HS2.1.5

Aufeis are produced annually in the rivers valleys in permafrost environment as the result of layer-by-layer freezing of groundwater flowing to the surface. Aufeis are widespread in the territory of the North-East of Eurasia (including the basins of large rivers in permafrost, such as the Yana, Indigirka, Kolyma, Anadyr, Penzhina Rivers and rivers of the Chukchi Peninsula (total area about 2 mln. km²).  They comprise an important water resource of the study region.

Based on the analysis of Landsat satellite images for the period 2013-2019 the number and total maximum area were estimated. As Landsat images do not always allow correctly assess the maximum area of aufeis, it was adjusted to get the maximum value before the beginning of ablation period for the assessment of aufeis resources. Total number of giant aufeis (>0.1 km²) formed by groundwater reaches 6217 with maximum area of about 4500 km² (in average 0.22 % of studied area). For each aufeis field the assessment of maximum ice reserves was conducted.  

The aufeis resources of the North-East are at least 10.6 km³ or 5 mm of aufeis runoff. The aufeis resources vary from 0.4 to 4.25 km³ (or 3.7 – 11 mm) for individual basins of large rivers. The greatest aufeis resources in absolute values are found in the Indigirka River basin. The contribution of aufeis runoff to streamflow in different seasons was calculated for 58 hydrological gauges (area 523 – 526000 km²). Aufeis annual runoff varies from 0.3 to 29 mm (0.1 – 22%, average 3.8%) with the share in winter runoff amount about 6 – 712 % (average 112%) and the spring freshet 0.2 – 43% (average 7.1%).

The influence of aufeis and glaciers on the water balance is compared – in general, the aufeis runoff exceeds the glacial runoff. The response of aufeis to climate change depends on different factors of the natural system. The dynamics of aufeis formation is directly related to the winter runoff, which changes are observed in different parts of the cryolithozone. The presented results are relevant for studying the impact of climate change on the hydrological cycle and its components in the permafrost regions of the Northern Hemisphere.

The study was carried out with the support of RFBR (19-55-80028, 20-05-00666) and St. Petersburg State University (project 75295879).

How to cite: Nesterova, N., Makarieva, O., Ostashov, A., Zemlianskova, A., Shikhov, A., and Alexeev, V.: Aufeis impact on the hydrological cycle in the North-Eastern Russia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-172, https://doi.org/10.5194/egusphere-egu22-172, 2022.

Since 2014, mountain communities in Ladakh, India have been constructing dozens of ArtificialIce Reservoirs (AIRs) by spraying water through fountain systems every winter. The meltwater from these structures is crucial to meet irrigation water demands during spring. However, there is a large variability associated with this water supply due to the local weather influences at the chosen location. This study compared the ice volume evolution of an AIR built in Ladakh, India with two others built in Guttannen, Switzerland using a surface energy balance model. Model input consisted of meteorological data in conjunction with fountain discharge rate (mass input of an AIR). Validation with drone’s ice volume observations shows the model performs well. Our results show that the conical shape of AIRs significantly reduce solar radiation-induced melt. The location in Ladakh had a maximum ice volume four times larger compared to the Guttannen site. However, the corresponding water losses for all the AIRs were more than three-quarters of the total fountain discharge due to high fountain wastewater. Drier and colder locations in relatively cloud-free regions are expected to produce long-lasting AIRs with higher maximum ice volumes. This is a promising result for dry mountain regions, where AIR technology could provide a relatively affordable and sustainable strategy to mitigate climate change induced water stress.

How to cite: Balasubramanian, S., Hoelzle, M., Lehning, M., Bolibar, J., Wangchuk, S., Oerlemans, J., and Keller, F.: The surprising weather conditions favoring artificial ice reservoirs (Icestupas), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4005, https://doi.org/10.5194/egusphere-egu22-4005, 2022.

Central Asia's river systems are largely fed by reliable snow and glacier melt which allows agricultural production in the dry lowlands and hydropower production. However, climate forcing is changing faster than ever and predictions of river discharge relying on past observations (as are currently applied by Central Asia’s Hydrometeorological Agencies) may no longer pass stringent quality criteria for good forecasts. There is a growing need for hydrological models for nexus studies and the feasibility study for small hydropower plants in the region. Central Asia is a large region with a sparse hydrometeorological monitoring network which makes it difficult to calibrate hydrological models with traditional methods. It is therefore good news that the amount of remotely sensed data or data from reanalysis products has been increasing in both quantity, and quality in the past few years. Such data offers a huge potential to improve hydrological modelling efforts but the required pre-processing of such data often exceeds the capacities of local stakeholders in Central Asia which does not allow them to valorize these data. As local workflows being digitized, tools need to be developed to facilitate the integration of improved model forcing and modelling techniques in applied hydrology. 

