HS2.1.7
Orals: Wed, 26 Apr | Room 2.44
In high-mountain environments such as the European Alps, glaciers are an important component of the water cycle. With ongoing climate change, this role seems in jeopardy though: glaciers in Switzerland, for example, have lost more than 30% of their volume since the year 2000, and future projections indicate a future with ice-free landscapes if society was to fail in taking immediate and stringent climate action.
In this contribution, the role of glaciers as water resource will be reviewed. By taking the Swiss Alps as an example, their contribution to regional water supplies and usage will be quantified. A focus will be on the glaciers’ role in providing water during dry periods, as well as the relevance of glacier melt in the context of hydropower production.
Based on both extended glaciological measurements collected in the frame of the Glacier Monitoring Switzerland (GLAMOS) program and daily glacier melt data retrieved through automated methods, we will for example quantify the meltwater contribution that glaciers had in the extremely hot summer 2022. The year saw a record-high 6% glacier volume loss and we show that individual heat waves contributed over-proportionally to this amount: 35% of the total summer ice loss, for example, occurred in the 25 hottest days, delivering a water amount that corresponds to 56% of the total summer melt seen on average for the past decade.
Such phases of extreme melt can also be challenging for water resource management. In high-alpine rivers, where annual glacier contributions to streamflow were up to 80% in 2022, existing hydropower infrastructure can for example be overwhelmed. For a country that sees some 2.1kWh of hydro-electricity being produced for every cubic meter of glacier melt, this raises questions about future management strategies, and calls for robust projections of future streamflow.
How to cite: Farinotti, D., Cremona, A., van Tiel, M., and Huss, M.: Glaciers’ role as water resource in the Swiss Alps, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11164, https://doi.org/10.5194/egusphere-egu23-11164, 2023.
Assessments of glacier retreat impacts on water resources are often carried out using hydrological models calibrated using stream discharge time series. Because long-term discharge measurements are scarce in different regions of the world, models’ outcomes are analyzed assuming implicitly that stream discharge evolution projections at the outlet of a watershed affect the entire drainage area following a uniform pattern. In the present study, building on the learnings from the peak water analysis we performed in 2012, we explore the heterogeneity in Rio Santa sub-watersheds responses to deglaciation. The future of water resources at each watershed is projected by applying the peak water model with the latest glacier area estimations. The resulting map of the projected water availability across the Rio Santa watershed is then overlayed with previous works and literature-based water quality and demand maps.
Results show that, while glaciers are losing their hydrological influence across the Cordillera Blanca, gaps open between water availability and demand for water at different levels of the watershed. Moreover, the dry season share of polluted sub-watersheds into the Rio Santa discharge increasing due to glacier retreat, water quality evolution will add up to the challenge of sharing an already scarce resource.
Our study suggests that deglaciation in the tropical Andes affects populations and economic activities in a complex, disparate and evolutive way. Therefore, anticipating glaciers retreat redistribution of the water resources requires integrating hydrological, chemical, biological, economic, and sociological water resources aspects in locally grounded studies.
How to cite: Baraer, M., Mark, B., and McKenzie, J.: Toward a glacier retreat driven redistribution of water resources, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10137, https://doi.org/10.5194/egusphere-egu23-10137, 2023.
After several decades of climate change impact studies on high alpine environments, the hydrological community has come to a good agreement on how cryosphere-dominated streamflow regimes will evolve in the future. And observed streamflow regime trends largely confirm existing predictions for Alpine environments. Many of these predictions are based on models that lack a detailed representation of hydrological processes that occur below the snowpack or the ice-cover; these model focus on the representation of snow accumulation and snow and ice-melt and use simply methods to transform liquid water input into streamflow.
However, the gradual reduction of snow cover duration might significantly affect streamflow generation processes in Alpine environments, e.g. via the evolution of spatial and temporal patterns of groundwater recharge or of hydrologic connectivity and of the related seasonal stream network structure.
In this presentation, we will synthesize what we learned about the interaction of the cryosphere with streamflow generation from our multiyear process studies in two high Alpine catchments in Western Switzerland, the Vallon de Nant and the Otemma glacier catchment. We elaborate perspectives for future field work but also for hydrological model development.
How to cite: Schaefli, B. and Ceperley, N.: When snow and ice are gone: beyond hydrological regime changes, what are the nuts and bolts of future streamflow generation processes?, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15908, https://doi.org/10.5194/egusphere-egu23-15908, 2023.
Summer 2022 broke numerous glaciological, hydrological and climatological records in Europe. Dry and warm conditions led to extreme low-water levels and problems with water supply. The hot summer in combination with little snow in winter was disastrous for the Swiss glaciers; they never lost as much volume in the century-long observational record. At the same time, this massive glacier melt meant an alleviation of the downstream hydrological drought situation. Glacier contributions to streamflow during hot and dry periods, as well as their changes due to glacier retreat are, however, poorly quantified.
In this study, we characterize the glacio-hydrometeorological extremeness of the hydrological year 2022 in Switzerland and compare it with other exceptional years in the past. Observational streamflow records from about 80 stations along glacier-fed rivers were analyzed, together with (i) temporally downscaled and spatially extrapolated glacier mass balance observations, as well as (ii) temperature and precipitation information. Results show that precipitation and temperature were exceptional, but there have been years since 1961 that were warmer or drier. However, the combined effect of low precipitation and high temperatures led to record-low summer flows throughout Switzerland, apart from the Rhone river, the upstream part of the Aare river, and a few high-elevation catchments. Catchments with a glacier cover of more than 20% even resulted in above normal summer streamflow in 2022.
The annual relative meltwater contribution from glacierized areas ranged from a few percent up to 80% of the total streamflow among the catchments and equaled up to double the mean contribution estimated for the period 1981-2010. Although 2022 glacier volume losses broke records, only a few catchments showed a record amount of glacier melt water contribution to streamflow. This may hint that for most catchments, glacier retreat is dominating the melt response to extreme warm conditions, instead of differences in the respective meteorological conditions. This process reduces the crucial capacity of glaciers to alleviate downstream drought conditions. Overall, the study highlights the need for an integrated analysis of meteorological, hydrological and glaciological data to understand the spatiotemporal dynamics of extreme dry and warm years.
How to cite: Van Tiel, M., Huss, M., Zappa, M., and Farinotti, D.: A glacio-hydrological perspective on the extreme year 2022 in Switzerland, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4515, https://doi.org/10.5194/egusphere-egu23-4515, 2023.
