Rheological characterization of debris flows in the western himalayas using XGBoost and laboratory data

Abstract

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 = 0.90 for yield stress and R2 = 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 Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.