High Alpine Catchments Research Articles

Evaluating precipitation corrections to enhance High-Alpine hydrological modeling

Gridded meteorological data products often fall short in accurately capturing the amount of precipitation and its patterns in regions characterized by high elevations and complex topography. However, realistic precipitation data is crucial for high-alpine hydrological modeling. To address these discrepancies, we analyze possible corrections for solid, liquid and total precipitation of the 1 km2 gridded meteorological INCA-product in the high-alpine catchment of the Kölnbrein hydropower reservoir operated by VERBUND Energy4Business GmbH in the Malta Valley in Austria. By leveraging information from a stereo-satellite-derived snow depth map with physically-based snowpack modeling with Alpine3D, we quantitatively adjust and spatially redistribute solid precipitation, complemented by a multiplicative, stepwise correction model for liquid precipitation. We compare and evaluate five approaches using the hydrological COSERO model to our a) baseline simulation with no corrections on INCA in contrast of correcting, b) the amount and distribution of solely solid precipitation, c) the amount of liquid and solid precipitation, d) the amount of liquid and solid precipitation and the spatial distribution of the latter, e) precipitation inversely by the inflow bias, and f) calibrating the precipitation correction factor. In evaluating these strategies to improve the accuracy of reservoir inflow predictions, we found that separately correcting solid and liquid precipitation yielded the best results (c &d), with a substantial increase of up to 65 % over the study period (1.10.2015–30.9.2023), while the other correction variants ranged between 42 and 52 %. The inflow predictions by COSERO showed an increase in Nash-Sutcliffe Efficiency (NSE) by 17 % and in Kling-Gupta Efficiency by 57 % and 59 % for variants c and d, respectively, along with an almost complete elimination of model bias. The higher KGE values observed for variant d compared to c during spring, summer, and fall suggest that a more realistic snow distribution enhances the simulation of snowmelt-driven runoff dynamics. In contrast, using a global (i.e., spatially homogeneous) and uniform (i.e., not distinguishing between liquid and solid precipitation phase) correction factor, inversely derived from the inflow bias (e), or solely correcting solid precipitation (b), demonstrated less performance, with a KGE increase of 47 % and 49 %, respectively, compared to 59 % for variant d. Conversely, the calibration of the global and uniform correction factor (f) resulted in significant performance metric improvements (17 % NSE, 60 % KGE and 90 % pBias), similar to variant d, however also led to unrealistic simulations of evapotranspiration, sublimation and glacier net runoff. The simulated water balance components – evapotranspiration and sublimation, as well as glacier runoff – in variant d were deemed plausible based on our comparison with additional simulations using Alpine3D, as well as findings from other high-alpine catchments in Austria reported in the literature. Overall, our results underscore the importance of applying a dual correction strategy for both liquid and solid precipitation, particularly when significant deficiencies are present in meteorological datasets, and suggest that such corrections should be supplemented by a comprehensive analysis of the simulated high-alpine water balance components.

Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool

Abstract. Future changes in suspended sediment export from deglaciating high-alpine catchments affect downstream hydropower reservoirs, flood hazard, ecosystems and water quality. Yet, quantitative projections of future sediment export have so far been hindered by the lack of process-based models that can take into account all relevant processes within the complex systems determining sediment dynamics at the catchment scale. As a promising alternative, machine-learning (ML) approaches have recently been successfully applied to modeling suspended sediment yields (SSYs). This study is the first, to our knowledge, exploring a machine-learning approach to derive sediment export projections until the year 2100. We employ quantile regression forest (QRF), which proved to be a powerful method to model past SSYs in previous studies, for two nested glaciated high-alpine catchments in the Ötztal, Austria, above gauge Vent (98.1 km2) and gauge Vernagt (11.4 km2). As predictors, we use temperature and precipitation projections (EURO-CORDEX) and discharge projections (AMUNDSEN physically based hydroclimatological and snow model) for the two gauges. We address uncertainties associated with the known limitation of QRF that underestimates can be expected if values in the projection period exceed the range represented in the training data (out-of-observation-range days, OOOR). For this, we assess the frequency and extent of these exceedances and the sensitivity of the resulting mean annual suspended sediment concentration (SSC) estimates. We examine the resulting SSY projections for trends, the estimated timing of peak sediment and changes in the seasonal distribution. Our results show that the uncertainties associated with the OOOR data points are small before 2070 (max. 3 % change in estimated mean annual SSC). Results after 2070 have to be treated more cautiously as OOOR data points occur more frequently, and glaciers are projected to have (nearly) vanished by then in some projections, which likely substantially alters sediment dynamics in the area. The resulting projections suggest decreasing sediment export at both gauges in the coming decades, regardless of the emission scenario, which implies that peak sediment has already passed or is underway. This is linked to substantial decreases in discharge volumes, especially during the glacier melt phase in late summer, as a result of increasing temperatures and thus shrinking glaciers. Nevertheless, high(er) annual yields can occur in response to heavy summer precipitation, and both developments would need to be considered in managing sediments, as well as e.g., flood hazard. While we chose the predictors to act as proxies for sediment-relevant processes, future studies are encouraged to try and include geomorphological changes more explicitly, e.g., changes in connectivity, landsliding, rockfalls or vegetation colonization, as these could improve the reliability of the projections.

