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

中文翻译：

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印度尼西亚南部Code River河水流状况与ENSO和IOD气候指数的关系

利用气候动力学预测河流流态在水资源管理中很重要。但是，在印度尼西亚，针对气候指数和流量的研究很少。先前的研究发现，由于这种关系的非线性性质，很难为这种关系建立统计预测模型。这项研究试图通过应用使用二阶和三阶多项式函数的多元回归（MR）模型来显示气候和流态指数之间的非线性关系，从而解决这一差距。首先，进行相关分析以检查变量关系。厄尔尼诺南方涛动（ENSO）与流态指数之间存在良好且显着的相关性。其次，开发了具有相同时间变量的MR模型。发达的模型表明，印度洋偶极子（IOD）具有极大地增加拉尼娜相中高流量的作用。最后，开发了时滞MR，以进行预测。具有六个月领先气候指数的滞后MR模型与观察到的数据具有相对较好的相关性（主要是R > 0.700），精度中等（均方根误差= 44–51％）。这表明使用ENSO和IOD指数可能对流态进行预测。