Alpine glaciated catchments are rapidly changing with glacier retreat. Combined with future earlier snow melt and more liquid precipitation, the importance of high alpine catchments to provide essential water resources for downstream uses will increase. In this context, groundwater storage may play a critical role in maintaining baseflow during drought events. In this study, we provide an overview of the hydrogeological functioning of the Otemma glacier catchment, a typical glaciated catchment in the Swiss Alps. Based on three years of field data, we provide a complete conceptual model of the volumes and timescales at which different landforms store and release water and compare those results with a catchment-scale analysis of the winter discharge recession. Based on water isotopes and geochemical data, we show the strong spatial heterogeneity in the water sources that recharge those landforms and how they are interconnected. Finally, we present results of a 3D model of the groundwater-surface water interactions in the proglacial outwash plain, discuss where potential new floodplains may form in the future and show a rather limited potential storage of the order of 20 mm. We conclude that superficial landforms have a limited potential to provide significant baseflow for downstream users but can provide significant moisture for high alpine ecosystems. Nevertheless, we show that bedrock infiltration likely represents the largest groundwater reservoir but more research is needed to characterize its role in the future.
How to cite: Müller, T., Lane, S. N., and Schaefli, B.: Characterizing the current and future groundwater storages in a highly glaciated catchment : a synthesis of 3 years of field observations and modelling results, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11831, https://doi.org/10.5194/egusphere-egu23-11831, 2023.
In the cold-arid Trans-Himalayan region of Ladakh, cryospheric meltwater plays a critical role for irrigated agriculture and local livelihoods. Despite the vital importance of reliable water supply under conditions of ongoing climate change, the relative contributions from glaciers and seasonal snow cover melt, together with permafrost thaw to surface and subsurface discharge are largely unknown due to the lack of in-situ data and local hydrological modelling. This study attempts to improve the understanding of regional hydrology, based on the case study of Stok catchment, where snow and glacier meltwater feeds a village of more than 300 households. We quantified long-term (2003-2019) surface and subsurface flow using a distributed temperature index and coupled surface/subsurface flow models forced by daily in-situ, meteorological, satellite and reanalysis data. These models were calibrated with the measured discharge data from two summer periods (2018 and 2019) in order to better understand the characteristics of surface and subsurface hydrology of the catchment. We also investigated the specific contributions from the cryospheric components and from rainfall to the total flow, and water loss through sublimation. A decline in annual discharge with characteristic inter-annual variations was identified over the observation period with about half of the total accumulated flow through the subsurface. We found that snowmelt contribution was highest (~60%) followed by ice melt (~20%) and rainfall (~15%), whereas sublimation contributes to ~8% of the water loss in a hydrological year. The findings and approach of this study are important for applied hydrological studies and planning future water management strategies in the region of Ladakh.
How to cite: Soheb, M., Bastian, P., Nüsser, M., Schmidt, S., Singh, S., Kaushik, H., and Ramanathan, A.: Surface and subsurface hydrology of a high-altitude catchment in the Trans-Himalayan region of Ladakh, India, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7664, https://doi.org/10.5194/egusphere-egu23-7664, 2023.
The mountains of Central Asia are water towers servicing the arid downstream regions and maintaining irrigation and food production. There are several sources of runoff: liquid precipitation, snowpack, glacier ice, ground ice (including rock glaciers and permafrost), and ground water. The relative contributions of different water sources to stream flow are poorly quantified and its improved understanding will reduce uncertainty in hydrological modelling and projections of changes in water resources. In 2019-21, an extensive sampling programme was conducted to quantify the relative contributions of water sources to stream flow in the Tien Shan and Pamir-Alai using stable water isotope tracers (SWI) of oxygen and hydrogen. Samples of the event-based precipitation, river discharge taken daily or twice-daily at the designated sampling points and every fortnight along the river courses, and water sources were collected in the glacierized catchments in Kazakhstan (Ulken Almaty and Kishi Almaty catchments), Kyrgyzstan (Ala-Archa and Chon-Kyzyl Suu), Tajikistan (Varzob and Kafornihon), and Uzbekistan (Chirchik). The samples were processed using Picarro isotope analyser. A data set of SWI ratios from approximately 6000 samples has been produced and analysed. It is the first comprehensive SWI database in Central Asia contributing to understanding of regional and global isoscapes and water resources. The local meteoric water line (LMWL) was developed from the event-based precipitation samples. It is approximated as δD = 7.6δ18O + 8.7. The values of SWI in precipitation exhibit a clear annual cycle and depend on precipitation type (rain, snow, and mixed). The derived seasonal SWI values are different from those available from the Water Isotopes Database being nearly twice as high in winter. Snow, glacier ice and permafrost exhibit distinct isotopic signatures although these vary between the basins. Glacier ice in the Chirchik basin appears to be more depleted than elsewhere. Rock glaciers were sampled in the Ulken Almaty basin showing SWI ratios similar to those of glacier ice but both are distinct from permafrost. These results point at the feasibility of the application of the mixing model and end-member mixing analysis approaches to the partitioning of runoff and quantifying relative contributions of different water sources in the Tien Shan and Pamir-Alai. This is a policy-relevant task under the conditions of climate change.
How to cite: Saidaliyeva, Z., Shahgedanova, M., Yapiyev, V., Wade, A., Akbarov, F., Esenaman, M., Kapitsa, V., Kassatkin, N., Kayumova, D., Rakhimov, I., Satylkanov, R., Sayakbaev, D., Severskiy, I., Petrov, M., Usubaliev, R., and Umirzakov, G.: Isotopic composition as a tracer of different source contributions to stream flow in the glacierized catchments of Central Asia, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10181, https://doi.org/10.5194/egusphere-egu23-10181, 2023.
The water balance of high-alpine glacierized catchments is largely dominated by snow and ice processes. When modelling the hydrological response of such catchments, a reliable representation of snow/ice accumulation and melt should be ensured, especially when studying the effects of climate change. Even though numerous state-of-the-art hydrological models are able to adequately represent the contribution of snow melt into the total runoff with the use of complex approaches (e.g. energy balance models), glacier dynamics are still based on conceptual or empirical methods, which exhibit some limitations compared to more sophisticated models (e.g. explicit ice-flow dynamics).
The Water Flow and Balance Simulation Model (WaSiM) is a process-based hydrological model that includes an empirical volume-area scaling approach for describing the glacier’s evolution. Although acceptable estimates can be obtained with this approach, an integration to a more complex glacier representation is still missing. For this reason, a coupling scheme between WaSiM and the Open Global Glacier Model (OGGM) is developed, hence accounting for explicit ice-flow dynamics.
The workflow consists mainly on three steps: i) a first WaSiM run to obtain monthly values of temperature and precipitation that serve as input for the ii) second step, which is running OGGM. Finally, iii) a dynamic model run of WaSiM with the updated output from OGGM (annual glacier outlines and ice thickness) is performed. Within this last step, the glacier’s volume internally calculated by WaSiM (i.e. with the VA-scaling approach) is replaced by OGGM’s output, while performing a simultaneous multi-data set automatic calibration. In this calibration, only WaSiM parameters are adjusted and simulation results are compared against glacier mass balances (OGGM) and observed runoff. The performance of the calibration is then evaluated in terms of a weighted multi-objective function. Although the best fit between observed and simulated runoff is achieved when considering only runoff observations (single-data calibration), glacier components are better represented when calibrating the coupled model with the multi-data set (i.e. also including glacier mass balances). Therefore, a trade-off is made between general model performance and accurate runoff prediction.