Morphological indexes to describe snow-cover patterns in a high-alpine area

Abstract The spatiotemporal distribution of snow affects hydrological and climatological processes at different scales. Accordingly, quantifying geometric features of snow-cover patterns is important, providing a valuable complement for snow water equivalent (SWE) modelling. This study on satellite-based morphological analysis originally uses two types of geometric indexes: (1) MN, Minkowski numbers (area (MN1), perimeter (MN2), Euler number (MN3)), and (2) CL, average chord length, to describe the morphology of Sentinel-2-derived snow-covered areas (SCAs), within the high-alpine site Zugspitze for a 5 year period. Results indicate that they capture the seasonal variability of snow-cover patterns, particularly during accumulation and ablation. Being to some degree independent from each other, MN2, MN3 and CL provide additional information upon shape, connectivity and length scale of snow cover, compared to most used indexes (e.g. fractional SCA). Correlation values up to +0.7 for MN2, +0.58 for MN3 and +0.46 for CL were observed with selected topographic characteristics, suggesting a close connection between geometric features of snow cover and ground features. Comparing in situ SWE measurements with MN and CL shows a correlation between −0.5 and +0.5. These indexes can hence be applied in combination with in situ data and/or modelling approaches to improve spatially distributed SWE in high-alpine catchments.

Robust estimations of areal grain size distribution from geometric surface roughness in a proglacial outwash area

Rapid glacier mass loss in high-alpine catchments exposes unconsolidated sediments to erosion by meltwater-fed mountain streams, with impact on the catchment-scale sediment dynamics. Proglacial outwash areas (OWA) are a key spatial element in this sediment flux cascade, with grain size distributions (GSD) as an integral variable in current and future glacio-fluvial processes and associated effects.In this study, surface grain size estimation methods based on linear correlations between geometric surface roughness and GSD data are adapted to test this new mapping approach for areal GSD patterns and their changes in a proglacial OWA. Surface roughness is computed with adaptive kernel sizes from high-resolution topographic point clouds derived from UAV-based photogrammetry. For model calibration, ground truth data is manually obtained from 30 dry-exposed GSD sampling patches of 1 m2 each. The novelty and potential of this surface roughness regression model lies in its capability to robustly map GSD percentiles at 1-m cell resolution in highly dynamic proglacial environments and inherent data scarcity, drastically reducing the portion of labour-intensive and time-consuming manual surveying.Our optimized linear regression function for the key figure D84, which is widely used in practice, returns a coefficient of determination of 76.4 %. The linear relation found between the D84 of field GSD and the 84th distribution percentile of surface roughness metrics has a slope of α = 6.01, which is consistent with the range of recently published studies using LiDAR-based and photogrammetric surveys. The presented surface roughness regression model provides realistic surficial estimations of areal GSD patterns in a proglacial domain of sediment remobilization. In addition, this work analyses and discusses detected changes in the estimated D84 over a three-month period. A systematic shift is identified for sediment compositions with an initial D84 above 60 mm. This is thought to be an effect of the original image quality and variable lighting conditions between photogrammetric surveys and indicates that best practice should include careful survey planning for most uniform flight settings. Nevertheless, visually verified significant changes in D84 along frequently wet low-flow channels can be detected automatically, and thus the findings demonstrate the feasibility of this GSD monitoring approach for tracking fluvial re-working of surface sediment.

