The vadose zone governs critical subsurface processes, including groundwater recharge, nutrient cycling, carbon turnover, and contaminant fate. Yet predictive modeling of unsaturated systems remains limited by unresolved heterogeneity, strong process coupling, scale translation challenges, and sparse observational constraints. This session focuses on next-generation vadose zone modeling that moves beyond isolated process representation toward integrated, transferable, and efficient predictive frameworks. We welcome contributions advancing representation of preferential flow, macroporosity, and complex three-dimensional subsurface architecture; coupling hydrologic, thermal, geochemical, and biological processes under transient conditions; improving translation of process understanding and parameterization across pore to watershed scales; and strengthening calibration and prediction through model–data assimilation using geophysical, remote sensing, sensor networks, and long-term observations. We also encourage studies exploring computational frontiers, including multiscale multiphysics models, reduced-order methods, and hybrid physics–machine learning approaches. Contributions addressing contaminants, climate-driven extremes, and cross-scale prediction in vadose zone systems are encouraged.

• B - Biogeosciences
• EP - Earth and Planetary Surface Processes
• IN - Informatics
• NS - Near Surface Geophysics