3.2.1 Natural tracers
Time series of EC available at the gauging station were used in
combination with individual samples analysed for EC and stable isotopes
(δ18O and δ2H) taken during various field trips between 31.07.2017 and
15.09.2017. These samples include glacial meltwater (4 samples), a
cumulative rainfall sample collected during the same period using a
funnel connected via a flexible tube to a bottle (placed 1 m deep within
the coarse blocky surface to avoid evaporation by direct radiation), as
well as 18 samples taken by an automatic sampler between 01.08.2017 and
06.08.2017 (Figure 2; sampling locations indicated in Figure 1b). During
field campaigns no direct access to permafrost ice (below the active
layer) was obtained, so the actual signature of permafrost ice in this
catchment remains unknown.
Natural tracer data (EC, isotopes) allow to determine variations in
event water contributions from the endmembers of rain, snowmelt and ice
melt (e.g. Winkler et al., 2016). The restricted rock-water interaction
in the alpine catchment composed of metamorphic bedrock allows regarding
EC as a conservative tracer (cf. Winkler et al., 2016). Based on this
assumption a two component mixing model was applied to identify
groundwater and event water components at diurnal and seasonal time
scales (Harrington et al., 2018; Williams et al., 2006; Winkler et al.,
2016). The event water component is composed of low mineralized
rainfall, snowmelt and glacier ice melt, which is distinguishable from
the higher mineralized groundwater component.
3.3 Rainfall-Runoff Modelling
For a better understanding of the discharge pattern and to further
constrain the contribution of rainfall, snowmelt and ice melt within the
rock glacier catchment, a parsimonious lumped parameter rainfall-runoff
model was deployed. The model was successfully applied for a relict rock
glacier and catchments downstream of relict rock glaciers by Wagner et
al. (2016) and was shown to be especially valuable in alpine catchments
where input data are usually scarce (e.g. Wagner et al., 2013, 2016).
Here, the model was extended by an ice store module (Figure 3) to
account for ice melt within the spring catchment. The module is based on
a degree-day factor and contributes ice melt as input in the production
store if seasonal snow is melted as described in Nepal et al. (2017).
This model setup relates ice melt to melt from glaciers and not from
permafrost. For simplicity the initial glacier ice water volume is
assumed to be large so that over the analysed period of more than 4
years, ice melt is warranted. The actual percentage of runoff
contribution within the catchment is related to the areal coverage of
the cirque glaciers within the total catchment of ~ 10
% (Figure 1b) and is assumed to remain constant over the time period of
4 years. Input data for the model are daily values of precipitation and
average temperature for the catchment.
Discharge data from the gauging station are used to calibrate and
validate the model using split sample tests (e.g. Klemes, 1986). The
results are compared to the hydrograph analyses and natural and
artificial tracer data thereby allowing to differentiate the various
input (“recharge”) components over time (in contrast to the other data
that indicate discharge variations). Moreover, the model is then used to
hypothetically remove/ignore the cirque glacier ice stores and explore
potential changes in the runoff characteristics. In addition, the model
parameters representing a relict rock glacier (Wagner et al., 2016) can
be used to account for a hypothetical decay from an active to a relict
rock glacier (a trading space-for-time approach accounting for changing
watershed behaviour; Singh et al., 2011) and observe a potential change
in storage-discharge characteristics.
[Insert Figure 3]