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Precise streamflow prediction is necessary for better planning and managing available water and future water resources, especially for high altitude mountainous glacier melting affected basins in the climate change context. In the current study, a novel hybridized machine learning method, extended marine predators algorithm (EMPA)-based ANN (ANN-EMPA), is developed for streamflow estimation in the Upper Indus Basin, a key mountainous glacier melt affected basin of Pakistan. The prediction accuracy of the novel metaheuristic algorithm (EMPA) was also compared with several benchmark metaheuristic algorithms, including the marine predators algorithm (MPA), particle swarm optimization (PSO), genetic algorithm (GA), and grey wolf optimization (GWO). The results revealed that the newly developed hybridized ANN-EMPA outperformed the other hybrid ANN methods in streamflow prediction. ANN-EMPA …