Enhanced representation of hydrological processes in urban climate modeling: A multi-city global assessment

Rapid urbanization has transformed global landscapes by expanding impervious surfaces and reducing vegetation, leading to altered hydrological and hydrometeorological processes and intensified risks of flooding and heat stress in cities. Urban canopy models are important tools for understanding these processes, but their performance often depends on local climate and urban surface characteristics. Among various modeling challenges, the initialization of soil moisture also remains a key source of uncertainty that constrains predictive reliability. In this study, we employed the recently developed ASLUM-Hydro model, which incorporates multiple parameterization schemes, to evaluate energy and water fluxes across 15 urban sites with diverse climates and surface conditions. Model performance is generally robust, with mean bias errors of 6.56 W m⁻² for sensible heat flux, −4.95 W m⁻² for latent heat flux, 1.27 W m⁻² for net shortwave radiation, and −8.30 W m⁻² for net longwave radiation averaged across all sites. Simulated energy fluxes overall are relatively insensitive to hydrological scheme choice, while water partitioning, particularly evapotranspiration and runoff, shows substantial sensitivity. Runoff exhibits a strong linear relationship with precipitation, and impervious surface fraction is moderately correlated with runoff-to-precipitation ratios. Moreover, while spin-up strategies have overall limited impact on model performance, they become critical in short-term simulations or certain climates, suggesting the need for context-specific initialization. These findings offer practical guidance for improving hydrological and hydrometeorological representation in urban canopy models and are expected to inform the development of future modeling tools that support nature-based solutions and climate-sensitive urban design.