Hourly snowmelt estimations improved performance on daily karst spring discharge predictions: A case study in the Austrian Alps 逐小时融雪估算提高了喀斯特泉日流量预测性能：以奥地利阿尔卑斯山区为例 Les estimations horaires de la fonte neigeuse augmentent la performance des prévisions du débit journalier d’une source karstique : une étude de cas dans les Alpes Autrichiennes Estimativas horárias de derretimento de neve melhoraram o desempenho nas previsões diárias de descarga cárstica na nascente: um estudo de caso nos Alpes Austríacos Estimaciones horarias del deshielo para mejorar el rendimiento de las predicciones diarias de descarga en manantiales kársticos: un estudio de caso en los Alpes austríacos
Hydrogeology Journal, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s10040-026-03090-7
- Dergi Adı: Hydrogeology Journal
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, Environment Index, Geobase, INSPEC
- Anahtar Kelimeler: Austria, Karst, Mountain hydrology, Numerical modeling, Springs
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Ankara Üniversitesi Adresli: Evet
Özet
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.