Water Resources Management

, Volume 33, Issue 10, pp 3377–3400 | Cite as

Spatial Assessment of Climate Risk for Investigating Climate Adaptation Strategies by Evaluating Spatial-Temporal Variability of Extreme Precipitation

  • Bing-Chen JhongEmail author
  • Jung Huang
  • Ching-Pin Tung


In response to the impacts of extreme precipitation on human or natural systems under climate change, the development of climate risk assessment approach is a crucial task. In this paper, a novel risk assessing approach based on a climate risk assessment framework with copula-based approaches is proposed. Firstly, extreme precipitation indices (EPIs) and their marginal distributions are estimated for historical and future periods. Next, the joint probability distributions of extreme precipitation are constructed by copula methods and tested by goodness-of-fit indices. The future joint probabilities and joint return periods (JRPs) of the EPIs are then evaluated. Finally, change rates of JRPs for future periods are estimated to assess climate risk with the quantitative data of exposure and vulnerability of a protected target. An actual application in Taiwan Island is successfully conducted for climate risk assessment with the impacts of extreme precipitation. The results indicate that most of regions in Taiwan Island might have higher potential climate risk under different scenarios in the future. The future joint probabilities of precipitation extremes might cause the high risk of landslide and flood disasters in the mountainous area, and of inundation in the plain area. In sum, the proposed climate risk assessing approach is expected to be useful for assisting decision makers to draft adaptation strategies and face high risk of the possible occurrence of natural disasters.


Climate change Spatial assessment Climate risk Adaptation strategy Precipitation extremes Joint probability distribution Copula function 



The authors are grateful to the Taiwan Climate Change Projection and Information Platform Project (TCCIP) funded by Ministry of Science and Technology (MOST) providing the projections of general circulation models with the climate scenarios and revised by the method of bias correction and spatial disaggregation. The authors would also like to appreciate all colleagues and students from Sustainable Development Laboratory (SDLab) in the Department of Bioenvironmental Systems Engineering, who contributed to this study.

Compliance with Ethical Standards

Conflict of Interest


Supplementary material

11269_2019_2306_MOESM1_ESM.docx (285 kb)
ESM 1 (DOCX 285 kb)


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Civil and Earth Resources Engineering, Graduate School of EngineeringKyoto UniversityKyotoJapan
  2. 2.Department of Bioenvironmental Systems EngineeringNational Taiwan UniversityTaipeiTaiwan

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