This coupling scheme is aimed for hydrological modellers with no additional expertise on glacier modelling, since OGGM is set up according to its default parameters. Finally, it could serve as a tool not only to predict the hydrological response of any glacierized catchment (even without any available glacier data), but also to make predictions under future climate projections with a more reliable representation of glaciers.
How to cite: Pesci, M. H. and Förster, K.: Process-based water balance modelling with explicit ice-flow dynamics and multi-data set calibration: the WaSiM-OGGM coupling scheme, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7688, https://doi.org/10.5194/egusphere-egu23-7688, 2023.
Antarctic Peninsula region experienced a rapid increase in air temperature during the second half of the 20th century. Although the warming was interrupted in the first decades of the 21st century, future climate projections predict that air temperature will increase significantly until the end of the 21st century in this area. Changes in air temperature have large impact on runoff process, especially in proglacial environment. Even though these changes affects both terrestrial and marine ecosystems, runoff generation in Antarctic Peninsula region is still poorly understood. Therefore, we analysed runoff process in small, partly glaciated catchment on James Ross Island, which belongs to the largest deglaciated area in Antarctica. Our objective was to 1) describe runoff variability in this area and 2) to estimate glacier, snow, and rain contributions to runoff in relation to climate variability.
Due to limited discharge measurements, we used semi-distributed bucket-type HBV model to simulate runoff process in years 2010–2020 in a daily temporal resolution. Input data for the model were time series of in situ measured air temperature, and simulated precipitation. Precipitation was simulated by the Weather Research and Forecasting model driven by ERA5 reanalysis. The HBV model was calibrated against measured daily discharge from six weeks long period in February and March 2018, and seasonal ablation measurements from years 2014–2020.
The results showed that 93% of the annual runoff occurred from October to May. The highest mean monthly runoff occurred in the second half of summer due to combination of strong glacier and snow melt. Additionally, large runoff was found in November which was caused by melt-out of seasonal snow cover. The major part (53%) of runoff originates from snow cover, 41% originates from glacier and only 6% from rainfall. Snowmelt runoff dominated during winter (with overall low absolute values of runoff) and in autumn. In summer, snowmelt runoff was almost the same as glacier runoff. In autumn, contribution of glacier to total runoff was slightly higher than contribution of snow. Contribution of snow to total runoff was higher in colder years with higher precipitation. In contrast, melting glacier contributed more during warmer years with less precipitation.
How to cite: Nedělčev, O., Matějka, M., Láska, K., Engel, Z., Kavan, J., and Jeníček, M.: Glacier and snow melt contributions to streamflow on James Ross Island, Antarctic Peninsula, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8748, https://doi.org/10.5194/egusphere-egu23-8748, 2023.
Snowmelt runoff is a significant component in the glacierized and snow-covered basins of the western Himalaya. Modelling is the most useful tool to quantify snowmelt contribution in mountainous rivers, but the paucity of in-situ observations makes the model calibration quite challenging and therefore model parameters are often adopted from the neighboring river basins. In the present study, we applied Snowmelt Runoff Model (SRM) in the Chandra-Bhaga Basin and Chhota Shigri Glacier Catchment in the western Himalaya. We systematically checked the transferability of the model parameters between the catchment and basin. Using snow cover area (SCA), precipitation, and temperature as inputs, the daily discharge for the Chhota Shigri Catchment and Chandra-Bhaga Basin was reconstructed over 2003–2018. The mean annual discharge was found as 1.2 ± 0.2 m3/s and 55.9 ± 12.1 m3/s over 2003-2018 for the Chhota Shigri Catchment and Chandra-Bhaga Basin, respectively. The discharge in the Chhota Shigri Catchment was mainly controlled by summer temperature and summer SCA, whereas in the Chandra-Bhaga Basin summer SCA and summer precipitation controlled the discharge. At both the catchment and basin scale, the decadal comparison revealed an increase (11% and 9%) and early commencement (10 days and 20 days) of the maximum monthly discharge over 2011-2018 compared to 2003-2010. In the Chhota Shigri Catchment, the model output is almost equally sensitive to the 'degree day factor' and 'runoff coefficient for snow,' but most sensitive to the 'runoff coefficient for snow' in the Chandra-Bhaga Basin. Even though the SRM parameters were calibrated in a data-rich Chhota Shigri Glacier Catchment, their application in the Chandra-Bhaga Basin led to a large discharge overestimation at the basin scale and was not transferable even in the same basin. We suggest to be cautious while adopting/transferring model parameters for SRM from other basins, particularly for the ungauged basins.
How to cite: Vinze, P. and Azam, M. F.: Evaluation of Parameter Transferability of Snowmelt Runoff Model in Chandra-Bhaga Basin, India, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-534, https://doi.org/10.5194/egusphere-egu23-534, 2023.
The Colorado River, which supplies water to the Western United States (WUS) and Mexico, is fed primarily from snow melting out of the Rocky Mountains. Currently, snowmelt contribution to streamflow is forecast using a calibrated temperature index model (SNOW-17). This approach is simple, and computationally efficient, but loses efficacy when snow conditions are outside the calibration period as temperature index models do not represent all of the physical processes that control accumulation and melt rates. For example, in the southern headwaters of the Colorado River forecasting errors have been related to surface darkening and accelerated melt following episodic dust on snow events. Here, we present an ongoing project to develop and mature a spatially distributed snow energy balance model, informed with numerical weather prediction (NWP) and remote sensing, to support operational decision making. This effort is a collaboration between the University of Utah's Snow Hydrology Research to Operations (Snow HydRO) Laboratory, the USDA-ARS Northwest Watershed Research Center (NWRC), and the Colorado Basin River Forecast Center (CBRFC). The model, iSnobal, is forced with the High Resolution Rapid Refresh (HRRR) NWP and is assessed against in situ observations and snow depth maps from the Airborne Snow Observatory in representative headwater basins. Initial testing of the HRRR-iSnobal combination showed that it can simulate snow accumulation, in terms of both patterns and magnitude, but that snowmelt rates were too slow. This was attributed to inaccurate radiation balance, specifically shortwave radiation due to the traditional treatment of net shortwave, including a 'time since snowfall' albedo decay curve. To account for spatial and temporal variability in snow albedo, daily observations from the spatially and temporally complete MODIS fractional snow products (MODSCAG+MODDRFS) were incorporated to update net solar radiation inputs. The updates were tested in different ways including direct albedo updates, direct decay curve component updates, and basin specific calibration decay curves. Although all remote sensing based update approaches improved snowmelt timing, direct updates had the greatest improvement in years with more intense snow darkening. This presentation will include a summary of current results, updates on incorporation into operational forecasting, and highlight plans for future developments.
