Hydropower development significantly impacts the fragile fish habitats in river reaches of the Tibetan Plateau. To support the conservation of fish resources in these reaches, this study developed a physical habitat evaluation model for spawning grounds based on the ecological requirements of key fish species. An artificial neural network (ANN) model was employed to fit the response relationships between spawning ground indicators and environmental factors. Results indicate that water temperature is a critical factor influencing spawning grounds. In natural river reaches, suitable spawning periods occur primarily in the afternoon. In contrast, water temperature in dam-downstream reaches is significantly affected by hydropower operations, leading to distinct differences in spawning rhythms compared to natural reaches. The Weighted Usable Area (WUA) and Patch Number (PN) of spawning grounds initially increase and then decrease with rising flow. The ANN model effectively fits the response relationships between environmental factors and WUA and PN (R2 > 0.87). Water temperature exhibits a stronger influence, while flow primarily affects WUA and PN by altering suitable substrate area. This study presents the development and application of physical and ANN models for fish spawning grounds in hydropower-affected river reaches of the Tibetan Plateau. The findings reveal the distribution patterns of spawning grounds and identify key environmental factors. These results provide methodological references and scientific evidence for the evaluation and conservation of fish resources, supporting the sustainable management of native fish populations in plateau rivers.