Abstract: Sediments in freshwater rivers, lakes, and reservoirs serve not only as vital reservoirs for the long-term accumulation of pollutants and nutrients but also as key media for studying material cycles and ecosystem processes. Traditional sediment sampling methods are generally characterized by high disturbance, limited environmental adaptability, insufficient real-time monitoring capabilities, and high operational costs, making them inadequate for supporting high spatiotemporal resolution research in complex aquatic environments. In recent years, the introduction of unmanned platforms and in-situ sensing technologies has significantly enhanced sampling depth, data continuity, and timeliness. However, challenges remain in equipment costs, system operation complexity, and technical standardization. This paper systematically reviews the development of sediment sampling techniques in lakes and reservoirs, compares the technical characteristics and applicable scenarios of traditional and emerging methods, and explores the suitability of different technical approaches and critical aspects of sample preservation based on specific application needs such as pollution source tracing and paleoenvironmental inversion. Based on this analysis, it proposes that future sediment sampling and analysis technologies should evolve toward integration, precision, and intelligence. Breakthroughs are urgently needed in enhancing environmental adaptability, improving quality control systems, and achieving low-cost, widespread adoption to more effectively serve water environment monitoring and ecological restoration practices.