How to cite: Skiles, M., Meyer, J., Ragar, D., Kormos, P., and Hedrick, A.: Development of an operational snow energy balance model informed by numerical weather prediction and remote sensing for the Western United States, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10634, https://doi.org/10.5194/egusphere-egu23-10634, 2023.
Glacial melt is the primary source of freshwater for the fragile microbial ecosystem in the McMurdo Dry Valleys (MDV) of Antarctica. These glaciers are cold-based, with internal temperatures around -18°C, however, air temperatures hover around 0°C for several weeks in the summer and föhn wind events can rapidly raise ice surface temperatures to the melting point. Thus, episodical glacial melt is sensitive to small changes in the climate.
The aim of this research is to adapt a detailed snowpack model embedded in a distributed hydrological model to simulate the surface energy balance and run-off of a glacier in the MDV. To do this, the snowpack model in the WRF-Hydro-Crocus modelling scheme, which has been used for avalanche forecasting and temperate glaciers, is adapted to the MDV. Several modifications are made to model calculations and parameters to allow the model to successfully simulate surface energy balance and runoff in this environment. For example, the parameters for the Crocus albedo scheme are adjusted to obtain band profiles for snow, firn and ice that replicate observed albedo and remain internally consistent between surface types. The modelling system is then validated against data from an automatic weather station, eddy covariance measurements and stream discharge. It is shown to be suitable for future efforts to model the full hydrological cycle of glacial meltwater in this region.
How to cite: Pletzer, T., Cullen, N., Conway, J., Eidhammer, T., and Katurji, M.: Adapting a snowpack model to simulate cold-based glacial hydrological processes in the McMurdo Dry Valleys, Antarctica, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9243, https://doi.org/10.5194/egusphere-egu23-9243, 2023.
The latest advances and availability of satellite observations have great potential for improving hydrological model simulations of the water cycle. The recent study by Tong et al. (2021) showed that satellite observations of snow cover and soil moisture could improve river runoff simulations of conceptual hydrologic models with lumped model parameters. Still, the value and potential of spatial patterns of satellite observations for hydrologic model parametrization need to be better understood. This study aims to evaluate and compare different multiple-objective calibration strategies that use model inputs and satellite observations for the model calibration in lumped, spatially distributed and stepwise ways. We aim to test the potential of daily MODIS (Moderate Resolution Imaging Spectroradiometer) snow cover and ASCAT (Advanced Scatterometer) soil water index images observed over 204 Austrian catchments in 2000-2014. Results show that stepwise calibration strategies that first calibrate the snow model parameters to satellite snow cover data followed by calibrating the remaining model parameters outperform (particularly in lowlands) the classical calibration strategies estimating model parameters in one single calibration step. The use of distributed snow cover and soil moisture patterns in model calibration improves the snow and soil moisture simulation performance of the model. The use of MODIS snow cover data has a more significant contribution to the overall improvement in model performance than ASCAT soil moisture data.
References:
Tong, R., Parajka, J., Salentinig, A., Pfeil, I., Komma, J., Széles, B., Kubáň, M., Valent, P., Vreugdenhil, M., Wagner, W., and Blöschl, G.: The value of ASCAT soil moisture and MODIS snow cover data for calibrating a conceptual hydrologic model, Hydrol. Earth Syst. Sci., 25, 1389-1410, 10.5194/hess-25-1389-2021, 2021.
How to cite: Tong, R., Parajka, J., Tian, F., Széles, B., Greimeister-Pfeil, I., Vreugdenhil, M., Komma, J., and Blöschl, G.: The value of distributed snow cover and soil moisture data for multi-objective calibration of a conceptual hydrologic model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10420, https://doi.org/10.5194/egusphere-egu23-10420, 2023.
Flood hazard assessment and its relationship with extreme rainfall probabilities is a well-addressed topic in the literature, but not enough in mountain areas, where the climate change effect can hit much more than in other physical contexts. In mountain basins, the lack of systematic data and the complexity of the rain/snow phenomena make investigations even more necessary to figure out the consequences of global warming.
This study explores how the partial contributing area effect due to snow accumulation, on the one hand, and the basin runoff coefficient, on the other hand, shape the relationship between rainfall and flood probabilities in high elevation areas. To this aim, the FloodAlp geomorphoclimatic model (Allamano P. et al., 2009) is used.
The model is based on the derived distribution approach, producing as a result a simplified flood frequency curve based on the intra-annual variability of the portion of the catchment area covered by snow, according to simple descriptions of the seasonal variation of the freezing elevation and of the hypsographic curve of the basin.
To model the basin hypsometric features, we propose the use of a two-parameter Strahler function, which is a more accurate and alternative formulation to the simple one-parameter function originally used in the model. The role of the extreme rainfall frequency analysis is also explicitly analysed, by applying the model using rainfall extremes recorded both in the daily and 24-hours windows. In this application, the only parameter that requires calibration is the runoff coefficient. Considering recordings of annual maximum daily discharges, the runoff coefficients for more than 100 gauged basins in north-western Italy have been calibrated. Comparisons are then possible between the shapes of rainfall and flood frequency distributions within the sample analysed, that also take into account the basin geomorphoclimatic features. Results of this application address the selection of relevant characteristics in relation to the impact of climate change on mountain floods as a result of changes in temperatures and in the statistics of rainfall extremes.
How to cite: Evangelista, G., Monforte, I., Demateis Raveri, M., and Claps, P.: Relationship between rainfall and flood frequency curves in high elevation areas, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16657, https://doi.org/10.5194/egusphere-egu23-16657, 2023.
In high elevation Alpine areas, characterised by high snow accumulation and radiation-driven melt processes, the formation of peculiar ablation features called sun cups can be observed. Sun cups likely influence the energy and mass balance of the wet snowpack by locally reducing the snow albedo, leading to an enhanced ablation in the hollows. To our knowledge, these phenomena are to date poorly explored in the literature and little to no attempts have yet been made to study their evolution in time and correlate them with meteorological forcings and energy fluxes over the wet snowpack.
The dynamics of the sun cups was investigated at the high elevation Alpine site of Weissfluhjoch (Davos, Switzerland) over the Spring of 2022. At the site, the snow surface was mapped on an hourly basis by means of a fixed, automated high-resolution 3D terrestrial laser scanner. Snow height maps were obtained by processing the registered point clouds.
Sun cups were individually and automatically detected over the snow surface maps by a delineation algorithm in Python. The evolution of sun cups in time was studied with respect to their maximum depth and cross-section.
The maximum depth and cross-section evolution of sun cups showed a high correlation with the measured albedo, especially when they are fully-formed. This finding suggests that peculiar snow surface formations that can be detected by means of remote sensing systems can give valuable additional information about the ongoing processes within the wet snowpack, paving the way to a radar-assisted modelling of the snowmelt dynamics. In an era of increasing concern over the availability of water resources, a better understanding and modelling of snowmelt dynamics is of major importance, especially in remote areas where accurate predictions are required for operational purposes (e.g. hydropower and irrigation).
