Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia

Research Article

Joint Modeling of Wet Condition Characteristics of Makassar City

Download408 downloads
  • @INPROCEEDINGS{10.4108/eai.12-10-2019.2296438,
        author={Wahidah  Sanusi and Sahlan  Sidjara and Sudarmin  Sudarmin and Muhammad  Abdy},
        title={Joint Modeling of Wet Condition Characteristics of Makassar City},
        proceedings={Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia},
        publisher={EAI},
        proceedings_a={MSCEIS},
        year={2020},
        month={7},
        keywords={bivariate distributions copula wet duration wet severity},
        doi={10.4108/eai.12-10-2019.2296438}
    }
    
  • Wahidah Sanusi
    Sahlan Sidjara
    Sudarmin Sudarmin
    Muhammad Abdy
    Year: 2020
    Joint Modeling of Wet Condition Characteristics of Makassar City
    MSCEIS
    EAI
    DOI: 10.4108/eai.12-10-2019.2296438
Wahidah Sanusi1,*, Sahlan Sidjara1, Sudarmin Sudarmin2, Muhammad Abdy1
  • 1: Department of Mathematics, Universitas Negeri Makassar, Parangtambung, Makassar, 90224, Indonesia
  • 2: Department of Statistics, Universitas Negeri Makassar, Parangtambung, Makassar, 90224, Indonesia
*Contact email: wahidah.sanusi@unm.ac.id

Abstract

A multivariate analysis of rainfall variables is needed to understand relationships among characteristics of rainfall variables. The monthly rainfall amount of records from three stations during the period of 1985-2014 in Makassar is used. The Standardized Precipitation Index (SPI) is employed to classify data into the wet category. The study aims are to investigate the most appropriate joint distribution function of wet duration and wet severity based on bivariate Archimedean copulas. The copulas are Gumbel-Hougaard, Frank, Joe, and Clayton. Parameter of copulas is estimated by Kendall’s tau correlation coefficient. The study result shows that the Frank copula was identified as the best copula in joint modeling between wet duration and wet severity at Meteorologi Maritim Paotere (MMP) and Biring Romang Panakkukang (BRP) stations, meanwhile the Gumbel-Hougaard copula at Balai Besar Meteorologi, Klimatologi, and Geofisika (BBMKG) station. This result could be useful information for determining return periods of wet condition characteristics.