Reconstructing five decades of sediment export from two glacierized high-alpine catchments in Tyrol, Austria, using nonparametric regression

Abstract. Knowledge on the response of sediment export to recent climate change in glacierized areas in the European Alps is limited, primarily because long-term records of suspended sediment concentrations (SSCs) are scarce. Here we tested the estimation of sediment export of the past five decades using quantile regression forest (QRF), a nonparametric, multivariate regression based on random forest. The regression builds on short-term records of SSCs and long records of the most important hydroclimatic drivers (discharge, precipitation and air temperature – QPT). We trained independent models for two nested and partially glacier-covered catchments, Vent (98 km2) and Vernagt (11.4 km2), in the upper Ötztal in Tyrol, Austria (1891 to 3772 m a.s.l.), where available QPT records start in 1967 and 1975. To assess temporal extrapolation ability, we used two 2-year SSC datasets at gauge Vernagt, which are almost 20 years apart, for a validation. For Vent, we performed a five-fold cross-validation on the 15 years of SSC measurements. Further, we quantified the number of days where predictors exceeded the range represented in the training dataset, as the inability to extrapolate beyond this range is a known limitation of QRF. Finally, we compared QRF performance to sediment rating curves (SRCs). We analyzed the modeled sediment export time series, the predictors and glacier mass balance data for trends (Mann–Kendall test and Sen's slope estimator) and step-like changes (using the widely applied Pettitt test and a complementary Bayesian approach). Our validation at gauge Vernagt demonstrated that QRF performs well in estimating past daily sediment export (Nash–Sutcliffe efficiency (NSE) of 0.73) and satisfactorily for SSCs (NSE of 0.51), despite the small training dataset. The temporal extrapolation ability of QRF was superior to SRCs, especially in periods with high-SSC events, which demonstrated the ability of QRF to model threshold effects. Days with high SSCs tended to be underestimated, but the effect on annual yields was small. Days with predictor exceedances were rare, indicating a good representativity of the training dataset. Finally, the QRF reconstruction models outperformed SRCs by about 20 percent points of the explained variance. Significant positive trends in the reconstructed annual suspended sediment yields were found at both gauges, with distinct step-like increases around 1981. This was linked to increased glacier melt, which became apparent through step-like increases in discharge at both gauges as well as change points in mass balances of the two largest glaciers in the Vent catchment. We identified exceptionally high July temperatures in 1982 and 1983 as a likely cause. In contrast, we did not find coinciding change points in precipitation. Opposing trends at the two gauges after 1981 suggest different timings of “peak sediment”. We conclude that, given large-enough training datasets, the presented QRF approach is a promising tool with the ability to deepen our understanding of the response of high-alpine areas to decadal climate change.

Weekly high-resolution multi-spectral and thermal uncrewed-aerial-system mapping of an alpine catchment during summer snowmelt, Niwot Ridge, Colorado

Abstract. Alpine ecosystems are experiencing rapid change as a result of warming temperatures and changes in the quantity, timing and phase of precipitation. This in turn impacts patterns and processes of ecohydrologic connectivity, vegetation productivity and water provision to downstream regions. The fine-scale heterogeneous nature of these environments makes them challenging areas to measure with traditional instrumentation and spatiotemporally coarse satellite imagery. This paper describes the data collection, processing, accuracy assessment and availability of a series of approximately weekly-interval uncrewed-aerial-system (UAS) surveys flown over the Niwot Ridge Long Term Ecological Research site during the 2017 summer-snowmelt season. Visible, near-infrared and thermal-infrared imagery was collected. This unique series of 5–25 cm resolution multi-spectral and thermal orthomosaics provides a unique snapshot of seasonal transitions in a high alpine catchment. Weekly radiometrically calibrated normalised difference vegetation index maps can be used to track vegetation health at the pixel scale through time. Thermal imagery can be used to map the movement of snowmelt across and within the near sub-surface as well as identify locations where groundwater is discharging to the surface. A 10 cm resolution digital surface model and dense point cloud (146 points m−2) are also provided for topographic analysis of the snow-free surface. These datasets augment ongoing data collection within this heavily studied and important alpine site; they are made publicly available to facilitate wider use by the research community. Datasets and related metadata can be accessed through the Environmental Data Initiative Data Portal, https://doi.org/10.6073/pasta/dadd5c2e4a65c781c2371643f7ff9dc4 (Wigmore, 2022a), https://doi.org/10.6073/pasta/073a5a67ddba08ba3a24fe85c5154da7 (Wigmore, 2022c), https://doi.org/10.6073/pasta/a4f57c82ad274aa2640e0a79649290ca (Wigmore and Niwot Ridge LTER, 2021a), https://doi.org/10.6073/pasta/444a7923deebc4b660436e76ffa3130c (Wigmore and Niwot Ridge LTER, 2021b), https://doi.org/10.6073/pasta/1289b3b41a46284d2a1c42f1b08b3807 (Wigmore and Niwot Ridge LTER, 2022a), https://doi.org/10.6073/pasta/70518d55a8d6ec95f04f2d8a0920b7b8 (Wigmore and Niwot Ridge LTER, 2022b). A summary of the available datasets can be found in the data availability section below.

