# A 3D Two-Phase Landslide Dynamical Model on GIS Platform
## 5 Discussion  
At present, the mainstream models for landslide numerical simulations on GIS platforms are two-dimensional models based on the depth-averaged theory. This model simplifies the complex fluid motion in the \(Z\)-direction through depth integration, enabling fast computation. Due to its simplicity and relatively low computational requirements, this model has gained widespread application worldwide. However, its success is limited to predicting the depth, average velocity, and distribution range of the fluid. This model cannot predict the velocity variations along the flow depth direction; it can only derive internal pressure through depth-averaged velocity and cannot obtain complete dynamic pressure and internal pressure profiles. The model fails to capture phenomena such as laminar flow, turbulence, and surges during the fluid motion process. At the same time, in areas where the landslide initiates motion, where it eventually deposits, and where significant terrain changes occur, the assumptions of shallow mass flow are no longer met. The reliability of the depth-averaged model will significantly decrease in such regions. In order to provide a comprehensive physical description of the entire process of landslide motion and enhance our understanding of the phenomenon, a three-dimensional landslide dynamics model that takes into account the influence of complex terrain is required. Therefore, we propose an alternative solution: constructing a three-dimensional landslide dynamics model on the GIS platforms. This study's three-dimensional model assumes the landslide to be an incompressible Newtonian fluid. The model employs methods such as the VOF method to achieve the three-dimensional solution of the Navier-Stokes equations. In comparison to the two-dimensional depth-averaged model, this model is constructed based on the three-dimensional geometry of the landslide. Therefore, it can provide a more realistic representation of the terrain, unrestricted by complex topography. Additionally, the model considers fluid motion in all directions, providing details such as the three-dimensional velocity field and pressure field of the landslide. Consequently, it captures physical phenomena such as surges and turbulence during the landslide motion. When dealing with complex boundary conditions, this model excels in simulating interactions with the external environment more effectively. Being an Eulerian-based model, the numerical stability poses a challenge for three-dimensional models of this type. Ignoring higher-order terms in the equations can lead to numerical dispersion. While higher-order linear numerical schemes provide more accurate solutions for the linearized equations, they tend to introduce spurious oscillations in regions with discontinuities. Therefore, achieving a balance between numerical diffusion and numerical oscillations is crucial for obtaining an appropriate physical solution. Although this study has alleviated these effects through adaptive grid refinement techniques, these issues remain prominent and cannot be overlooked. For Eulerian-based models, the accuracy of the model depends on the grid resolution. A higher resolution, meaning smaller grid cells, results in a three-dimensional landslide model that closely approximates real topographical conditions and better reflects actual motion. However, the solution process for this model is conducted on each grid cell. With more grid cells, the model's solving time increases, consuming more computational resources. The balance between the computational cost of model solving and model accuracy is a challenging issue that needs to be addressed. In this scenario, when our focus is on the distribution range of landslides, the depth-averaged model with faster solving speed may be a better choice. However, when attention is directed towards more details in the landslide motion process, the three-dimensional model proposed in this study becomes a preferable option [38].