How to cite: Carletti, F., Brouet, L., Lehning, M., and Bavay, M.: Influence of sun cups on surface albedo of wet Alpine snowpack, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14338, https://doi.org/10.5194/egusphere-egu23-14338, 2023.
Accurate characterization of peak snow water storage is essential for assessing warm-season water availability in regions reliant on snowmelt-driven runoff. However, knowledge of peak snow water storage in data-sparse regions, such as High Mountain Asia (HMA), is still lacking due to overreliance on model-based estimates. Here, estimates of peak snow storage from eight global snow products were evaluated over HMA, using a newly developed High Mountain Asia Snow Reanalysis (HMASR) dataset as a reference. The particular focus of this work was on peak annual snow storage, as it is the first-order determinant of warm-season water supply in snow-dominated basins.
The results suggest large uncertainty in the eight global snow products in High Mountain Asia, with the climatological peak storage found to be 161 km3 ± 102 km3 across products. Compared to HMASR, most global snow products underestimate peak snow storage in HMA, with an average 33% underestimation. Large inter-product variability in cumulative snowfall (335 km3 ± 148 km3) is found to explain most of the peak snow storage uncertainty (>80%). Significant snowfall loss to ablation during accumulation season (51% ± 9%) also plays an important role in peak snow storage uncertainty, and deserves more investigation in future work.
How to cite: Liu, Y., Fang, Y., Li, D., and Margulis, S. A.: How well do global snow products characterize snow storage in High Mountain Asia?, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4012, https://doi.org/10.5194/egusphere-egu23-4012, 2023.
Posters on site: Wed, 26 Apr, 10:45–12:30 | Hall A
Quantifying the amount of snow deposited across the landscape at any given time is the main goal of snow hydrology. Yet, answering this apparently simple question is still elusive -- particularly in complex and high-elevation terrains where data are sparse. To contribute to the advancement of snow hydrology in Mediterranean regions, we present the first serially complete and multi-year snow reanalysis for Italy (IT-SNOW). IT-SNOW covers the period from September 2010 to August 2021, with future updates envisaged on a regular basis. This reanalysis is the output of a real-time snow and glacier monitoring chain – S3M Italy -- developed for the Italian Civil Protection Department by CIMA Research Foundation. Spatial resolution is 500 m, with input data coming from thousands of weather stations across the Italian territory. By assimilating blended snow-covered area maps from Sentinel-2, MODIS, and the Eumetsat H-SAF products, as well as interpolated snow-depth maps from in-situ data, IT-SNOW optimally combines dynamic modeling and data towards reconciled estimates of snow amount and water equivalent at various scales. IT-SNOW was validated using Sentinel-1-based maps of snow depth and in-situ snow data in the Alps and the Apennines, with little bias compared to the former and typical Root Mean Square Errors of 30 to 60 cm and 90 to 300 mm for snow depth and Snow Water Equivalent, respectively. A comparison at 102 gauge stations showed a strong (0.87) correlation between peak SWE in IT-SNOW and measured annual streamflow, with snow being 22% of annual streamflow on average. IT-SNOW is freely available at the following DOI: https://doi.org/10.5281/zenodo.7034956 and we encourage users to validate and provide critical feedback for future releases.
How to cite: Avanzi, F. and the IT-SNOW team: A snow reanalysis for Italy: IT-SNOW , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1361, https://doi.org/10.5194/egusphere-egu23-1361, 2023.
A large portion of boreal and alpine forests of the Northern Hemisphere hosts seasonal snowpacks over multiple months of the year. Rising temperatures and forest disturbances are causing rapid change to these environments; therefore, accurate prediction of forest snow is relevant for a variety of disciplines such as biogeochemistry, ecohydrology, cryospheric, and climate sciences. Research in each of these fields relies on process-based models that are usually discipline-specific, e.g., snow hydrology and land surface models. These models are intended for a broad range of spatiotemporal scales and consequently include canopy and snowpack process representations of varying complexity. Detailed snow physics models that resolve the microstructure of individual snow layers, motivated by avalanche forecasting and snow remote sensing, have existed for years. More recent advances in forest snow process representation and increasing availability of high-resolution canopy structure datasets have led to the development of snow-hydrology models capable of resolving tree-scale processes.
Here, we introduce a new model system that combines concepts from two such sophisticated models: the snowpack representation from Crocus, and the canopy representation from the Flexible Snow Model. We present multi-year simulations at 2-m resolution across sub-alpine and boreal forest landscapes. Spatially explicit simulations allow us to assess the spatio-temporal dynamics of snow properties, ground conditions and land surface states, and to unravel their distinct dependencies on canopy structure heterogeneities at a previously unfeasible level of detail. This work aims to inform and further promote the use of process-based modelling tools in interdisciplinary ecosystem research at the interface between snow and ecosystem science, and in support of environmental change impact studies, management practices and mitigation/adaptation strategies.
How to cite: Mazzotti, G., Nousu, J.-P., Jonas, T., and Lafaysse, M.: Linking detailed canopy structure and snow process model representations to explore the dynamics of snowpack properties and ground conditions, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13878, https://doi.org/10.5194/egusphere-egu23-13878, 2023.
The Salar de Atacama basin is one of the best-studied saline endorheic basins in the world due to the delicate balance between extraction of lithium-rich brine from its core, tourism, and the unique ecosystems of its surrounding lagoons. However, no study to date has quantified the contribution of snowmelt compared to rainfall in supporting groundwater recharge in the basin. In this work, satellite information (Moderate Resolution Imaging Spectroradiometer, MODIS) is used to characterize the spatial and temporal dynamics of snow coverage. However, snow equivalent water is not available from remote sensing, so the Cold Regions Hydrological Model (CRHM) was used to simulate snow water equivalent, runoff, infiltration and other hydrological processes governing the water balance and groundwater recharge. CRHM makes it possible to link physical processes to hydrological processes using hydrological response units (HRU) as control volumes for water balances and as a means of discretizing the basin. HRU were defined in the Toconao sub-basin, in the eastern part of the Salar de Atacama watershed and CRHM was parameterized from regional hydrological knowledge and run for several years, forced by reanalysis data. Special attention was paid to better understand the energy balance of snow, including sublimation and wind transport ablation losses, soil infiltration processes, and the role of snowmelt in surface runoff generation and direct and indirect groundwater recharge.
Satellite observations of snow cover recorded from 2000 to 2020 showed frequent snowfalls both in summer and winter. The greatest extent of snow cover occurred during winter, accounting for 60% of the annual snow-cover extent. Snow cover is generally located above 4500 m asl in summer, while in winter the snow cover is more extensive, covering a large part of the basin. The CRHM simulations show that the greatest amount of precipitation of the year falls as rain in the summer months with the drier winter dominated by snowfall. The intense summer rains produce the greatest annual fluxes of runoff and infiltration. In winter, snowmelt infiltration is approximately twice that from rainfall. Snow losses by wind transport and sublimation had little impact on the overall water balance despite the dry environment.
