Advancing Hydrological Process Representation with the Dual-grid Rainfall-Runoff-Inundation Model

Accurate representation of hydrological processes across varying spatio-temporal scales is essential for effective flood risk assessment and water resource management. Traditional distributed hydrological models often struggle to integrate rainfall-runoff processes with floodplain inundation dynamics, limiting their ability to assess flood risk at the river basin scale. The Rainfall-Runoff-Inundation (RRI) model addresses this challenge by providing a unified framework that couples both rainfall-runoff and flood inundation in a two-dimensional context.

The original version, RRI v.1, demonstrated the potential for integrated hydrological modeling but had limitations, particularly in underestimating peak discharges in small to medium-sized basins. This issue arose from the model’s structural design, where rainfall passed through multiple slope grid cells before reaching the river channel, delaying flow accumulation, especially in steep or small catchments. Additionally, the model's uniform grid treatment for both rainfall-runoff and inundation increased computational demands for high-resolution inundation simulations. The simplified floodplain representation also failed to differentiate between left and right bank floodplains, limiting its application in complex flood inundation.

To address these issues, RRI v.2 introduces a dual-grid approach and improved hydrologic process-representations with the following key advancements.

• Dual-grid Framework: Coarse grids (e.g., 150 m) for rainfall-runoff computations and finer grids (e.g., 30 m) for floodplain inundation enhance spatial resolution where necessary while optimizing computational efficiency.
• Improved Slope Representation: River channels are included in all grid cells, and slope length is directly incorporated into runoff computations, providing more accurate flow routing and addressing peak discharge underestimation in small basins.
• Enhanced Floodplain Dynamics: Differentiating left and right bank interactions improves floodplain process representation, enhancing model reliability in complex inundation settings.

Additionally, RRI v.2 integrates observed soil characteristics into the runoff model, improving the representation of infiltration and subsurface flow processes referring to our recent work (Sugawara and Sayama, Journal of Hydrology, 2024). Using high-resolution terrain data (e.g., 10 m DEM) and reflecting localized hydrological conditions, the model captures small-scale basin dynamics with greater accuracy.

Preliminary applications to the September 2024 Noto Peninsula heavy rainfall event demonstrate the ability of RRI v.2 to simulate observed flood patterns, peak discharges, and inundation extents. The dual-grid approach not only increases computational efficiency but also ensures scalability for more complex rainfall-runoff and inundation processes. This new development provides a versatile tool for real-time flood forecasting and risk assessment under climate change.