The present study uses the daily CHELSA-W5E5 v1.1 data set at daily 1km by 1km resolution, which is an ERA5 derivative with corrections for high mountain regions, to force degree-day melt models for glaciers and semi-distributed hydrological models using HBV. We combine the data from the Randolph Glacier Inventory in the region with recently available information on individual glacier elevation change (2000 - 2019), thickness and glacier discharge (2000 - 2016) to calibrate degree-day melt models for glaciers in Central Asia and to estimate daily glacier discharge until the end of the century for the 4 GCM models of the CIMIP6 climate projections with the highest priority for the region and for 4 socio-economic scenarios (i.e. 16 modeling scenarios). We also validate existing glacier volume, length and area scaling relationships for Central Asian glaciers from the literature. 

The glacier discharge time series is used as a source to a semi-distributed hydrological model to estimate the future water availability of the river Koksu,  a tributary to the Shakhimardan catchment in the south of the Fergana valley, and is a key input for the design of a small-hydropower plant. We further demonstrate a workflow to calibrate the snow components of the HBV modules in the hydrological model using the high mountain snow reanalysis product. 

We strive to streamline the use of such novel data products in the hydrological modelling process for Central Asian river basins by developing a suite of publicly available R packages & vignettes that facilitate data processing and modelling. The presented modelling effort is part of the ongoing EU Horizon 2020 project Hydro4U which aims at promoting sustainable small-hydropower solutions in Central Asia. The project's demonstration site of Shakhimardan is especially interesting because of its sensitive transboundary nature and the potential for socio-economic development in this remote enclave which is frequently cut off from power supply.

How to cite: Marti, B., Karger, D., and Siegfried, T.: Using recent public glacier data sets to calibrate glacier melt models and drive hydrological models in Central Asia: Facilitating hydrological modelling workflows, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7983, https://doi.org/10.5194/egusphere-egu22-7983, 2022.

Mountainous regions of the world are the source of water for large amount of population living downstream. This is also the case for Pamir Mountains in Tajikistan which produces majority of the water for the several countries in the region. Despite increasing impacts of climate change, last several decades, there have been critical decrease of number of monitoring networks in mountainous areas of Central Asia bringing high uncertainty to water resources management and planning. In this study we investigate the possibility to combine the remote sensing data, ground observations and a modelling approach to estimate discharge of Gunt River in the Eastern Pamir, Tajikistan. The Gunt River watershed is of great importance for the region, as about 60 settlements are concentrated along the entire length of the river, including the administrative city of Khorog. Two hydropower stations were built in the lower reaches of the river to provide electricity for the local communities. These headwater glacier-fed basins of Central Asia are particularly vulnerable; as climate change threatens water supply from glacier systems and increases evaporative losses, while demand to irrigation water and electricity is rising. This uncertainty in water supply can result, to a deterioration in the development of the economy and the quality of life in the region. Therefore, for sustainable electricity production and economic development in the region, a better understanding of water availability in the river, is required.

The aim of the study is to assess the characteristics of the flow regime of the Gunt River. We used "Hydrograph" hydrological model to simulate daily discharge of the Gunt River. The model algorithms combine physically based and conceptual approaches to describe snow and glacier melting and runoff generation processes. "Hydrograph" model has also successfully used to simulate river flow in Varzob River with similar climatic conditions in Tajikistan. Parametrization of the model including the assessment of precipitation distribution in the high mountainous areas is based on the data from the research watershed of the Varzob River with long term historical data availability. The verification and evaluation of the model was conducted based on the historical data (1970-1980) using data from the Dzhavshangoz and Khorog meteorological stations. The model performance and simulations for the recent period (2000-2020) were also evaluated by using the remote sensing data. The results have shown satisfactory quality with difference between the observed and simulated runoff does not exceed 2%. In general, the results of the paper confirm the possibility of using the deterministic model "Hydrograph" to simulate the daily water runoff in the river which is critical for hydropower and irrigation purposes. However, the lack of accurate information on distribution of precipitation in the catchment, significantly reduces the model results accuracy. The study was carried out with the support of St. Petersburg State University (project 75295879).

How to cite: Jarihani, B., Zemlyanskova, A., and Makarieva, O.: Simulation of river flow in the Gunt River Basin in Tajikistan, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8568, https://doi.org/10.5194/egusphere-egu22-8568, 2022.

Mountain catchments receive, retain, transport and release water that determines downstream ecology, landforms, hazards and human livelihoods. The hydrological regimes of such catchments are seasonally governed by the storage and release of water by snow and glaciers, and are modulated by the seasonality of liquid precipitation rates and energy fluxes. The wide range of climatic-topographical situations across High Mountain Asia creates a variety of hydrological regimes in this region.

In this study we apply a sophisticated modelling framework in two heavily glacierized catchments at opposite ends of the climatic spectrum in High Mountain Asia: an arid catchment with winter accumulation glaciers (Vaksh headwaters, Northern Pamir) and  a humid catchment with spring-summer accumulation (the Upper Parlung, South-Eastern Tibet). Both catchments span an elevation range of several thousand metres and a number of vegetation zones. To study the concomitant response of the cryosphere and biosphere, we use a land surface model with a mechanistic and energy-balance-based representation of both the cryosphere and biosphere, at 100m spatial and hourly temporal resolution. We force the model with statistically-downscaled and bias-corrected reanalysis data. For model setup and independent validation, we leverage extensive in-situ observations, collected at both sites. We complement those with spatial datasets, such as ice-dynamics-corrected glacier mass balance, snow cover, and vegetation indices.