Hydrodynamics of a high Alpine catchment characterized by four natural tracers

Abstract. Hydrological processes in high-elevation catchments are strongly influenced by alternating snow accumulation and melt in addition to summer rainfall. Although diverse water sources and flow paths that generate streamflow in the world's water towers emerge from these two driving inputs, a detailed process understanding remains poor. We measured a combination of natural tracers of water at a high frequency, including stable isotope compositions, electrical conductivity (EC), and water and soil temperature to characterize hydrological processes in a snow-dominated Alpine catchment and to understand the diversity of streamflow sources and flow paths. Stable isotope composition of the sampled water revealed the prominence of snowmelt year-round (even during winter baseflow), and a strong flushing of the entire system with snowmelt at the start of the main melt period, sometimes referred to as the freshet, led to a reset, or return to baseline, of the isotopic values in most sampled water. Soil temperature measurements help identify snow-free periods and indicate sub-snowpack local flow, for example, in the case of rain-on-snow events. Water temperature measurements in springs can indicate flow path depth. EC measurements reflect the magnitude of subsurface exchange and allow for the separation of subsurface snowmelt contribution to streamflow from the contribution of stored groundwater. These insights into the details of streamflow generation in such a dynamic environment were only made possible due to intense, year-round water sampling. The sampled tracers are revealed to complement each other in important ways particularly because they were sampled during winter and spring, both snow-covered periods, the importance of which is a key implication of this work.

Establishing a record of extreme debris flow events in a high Alpine catchment since the end of the Little Ice Age using lichenometric dating

ABSTRACT Establishing a record of large debris flow events in high Alpine areas prior to the availability of high resolution remote sensing data can be very challenging. In this study, we investigate the debris flow activity in two tributary valleys of the Horlachtal catchment in Tyrol, Austria between the end of the Little Ice Age at about 1850 and the first available area wide aerial images from 1947. To accomplish this, we calculated a local lichenometric calibration curve using the long axis diameters of the five largest Rhizocarpon lichen thalli at 51 different reference locations. Because of the interval-censored dating of most of the reference sites, we established a bootstrapping approach within the calibration curve calculation process. With the help of the lichenometric calibration data, we were able to date 47 old debris flow deposits in the study area. The results indicate no increasing or decreasing trends in frequencies of extreme debris flow events. In addition, the results point to a very local character of debris flow triggering precipitation events, as we can detect major differences in neighbouring valleys. Lichenometric derived datings also provide temporal informations about the end of debris flow activity at some sites in the study area and thus can contribute to a better understanding of debris flow systems.

Diurnal cycle of surface energy fluxes in high mountain terrain: High‐resolution fully coupled atmosphere‐hydrology modelling and impact of lateral flow

AbstractWater and energy fluxes are inextricably interlinked within the interface of the land surface and the atmosphere. In the regional earth system models, the lower boundary parameterization of land surface neglects lateral hydrological processes, which may inadequately depict the surface water and energy fluxes variations, thus affecting the simulated atmospheric system through land‐atmosphere feedbacks. Therefore, the main objective of this study is to evaluate the hydrologically enhanced regional climate modelling in order to represent the diurnal cycle of surface energy fluxes in high spatial and temporal resolution. In this study, the Weather Research and Forecasting model (WRF) and coupled WRF Hydrological modelling system (WRF‐Hydro) are applied in a high alpine catchment in Northeastern Tibetan Plateau, the headwater area of the Heihe River. By evaluating and intercomparing model results by both models, the role of lateral flow processes on the surface energy fluxes dynamics is investigated. The model evaluations suggest that both WRF and coupled WRF‐Hydro reasonably represent the diurnal variations of the near‐surface meteorological fields, surface energy fluxes and hourly partitioning of available energy. By incorporating additional lateral flow processes, the coupled WRF‐Hydro simulates higher surface soil moisture over the mountainous area, resulting in increased latent heat flux and decreased sensible heat flux of around 20–50 W/m2 in their diurnal peak values during summertime, although the net radiation and ground heat fluxes remain almost unchanged. The simulation results show that the diurnal cycle of surface energy fluxes follows the local terrain and vegetation features. This highlights the importance of consideration of lateral flow processes over areas with heterogeneous terrain and land surfaces.

