Hill Publishing Group | contact@hillpublisher.com

Hill Publishing Group

Location:Home / Journals / Journal of Applied Mathematics and Computation /

DOI:http://dx.doi.org/10.26855/jamc.2022.03.006

Estimated Parameters of Rain Flow Distribution Using L-Moment Method in South Sulawesi, Indonesia

Date: February 23,2022 |Hits: 885 Download PDF How to cite this paper

Wahidah Sanusi1, Srie Chaerunnisa1, Suwardi Annas2, Syafruddin Side1,*, Muhammad Abdy1

1Department of Mathematics, Faculty of Mathematics and Natural Science, State University of Makassar (Universitas Negeri Makassar), Makassar, South Sulawesi, Indonesia.

2Department of Statistics, Faculty of Mathematics and Natural Science, State University of Makassar (Universitas Negeri Makassar), Makassar, South Sulawesi, Indonesia.

*Corresponding author: Syafruddin Side

Abstract

This research is an applied research which aims to determine the type of distribution of each district/city in South Sulawesi Province. The data used are secondary data belonging to the Water Resources Management Office (PSDA) from 58 rainfall stations with a span of 31 years (1988-2018). The L-Moment method is a method that defines the probability density function of a distribution with its first 4 characteristics. The four characteristics are L-location λ1, L-variability λ2, L-skewness τ3 dan L-curtosis τ4. Several types of distribution in this study are the distribution of Generalized Extreme Value (GEV), Generalized Logistics (GLo), Generalized Pareto (GPa), Lognormal III (LN3), Pareto type III (Pe3) and Gumbel. Determination of the best distribution based on 3 test indicators, namely the minimum value of Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) and the maximum value of the Correlation Coefficient (CC). The results obtained are Soppeng district have the GPa distribution; The results of this research can be utilized by the PSDA Service, Public Works Service, civil engineering sector, and researchers in the fields of hydrology, climatology and geography to plan irrigation development, prevention of future disasters or the need for science.

References

[1] Fauzi, M., Rinaldi, dan Handayani, F. Y. (2012). Selection of the type of frequency of maximum annual daily rain in the Akuaman River area, West Sumatra Province. Jurnal Sains dan Teknologi, Vol. 11, No. 1, 18-24.

[2] Annas, S., Arisandi, R. (2016). Rainfall Forecasting Using Bayesian Nonparametric Regression. Proceeding of 3th International Conferense on Research, Implementation and Education of Mathematics and Science. Yogyakarta.

[3] Sidehabi, S. W. dan Indrabayu. (2013). ANFIS for Daily Rainfall Prediction. Seminar Nasional Teknik Informatika (SNATIKA). ISBN: 978-602-8509-20-6.

[4] Annas, S., Arisandi, R. (2016). Improving the accuracy of rainfall forecasting using multivariate transfer function and resilient backpropagation neural network. AIP Conference Proceedings, 1885(1), 020184.

[5] Abdy, M., Syam, R., Haryanensi, E. (2018). Metode Automatic Clustering-Fuzzy Logical Relationships on Population Forecasting in Makassar City. Journal of Mathematics, Computations, and Statistics, Vol. 1. No. 2, 193-205.

[6] Annas, S., Kanai, T., Koyama, S. (2005). Neuro-fuzzy System for Modeling Rainfall in Indonesia. Proceeding of the International Conference on Research Highlights and Vanguard Technology on Environmental Engineering in Agricultural Systems. Kanazawa University, Japan, September 12-15, 2005, pp. 77-82.

[7] Annas, S., Kanai, T., Koyama, S. (2007). Assessing Daily Tropical Rainfall Variations Using a Neuro-fuzzy Classification Model. Ecological Informatics. Elsevier. Volume 2, Issue 2, 1 June 2007, Pages 159-166.

[8] Musadar, F., Zainuddin, Z., Baharuddin, M. (2012). Algorithm Implementation of Rain Precipitation Forecasting in Early Flood Disaster Detection System. Hasanuddin University Postgraduate. Makassar.

[9] Kysely, J. and Picek, J. (2007). Probability estimates of heavy precipitation events in a flood-prone central-European region with enhanced influence of Mediterranean cyclones. Advances in Geosciences, Vol. 12, 43-50.

[10] Bílková, D. (2014). Robust parameter estimations using L-Moments, TL-Moments and the order statistiks. American Journal of Applied Mathematics, Vol. 2, No. 2, 36-53.

[11] Sanusi, W., Abdy, M., Side, S. (2018). The use of the L-Moment method in modeling the maximum daily rainfall of Makassar City. Prosiding Seminal Nasional Lembaga Penelitian UNM. ISBN: 978-602-5554-71-1.

[12] Forestieri, A., Conti, F. L., Blenkinsop, S., Cannarozzo, M., Fowler, H. J., dan Noto, L. V. (2018). Regional frequency analysis of extreme rainfall in Sicily (Italia). Internasional Journal of Climatology, 2018, Publish online in wileyonlinelibrary.com.

[13] Sanusi, W., Mulbar, U., Jaya, H., Purnamawati dan Side, S. (2017). Modeling of rainfall characteristics monitoring of the extreme rainfall event in Makassar City. American Journal of Applied Sciences, Vol. 14, No. 4, 456-461.

[14] Rinaldi, A., Yulianur, A., Yulizar. (2018). Analysis of the frequency of extreme rainfall in Nagan Raya District using the L-Moment method. Konferensi Nasional Teknik Sipil 12. ISBN: 978-602-60286-1-7.

[15] Alahmadi, F. (2017). Regional rainfall frequency analysis by L-Moment approach for Madina region, Saudi Arabia. International journal of engineering research and development, Vol. 13, No. 7, 39-48.

[16] Sabri, A. dan Ariff, N. M. (2009). Frequency analysis of maximum dalily rainfalls via L-Moment approach. Sains Malaysiana, Vol. 38, No. 2, 149-158.

[17] BPS Provinsi Sulawesi Selatan. (2019). South Sulawesi Province in Numbers 2019. Catalog 1102001.73. ISSN/ISBN 0215-2290. (Accesses 30 September 2019).

How to cite this paper

Estimated Parameters of Rain Flow Distribution Using L-Moment Method in South Sulawesi, Indonesia

How to cite this paper: Wahidah Sanusi, Srie Chaerunnisa, Suwardi Annas, Syafruddin Side, Muhammad Abdy. (2022) Estimated Parameters of Rain Flow Distribution Using L-Moment Method in South Sulawesi, Indonesia. Journal of Applied Mathematics and Computation6(1), 30-40.

DOI: http://dx.doi.org/10.26855/jamc.2022.03.006

Volumes & Issues

Free HPG Newsletters

Add your e-mail address to receive free newsletters from Hill Publishing Group.

Contact us

Hill Publishing Group

8825 53rd Ave

Elmhurst, NY 11373, USA

E-mail: contact@hillpublisher.com

Copyright © 2019 Hill Publishing Group Inc. All Rights Reserved.