A Novel Intelligent Model for Monthly Streamflow Prediction Using Similarity-Derived Method

Accurate monthly streamflow prediction is crucial for effective flood mitigation and water resource management. The present study proposes an innovative similarity-derived model (SDM), developed based on the observation that similar patterns recur across different years under comparable hydrological climate conditions. applied to Lancang River Basin in China. performance compared with commonly used support vector machine (SVM) Mean methods. Evaluation measures such as RMSE, MAPE, NSE confirm SDM6 a reference period of six months achieves best performance, improving by 79.9 m3/s 6.07% 8.62% NSE, SVM 53.65 m3/s, 0.24%, 5.53%, respectively.