We analyse the differences in the catchment water balance and flux partitioning between these two study sites in terms of energy fluxes, snow and glacier accumulation and ablation, vegetation distribution and phenology, and give special attention to patterns of evapotranspiration (ET). Using the model we determine the importance of supraglacial debris cover, widespread in the catchments, and its role in modifying the glacier mass balance under different moisture regimes. We also determine the links between snow melt seasonality, glacier mass balance, plant productivity and the responses in catchment runoff. This work presents one of the first applications of hyper-resolution land surface modelling to understand biosphere-cryosphere-hydrosphere interactions in High Mountain Asia, and will provide insights into the skills and drawbacks of such modelling approaches.

How to cite: Fugger, S., Buri, P., Shaw, T. E., Fatichi, S., Miles, E. S., McCarthy, M., Fyffe, C., Kneib, M., Jouberton, A., and Pellicciotti, F.: Modelling blue-green water fluxes in mountain headwaters at the climatic ends of High Mountain Asia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11243, https://doi.org/10.5194/egusphere-egu22-11243, 2022.

Antarctica has been significantly warming in the last decades. According to climate projections, the increase in air temperature is likely to continue in the future, which will affect runoff dynamics due to glacier retreat and changes in snow cover. Despite the large changes in glacier volume in some parts of Antarctica, little is known about streamflow dynamics and contribution of different water sources to total catchment runoff. Therefore, the objective of our research was to 1) describe runoff dynamics in six catchments located in the Ulu Peninsula, James Ross Island, which represents one of the largest deglaciated areas in Antarctica and 2) to assess the inter-annual variations in glacier melt, snowmelt and potentially rain contributions to runoff over the years 2015 – 2021. The study catchments have different glaciation, and thus considerable diurnal regime of streamflow. Streamflow measurements performed in 2018 austral summer were used to describe the streamflow dynamics of the six catchments. Additionally, a conceptual bucket-type catchment model has been set-up for two of the six catchments, first partly glacierized and second without glacier coverage. In-situ measurements of glacier ablations (2015–2019) and daily precipitation and air temperature partly measured directly at automatic weather stations located in the catchments and partly derived from ERA5-land reanalysis were used as model inputs. Since water level and streamflow data are limited for the study area, a genetic algorithm procedure was used to calibrate the model.

Direct streamflow measurements performed in 2018 austral summer showed the largest variations in Triangular and Shark Streams, which represent the most glaciated catchments among all study catchments. The less variable streamflow was found in Algal Stream, a completely deglaciated catchment. Highest streamflow was recorded in late afternoon, whereas minimum streamflow was recorded in late night or early morning which suggests the strong diurnal regime. In glacierized catchments, the streamflow responded fast on increased air temperature and solar radiation during day. In contrast, soil water stored in the active layer and snow patches mostly controlled streamflow dynamics in deglaciated catchments. Besides, the runoff response was somewhat delayed in these catchments compared to glaciated catchments due to temporal subsurface storage. The above findings were proved also by model simulations, which extended streamflow data for the period 2015-2021. Besides, the simulations showed different glacier and snow contributions to total runoff in study catchments and also different times of streamflow responses to changes in meteorological inputs in combination with different catchment storages which influence runoff delays.

How to cite: Jenicek, M., Nedelcev, O., and Kavan, J.: Changes in glacier and snow melt contributions to streamflow in James Ross Island, Antarctic Peninsula, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2690, https://doi.org/10.5194/egusphere-egu22-2690, 2022.

Rapid glacier retreat leads to the emergence of new rocky landscapes. The common assumption of the presence of bare bedrock underlying glaciers and the closely related assumption that glacier and snow melt manifest themselves essentially as surface runoff, is challenged by the rapid sediment accumulation and the formation of geomorphological landforms where water may be infiltrated and stored. Although some studies have provided rough estimates of groundwater storage and release in high elevation catchments, the actual reservoirs providing baseflow discharge are difficult to identify. While the combined effect of future glacier decline and earlier snowmelt are well recognized, it remains unclear how the rapid hydrogeomorphological transformations will modify the potential groundwater stores.

In this study we will provide results of a case study of a glaciated catchment in the Swiss Alps. Firstly, we will discuss, based on a simple modelling approach, the hydrological functioning of different landforms and show to which extend each hydrological unit is currently contributing to groundwater storage. We will then focus on a detailed assessment of the hydrological dynamics of an outwash plain using a 3D Modflow modelling approach. We will show how such a small fluvial aquifer is connected to other landforms and how it can maintain high storage during much longer time scales than other landforms due to strong river-groundwater interactions. Even though the current storage of the outwash plain is limited, we will discuss how glacier retreat may increase its relative contribution in the future. Finally, we will focus on the remaining unidentified storages in our field study and we will provide some geochemical analysis of their potential location and finally conclude with a summary of the hydrogeological functioning of a rapidly deglaciating proglacial catchment.

