Assessing the Performance of Land Surface Models in Representing Flood Dynamics: A HydroBlocks-SWOT Approach in the Connecticut River Basin, US

Climate conditions and human impact influence surface water variability. Extreme events like river flooding alter interactions between land surfaces and groundwater, affecting sediment and nutrient exchange, ecosystems, and land-atmosphere feedback. Modeling these interactions is challenging due to uncertainties in inputs like floodplain topography, channel morphology, and river flow parameterizations, which impact water and energy balances. Coarse-resolution land surface models (LSMs) (over 10 km) struggle to accurately represent surface water dynamics because they cannot capture complex topography while still accounting for local and regional hydroclimatological dynamics.

This study uses the HydroBlocks Land Surface Modeling framework to address these challenges by resolving land-surface interactions at finer spatial resolutions (~90 m). Through a hierarchical multivariate tiling structure, HydroBlocks overcomes the limitations of coarser models and better represents small-scale heterogeneity. A two-way coupling scheme allows for horizontal water redistribution through the kinematic wave equation.

Water levels are highly sensitive to local factors like channel bathymetry, riverbed slope, and floodplain inundation. Validating water level dynamics requires extensive observations. The launch of the Surface Water and Ocean Topography (SWOT) mission in December 2022 provides high-resolution (~100 m) water surface elevation observations, offering a unique opportunity to study flooding dynamics and improve its representation in LSMs.

This study aims to enhance understanding of water surface dynamics by comparing SWOT observations with HydroBlocks simulations. This integrated approach provides insights into localized and broader trends in water surface elevation, enabling the identification of groundwater signatures and climatological influences. By validating HydroBlocks against SWOT data and conducting sensitivity analyses, the study aims to improve understanding of processes controlling flooding dynamics and better inform the structure of LSMs and spatially distributed validation strategies.

The study examines the Connecticut River watershed, covering 29,200 square kilometers across six northeastern U.S. states, with elevations ranging from sea level to over 1,200 m. Seasonal variations in precipitation and snowmelt create a complex hydrological system, making it suitable for our model validation.