How to cite: Valdivielso, S., Vázquez-Suñé, E., López Moreno, J. I., Custodio, E., Criollo Manjarrez, R., Pomeroy, J. W., and Hassanzadeh, A.: The importance of snowmelt in the water balance of the Toconao sub-basin, Salar de Atacama, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-315, https://doi.org/10.5194/egusphere-egu23-315, 2023.
Snow water equivalent is a key variable in hydrology. An accurate SWE estimation is crucial for runoff prediction, especially for catchments with strong nival regimes. Direct observations are unfortunately rare and are available only at a point scale. Accurate spatialized estimates of SWE are thus difficult to be obtained. Physically based models often suffer from the inaccuracies of input data and uncertainty of model parametrization. In this sense, the integration of traditional techniques with remote sensing observation is valuable. Although current satellite missions do not provide direct SWE observation, they allow us to extract important proxy information that is crucial for SWE reconstruction. In this sense, we propose to exploit optical and radar sensors to retrieve accurate information on the persistence of snow on the ground. In fact, the longer the persistence, the deeper the snowpack. To achieve enough spatial and temporal detail, we merged multi-scale information from MODIS, Sentinel-2, and Landsat missions. The key idea is to exploit the snow pattern persistence that we can observe with good spatial detail from Landsat and Sentinel-2 missions to reconstruct the scene when a low-resolution image (MODIS) is acquired. Furthermore, information on the duration of the melting phase can also be retrieved by exploiting the synthetic aperture radar (SAR) mounted on board of Sentinel-1. Hence, we can estimate the number of days of melting. In-situ data, when available, are also exploited in the reconstruction. In detail, air temperature is used to estimate the potential melting and the snow depth increases to determine the number of days in accumulation. The reconstruction approach is then simple: by knowing the days in melting, the total amount of melted SWE is determined. Assuming that the melted SWE is equal to the accumulated SWE, we can redistribute SWE throughout the season using a simple approach as the degree day. The final output is a daily time-series with a spatial resolution of few dozens of m. One of the major advantage of the proposed approach, compared to more traditional SWE estimation techniques, is that it does not depend from precipitation observation, often highly uncertain in high-elevation catchments. When evaluated against a reference product (i.e., Airborne Snow Observatory), the method shows a bias of -22 mm and an RMSE of 212 mm for a catchment of 970 km2 in Sierra Nevada (CA). In this work, we investigate the relationship between the melted SWE and the measured riverine discharge for a number of catchments in South Tyrol (Italy). The results may be of great interest, especially for poorly monitored basins with highly variable snow accumulation that are exploited for hydroelectric energy production. In detail, we propose a long-term analysis on SWE time-series to understand if there are evident trends that might improve hydroelectric power management.
How to cite: Premier, V., Ciapponi, N., Bozzoli, M., Bertoldi, G., Rigon, R., Notarnicola, C., and Marin, C.: The potential use of high-resolution SWE estimates from remote sensing imagery to predict snow melt rates, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1557, https://doi.org/10.5194/egusphere-egu23-1557, 2023.
Several studies have been showing that major environmental changes will occur in mountainous regions, with dramatic effects in glacierized areas. In particular, the Alps are experiencing a sharper rising in air temperature, compared to other regions. The European Alps are water towers providing fresh water to highly populated areas in a fragile environment with ecosystems and human activities that adapted to low flow and storage in winter followed by high flow in summer. This dynamic is in phase with agricultural use and touristic needs while hydropower makes use of reservoirs to allow
flexibility and increase production in the most profitable periods. Climate change may significantly impact this timing, thereby changing the scenario and introducing new challenges in water resources management.
In the present work, we comprehensively analyzed the long-term (1976-2019) meteorological and streamflow time series of a small (8.5 km2) Alpine glacierized catchment, fed by the Careser glacier, in Peio valley, Italy. A Dense Deep feed-forward Neural Network (DNN) was employed to gap-fill the daily time series of the streamflow, available since 1976. Daily temperature and monthly precipitations at the glacier were obtained by interpolating the measurements at the 32 closest meteorological stations by Kriging with the External Drift.
The resulting reconstructed time series were used to investigate the changes in streamflow from 1976. The analysis revealed that precipitation did not change significantly in the observed period. On the contrary, a statistically significant temperature increase was observed (∆T = 0.022, 0.052, 0.046 oC y−1 for the maximum, minimum and mean daily temperatures), which is, therefore, the main driver of the observed changes in the streamflow. Ablation, in terms of loss of glacier thickness, continued to increase, but the glacier’s contribution to summer runoff first increased, up to the middle of the nineties of the previous century, and successively decreased dramatically as an effect of the reduction of the glacier area. In addition, significant anticipation of the summer streamflow peak was observed in the last decade.
The proposed analysis evidenced how the rise of temperature in the Alpine region is already having a profound impact on streamflow seasonality, which is expected to exacerbate in the near future, given the projected further increase of the temperature. More from a technical point of view, the combination of classical geostatistical methods with DNN allowed a reliable reconstruction of meteorological and hydrological missing data. The algorithms developed in this study can be easily exported in other similar situations.
How to cite: Zanoni, M. G., Stella, E., and Bellin, A.: Long term hydrological dynamics of an Alpine glacier, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4071, https://doi.org/10.5194/egusphere-egu23-4071, 2023.
Mountains are referred to as water towers because they substantially affect the hydrology of downstream areas. However, snow storages will decrease in the future due to the increase in air temperature which will affect streamflow regime and water availability. Therefore, the main objectives of our research were 1) to quantify past and future changes in snow storages for a large set of mountain catchments representing different elevations and 2) to analyse how snow responds to climate variability. The snow storage was simulated for 59 mountain catchments located in six mountain regions in Czechia for the period 1965–2019 using a bucket-type catchment model. The predictions of the future climate from EURO-CORDEX experiment were considered in the model to simulate the future change in snow.
Analyses using the Mann-Kendall test identified decreasing trends in snow storages in western parts of Czechia (by up to −45 mm per decade), while no trends were detected in eastern part of Czechia suggesting the partly different climatology of both regions. In contrast to weak trends in SWE, significant trends were documented for snow cover duration, which decreased on average by 5.5 days per decade. The reason was mostly earlier snowmelt and melt-out, while trends in snow cover onset were not identified. Nevertheless, snow responded differently to climate variables across elevations. Below 900 m a.s.l., the snow was controlled mainly by air temperature, while above 1200 m a.s.l., snow responded dominantly to changes in precipitation. With the increase in air temperature in last five decades, its importance in controlling snow storage and variability increased at all elevations.
