Innovative trend analysis of annual maximum precipitation in Gowa regency

Sanusi, Wahidah and Abdy, Muhammad and Sulaiman, Sulaiman (2021) Innovative trend analysis of annual maximum precipitation in Gowa regency. In: 2nd Workshop on Engineering, Education, Applied Sciences and Technology (WEAST) 2020 5 October 2020, Makassar, Indonesia, 5 Oktober 2020, Makassar.

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Official URL: https://iopscience.iop.org/article/10.1088/1742-65...

Abstract

Floods and drought are two events that can have a negative impact on human survival. In addition, the impact of these two events can also affect agriculture, fisheries, tourism, housing, transportation and others. Trend analysis is an analysis that can be used to identify extreme rainfall events such as floods and drought. The results of the trend analysis can be useful for water resource planning and management. Therefore, the aim of this study is to obtain an overview of the annual maximum precipitation trend in Gowa Regency. The study uses the daily precipitation data from the Sungguminasa and Bonto Sallang Stations of Gowa Regency for 31 years (1988 – 2018). The data was obtained from the Water Resources, Human Settlements, Spatial Planning and Development Office of South Sulawesi Province. The method used is the Mann-Kendall test, Theil-Sen approach, and innovative trend analysis. The results of a lag-one serial correlation test found that all stations are serially independent. Based on the MK method that both stations show negative trend, but significant only at Sungguminasa station at the 95% confidence level. The results of the ITA method show that all stations are significant negative trends at the 95% level. One of advantages of the ITA method is the ability to detect the significant hidden trends in time series.

Item Type: Conference or Workshop Item (Paper)
Subjects: FMIPA > Matematika
KARYA ILMIAH DOSEN
Universitas Negeri Makassar > KARYA ILMIAH DOSEN
Divisions: FAKULTAS MIPA
Depositing User: Dr. Muhammad Abdy
Date Deposited: 01 Jul 2021 12:57
Last Modified: 20 Jul 2021 14:40
URI: http://eprints.unm.ac.id/id/eprint/20636

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