3. DATA AND METHODS
3.1 Spring hydrograph
Spring discharge data for the time period June 2014 to June 2017 was analysed among other discharge data from active rock glacier springs by Wagner et al. (2020a) using master recession curves based on the approach proposed by Posavec et al. (2017). Fitted recession functions are based on the exponential model of Maillet (1905) and related assumptions are described in more detail in Wagner et al. (2020a). Here we use the same data and add more recent data until July 2018 (Figure 2, to overlap with available natural tracer data). On the one hand, the data are used to calibrate and validate the rainfall-runoff model; on the other hand the data serve as a base for a detailed event water separation in combination with electrical conductivity (EC) and isotopic data.
Water level and EC were measured directly at the gauging station (Figure 1b). The former was converted to discharge by applying a rating curve based on the salt dilution method implemented under a wide range of flow conditions (Heigert, 2018). Several data gaps in the discharge and EC record are due to the harsh alpine environment and related maintenance restrictions (Figure 2). However, the overall dynamics are captured reasonably well and the presented analyses take into account the associated uncertainties. Note that in contrast to the pressure probe, the EC probe fell dry due to low water levels during the winter months as the probe is situated higher than the pressure probe (Figure 2). Precipitation and air temperature were recorded at a measurement interval of 15 min at the meteorological station Weißsee (2464 m a.s.l.; distance ~4 km to the southwest; courtesy of TIWAG). The mean catchment air temperature and precipitation were calculated applying a correction factor of 0.5°C /100 m and 7 % /100 m, respectively, to account for the mean catchment elevation of 2887 m a. s. l. (Kuhn et al., 2013; Wagner et al., 2020a).
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3.2 Tracers analysis