TY - JOUR
T1 - Spatial extreme modeling using student t copula approach in Ngawi Regency
AU - Fauziyah, M.
AU - Sutikno,
AU - Purnomo, J. D.T.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2020/6/19
Y1 - 2020/6/19
N2 - Extreme rainfall is an unpredictable phenomenon which causes suffering effect such as flooding. Located on the Equator area, Indonesia results in a high intensity of extreme rainfall. Initial information regarding the patterns, characteristics, and rainfall prediction is needed in order to minimize the negative effect of such phenomenon. A method that can be used to predict extreme rainfall is the spatial extreme value using the copula approach. The copula approach used in this study is student-T copula. The Generalized Extreme Value (GEV) distribution used for the student-T copula with parameter estimation is Pseudo-Maximum Likelihood Estimation (PMLE). The proposed method was applied to model the extreme rainfall atNgawi Regency. An extreme spatial dependency on location is shown by extreme coefficient graphic. The best model that is obtained is based on Akaike Information Criteriation's (AIC) lowest value. The best model then continues to be used to predict the rainfall intensity return level. The prediction result of the rainfall intensity return level value shows that the maximum value of rainfall intensity increases from year to year in each station.
AB - Extreme rainfall is an unpredictable phenomenon which causes suffering effect such as flooding. Located on the Equator area, Indonesia results in a high intensity of extreme rainfall. Initial information regarding the patterns, characteristics, and rainfall prediction is needed in order to minimize the negative effect of such phenomenon. A method that can be used to predict extreme rainfall is the spatial extreme value using the copula approach. The copula approach used in this study is student-T copula. The Generalized Extreme Value (GEV) distribution used for the student-T copula with parameter estimation is Pseudo-Maximum Likelihood Estimation (PMLE). The proposed method was applied to model the extreme rainfall atNgawi Regency. An extreme spatial dependency on location is shown by extreme coefficient graphic. The best model that is obtained is based on Akaike Information Criteriation's (AIC) lowest value. The best model then continues to be used to predict the rainfall intensity return level. The prediction result of the rainfall intensity return level value shows that the maximum value of rainfall intensity increases from year to year in each station.
UR - http://www.scopus.com/inward/record.url?scp=85088314684&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1538/1/012051
DO - 10.1088/1742-6596/1538/1/012051
M3 - Conference article
AN - SCOPUS:85088314684
SN - 1742-6588
VL - 1538
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012051
T2 - 3rd International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2019
Y2 - 26 October 2019 through 27 October 2019
ER -