Historical hydrometric context and explainable multi-horizon evaluation of a GloFAS-derived discharge product near Babahoyo, Ecuador

Open global hydrological products are often the only continuous source available for data-scarce locations, but their local use is stronger when the modelled signal is connected to documented hydrometric evidence. This study evaluates an explainable machine-learning workflow for anticipating the Glo...

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Autores principales:	Alexander Haro-Sarango, Silvia Cachay-Salcedo, Jessica Karina Saavedra-Vasconez, Rosa Salcedo-Dávalos, Elizabeth Proaño-Altamirano
Formato:	Artículo
Lenguaje:	inglés
Publicado:	2026
Materias:	GloFAS river discharge prediction explainable machine learning SHAP permutation importance backtesting data-scarce regions Babahoyo lead time Hydrological Forecasting Using AI Hydrology and Watershed Management Studies Environmental Monitoring and Data Management
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