{"title":"洪水预警系统中南苏拉威西省极端降雨数据的时空模型","authors":"B. Bakri, Khaeryna Adam, Amran Rahim","doi":"10.7494/GEOM.2021.15.2.5","DOIUrl":null,"url":null,"abstract":"In this study, we model extreme rainfall to study the high rainfall events in the province of South Sulawesi, Indonesia. We investigated the effect of the El Nino South Oscillation (ENSO), Indian Ocean Dipole Mode (IOD), and Mad‐ den–Julian Oscillation (MJO) on extreme rainfall events. We also assume that events in a location are affected by events in other nearby locations. Using rain‐ fall data from the province of South Sulawesi, the results showed that extreme rainfall events are related to IOD and MJO.","PeriodicalId":36672,"journal":{"name":"Geomatics and Environmental Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Spatio‑Temporal Model of Extreme Rainfall Data in the Province of South Sulawesi for a Flood Early Warning System\",\"authors\":\"B. Bakri, Khaeryna Adam, Amran Rahim\",\"doi\":\"10.7494/GEOM.2021.15.2.5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, we model extreme rainfall to study the high rainfall events in the province of South Sulawesi, Indonesia. We investigated the effect of the El Nino South Oscillation (ENSO), Indian Ocean Dipole Mode (IOD), and Mad‐ den–Julian Oscillation (MJO) on extreme rainfall events. We also assume that events in a location are affected by events in other nearby locations. Using rain‐ fall data from the province of South Sulawesi, the results showed that extreme rainfall events are related to IOD and MJO.\",\"PeriodicalId\":36672,\"journal\":{\"name\":\"Geomatics and Environmental Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geomatics and Environmental Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7494/GEOM.2021.15.2.5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geomatics and Environmental Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7494/GEOM.2021.15.2.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
Spatio‑Temporal Model of Extreme Rainfall Data in the Province of South Sulawesi for a Flood Early Warning System
In this study, we model extreme rainfall to study the high rainfall events in the province of South Sulawesi, Indonesia. We investigated the effect of the El Nino South Oscillation (ENSO), Indian Ocean Dipole Mode (IOD), and Mad‐ den–Julian Oscillation (MJO) on extreme rainfall events. We also assume that events in a location are affected by events in other nearby locations. Using rain‐ fall data from the province of South Sulawesi, the results showed that extreme rainfall events are related to IOD and MJO.
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