the Basic Research Program of the Korea Science and Engineering Foundation. This contribution is gratefully acknowledged.

PY - 2007/3/15

Y1 - 2007/3/15

N2 - This study proposes a methodology to estimate the areal reduction factor (ARF) using mixed probability density functions. In practice, ARFs are estimated by using contemporaneous rainfall data from a high density rain gauge network over the basin, which are rarely available. The methodology proposed in this study uses all rainfall data available, whether or not they are concurrent with others. A mixed probability density function is introduced to explain both the rainfall intermittency and variability, and is applied to both point rainfall and areal average rainfall, which are compared to estimate the ARFs. In this study, a mixed gamma distribution was applied for the Geum river basin, Korea, to estimate the ARFs of a one-day (or, 24 h) rainfall as an example. The new method was easier to apply and provided similar results with those of other studies.

AB - This study proposes a methodology to estimate the areal reduction factor (ARF) using mixed probability density functions. In practice, ARFs are estimated by using contemporaneous rainfall data from a high density rain gauge network over the basin, which are rarely available. The methodology proposed in this study uses all rainfall data available, whether or not they are concurrent with others. A mixed probability density function is introduced to explain both the rainfall intermittency and variability, and is applied to both point rainfall and areal average rainfall, which are compared to estimate the ARFs. In this study, a mixed gamma distribution was applied for the Geum river basin, Korea, to estimate the ARFs of a one-day (or, 24 h) rainfall as an example. The new method was easier to apply and provided similar results with those of other studies.

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KW - Rainfall

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DO - 10.1016/j.jhydrol.2006.11.026

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SN - 0022-1694

VL - 335

SP - 271

EP - 284

JO - Journal of Hydrology

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IS - 3-4

ER -

Estimation of areal reduction factors using a mixed gamma distribution

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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