While only some significant changes in Czechia were documented in last five decades, substantial changes are expected by the end of the 21st century, such as the decrease in annual maximum SWE by 30-75%, mainly at elevations below 1200 m a.s.l. Changes are also expected for other snow-related variables, such as snow cover duration, which will be shorter, especially due to earlier start of the melting season and thus melt-out. In general, the melt-out day is projected to occur by 30-60 days earlier compared to current conditions by the end of the century. The results also showed the large variability between individual climate projections and indicated that the increase in air temperature causing the decrease in snowfall might be partly compensated by the increase in winter precipitation. Changes in snowpack will cause the highest streamflow during melting season to occur one month earlier, in addition to lower spring runoff volumes due to lower snowmelt inputs. Additionally, the model predicted the increase in winter runoff for the future period due to the increase in air temperature and thus the shift from snowfall to rain. These changes may impose more pressure to create adaptation strategies for water reservoirs management to keep all reservoir functions, such as flood and drought protection, drinking water supply and hydropower.
How to cite: Jenicek, M., Nedelcev, O., Hnilica, J., and Sipek, V.: Past and future decrease in snow in the central European rain-snow transition zone, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5576, https://doi.org/10.5194/egusphere-egu23-5576, 2023.
Rock glaciers have been proved to be able of storing water both as permafrost ice (solid form) and as groundwater (liquid form). The aim of the present study is the characterization of the runoff pattern of the active rock glacier Lazaun, its seasonal variations and its relationship to permafrost ice in the rock glacier. For this purpose, a recession analysis and a lumped-parameter rainfall-runoff model have been implemented on a multi-year dataset, supported by stable isotope and electrical conductivity analyses. Stable isotope and electrical conductivity values as natural tracers allow the separation of flow components. Therefore, reference samples for snowmelt, ice melt and rainwater were collected and analyzed, and electrical conductivity in combination with discharge data was applied for a two-component mixing model. The recession analysis also supports the flow component separation. Preliminary results show a typical discharge pattern for active rock glaciers, with maximum discharge during the snowmelt period (June-July) and a gradual decrease towards the fall season, interrupted by rainfall-induced runoff peaks. Discharge and water temperatures around 1.2-1.4 °C are recorded during winter, supporting the hypothesis of a groundwater dominated base flow. Isotope data in combination with electrical conductivity indicate at least 3 sources of the discharge components: i) low electrical conductivity, low δ18O values during spring and early summer indicate melt water of the winter snow cover, ii) a baseflow component with high electrical conductivity values and enriched in δ18O mainly during autumn and winter indicates most probably groundwater, and iii) rainwater of summer precipitation as the event water component with lower electrical conductivity and slightly higher δ18O values. A fourth source (melt water of the permafrost or glacial ice) is assumed. In general, electrical conductivity increases from the beginning of the melt season until autumn/winter and δ18O of the stream water becomes more and more positive. This correlates with the results of the two-component mixing model, which shows an increasing percentage of event water versus total discharge in spring, and its decrease towards the summer (mean 24%; min 0%; max 70%). Recession analysis also shows 2 to 3 components (“fast flow” and “baseflow”, plus an intermediate flow component), characterized by different recession coefficients. These indicate also at least two different storage units. The baseflow storage unit might be ascribed to an unfrozen sediment layer detected by core drilling at the base of the frozen core of the Lazaun rock glacier. Thickness and storage capacity of this layer are, however, still unknown. The designated results of the rainfall-runoff model are expected to provide a better understanding of the future development of active rock glacier discharge.
How to cite: Bertolotti, G., Winkler, G., and Krainer, K.: Active Rock Glaciers as Dynamic Water Storage: The Case Study of Rock Glacier Lazaun (South Tyrol, Italy), EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6204, https://doi.org/10.5194/egusphere-egu23-6204, 2023.
Groundwater can be an important water source for mountain streams. To gain insights into the sources of groundwater recharge and their pathways to the downstream environments, the interactions between surface water and groundwater are investigated for the Langshisha catchment, in the Langtang basin, Nepal Himalaya. The 0.81 km2 study area ranges in elevation from 4130 to 4450 m. a.s.l., with a landscape of coarse debris, pocket meadows and moraine sediments. It is bordered on three sides by steep mountain cliffs, the Langshisha glacier outlet creek, and the Langtang river. To simulate the hydrological behaviour of the area, we couple the glacio-hydrological model Spatial Processes in Hydrology (SPHY), a spatially distributed water balance model and the groundwater flow model MODFLOW6. We analyze three approaches to simulate the subsurface hydrology of the area: (1) using the glacio-hydrological model alone, (2) a one-way coupling of the glacio-hydrological model with a groundwater numerical model, where the groundwater recharge from the glacio-hydrological model is used as input to the groundwater model, and (3) a two-way coupled surface water and groundwater model. The model is evaluated with in-situ field data of soil moisture, shallow groundwater levels and streamflow measurements collected intermittently over the 2013-2022 period as well as isotopic and geochemistry water sample data collected in November 2022. Preliminary results suggest that despite the additional computational demands and time required to develop and apply a fully coupled approach, it provides essential knowledge regarding the cryosphere-surface water-groundwater interactions. Our preliminary results showcase the importance of field observations to constrain modelling efforts and will serve to guide further model applications to assess the importance of representing cryosphere-surface water-groundwater interactions in mountain landscapes.
How to cite: Aubry-Wake, C., Somers, L., Bazilova, V., Kraaijenbrink, P., Khanal, S., and Immerzeel, W.: Exploring the pathways of precipitation, snowmelt and glacier melt through the subsurface in high resolution, coupled, data-driven modeling experiment of the Langshisha catchment in the Himalaya, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6591, https://doi.org/10.5194/egusphere-egu23-6591, 2023.
Simulations and information on snow cover dynamics and snowmelt in high-alpine catchments are essential for the operation of storage hydropower plants in order to predict reservoir inflow during the snowmelt season. The distribution of the seasonal snowpack is driven by the mountainous topography and vegetation, the predominant weather patterns as well as the microclimatic conditions in the area of interest. At the same time, observations of precipitation and its distribution, the basis for modelling the spatio-temporal distribution of the snowpack, are rare and error-inflicted in these regions. Especially winter precipitation is often largely underestimated in high-alpine areas. Due to the manifold and multiscale influencing factors and scarcity of measurements, the estimation of inputs for hydrological simulations in the mountains is challenging and afflicted by many uncertainties. Snow depth data in a high spatial resolution can, e.g., be obtained via terrestrial, airborne or spaceborne remote sensing techniques and can be used to support snow-hydrological modelling. Vögeli et al. (2016) showed that such snow depth maps, taken at the end of the snow accumulation period, can be utilized for precipitation scaling to significantly improve snowpack modelling in terms of spatial distribution and quantity. This study examines the benefit and challenges of precipitation scaling for enhancing reservoir inflow predictions by applying the conceptual hydrological model COSERO (Herrnegger et al., 2016). The model is computationally efficient and was successfully calibrated and validated in numerous catchments in Austria and neighbouring countries. Among other catchments, COSERO is used operationally by the hydropower operator VERBUND AG in the high-alpine headwater catchments of the Kölnbrein reservoir in the Malta Valley, the largest reservoir in Austria with a capacity of 200 million m³. The basis of our meteorological model forcings is the INCA precipitation analysis product, provided by the Austrian Central Institute for Meteorology and Geodynamics. We applied the precipitation scaling based on snow depth patterns on the INCA data in a sub-daily and sub-kilometre resolution. We investigate, if this approach leads to a more realistic representation of alpine snowpack and runoff simulated by COSERO, aiming to improve operational reservoir management.
