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    Machine Learning Models for Prediction of Shade-Affected Stream Temperatures 

    Source: Journal of Hydrologic Engineering:;2025:;Volume ( 030 ):;issue: 001:;page 04024058-1
    Author(s): Efrain Noa-Yarasca; Meghna Babbar-Sebens; Chris E. Jordan
    Publisher: American Society of Civil Engineers
    Abstract: This study evaluates the selection of predictor variables for machine learning (ML) models of stream temperatures affected by riparian shading. Two scenarios of model development were examined—ML models for the prediction ...
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