Abstract: 　　Similarity of geomorphic physical modeling serves as a fundamental principle for applying laboratory experiments to understand the interactions among tectonics, climate, and surface processes. This paper reviews the research progress on similarity in analog modeling, focusing on the comparison between experimental landforms and their natural counterparts. We synthesize previous work that evaluates model similarity through various geomorphic parameters, including drainage basin morphology (self-similarity, Hack’s law, hypsometric integral), channel characteristics (sinuosity, spacing ratio), slope-area relationships, and knickpoint migration dynamics. Studies demonstrate that, despite significant scaling differences in geometry, materials, and dynamics, well-designed physical models can replicate key structural features and evolutionary patterns observed in natural tectonic landscapes. However, similarity validation remains constrained by factors such as the physical properties of analog materials, simplified erosion mechanisms, and model boundary conditions. Future advances require the integration of high-resolution monitoring, multi-process coupling, and numerical model validation to enhance the similarity and predictive power of physical experiments. This will enable their broader and more quantitative application in interpreting tectonic activity, climate forcing, and landscape response.
　　Similarity of geomorphic physical modeling serves as a fundamental principle for applying laboratory experiments to understand the interactions among tectonics, climate, and surface processes. This paper reviews the research progress on similarity in analog modeling, focusing on the comparison between experimental landforms and their natural counterparts. We synthesize previous work that evaluates model similarity through various geomorphic parameters, including drainage basin morphology (self-similarity, Hack’s law, hypsometric integral), channel characteristics (sinuosity, spacing ratio), slope-area relationships, and knickpoint migration dynamics. Studies demonstrate that, despite significant scaling differences in geometry, materials, and dynamics, well-designed physical models can replicate key structural features and evolutionary patterns observed in natural tectonic landscapes. However, similarity validation remains constrained by factors such as the physical properties of analog materials, simplified erosion mechanisms, and model boundary conditions. Future advances require the integration of high-resolution monitoring, multi-process coupling, and numerical model validation to enhance the similarity and predictive power of physical experiments. This will enable their broader and more quantitative application in interpreting tectonic activity, climate forcing, and landscape response.