Subaqueous geomorphology and delta dynamics of Lake Brienz (Switzerland): implications for the sediment budget in the alpine realm

Non-invasive techniques such as seismic investigations and high-resolution multibeam sonars immensely improved our understanding of the geomorphology and sediment regimes in both the lacustrine and the marine domain. However, only few studies provide quantifications of basin wide-sediment budgets in lakes. Here, we use the combination of high-resolution bathymetric mapping and seismic reflection data to quantify the sediment budget in an alpine lake. The new bathymetric data of Lake Brienz reveal three distinct geomorphological areas: slopes with intercalated terraces, a flat basin plain, and delta areas with subaquatic channel systems. Quasi-4D seismic reflection data allow sediment budgeting of the lake with a total sediment input of 5.54 × 106 t sediment over 15 years of which three-quarter were deposited in the basin plain. Lake Brienz yields extraordinarily high sedimentation rates of 3.0 cm/yr in the basin plain, much more than in other Swiss lakes. This can be explained by (i) its role as first sedimentary sink in a high-alpine catchment, and by (ii) its morphology with subaquatic channel-complexes allowing an efficient sediment transfer from proximal to distal areas of the lake.

Technical note: Introduction of a superconducting gravimeter as novel hydrological sensor for the Alpine research catchment Zugspitze

Abstract. GFZ (German Research Centre for Geosciences) set up the Zugspitze Geodynamic Observatory Germany with a worldwide unique installation of a superconducting gravimeter at the summit of Mount Zugspitze on top of the Partnach spring catchment. This high alpine catchment is well instrumented, acts as natural lysimeter and has significant importance for water supply to its forelands, with a large mean annual precipitation of 2080 mm and a long seasonal snow cover period of 9 months, while showing a high sensitivity to climate change. However, regarding the majority of alpine regions worldwide, there is only limited knowledge on temporal water storage variations due to sparsely distributed hydrological and meteorological sensors and the large variability and complexity of signals in alpine terrain. This underlines the importance of well-equipped areas such as Mount Zugspitze serving as natural test laboratories for improved monitoring, understanding and prediction of alpine hydrological processes. The observatory superconducting gravimeter, OSG 052, supplements the existing sensor network as a novel hydrological sensor system for the direct observation of the integral gravity effect of total water storage variations in the alpine research catchment at Zugspitze. Besides the experimental set-up and the available data sets, the gravimetric methods and gravity residuals are presented based on the first 27 months of observations from 29 December 2018 to 31 March 2021. The snowpack is identified as being a primary contributor to seasonal water storage variations and, thus, to the gravity residuals with a signal range of up to 750 nm s−2 corresponding to 1957 mm snow water equivalent measured with a snow scale at an altitude of 2420 m at the end of May 2019. Hydro-gravimetric sensitivity analysis reveal a snow–gravimetric footprint of up to 4 km distance around the gravimeter, with a dominant gravity contribution from the snowpack in the Partnach spring catchment. This shows that the hydro-gravimetric approach delivers representative integral insights into the water balance of this high alpine site.

The evaluation of the potential of global data products for snow hydrological modelling in ungauged high-alpine catchments

