Abstract Mountains form the headwaters of many hydrological basins, supplying surface and groundwater resources to downstream environments. Karst mountain systems, in particular, require special consideration due to their pronounced heterogeneity in recharge, storage, and flow pathways, as well as their rapid groundwater response under changing climatic conditions. Accurately representing these processes requires robust karst hydrological models for more reliable future predictions. However, the majority of hydrological modelling efforts in karst groundwater systems rely on daily discharge measurements, limiting simulations to a daily temporal resolution. This poses challenges in snow-dominated regions, as snow accumulation and melt are sub-daily processes. Consequently, daily scale models may overlook rapid melt events and the associated recharge dynamics that are especially pronounced in karst settings. The use of hourly hydrological models remains rare, primarily due to the limited availability of high-resolution discharge datasets. To address this challenge, an hourly snow routine was implemented within a daily karst hydrological model and its performance was evaluated in a snow-dominated karstic mountain catchment in Tyrol, Austria. Results indicate that integrating hourly snow dynamics improves model performance, as measured by the Nash–Sutcliffe efficiency (NSE 0.77) and Kling–Gupta efficiency (KGE 0.89), relative to the standard daily routine (NSE 0.74, KGE 0.82). The newly proposed routine was particularly effective in simulating early season melt events, when daily mean air temperatures remain below the melting threshold but midday temperatures exceed it, triggering snowmelt. Moreover, the approach substantially increased the number of behavioural simulations without inflating predictive uncertainty.
Süleyman Selim Çallı (Mon,) studied this question.