How to cite: Müller, T., Schaefli, B., and Lane, S. N.: On the identification of hydrogeological reservoirs in a proglacial catchment and their future groundwater storage, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-859, https://doi.org/10.5194/egusphere-egu22-859, 2022.

Glaciers are key components of the Asian water towers and provide water to large downstream communities for domestic, agricultural and industrial uses. In the Nepal Himalaya, the Indian Summer Monsoon dominates climate, and results in a complex meteorology and simultaneous accumulation and ablation that complicate the quantification of snow processes. Assessing solid precipitation input, especially in the upper accumulation area (> 6000 m a.s.l.), remains key to understanding recent mass losses. Catchment-scale glacio-hydrological modelling in the Himalaya has to date mostly relied on temperature-index or intermediate-complexity enhanced temperature-index methods, but recent studies have shown that such approaches can lead to inaccurate amounts of melt, especially at high elevations where refreezing, sublimation and avalanches influence the snow depth variability. The Trakarding–Trambau Glacier system experienced significant mass loss over the last decades, and recent field measurements of meteorology and glacier change present the opportunity to examine these problems with physically-based and spatially-resolved atmospheric and glacio-hydrological modelling.

We combine a novel non-hydrostatic atmospheric model (NHM; atmospheric core of the cryosphere-oriented regional climate model NHM-SMAP) and an advanced land surface model at cloud-permitting hyper-resolution (~ 100 m) to explore the role of snow processes in the water balance of this glacierized catchment. We force the land-surface model of the catchment with dynamically downscaled, hourly outputs from  NHM for the 2018-2019 hydrological year. We evaluate the NHM output using available in-situ meteorological observations  and evaluate the land surface model skills and process representation with in-situ mass balance observations, remotely sensed surface elevation change and snow cover. Coupling of the two types of models is unprecedented in the Himalaya, and holds promise to reveal processes that cannot be explicitly assessed by simpler models or forcing data. We investigate the contribution of sublimation and precipitation partition to the glacier mass balance and catchment runoff, and analyze the difference in mass balance and its drivers between the debris-covered and debris free-glaciers. To place this very novel type of simulations into the context of current research, we compare our NHM-forced simulations with simulations forced by station data and ERA5-Land reanalysis.  Finally, we evaluate the effect of spatial resolution (50 m, 100 m, 200 m) on model performance and process representation. 

Our results highlight the potential of sophisticated models based on the calculations of energy and mass fluxes to unravel the complex processes that shape the response of Himalayan catchments, and provide an assessment of their skills as a function of spatial resolution.

How to cite: Jouberton, A., Sato, Y., Hashimoto, A., Niwano, M., Shaw, T. E., Miles, E. S., Buri, P., Fugger, S., McCarthy, M., Fujita, K., and Pellicciotti, F.: Combining high resolution atmospheric simulations and land-surface modelling to understand high elevation snow processes in an Himalayan catchment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8896, https://doi.org/10.5194/egusphere-egu22-8896, 2022.

In the face of climate change and socio-economic developments, water scarcity is a tremendous challenge. In particular, a significant portion of the world’s population rely on water from cryospheric sources such as snow and/or glacier fed mountain rivers. However, the data coverage in mountain regions is often sparse, which substantially hampers the assessment of climate impacts on hydrological systems. Furthermore, the large impact of climate change on snow and glacier hydrology require physically sound hydrological models.

The gap between the growing need for sustainable water resources management, low data availability and uncertain hydrological projections calls for new approaches. To close this gap, a modular modelling framework was developed to foster the use of complementary data sets in hydrological models. The framework enables a flexible combination of remote sensing and in situ data for model calibration and validation providing a multi-model and multi-input ensemble. The additional consideration of data regarding snow covered area, snow water equivalent and soil moisture allows for physically meaningful representations of key hydrological processes, even in the absence of a dense network of meteorological stations and river discharge gauges.

Case studies in the European Alps (Inn and Adige/Etsch) and in Central Asia (Ala Archa and Karadarya) illustrate the high value of this approach for physically meaningful representations of the hydrological processes. Furthermore, a high impact of glacier retreat on future water availability was found for the highly glacierised basins of the Fagge river in the upper part of the Inn basin and the Ala Archa river.

How to cite: Schattan, P., Winter, B., van der Laan, L., Gafurov, A., Meißl, G., Cuozzo, G., Greifeneder, F., Premier, V., Huttenlau, M., Stötter, J., and Förster, K.: The value of complementary data for physically consistent hydrological models in mountain regions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12251, https://doi.org/10.5194/egusphere-egu22-12251, 2022.