Abstract. For many ungauged mountain regions, global datasets of different meteorological and land surface parameters are the only data sources available. However, their applicability in modelling high-alpine regions has been insufficiently investigated so far. Therefore, we tested a suite of globally available datasets by applying the physically based Cold Regions Hydrological Model (CRHM) for a 10-year (September 2000–August 2010) period in the gauged high-alpine Research Catchment Zugspitze (RCZ), which is 12 km2 and located in the European Alps. Besides meteorological data, snow depth is measured at two stations. We ran CRHM with a reference run with in situ-measured meteorological data and a 2.5 m high-resolution digital elevation model (DEM) for the parameterization of the surface characteristics. Regarding different meteorological setups, we used 10 different globally available datasets (including versions of ERA, GLDAS, CFSR, CHIRPS) and additionally one transferred dataset from a similar station in the vicinity. Regarding the different DEMs, we used ALOS (Advanced Land Observing Satellite) and SRTM (Shuttle Radar Topography Mission) (both 30 m) as well as GTOPO30 (1 km). The following two main goals were investigated: (a) the reliability of simulations of snow depth, specific snow hydrological parameters and runoff with global meteorological products and (b) the influence of different global DEMs on snow hydrological simulations in such a topographically complex terrain. The range between all setups in mean decadal temperature is high at 3.5 ∘C and for the mean decadal precipitation sum at 1510 mm, which subsequently leads to large offsets in the snow hydrological results. Only three meteorological setups, the reference, the transferred in situ dataset and the CHIRPS dataset, substituting precipitation only, showed agreeable results when comparing modelled to measured snow depth. Nevertheless, those setups showed obvious differences in the catchment's runoff regime and in snow depth, snow cover, ablation period, the date, and quantity of maximum snow water equivalent in the entire catchment and in specific parts. All other globally available meteorological datasets performed worse. In contrast, all globally available DEM setups reproduced snow depth, the snow hydrological parameters and runoff quite well. Differences occurred mainly due to differences in radiation model input due to different spatial realizations. Even though SRTM and ALOS have the same spatial resolution, they showed considerable differences due to their different product origins. Despite the fact that the very coarse GTOPO30 DEM performed relatively well on the catchment mean, we advise against using this product in such heterogeneous high-alpine terrain since small-scale topographic characteristics cannot be captured. While global meteorological data are not suitable for sound snow hydrological modelling in the RCZ, the choice of the DEM with resolutions in the decametre level is less critical. Nevertheless, global meteorological data can be a valuable source to substitute single missing variables. For the future, however, we expect an increasing role of global data in modelling ungauged high-alpine basins due to further product improvements, spatial refinements and further steps regarding assimilation with remote sensing data.

A Framework for Modeling Rock Glaciers and Permafrost at the Basin‐Scale in High Alpine Catchments

AbstractSince rock glaciers are believed to be more resilient to climate change, water stores therein may become important water reservoirs in future, in particular in dry regions, which currently rely on glacial runoff. In order to estimate and evaluate the future runoff potential from permafrost and rock glaciers, distributed runoff models suitable for high Alpine catchments are needed. An extension to the distributed Glacier Evolution and Runoff Model (GERM) to include permafrost and rock glaciers in Alpine catchments is presented here, and compared to the established one dimensional (1D) physics‐based model SNOWPACK. The new permafrost component introduced to GERM treats permafrost as discreet depth layers in a 1D column for all grid cells, which have bulk thermal properties calculated from their constituents (ice, water, air, and solid component). The temperature evolution is computed using heat conduction and latent heat exchanges, modified by ventilation effects. Finally, we infer water runoff from permafrost degradation. Ground temperature variations calculated by both models are compared to borehole measurements at three Alpine sites and similar performances are found. Differences between the models are present in the amplitude of seasonal ground temperature variations, with SNOWPACK having a tendency to slightly overestimate them, while GERM underestimates them.

Seasonal snow cover decreases young water fractions in high Alpine catchments

AbstractEstimation of young water fractions (Fyw), defined as the fraction of water in a stream younger than approximately 2–3 months, provides key information for water resource management in catchments where runoff is dominated by snowmelt. Knowing the average dependence of summer flow on winter precipitation is an essential context for comparing regional drought severity and provides the hydrological template for downstream water users and ecosystems. However, Fyw estimation based on seasonal signals of stable isotopes of oxygen and hydrogen has not yet explicitly addressed how to parsimoniously include the seasonal shift of water input from snow. Using experimental data from three high‐elevation, Alpine catchments (one dominated by glacier and two by snow), we propose a framework to explicitly include the delays induced by snow storage into estimates of Fyw. Scrutinizing the key methodological choices when estimating Fyw from isotope data, we find that the methods used to construct precipitation input signals from sparse isotope samples can significantly impact Fyw. Given this sensitivity, our revised procedure estimates a distribution of Fyw values that incorporates a wide range of possible methodological choices and their uncertainties; it furthermore compares the commonly used amplitude ratio approach to a direct convolution approach, which circumvents the assumption that the isotopic signals have a sine curve shape, an assumption that is generally violated in snow‐dominated environments. Our new estimates confirm that high‐elevation Alpine catchments have low Fyw values, spanning from 8 to 11%. Such low values have previously been interpreted as the impact of seasonal snow storage alone, but our comparison of different Fyw estimation methods suggests that these low Fyw values result from a combination of both snow cover effects and longer storage in the subsurface. In contrast, in the highest elevation, glacier dominated catchment, Fyw is 3–4 times greater compared to the other two catchments, due to the lower storage and faster drainage processes. A future challenge, capturing spatio‐temporal snowmelt isotope signals during winter baseflow and the snowmelt period, remains to improve constraints on the Fyw estimation technique.

