Return Level Estimation in Spatial Extreme Value Modeling of Bali Sea Currents Velocity using The Smith and Brown-Resnick Max-Stable Process Approach

Authors

  • Nyoman Gede Trisna Sanjaya Departemen Aktuaria, Fakultas Sains dan Analitika Data, Institut Teknologi Sepuluh Nopember
  • Pratnya Paramitha Oktaviana Departemen Aktuaria, Fakultas Sains dan Analitika Data, Institut Teknologi Sepuluh Nopember
  • Galuh Oktavia Siswono Departemen Aktuaria, Fakultas Sains dan Analitika Data, Institut Teknologi Sepuluh Nopember

DOI:

https://doi.org/10.20956/j.v20i1.27436

Keywords:

Brown-Resnick Model, Max-Stable Process, Return Level, Sea Currents Velocity, Smith Model

Abstract

Bali is the world's second most popular tourist destination in 2023. One of the best tourisms is the beauty of its coasts. Even though it is the best tourism destination, it is not uncommon for disasters to occur in the coastal areas of Bali. One important factor in the occurrence of coastal disasters from waters such as tidal flooding and abrasion is ocean currents. Spatial analysis of sea currents velocity was carried out using the Smith and Brown-Resnick Max-Stable Process Approach. The purpose of this study was to determine parameter estimation and comparison of the results of Spatial Extreme Value modeling with the Smith and Brown-Resnick Max-Stable Process approach, and to determine the Return Level of Bali Sea current velocity for the same period after data testing with the best model. The data used is daily data for the period March 2, 2017 to December 30, 2020. Extreme data selection with Block Maxima uses 14 daily blocks, so there are 100 blocks for each water location. The proportion of training and testing data is 80:20. The training data follows the Generalized Extreme Value distribution and has no pattern trend (stationary). The results of the extremal coefficient measurements ranged from 1.18604 to 1.59485 indicating a fairly strong dependency between locations. The best trend surface model is a model that only has longitude coordinates on the location parameter and latitude on the scale parameter. The estimated value of the spatial parameters of the Smith model tends to be greater than that of the Brown-Resnick model. The Root Mean Square Error and Mean Absolute Percentage Error for the Smith model are 0.15503 and 7.75076%. Meanwhile, the Brown-Resnick model is 0.29576 and 14.12131%. Return Level values for the same period after data testing are classified as strong currents and are respectively 1.20586 m/s, 1.63592 m/s, 1.51322 m/s and 2.13233 m/s for Serangan, Gianyar, Nusa Dua, and Nusa Lembongan Waters. Information on estimated Return Levels is expected to be a consideration that can be used by related agencies such as the Coastal and Marine Resources Management Agency (BPSPL) and the Bali Province Regional Disaster Management Agency (BPBD) as a coastal disaster mitigation effort to make it more effective, efficient and on target.

 

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Published

2023-09-06

How to Cite

Sanjaya, N. G. T. ., Oktaviana, P. P. ., & Siswono, G. O. . (2023). Return Level Estimation in Spatial Extreme Value Modeling of Bali Sea Currents Velocity using The Smith and Brown-Resnick Max-Stable Process Approach. Jurnal Matematika, Statistika Dan Komputasi, 20(1), 116–135. https://doi.org/10.20956/j.v20i1.27436

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Research Articles