Late in the ablation season the snow cover gets patchy. The resulting surface temperature gradients and the lateral advection of heat over the partial snow cover engage different atmospheric processes such as the development of stable internal boundary layers (SIBL) or atmospheric decoupling close to the snow surface. Even though lateral advection of heat and the resulting atmospheric phenomena significantly influence the energy balance of the melting snow pack in spring, there is a lack of understanding and, thus, they are not explicitly taken into account in snow melt runoff models yet.
To gain further understanding of those complex near-surface atmospheric processes at the meter to sub-meter scale, we conducted a comprehensive field campaign at an alpine research site. The field campaign included the measurement of meteorological parameters, snow ablation pattern, and turbulence using eddy-covariance sensors. Furthermore, we applied a novel experimental method. Two thin synthetic screens were vertically, in parallel to the prevailing wind direction, deployed across the transition from bare ground to snow covering a horizontal distance of 6m. The screens quickly adapt to ambient temperature and, thus, serve as a proxy for the local air temperature. Using a high resolution thermal infrared camera, a 30Hz sequence of infrared frames was recorded. The recorded air temperature fields capture the dynamics of turbulent eddies adjacent to the surface depending on different parameters such as wind speed or the snow coverage. A thin SIBL develops above the leading edge of snow patches possibly protecting the snow surface from warmer air above. However, sometimes the warm air entrains into the SIBL and reaches down to the snow surface adding further energy to the snow pack.
In an attempt to quantify exchange processes from those dynamics, we developed a method to estimate high-resolution, near-surface 2D wind fields from tracking the air temperature pattern on the screens. A spatial correlation search yields the shift of an eddy or air parcel between two subsequent frames, using air temperature as a passive tracer. From this shift, the wind speed can be calculated at a very high spatial resolution. Vertical profiles of air temperature, horizontal, and vertical wind speeds across the transition from bare ground to snow can be evaluated with the advantage of a high spatial (0.01 m) and temporal (30 Hz) resolution.
The screen measurements and wind speed estimation are validated with 3D short-path ultrasonic anemometer measurements close to the surface, which provide further insights into the turbulence characteristics close to the snow surface.
With the high spatio-temporal resolution data we aim to better understand and quantify small scale energy transfer processes over patchy snow covers and their dependency on the atmospheric conditions. This will allow to improve parameterizations of these processes in coarser resolution snow melt models.

How to cite: Haugeneder, M., Lehning, M., Jonas, T., and Mott, R.: A novel method to understand the interaction between a patchy snow cover and the adjacent atmosphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9049, https://doi.org/10.5194/egusphere-egu22-9049, 2022.

This study investigates satellite-based information driven snow accounting routines to simulate snow processes in mountainous regimes that are inherently associated with data scarcity. Simple, independent and parsimonious snow accounting routines that are fully driven by remote sensing (RS) information such as the land surface temperatures and snow-cover information along with distributed temperature index-based snow-melt models, are presented. RS based snow-cover distribution does not only provide the crucial information on areal extent of snow, but can also be a highly imperative proxy for the precipitation accumulations in these data scarce regions, as the availability and resolution of the data doesn’t depend on the mountainous terrain. These models are calibrated independently on the snow-cover distribution, can be coupled with any rainfall-runoff models to simulate “snow-processes informed” discharge and are flexible enough to be extended to a wide geographical extent. These models, in addition to simulating the snow accumulation and melt processes, also use the timing of snow appearance and disappearance. This accounting of snow can be inverted to obtain seasonal precipitation estimates in data scarce snow dominated regions, which can be a very crucial information for water resources planning. Specific results pertaining to the validation of the models in Switzerland and southern Germany (ungauged scenario) are shown. 

How to cite: Gyawali, D. R. and Bárdossy, A.: Can fully satellite-products-driven simple models account for snow processes in data scarce regions?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8570, https://doi.org/10.5194/egusphere-egu22-8570, 2022.

The MODIS sensor on the NOAA Terra satellite has been providing daily information on global snow cover with a nominal spatial resolution of 500 m since February 2000. Since July 2022, this sensor is also located on NOAA's Aqua Satellite in orbit. The daily snow cover product of both platforms constitutes the basis for the DLR Global SnowPack (GSP) processor.

In the course of the GSP processing, the daily data of both MODIS sensors are merged and data gaps (e.g., clouds or polar night) are interpolated over 3 days. From a digital elevation model, the snow height (elevation above which only snow occurs), as well as the snow-free height (elevation below which no snow occurs) are determined. Heights above or below these thresholds are filled accordingly. Finally, remaining gaps are gradually filled by the values of preceding days. Since the year 2022, the daily cloud free GSP data has been made available in near real time (3 days delay due to the preprocessing of the NSIDC) via the GeoService Portal of the Earth Observation Center (EOC).

The rapid provision of the information on global snow coverage allows completely new applications of time-critical questions. These include hydrological estimates to what extent the snow conditions in the catchment area influence the drainage behavior. In addition to the satellite data, meteorological and hydrological data of the past 20 years are used to estimate the impact of a changing snow cover on the runoff. In the course of climate change, a delayed onset of snow cover and an earlier snowmelt is likely. Warmer winters also increase the risk of Rain-on-Snow events, which cause a strong increase in the outflow and have more dramatic ecological effects.