Active rock glaciers as shallow groundwater reservoirs, Austrian Alps

Rock glaciers are the most prominent landforms of alpine permafrost and comprise complex shallow aquifer systems in (high) alpine catchments. Recession analyses of groundwater discharge of four active rock glaciers that contain permafrost ground ice show that they have a base flow component of the order of a few liters per second, similar to that of a relict rock glacier in which permafrost ground ice is absent. This is related to an unfrozen (fine-grained) base layer with a thickness of about 10 m. Based on a threshold analysis of precipitation events and event water discharge, depressions atop the bedrock or the permafrost table seem to play only a minor role in storing groundwater. This important finding has rarely been documented, but is highly relevant for optimal groundwater resources management in sensitive (high) alpine catchments and ecosystems. All the rock glaciers analyzed here are located in the Austrian Alps and represent the nationwide sites where suitable discharge data are available. The analysis highlights the hydrogeological importance of these discrete permafrost-derived debris accumulations as complex shallow groundwater bodies with important—but limited—storage and buffer capabilities.

On the Ability of LIDAR Snow Depth Measurements to Determine or Evaluate the HRU Discretization in a Land Surface Model

To find the adequate spatial model discretization scheme, which balances the models capabilities and the demand for representing key features in reality, is a challenging task. It becomes even more challenging in high alpine catchments, where the variability of topography and meteorology over short distances strongly influences the distribution of snow cover, the dominant component in the alpine water cycle. For the high alpine Research Catchment Zugspitze (RCZ) a new method for objective delineation of hydrological response units (HRUs) using a time series of high resolution LIDAR derived snow depth maps and the physiographic properties of the RCZ is introduced. Via principle component analysis (PCA) of these maps, a dominant snow depth pattern, that turned out to be largely defined during the (winter) accumulation period was identified. This dominant pattern serves as a reference for HRU delineations on the basis of cluster analyses of the catchment’s physiographic properties. The method guarantees for an appropriate, objective, spatial discretization scheme, which allows for a reliable and meaningful reproduction of snow cover variability with the Cold Regions Hydrological Model—at the same time avoiding significant increase of computational demands. Different HRU schemes were evaluated with measured snow depth and the comparison of their model results identified significant differences in model output and best performance of the scheme which best represents measured snow depth distribution.

Beyond binary baseflow separation: a delayed-flow index for multiple streamflow contributions

Abstract. Understanding components of the total streamflow is important to assess the ecological functioning of rivers. Binary or two-component separation of streamflow into a quick and a slow (often referred to as baseflow) component are often based on arbitrary choices of separation parameters and also merge different delayed components into one baseflow component and one baseflow index (BFI). As streamflow generation during dry weather often results from drainage of multiple sources, we propose to extend the BFI by a delayed-flow index (DFI) considering the dynamics of multiple delayed contributions to streamflow. The DFI is based on characteristic delay curves (CDCs) where the identification of breakpoint (BP) estimates helps to avoid rather subjective separation parameters and allows for distinguishing four types of delayed streamflow contributions. The methodology is demonstrated using streamflow records from a set of 60 mesoscale catchments in Germany and Switzerland covering a pronounced elevation gradient of roughly 3000 m. We found that the quickflow signal often diminishes earlier than assumed by two-component BFI analyses and distinguished a variety of additional flow contributions with delays shorter than 60 d. For streamflow contributions with delays longer than 60 d, we show that the method can be used to assess catchments' water sustainability during dry spells. Colwell's predictability (PT), a measure of streamflow periodicity and sustainability, was applied to attribute the identified delay patterns to dynamic catchment storage. The smallest dynamic storages were consistently found for catchments between approx. 800 and 1800 m a.s.l. Above an elevation of 1800 m the DFI suggests that seasonal snowpack provides the primary contribution, whereas below 800 m groundwater resources are most likely the major streamflow contributions. Our analysis also indicates that dynamic storage in high alpine catchments might be large and is overall not smaller than in lowland catchments. We conclude that the DFI can be used to assess the range of sources forming catchments' storages and to judge the long-term sustainability of streamflow.

