A multi-model integration method for monthly streamflow prediction: modified stacking ensemble strategy

• Published in: Journal of hydroinformatics Vol. 22; no. 2; pp. 310 - 326
• Main Authors: Li, Yujie, Liang, Zhongmin, Hu, Yiming, Li, Binquan, Xu, Bin, Wang, Dong
• Format: Journal Article
• Language: English
• Published: London IWA Publishing 01.03.2020
• Subjects: Access; Canyons; Climate prediction; Computer applications; Forecasting; Hydrology; Integration; Learning algorithms; Machine learning; Mathematical models; Methods; Monthly; Precipitation; River basins; Rivers; Simulation; Stacking; Stream discharge; Stream flow; Streamflow forecasting; Support vector machines; Training

In this study, we evaluate elastic net regression (ENR), support vector regression (SVR), random forest (RF) and eXtreme Gradient Boosting (XGB) models and propose a modified multi-model integration method named a modified stacking ensemble strategy (MSES) for monthly streamflow forecasting. We appl...