Spatiotemporal Analysis on the Teleconnection of ENSO and IOD to the Stream Flow Regimes in Java, Indonesia

While many studies on the relationship between climate modes and rainfall in Indonesia already exist, studies targeting climate modes' relationship to streamflow remain rare. This study applied multiple regression (MR) models with polynomial functions to show the teleconnection from the two prominent climate modes-El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD)-to streamflow regimes in eight rivers in Java, Indonesia. Our MR models using data from 1970 to 2018 successfully show that the September-November (SON) season provides the best predictability of the streamflow regimes. It is also found that the predictability in 1970-1989 was better than that in 1999-2018. This suggests that the relationships between the climate modes and streamflow in Java were changed over periods, which is suspected due to the river basin development. Hence, we found no clear spatial distribution patterns of the predictability, suggesting that the effect of ENSO and IOD are similar for the eight rivers. Additionally, the predictability of the high flow index has been found higher than the low flow index. Having elucidated the flow regimes' predictability by spatiotemporal analysis, this study gives new insight into the teleconnection of ENSO and IOD to the Indonesian streamflow.