Identifying climate change impacts on water resources in Xinjiang, China

Water resources have an important role in maintaining ecological fuctions and sustaining social and economic development. This is especially true in arid and semi-arid areas, where climate change has a large impact on water resources, such as in Xinjiang, China. Using a combination of precipitation and temperature bias correction methods, we analyzed projected changes in different hydrological components in nine high-alpine catchments distributed in Xinjiang using the Soil and Water Assessment Tool (SWAT). The impacts of elevation, area and aspect of the catchments were analyzed. The results suggested an overall warming and wetting trend for all nine catchments in the near future, with the exception of summer precipitation decreasing in some catchments. The total runoff discharge, evapotranspiration and snow/ice melting will generally increase. Warming temperature plays a more important role in the changes of each hydrological component than increasing precipitation. However, northern Xinjiang was more sensitive to predicted precipitation changes than southern Xinjiang. These results also indicate that the overall increases in water resources are not sustainable, and the impacts of climate change are associated with the elevation, area and slope aspect of the catchments.

Groundwater Storage in High Alpine Catchments and Its Contribution to Streamflow

AbstractThere is limited knowledge about groundwater storage in alpine catchments, although it might strongly influence how these catchments react to earlier snowmelt due to climate change. The objective of the study was to develop and test a method to quantify seasonal groundwater storage in alpine catchments and evaluate how groundwater storage is related to hydrogeological properties. As representative water table observations are challenging to acquire in such environments, we used a water balance approach targeting the main snowmelt period when most groundwater recharge is expected to occur. Based on a detailed quantification of the snow water equivalent at the onset of snowmelt combined with discharge measurements, it is possible to quantify groundwater storage with a low uncertainty even if other terms of the water balance are less well constrained. The application of the method to an 11‐km2 research catchment revealed a large seasonal increase of groundwater storage by 300 mm or 45% of the premelt snow water equivalent. An independent quantification of groundwater storage depletion during the 7‐month‐long recession period provided a similar value of 330 mm, demonstrating that the stored groundwater is available to sustain streamflow. At the end of the recession, catchment outflow still amounted to 0.9 mm/day with a composite bedrock aquifer providing a disproportionally high share as demonstrated by hydrochemical data. The study demonstrates that high alpine aquifers can seasonally redistribute water and stabilize catchment outflow in an otherwise very dynamic environment and thus might strongly influence the response of such catchments to climate change.

Hydrological modelling in the anthroposphere: predicting local runoff in a heavily modified high-alpine catchment

Hydrological models within inflow forecasting systems for high-alpine hydropower reservoirs can provide valuable information as part of a decision support system for the improvement of hydropower production or flood retention. The information, especially concerning runoff, is however rarely available for the calibration of the hydrological models used. Therefore, a method is presented to derive local runoff from secondary information for the calibration of the model parameters of the rainfallrunoff model COSERO. Changes in water levels in reservoirs, reservoir outflows, discharge measurements at water intakes and in transport lines are thereby used to derive the local, “natural” flow for a given sub-catchment. The proposed method is applied within a research study for the ÖBB Infrastructure Railsystem division in the Stubache catchment in the central Austrian Alps. Here, the ÖBB operates the hydropower scheme “Kraftwerksgruppe Stubachtal”, which consists of 7 reservoirs and 4 hydropower stations. The hydrological model has been set up considering this human influences and the high natural heterogeneity in topography and land cover, including glaciers. Overall, the hydrological model performs mostly well for the catchment with highest NSE values of 0.78 for the calibration and 0.79 for the validation period, also considering the use of homogeneous parameter fields and the uncertainty of the derived local discharge values. The derived runoff data proved to be useful information for the model calibration. Further analysis, examining the water balance and its components as well as snow cover, showed satisfactory simulation results. In conclusion, a unique runoff dataset for a small scale high-alpine catchment has been created to establish a hydrological flow prediction model which in a further step can be used for improved and sustainable hydropower management.