The development of advanced computational models for improving the accuracy streamflow forecasting could save time and cost sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), Rotation Forest (RF) ensemble techniques in Jhelum Catchment, Pakistan. To build m...

Abstract. Streamflow drought forecasting is a key element of contemporary early warning systems (DEWS). The term streamflow (not forecasting), however, has created confusion within the scientific hydrometeorological community as well in operational weather and water management services. requires an additional step, which application identification method to forecasted time series. way identifie...

1. Adib M.N.M., Harun S., 2022, Metalearning approach coupled with CMIP6 multi-GCM for future monthly streamflow forecasting, Journal of Hydrologic Engineering, 27 (6), DOI: 10.1061/(ASCE)HE.1943-5584.0002176. CrossRef Google Scholar

The quality of precipitation forecasts from four Numerical Weather Prediction (NWP) models is evaluated over the Ovens catchment in Southeast Australia. Precipitation forecasts are compared with observed precipitation at point and catchment scales and at different temporal resolutions. The four models evaluated are the Australian Community Climate Earth-System Simulator (ACCESS) including ACCES...