Debris flows are catastrophic mass movements with significant social and environmental consequences, particularly in the Western Himalayas. Understanding the rheological properties of debris flow material is crucial for accurately modeling their behavior and predicting their impacts. In this study, rheological parameters such as yield stress and viscosity were determined through extensive laboratory testing using a parallel plate setup in a rheometer. Reconstituted soil samples from the debris flow zone were prepared using an optimized sampling approach to vary the solid volume concentration and water content (w/c). Experimental results revealed non-Newtonian behavior for all tested compositions, which closely aligned with the Herschel-Bulkley rheological model. The Herschel-Bulkley parameters were subsequently used to calibrate a smooth particle hydrodynamics (SPH) model in the open-access DualSPHysics tool. The results showed that water content and silt concentration played a significant role in influencing the rheology, with finer particles exhibiting higher viscosity and shear stress compared to coarser particles. The SPH simulations effectively replicated the flow behavior observed during the Kotrupi debris flow event (2017), providing insights into flow dynamics, such as velocity and shear distribution. This integration of experimental rheology and numerical modeling advances our understanding of debris flow mechanics and highlights the importance of incorporating rheological calibration in predictive debris flow models.

Debris flows are destructive mass movements that pose multifaceted challenges with profound social and environmental implications in the Western Himalayas. For precise modeling and flow behavior prediction, it is essential to understand the rheological characteristics of debris flow material. In the current study, rheological characteristics like yield stress and viscosity were determined by a series of lab tests using a parallel plate setup in a rheometer. An optimized sampling approach created the reconstituted soil samples of finer particles to change the solid volume concentration and volumetric water content (w/c). Later, the feature importance of finer particles in debris flow rheology was determined using a machine learning regressor. Non-Newtonian behavior was shown by each composition and was similar to Herschel-Bulkley's rheological model. The eXtreme Gradient Boosting (XGBoost) regression model was developed for rheological parameters with robust model fitting with R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}{2}$$\end{document} = 0.90 for yield stress and R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}{2}$$\end{document} = 0.94 for viscosity. The model helped in understanding the sensitivity of rheological parameters with solid constitutents of debris flows. The findings showed that water content and silt concentration substantially impacted the debris flow's rheology. The yield stress was more dominated by silt followed by fine sand, whereas water content influenced the viscosity more than any solid concentration. The flow behavior was also affected by the distribution of grain sizes, with finer particles exhibiting higher viscosity and shear stress than coarser particles. These results enhance understanding of debris flow rheology and highlight the complex interplay between geohazards and sustainable development.

The thickness estimation of landslides is crucial for better landslide evaluation. Traditional non-contact mass conservation methods using 3D deformation may be unsuitable due to observation limitations. This study proposes a more feasible approach based on 2D deformation from two-track Interferometric Synthetic Aperture Radar (InSAR) observations, applied to the Xiongba landslide. The comparison with geological and drilling measurements confirms the reliability of this method. The mapped InSAR LOS deformation rate fields reveal two regions: a significantly deformed frontal zone and a relatively stable zone. Analysis suggests that surface uplift at the Xiongba-H2 landslide's front edge results from rock-soil mass pushing in high-deformation areas. The estimated thickness ranges from 10 to 100 m, with an active volume of 6.17 x 10(7) m(3). A thicker region is identified at the front edge along the Jinsha River, posing the potential for further failure. This low-cost, easily implemented approach enhances InSAR's applicability for landslide analysis and hazard assessment.