Optimization of feature inputs in machine learning-based multi-source precipitation merging

doi:10.1016/j.jhydrol.2025.134185

Optimization of feature inputs in machine learning-based multi-source precipitation merging

2025-09-02

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DOI：10.1016/j.jhydrol.2025.134185

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• Gauge data dependence leads to overestimated spatial merging performance. • The importance of machine learning predictors shows notable regional variability. • Simpler features combinations outperform complex ones at low gauge density.

Optimization of feature inputs in machine learning-based multi-source precipitation merging

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