Acknowledgements: We thank the VERBUND AG for fruitful discussions and providing us with data.
Bibliography
Herrnegger, M., Senoner, T., Nachtnebel, H.-P., 2016. Adjustment of spatio-temporal precipitation patterns in a high Alpine environment. Journal of Hydrology 556, 913–921. https://doi.org/10.1016/j.jhydrol.2016.04.068
Vögeli, C., Lehning, M., Wever, N., Bavay, M., 2016. Scaling Precipitation Input to Spatially Distributed Hydrological Models by Measured Snow Distribution. Front. Earth Sci. 4. https://doi.org/10.3389/feart.2016.00108
How to cite: Pulka, T., Koch, F., Herrnegger, M., and Schulz, K.: Utilization of snow depth patterns to derive spatially distributed precipitation correction factors for operational hydrological modelling, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7950, https://doi.org/10.5194/egusphere-egu23-7950, 2023.
Central Asia is a climate change hot spot, facing an unprecedented juxtaposition of regional climate- and water-related issues. Meltwater from the Pamir Mountains plays a crucial role in Central Asia's hydrological cycle, yet there is a little detailed investigation on their response to climate change. Increasing water demand and the assumed ongoing transition from a snow-glacier runoff regime to a volatile rainfall regime in a changing climate demands for a better understanding of the processes governing surface flow in this region. Glacial-hydrological models are key tools for understanding the hydrological response to climate change, informing the planning of possible responses and adaptation. However, modeling is challenging here due to the lack of proper calibration and validation data. Most of the modeling studies in Pamir regions calibrated the model with runoff data only, which is fairly simple but potentially hides internal inconsistencies due to the complexity of feedback mechanisms that govern melt and runoff generation. Further, factors such as model forcing and/or data errors also contribute to simulation uncertainties. There is a clear need for a more detailed investigation of the regional hydrological processes, with systematic calibration and validation methods that allow more robust parameter constraints. This work employed a conceptual distributed hydrological model (SPHY) and tended to unravel the hydrological cycle in a representative catchment in the central Pamir, the Gunt River basin. We tested the usefulness of several state-of-the-art remote sensing, regional climate model, and reanalysis precipitation and temperature data sets in a hydrological application. We found none of them can be equally good in reproducing all targeted hydrological and cryospheric variables (runoff, snow cover fraction, and glacier mass balance). The aims of this study are hence (1) to develop a set of precipitation and temperature correction factors that could improve the model performance, (2) to develop a systematic calibration strategy that could guarantee internal consistency in the simulation of the single hydrological components, and (3) to test whether the corrected forcing data and model calibration strategy can be upscaled to other basins in the Parmir Mountains.
How to cite: Huang, J. and Pohl, E.: Towards better runoff simulation in the Pamir Mountains, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14930, https://doi.org/10.5194/egusphere-egu23-14930, 2023.
Discharge from glaciers plays an important role for ecosystems, land use and hydropower production in different regions of the world. The discharge hydrograph in glaciated catchments is determined by several parameters, like snow cover, glacier size and glacier mass balance, besides others. Variations in these parameters might considerably change the temporal availability of melt water in such regions, which needs to be taken into account for long term water management planning.
Here, we investigate in detail the characteristics of discharge in a highly glaciated catchment in the central eastern Alps. The Vernagtferner basin (11 km² area and 6.9 km² glacier area) is characterised by a high density of monitoring stations, which are an ideal basis for testing and applying models of snow and glacier evolution, as well as discharge simulations. The combination of a gauging station with meteorological observations and continuous monitoring of snow and ice melt at different locations, allows to investigate the major processes in detail. During the period 2019 to 2022 rather different mass balance conditions occurred, which strongly influenced the temporal evolution of the discharge generation. We investigate the significance of snow cover, firn and glacier ice to the melt water generation and the temporal characteristics of the hydrograph.
How to cite: Lambrecht, A. and Mayer, C.: Discharge characteristics for different glacier mass balance conditions at Vernagtferner, Ötztal Alps, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13841, https://doi.org/10.5194/egusphere-egu23-13841, 2023.
Due to global warming and glacial retreat, periglacial areas and headwater catchments are experiencing relevant changes in surface processes and in water budgets. The water cycle, altered by the changing snow accumulation/melting dynamics, ice ablation, higher altitude increasing rainfalls frequencies, is shifting towards larger average and peak runoff productions. These alterations have also an impact on sediment production, on geomorphological processes, on ecosystem dynamics. The goal of our research is to take advantage of multidisciplinary activities aimed at monitoring the glacial and peri-glacial area of the Rutor glacier, in the Aosta valley (north-western Italian Alps) to quantify its dynamics under climate change. The Rutor glacier is fast-retreating and has a terminus that moved more than 2 km since the mid-19th century: it is thus a perfect case study to investigate snow/ice dynamics and runoff production, considering also that the periglacial area is characterized by a number of lakes and channels that collect and convey the melt water, while dynamically responding to it. In this work, we present the results from a multidisciplinary collaboration that involves hydrologists, geophysicists, geomatics and water engineers with the goal of monitoring stream flows, water properties, lake water balance and runoff production. Thanks to the contribution of different disciplines, we could gain an advanced quantitative knowledge of the water budget in the area that will represent a starting point for further investigations of processes and interactions within this unique melting landscape.
How to cite: Tamea, S., Corte, E., and Camporeale, C.: Water budget in the Rutor glacier area: results from multidisciplinary activities, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16153, https://doi.org/10.5194/egusphere-egu23-16153, 2023.
With ongoing climate change, residual snow in the mountains is disappearing ever earlier each year. This reduces their potential to be used as a water source later in the year. Especially for infrastructures like mountain huts, this can lead to severe problems. Our study describes how to actively apply the basics of snowdrift fences as snow-farming to establish snow depots as summer water source. This project asses how drifting snow can be applied in a practical and sustainable way in alpine terrain without the use of snow-groomers or snow-cannons.
Existing, scientific models of snow transport are utilized in conjunction with the fundamentals of snow fence design to maximize the yield of residual snow in complex alpine terrain, contributing to water supply security. The study presents the results and approaches to the implementation of CFD modelling integrating meteo and snowpack models to analyze mountain terrain for potential sites. These results form the basis for the use of snowdrift fences to increase water storage in mountain regions.
How to cite: Crivelli, P.: The use of snow fences for snow conservation, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15485, https://doi.org/10.5194/egusphere-egu23-15485, 2023.
