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Evaluating Future Joint Probability of Precipitation Extremes with a Copula-Based Assessing Approach in Climate Change

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Abstract

Changes in climate extremes may cause the variation of occurrence and intensity of floods and droughts. To investigate the future changes in joint probability behaviors of precipitation extremes for water resources management, an approach including three stages for analyzing the spatial variation of joint return periods of precipitation extremes is proposed in this paper. In the first stage, a weather generator model (WGM) was conducted with general circulation models (GCMs) under representative concentration pathway (RCP) scenarios to generate daily rainfall time series during 2021–2040 (S) and 2081–2100 (L) based on the statistics of the observed rainfall data. Four extreme precipitation indices are defined to represent extreme precipitation events. In the second stage, copula methods are adopted to establish the joint distribution of the precipitation extreme indices. The watershed-scale assessment of flood and drought applied in Shih-Men reservoir in northern Taiwan is conducted to demonstrate the possible change of joint return period. In the third stage, the change rates of joint return periods for bivariate extreme indices are demonstrated to present the occurrence possibility of floods or droughts in the future. The results indicate that floods and droughts might occur more frequently in the upstream region of the reservoir during the twenty-first century. The reservoir operations would be more important for water supply and flood mitigation. In conclusion, the possible changes of future joint probability of the precipitation extremes should be paid attention to for water resources management and draft plans to confront potential challenges in the future.

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Acknowledgements

The authors are grateful to the Taiwan Climate Change Projection and Information Platform Project (TCCIP) funded by Ministry of Science and Technology (MOST) for providing the projections of general circulation models based on climate scenarios and revised by the method of bias correction and spatial disaggregation.

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Authors and Affiliations

  1. Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, 10617, Taiwan

    Bing-Chen Jhong & Ching-Pin Tung

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  1. Bing-Chen Jhong
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  2. Ching-Pin Tung
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Correspondence to Bing-Chen Jhong.

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Jhong, BC., Tung, CP. Evaluating Future Joint Probability of Precipitation Extremes with a Copula-Based Assessing Approach in Climate Change. Water Resour Manage 32, 4253–4274 (2018). https://doi.org/10.1007/s11269-018-2045-y

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  • DOI: https://doi.org/10.1007/s11269-018-2045-y

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