We will present results for selected river catchment areas with a special focus on hydrological extreme events (droughts and floods), and when their occurrence has been shown early in the development of seasonal snow coverage. Our goal is to provide an automatic early warning system based on near real time GSP for large river catchments with nival-influenced drainage regimes.

How to cite: Roessler, S. and Dietz, A.: Use of near real-time cloud-free MODIS snow cover data from DLR’s Global SnowPack for the early forecast of extreme hydrological events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9205, https://doi.org/10.5194/egusphere-egu22-9205, 2022.

Real-time flood forecasting and other hydrological applications in mountainous areas require a good understanding and accounting of snow accumulation and melt. The CemaNeige snow model is currently used with the GRP hydrological model by most regional operational services in France to produce floods forecasts with lead times varying from a few hours to a few days. The snow model is based on a degree-day approach and needs limited inputs (precipitation and air temperature) spatialized on altitude bands over the catchment. It was initially developed on snow-dominated catchments by Valéry et al. (2014) using only streamflow series as calibration information. The model was then adapted by Riboust et al. (2019) to better simulate snow-covered areas as estimated by MODIS satellite images. These data were used as a secondary source of information for parameter calibration. All these developments were made at the daily time step. However, for real-time purposes, the outputs from the snow model are often needed at a finer time step, typically hourly or sub-hourly.

Here the transposability and the consistency of the CemaNeige model were studied across a range of time steps, from hourly to daily, on a set of snow-influenced catchments. This follows previous works on the hydrological model to improve its consistency across time scales (see e.g. Viatgé et al., 2019). Several questions were addressed:

• To which extent are the outputs of the snow model and its parameters consistent across various time steps?
• Is the current snow model complexity (structure and parameters) sufficient to simulate the snow influence at the catchment scale at sub-daily time steps?
• Can we expect better results by running the snow model at sub-daily time steps than by disaggregating the outputs of the snow model run at the daily time?

The answers to these questions will be presented based on a comprehensive testing scheme and a set of numerical criteria. Perspectives in terms of operational use will be discussed.

How to cite: Véron, A.-L., Tilmant, F., Thirel, G., Bourgin, F., Perrin, C., and Zuber, F.: Investigating the impact of temporal resolution on a snow model used for hydrological modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9453, https://doi.org/10.5194/egusphere-egu22-9453, 2022.

The study focuses on the changes in the regime of the four High Arctic catchments in the last 40 years taking into account different percentages of glacial coverage. The selected catchments include Breelva, Ariebekken, Bratteggbekken and Fuglebekken with glacial coverage of 61%, 11.8%, 5.9% and 0% respectively.

The flow time series in the selected catchments were simulated using a glacio-hydrological model calibrated and validated based on the available archival hydro-meteorological data.

In the second step, the reconstructed flows from the period 1979-2020 were filtered and smoothed. This allowed for delineation of the seasonal pattern by filtering out small scale variability. The changes in flow regime were assessed with trend analysis for each calendar day.

Similar trends of change were detected in all studied catchments due to similar locations in the SW Spitsbergen and climatic conditions. These changes include the earlier onset of snowmelt driven floods, large increases in autumn flows, prolongation of the hydrologically active season (starts earlier and lasts longer), decrease in flows in the latter half of June and the early part of August (except for the Breelva catchment). These changes resulted in the changes of flood regime from snowmelt-dominated to the bi-modal with peaks in both July/August and September.

A comparison of the changes between the four catchments indicated differences in the magnitude of hydrological response depending on the percentage of glacial coverage in the catchments. The larger the glacierized area is, the larger the changes in the flow regime. The estimated changes are larger than observed in lower latitudes due to larger changes in climatic conditions.

How to cite: Osuch, M., Wawrzyniak, T., and Łepkowska, E.: Assessment of streamflow trends in snow and glacier melt dominated catchments of SW Spitsbergen, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2805, https://doi.org/10.5194/egusphere-egu22-2805, 2022.

