Urbanization and climate change pose significant challenges for urban water systems, particularly in northern regions where seasonal snowmelt, rain-on-snow events, and variable infiltration conditions increase flood risks. This study evaluates the new distributed, physics-based STYX model developed by Technical Research Centre of Finland (VTT) for simulating surface runoff, infiltration, and stormwater flows in urban catchments. STYX provides enhanced spatial resolution compared to conventional models like EPA's Storm Water Management Model (SWMM) by resolving processes at the grid-cell level, enabling dynamic interactions between surface, subsurface, and stormwater networks.

The model was tested in the Vallikallio catchment in Finland using high-resolution meteorological, land-use, and soil data. Results from the calibration and validation periods indicate that STYX effectively captures spatial hydrological variability, with a Nash-Sutcliffe Efficiency (NSE) of 0.71 in calibration and 0.71 in validation, comparable to the calibrated SWMM (NSE = 0.75 in calibration, 0.78 in validation). While both models underestimated peak discharges, STYX provided a more detailed representation of hydrological interactions, including infiltration dynamics and evapotranspiration partitioning.

A key advantage of STYX is its ability to simulate bidirectional flows and backwater effects, which are critical for assessing urban flood risks and the effectiveness of nature-based solutions (NBS). The model also distinguishes between evaporation and transpiration components, allowing for a more detailed evaluation of water balance dynamics. Sensitivity analysis highlighted that land cover properties, particularly Manning’s roughness for roads and buildings, as well as soil hydraulic parameters, had the strongest influence on simulated discharges. The model’s ability to capture spatially distributed infiltration patterns emphasizes the importance of accurate soil parameterization, particularly in regions where infiltration potential varies significantly due to shallow soils and heterogeneous land cover.

Despite these strengths, STYX remains computationally demanding, with a runtime of 137 seconds for the calibration period compared to a few seconds in SWMM. However, this cost is offset by its enhanced capability to represent detailed hydrological processes, making it a valuable tool for urban planners and hydrologists assessing NBS for flood mitigation and climate adaptation. The findings suggest that STYX is particularly well-suited for applications requiring high spatial granularity, such as evaluating the effectiveness of green infrastructure interventions.

Future research will focus on extending simulation periods to assess long-term hydrological trends, refining soil depth representations to improve infiltration modeling, and integrating Nordic-specific processes such as ground frost and seasonal snowmelt. The incorporation of automated mesh generation and parameterization methods will also enhance the model’s usability for broader urban hydrological applications. Ultimately, STYX offers a flexible and detailed framework for simulating complex urban hydrological interactions, contributing to more resilient urban water management strategies in a changing climate.

distributed hydrological modelling; urban stormwater management; nature-based solutions; climate adaptation

Lassi Warsta

ORAL