How Drag Laws Shape PDC Hazards: Adjoint Sensitivity in Depth-Averaged Models Applied to the Taupō 232 CE Eruption

Pyroclastic density currents (PDCs) are among the most hazardous particle-laden gravity currents on Earth, yet their runout and depositional footprints remain difficult to predict reliably. Accurate forecasting requires models that correctly represent flow density, which is strongly controlled by particle sedimentation rates. Recent high-fidelity Euler–Lagrangian simulations of polydisperse sedimenting particles have motivated a modified drag law that accounts for particle clustering, a common feature of highly mass-loaded flows such as PDCs. These simulations show enhanced settling of fine particles and hindered settling of coarse particles relative to isolated particle behavior. While this represents an important advance toward improved large-scale predictions, such as runout distance, the drag law constitutes only one component of a coupled, nonlinear system when embedded in depth-averaged hazard models such as IMEX_SfloW2D. Here, we apply adjoint-based sensitivity analysis to the clustering-aware drag law within IMEX_SfloW2D to quantify the influence of individual drag-law terms and model parameters on key quantities of interest, including deposition thickness and mean runout distance.