Although warming temperatures should intuitively lead to faster snowmelt, some studies suggest that melt rates might be slower in a warming world. This assumes that typically deep snowpacks are thinning and become isothermal earlier in the season when less solar radiation is available for melt. Investigating these changing snow dynamics is challenged by a lack of observations on water content of the snowpack, the Snow Water Equivalent (SWE). However, high quality observations of snow depth are generally more available in both space and time, even at higher elevations. Here we present a new dataset of historical SWE time series over the Northern Hemisphere, including a wide variety of climates. These time series are obtained converting historical ground-based snow depth time series to SWE by using the DeltaSNOW model. For the conversion to work over a range of climates, we apply a regional calibration of model parameters based on climatological data and provide model performance and uncertainty estimates. For >2.000 sites characterised by seasonal snow, we investigate changes in total snow accumulation, timing of snowmelt and melt rates for the period 1980-2020. Large decreases in total melt and earlier melt timing are widely observed. However, trends in snowmelt rates are generally weak and spatially inhomogeneous. Slower snowmelt in a warmer world occurs mostly on deep snowpacks that have been heavily depleted and where the number of days with melt has not significantly changed, making melt rates slower. However, both faster and slower melt are observed on sites where both the amount of melt and number of melt days have decreased. We provide an analysis of the causes for the spatial and temporal variability in trends. We find that trends can differ depending on the definition of melt rate and peak SWE, and that the drivers of the trends differ over different climates. Strong warming generates large melt events during the late accumulation season, challenging the commonly used definition of peak SWE and making it harder to compare the snowmelt dynamics of the past and the current climate. We note that focusing on melt rate change might mask important effects on melt timing and magnitude, because a proportional reduction in total melt and number of melt days can lead to no change in melt rate.

How to cite: Fontrodona-Bach, A., Larsen, J., Woods, R., Schaefli, B., and Teuling, R.: How are snowmelt rates changing across climates? Insights from a new Northern Hemisphere SWE dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11859, https://doi.org/10.5194/egusphere-egu22-11859, 2022.

Mountain catchments behavior is largely governed by snow accumulation and melting regime. These intricate water fluxes sustain the streamflow response for several months and maintain the surface moisture until late summer. The melting snow slowly percolates to the subsurface recharging underground reservoirs which later sustain the ecosystem during the dry periods. During the summer periods in mountainous catchment the rain contributes more to the surface runoff because of steep slopes. In this study, we hypothesise that middle elevation mountain catchments under a warming climate will shift from a snow hydrological recharging behavior to a flash flood behavior. We used ParFLOW-CLM, a fully distributed physical based surface-subsurface coupled integrated hydrological model to show how much water budget partitioning will change on a small subalpine mid-elevation (2000-2200 m) catchment at col du Lautaret (France). With a 10 m hyper-resolution setup, ParFLOW-CLM helps us to distinguish between the Hortonian and Dunian runoff along with the velocity of water movement in the x-y-z direction. Further, we applied a Lagrangian particle tracking model, EcoSLIM, to track the location, movement and residence time of the snow and rain sources. After running the model for the present climate we selected CMIP6 climate model projections that lead to temperature rise from 1 °C to 2.5 °C. The present climate results show that the snowmelt contributes to 90 % of subsurface source particles compared to rain and has a higher residence time in the catchment. These snow particles along with sustaining the streamflow also help in providing water to plants and evapotranspiration during the dry periods. Under warmer climates, the snow to rain ratio decrease leads to more surface runoff and less recharge to the subsurface. The decrease in subsurface recharge leads to reduced surface moisture in the dry season, which directly impacts the evaporation and transpiration through the vegetation. Hence, the rapid global warming leads to a decrease in the snow and subsurface storage which may impact downstream communities in terms of water availability, and at the same time, decrease water availability for the mountain vegetation through reduced surface moisture. In conjunction, the overall mountain ecosystem gets adversely impacted.

How to cite: Gupta, A., Voisin, D., and Cohard, J.-M.: Snow/rain source mixing and residence time modeling in a sub-alpine mountainous catchment under global warming, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7894, https://doi.org/10.5194/egusphere-egu22-7894, 2022.

The retreat of glaciers, particularly in catchments where they were extensive, has important consequences for future water management and in particular for hydropower production. Glaciers store water in liquid or solid form on short- to long-term time scales and thereby affect the precipitation-runoff behavior of heavily glacier-covered catchments from interannual and seasonal to sub-daily time scales. While today reliable predictions can be made about the change in quantity and timing of glacier melt runoff, the consequences of glacier retreat for summer rainfall events remain unclear. By intensively monitoring streamflow during the summer months in an area with a high degree of glacier cover, we can fill this research gap. Our key research question is hereby how strongly the glacier smooths out the observed rainfall peaks and how the smoothing effect evolves over the course of the glacier melt season. The answer to this question is crucial to anticipate potential water and sediment management challenges under intense summer rainfall events in catchments with strongly reduced glacier-cover.

In this presentation, we share results from the Oberaargletscher catchment (10 km², elevation 2310 - 3630 m a.s.l.) located in the Swiss Alps that was intensively monitored from July to October 2021. The monitored variables include precipitation, streamflow, electric conductivity, stable isotopes of water, water and air temperature. Based on the high resolution streamflow data, we analyze the influence of summer rainfall events on the runoff response, and in particular on the runoff lag time and the hydrograph shape. The obtained results are related to potential driving variables including the extent of snow cover and of the glacial drainage system, the precipitation intensity and air temperature.

We will furthermore discuss to what extent the rainfall fraction in the streamflow can be quantified based on streamflow observations alone, which will give valuable insights for future measurement campaigns at comparable sites.

