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Clustering Quantile Regression-Based Drought Trends in Taiwan

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  • Jenq-Tzong Shiau

    (National Cheng Kung University)

  • Jia-Wei Lin

    (National Cheng Kung University)

Abstract

Drought is a normal, recurring climatic feature and occurs in all climatic zones. Imbalanced water availability induced by droughts has far-reaching and adverse impacts both on human lives and natural environments. This study aims to summarize temporal and spatial drought variations in Taiwan by combining quantile regression and cluster analysis. Three-monthly rainfall series covering the 1947–2012 period for 12 rainfall stations are used in this study. Quantile regression is applied to 3-month SPI, drought duration, drought severity, and drought frequency series for exploring temporal drought trends at different quantiles. Various quantile slopes for these 12 stations are then analyzed by hierarchical agglomerative clustering algorithm to detect regional variation patterns. The results show considerable spatial diversity over Taiwan. Stations along east coast are prone to more severity due to declined SPI trends associated with increasing drought duration and severity. Positive SPI slope associated with decreasing drought duration and severity are noted at stations located in the west and lead to lessened droughts. However, temporal variations in drought-duration and drought-severity series are insignificant at most quantiles and stations. In addition, a distinct behavior is found in drought frequency since severe droughts may not accompany frequent droughts.

Suggested Citation

  • Jenq-Tzong Shiau & Jia-Wei Lin, 2016. "Clustering Quantile Regression-Based Drought Trends in Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1053-1069, February.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:3:d:10.1007_s11269-015-1210-9
    DOI: 10.1007/s11269-015-1210-9
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    Cited by:

    1. Jenq-Tzong Shiau, 2020. "Effects of Gamma-Distribution Variations on SPI-Based Stationary and Nonstationary Drought Analyses," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 2081-2095, April.
    2. Wilson Kalisa & Tertsea Igbawua & Fanan Ujoh & Igbalumun S. Aondoakaa & Jean Nepomuscene Namugize & Jiahua Zhang, 2021. "Spatio-temporal variability of dry and wet conditions over East Africa from 1982 to 2015 using quantile regression model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 2047-2076, April.
    3. Israel R. Orimoloye & Adeyemi O. Olusola & Johanes A. Belle & Chaitanya B. Pande & Olusola O. Ololade, 2022. "Drought disaster monitoring and land use dynamics: identification of drought drivers using regression-based algorithms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(2), pages 1085-1106, June.

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