Physics-based, integrated hydrologic modeling is a cornerstone of hydrology and water resources management. As model complexity grows and computational capabilities continue to expand, new opportunities are emerging to improve the numerical, algorithmic, and software foundations that make integrated hydrologic simulation possible. This session focuses on methodological and computational advances that enable more robust, efficient, and scalable integrated hydrologic modeling across coupled surface-subsurface, land-atmosphere, and human-water systems. We invite submissions on numerical methods, nonlinear and linear solver strategies, process coupling approaches, adaptive discretization, benchmarking and verification, uncertainty quantification, data assimilation, reduced-order and surrogate modeling, high-performance computing, cloud and GPU implementations, and AI-enabled computational workflows. Contributions that improve model fidelity, stability, reproducibility, or computational performance will help define the next generation of integrated hydrologic modeling tools.