How to cite: Schaefli, B., Binkert, L., Benelli, L., Ceperley, N., Leiser, P., Baumgartner, J., Berger, B., and Wyss, K.: What role do glaciers play in smoothing streamflow during summer rainfall events? A case study from the Swiss Alps., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9540, https://doi.org/10.5194/egusphere-egu22-9540, 2022.

Glacier meltwater is a vital component of river discharge in the Peruvian Andes, providing an important source of dry season runoff for communities, agriculture and fragile mountain ecosystems. Previous hydrochemical and modelling studies have identified the importance of glacier meltwater to downstream runoff and analysis of runoff records suggest ‘peak water’ has passed already. These studies, however, have been confined to the Rio Santa basin and the models applied have simplifications in their treatment of glacier melt and evolution. Our objectives are to i) determine the past glacier contribution to streamflow, determining when peak water passed and quantifying the recession of the glacier contribution to runoff; ii) predict future glacier evolution and its consequent impacts on water resources; and iii) to compare the hydrological response of catchments in central and southern Peru and establish their future response to glacier recession.

To meet these objectives we have applied the hourly physically-oriented, glacio-hydrological model TOPKAPI-ETH to two catchments in the Peruvian Andes: the Rio Santa in the Cordillera Blanca (4953 km²) and the Rio Urubamba draining the Cordilleras Vilcanota, Urubamba and Vilcabamba (11048 km²), the two most glacierised catchments in Peru. Past glacier recession has been substantial and future temperature rise is likely to lead to further glacier retreat, threatening water security in both regions. The model is forced with hourly atmospheric inputs from high-resolution (4 km), bias-corrected Weather Research and Forecasting (WRF) model outputs, which are downscaled to the TOPKAPI-ETH model resolution (100 m), using temperature and precipitation lapse rates defined from the WRF data for all sub-catchments of each domain. To reduce equifinality in model parameters we calibrate the model in a stepwise manner, using a combination of in-situ and remotely sensed data. Melt model parameters are calibrated based on full energy balance simulations at five sites across the two domains, with albedo parameters also derived from calibration with measured data. We calibrate the temperature decrease over glacier ice in an iterative manner using the WRF air temperatures, observed weather station data and the energy balance model outputs. Precipitation undercatch is a key unknown but it is constrained by careful comparison of modelled glacier surface mass balances with those inverted from remotely sensed data, while hydrological routing parameters are identified through calibration against hourly runoff records collected within the catchments. 

We use the model outputs to unravel the water balance characteristics of both catchments, their main drivers, including the relative importance of glacier and snow melt components within catchment runoff, and how they vary seasonally, inter-annually and through time due to glacier recession. By applying the model to two catchments with contrasting climatologies and glacier characteristics we are also able to disentangle the reasons for their distinct future trajectories. 

How to cite: Fyffe, C. L., Potter, E., Orr, A., Shaw, T. E., Loarte, E., Medina, K., Miles, E., von Ah, F., Baraer, M., Cochachin, A., Castro, J., Montoya, N., Westoby, M., Quincey, D. J., and Pellicciotti, F.: Modelling the glacier-hydrology of two large catchments in the Peruvian Andes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10540, https://doi.org/10.5194/egusphere-egu22-10540, 2022.

Streamflow of the river Rhine and its tributaries consists of rain, snowmelt and glacier ice melt components. The amounts of these components have already changed in the past years due to climate warming. Hydrological modelling until the year 2100 was carried out for the Rhine catchment using an ensemble of downscaled and bias-corrected climate projections and a chain of hydrological models considering cryosphere changes. The modelled daily streamflow components provide unique insight into the hydrological processes of a warmer future at different spatial and temporal scales down to individual events. In the Rhine basin, projected precipitation for the RCP8.5suggest wetter winters and drier summers, but annual net precipitation change differs in the up- and downstream regions with a net increase projected only in the lower basin. The model experiments suggest that the rain component of streamflow will dominate the seasonal variability in the future more than in the past. Snow will provide less seasonal water storage and melt earlier in winter and spring. Glaciers will continue their retreat with differences among individual glaciers and the ice melt component in the main river Rhine is projected to retreat fast with almost no ice melt component left at the end of the century. As a consequence, in particular low flows in downstream reaches will exacerbate due to the lack of buffering snow and ice melt; esp. during hot summer drought years. This change will affect environmental flows, water use for energy production, navigation and other water uses, changes of which can be estimated from the modelled scenarios. Overall, streamflow variability and extremes will increase. Despite propagated uncertainties from a range in the downscaled and bias-corrected climate model input, the projected changes are substantial and are a clear mandate to reconsider water uses and enhance river protection goals.

How to cite: Stahl, K., Weiler, M., Van Tiel, M., Kohn, I., Haensler, A., Freudiger, D., Seibert, J., Moretti, G., and Gerlinger, K.: Climate change impact on rain, snow and glacier melt components of streamflow for the river Rhine: synthesis of a model experiment and relevance for water use, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11271, https://doi.org/10.5194/egusphere-egu22-11271, 2022.