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L-Moment-Based Regional Frequency Analysis of Annual Extreme Precipitation and its Uncertainty Analysis

Author

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  • Yuyin Liang

    (Tongji University)

  • Shuguang Liu

    (Tongji University)

  • Yiping Guo

    (McMaster University)

  • Hong Hua

    (Tongji University)

Abstract

Estimation of precipitation amounts associated with different return periods is an important task for the planning and design of many types of infrastructures. In this study, regional frequency analysis based on L-moments is proposed to estimate the annual maximum daily precipitation quantiles in the Taihu basin, China. The Generalized Extreme Value (GEV) distribution is used to describe the frequency distributions of extreme rainfall events. At-site frequency analysis results based on L-moments are compared with those obtained from regional analysis. The 95% confidence intervals of estimated precipitation quantiles are calculated using Monte Carlo simulations (MCS). Uncertainty assessment results indicate that regional analysis is more robust and more accurate than at-site analysis. Furthermore, when conducting regional frequency analysis, the estimation of precipitation quantile confidence intervals can be simplified by assuming normality for the MCS results. The variation of the precipitation quantiles’ sample statistics for different return periods is expressed as a function of the return period. The proposed methods are useful for the Taihu Basin and are recommended for other regions.

Suggested Citation

  • Yuyin Liang & Shuguang Liu & Yiping Guo & Hong Hua, 2017. "L-Moment-Based Regional Frequency Analysis of Annual Extreme Precipitation and its Uncertainty Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 3899-3919, September.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:12:d:10.1007_s11269-017-1715-5
    DOI: 10.1007/s11269-017-1715-5
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    References listed on IDEAS

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    Cited by:

    1. Samiran Das, 2020. "Assessing the Regional Concept with Sub-Sampling Approach to Identify Probability Distribution for at-Site Hydrological Frequency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 803-817, January.
    2. Qianyu Gao & Guofang Li & Jin Bao & Jian Wang, 2021. "Regional Frequency Analysis Based on Precipitation Regionalization Accounting for Temporal Variability and a Nonstationary Index Flood Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4435-4456, October.

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