The Relationship between River Flow Regimes and Climate Indices of ENSO and IOD on Code River, Southern Indonesia

Predicting the streamflow regimes using climate dynamics is important in water resource management. However, Indonesia, there are few studies targeting indices and streamflow. A previous study found difficulty developing a statistical prediction model for this relationship due to its non-linear nature. This attempted address that gap by applying multiple regression (MR) models second- third-order polynomial functions show between flow regime indices. First, correlation analysis was performed check variable relationships. There good significant of El Niño Southern Oscillation (ENSO) with Secondly, MR were developed same-time variables. The showed Indian Ocean Dipole (IOD) had effect strongly increasing high La Niña phases. Finally, time-lagged MRs aiming at forecasting. Lagged six-month leading demonstrated relatively observed data (mostly R > 0.700) moderate accuracy (root mean square error = 44–51%). It suggests forecasting may be possible ENSO IOD