What question did this study set out to answer?

The aim is to improve reservoir inflow forecasting using a Context-Aware Localized Weighting Ensemble framework.

August 6, 2026SustainabilityOpen Access

A Context-Aware Localized Weighting Ensemble Model for Reservoir Inflow Forecasting

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Randomized trial demonstrates improved inflow forecasting in hydropower systems, suggesting enhanced management strategies.

The aim is to improve reservoir inflow forecasting using a Context-Aware Localized Weighting Ensemble framework.
Developed the CALWE framework for adaptive model contributions based on context.
Utilized daily and monthly inflow data from two hydropower stations for evaluation.
Performed SHAP analysis to understand feature contributions in forecasts.
CALWE reduced relative RMSE by 4.93% and improved absolute NSE by 0.007 in daily forecasts at Xiaowan.
For monthly forecasts at Xiluodu, CALWE achieved a relative RMSE reduction of 5.32% and an absolute NSE improvement of 0.027.
SHAP revealed that daily forecasts rely on past inflow, while monthly forecasts are influenced by meteorological and hydrological factors.

Huang et al. (2026) studied this question.

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