Abstract. Seasonal snow cover is an important temporary water storage in high-elevation regions. Especially in remote areas, the available data are often insufficient to accurately quantify snowmelt contributions to streamflow. The limited knowledge about the spatiotemporal variability of the snowmelt isotopic composition, as well as pronounced spatial variation in snowmelt rates, leads to high uncertainties in applying the isotope-based hydrograph separation method. The stable isotopic signatures of snowmelt water samples collected during two spring 2014 snowmelt events at a north-and a south-facing slope were volume weighted with snowmelt rates derived from a distributed physicsbased snow model in order to transfer the measured plotscale isotopic composition of snowmelt to the catchment scale. The observed δ 18 O values and modeled snowmelt rates showed distinct inter-and intra-event variations, as well as marked differences between north-and south-facing slopes. Accounting for these differences, two-component isotopic hydrograph separation revealed snowmelt contributions to streamflow of 35 ± 3 and 75 ± 14 % for the early and peak melt season, respectively. These values differed from those determined by formerly used weighting methods (e.g., using observed plot-scale melt rates) or considering either the north-or south-facing slope by up to 5 and 15 %, respectively.

Geochemical and isotopic tracers were often used in mixing models to estimate glacier melt contributions to streamflow, whereas the spatio‐temporal variability in the glacier melt tracer signature and its influence on tracer‐based hydrograph separation results received less attention. We present novel tracer data from a high‐elevation catchment (17 km2, glacierized area: 34%) in the Oetztal Alps (Austria) and investigated the spatial, as well as the subdaily to monthly tracer variability of supraglacial meltwater and the temporal tracer variability of winter baseflow to infer groundwater dynamics. The streamflow tracer variability during winter baseflow conditions was small, and the glacier melt tracer variation was higher, especially at the end of the ablation period. We applied a three‐component mixing model with electrical conductivity and oxygen‐18. Hydrograph separation (groundwater, glacier melt, and rain) was performed for 6 single glacier melt‐induced days (i.e., 6 events) during the ablation period 2016 (July to September). Median fractions (±uncertainty) of groundwater, glacier melt, and rain for the events were estimated at 49±2%, 35±11%, and 16±11%, respectively. Minimum and maximum glacier melt fractions at the subdaily scale ranged between 2±5% and 76±11%, respectively. A sensitivity analysis showed that the intraseasonal glacier melt tracer variability had a marked effect on the estimated glacier melt contribution during events with large glacier melt fractions of streamflow. Intra‐daily and spatial variation of the glacier melt tracer signature played a negligible role in applying the mixing model. The results of this study (a) show the necessity to apply a multiple sampling approach in order to characterize the glacier melt end‐member and (b) reveal the importance of groundwater and rainfall–runoff dynamics in catchments with a glacial flow regime.

Spatio-temporal variations of precipitation are presumed to influence the displacement rate of slow-moving deep-seated landslides by controlling groundwater recharge, pore-water pressure and shear strength. Phases of landslide acceleration responding to long-lasting rainfall and snowmelt events occur under site-and eventspecific time delays. Assessing groundwater recharge and simultaneous recording of landslide displacement in a sufficient spatial and temporal resolution is essential to deepen the understanding of mechanisms controlling a landslide's deformation behaviour and is indispensable when it comes to identifying and developing targetoriented mitigation strategies. The objective of this study was to assess hydrological landslide drivers (solid and liquid precipitation, snowmelt and evapotranspiration) and to investigate their spatio-temporal distribution in the context of movements recorded at the Vögelsberg landslide (Tyrol, Austria). Hydrometeorological variables were simulated using the AMUNDSEN (Alpine MUltiscale Numerical Distributed Simulation ENgine) hydroclimatological model and landslide movements were continuously monitored using an automated tracking total station. Area-wide simulated time series of available water were used: (i) to separate them into single landslide triggering hydrometeorological events; (ii) to analyse spatio-temporal patterns of water availability per triggering event including individual response times; (iii) to delineate an effective hydrological landslide catchment; and (iv) to identify relations between assessed water input and landslide displacement rate. For the observation period from 05-2016 until 06-2019 we identified three distinctive hydrometeorological events causing time-delayed periods of landslide acceleration. Spatio-temporal differences in water availability per triggering event result in spatially diverse response times varying from 20 to 60 days for rainfall-triggered events and between 0 and 8 days for events triggered by snowmelt. Pronounced spatio-temporal differences of snowmelt within the model domain were identified to offer a unique possibility to delineate the effective hydrological landslide catchment. While considering event-specific time-lags, logarithmic correlations between incoming water and landslide displacement rate become apparent.