Development of a parametric precipitation-karst spring discharge model for the mountainous karst aquifers

Karst aquifers are heterogeneous groundwater systems having both areal (diffuse) and point (concentrated) recharge at the same time. Groundwater recharge in the high-altitude mountainous karst catchments are mainy controlled by the snow. For this reason, there is a need for a representative snow hydrodynamics in the karst conceptual models in the mountainous karst catchments. In many karst hydrological models in the literature, a snow routine is absent to avoid the overparameterization and this absence is generally fulfilled by the pre-processing of the model input data. In these studies, the researchers generally prefer the degree-day snow routine due to its simplicity and applicability. In the context of this study, a satellite-data-driven snow routine (called SCA routine) is developed which can divide the input water into three physical phases such as rain, snow and mixed phase. This routine can make it possible to snow accumulation and snowmelt available at different altitudes of the catchment at the same time by the fractional snow covered area data generated from the MODIS daily snow cover maps. This facility differs the SCA routine from the classical degree-day routine. In this study, two of the most popular conceptual karst hydrological models are improved by the SCA routine to better predict the spring discharge in the mountainous karst catchments. The new versions of this models are named as KarstMod-SCA and VarKarst-SCA, respectively. The models are applied on Pınarbaşı (Seydişehir, Turkey) and Klaffer (Hochschwab, Austria) karst springs. The model results showed that KarstMod-SCA gave better model performances in both Pınarbaşı and Klaffer springs with NSE = 0.819 and NSE = 0.592 for the calibration periods, and NSE = 0.403, and NSE = 0.519 for the validation periods, respectively.