Spatially distributed modeling of urban runoff temperature under surface temperature forcing

Urbanization has increased impervious surfaces in cities, raising surface temperatures and consequently enhancing sensible heat fluxes and longwave emission while reducing latent heat exchange. These surfaces influence runoff temperature, reduce infiltration and increase runoff volumes, thereby affecting urban thermal environments and human thermal comfort. Existing models tend to inadequately represent coupled thermal–hydrological processes. Data-driven approaches often omit fine-scale spatial heterogeneity, while physically based water temperature models are mainly designed for rivers and lakes and only partially address heat exchange for urban pavements. Although recent advances have improved this understanding, these findings are rarely incorporated into spatially distributed hydrodynamic frameworks resolving flow depth, velocity, and routing in urban environments. This study develops a spatially distributed and temporally resolved modeling framework for urban environments that explicitly resolves runoff dynamics and water temperature evolution. The framework extends a two-dimensional hydrodynamic model based on the full shallow-water equations by incorporating a water temperature module with heat transfer driven by prescribed surface temperatures. Model performance is evaluated using in-situ measurements from a controlled experiment on a concrete surface that lasted approximately 6 min, during which water temperatures rose by more than 7 °C before reaching steady state. Including time-dependent surface temperature forcing, in addition to meteorological forcing, substantially improves agreement between simulated and observed water temperatures, reducing the mean absolute error from 3.4 °C to 0.2 °C. The application to the Seestadt Aspern city quarter demonstrates the framework’s potential for spatially resolving runoff temperature dynamics of heavy rain events in a realistic urban setting.