Trend Analysis of Hydroclimatic Variables in the Kamo River Basin, Japan

HANDLE Open Access
  • Hu, Maochuan
    Disaster Prevention Research Institute, Kyoto University
  • Sayama, Takahiro
    Disaster Prevention Research Institute, Kyoto University
  • TRY, Sophal
    Graduate School of Engineering, Kyoto University・Faculty of Hydrology and Water Resources Engineering, Institute of Technology of Cambodia
  • Takara, Kaoru
    Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University
  • Tanaka, Kenji
    Disaster Prevention Research Institute, Kyoto University

Abstract

Understanding long-term trends in hydrological and climatic variables is of high significance for sustainable water resource management. This study focuses on the annual and seasonal trends in precipitation, temperature, potential evapotranspiration, and river discharge over the Kamo River basin from the hydrological years 1962 to 2017. Homogeneity was examined by Levene’s test. The Mann–Kendall and a modified Mann–Kendall test as well as Sen’s slope estimator were used to analyze significant trends (p < 0.05) in a time series with and without serial correlation and their magnitudes. The results indicate that potential evapotranspiration calculated by the Penman–Monteith equation was highly related to temperature, and significantly increased in the annual and summer series. Annual river discharge significantly decreased by 0.09 m3/s. No significant trend was found at the seasonal scale. Annual, autumn, and winter precipitation at Kumogahata station significantly increased, while no significant trend was found at Kyoto station. Precipitation was least affected by the modified Mann–Kendall test. Other variables were relatively highly autocorrelated. The modified Mann–Kendall test with a full autocorrelation structure improved the accuracy of trend analysis. Furthermore, this study provides information for decision makers to take proactive measures for sustainable water management.

Journal

  • Water

    Water 11 (9), 2019-08-27

    MDPI AG

Details 詳細情報について

  • CRID
    1050848249740789760
  • NII Article ID
    120006861123
  • ISSN
    20734441
  • HANDLE
    2433/251425
  • Text Lang
    en
  • Article Type
    journal article
  • Data Source
    • IRDB
    • CiNii Articles

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