Machine-learning optimized wavelet framework for multi-scale streamflow forecasting to enhance water-resource management

doi:10.1016/j.ecoinf.2025.103480

Machine-learning optimized wavelet framework for multi-scale streamflow forecasting to enhance water-resource management

2025-10-23

0

OA

AI

Y

Yulia Gorodetskaya

R

Rodrigo Oliveira Silva

Celso Bandeira de Melo Ribeiro

L

Leonardo Goliatt

DOI：10.1016/j.ecoinf.2025.103480

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• AutoML with wavelet and Differential Evolution used for streamflow prediction. • Models tested on hourly, daily, and monthly river flow data. • The proposed approach delivers strong predictive skill without manual tuning. • Method uses real-world datasets from hydrology case studies. • DE fine-tunes model selection and configuration steps producing accurate predictions.

Keywords:

Streamflow forecasting

Wavelet transform

Differential evolution

Metaheuristic optimization

Multi-scale forecasting

AutoML

Machine-learning optimized wavelet framework for multi-scale streamflow forecasting to enhance water-resource management

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