ABSTRACTStream temperature is widely considered the master variable in stream ecosystems. One of the key drivers of diel and seasonal stream temperature variability is the solar radiation received at the stream surface, which can be influenced by shading associated with both larger scale topographic features and riparian vegetation. In this study, a stream shade model was developed that uses LiDAR point cloud data to model shading by riparian vegetation, including canopy overhang, and conventional elevation data to model stream shading by topography. The model was applied to a dominantly north–south oriented river flowing in a floodplain within a mountain valley. When compared with shade interpreted from PlanetScope visual imagery, the model predicted stream shade at the point scale with 92% agreement. Sources of error were attributed to pixel and azimuth band size, which can be refined within the model arguments, although at the cost of increased processing time. The shade model was re‐run after virtually rotating the reach by 90° and 270° clockwise to evaluate the effect of valley orientation. Peak reach‐wide sunlight exposure occurred approximately 2 h later in the day when the stream reach was rotated 90°, and produced greater shading from mid‐morning to mid‐afternoon. Further work should test the model on smaller streams using ground‐based oblique or drone‐based photography to provide ground‐truthing, particularly to assess the accuracy of predicted shade below over‐hanging vegetation.