Water stored in the snow pack and in glaciers represents an important component of the hydrological budget in many regions of the world, as well as a sustainment to life during dry seasons. Predicted impacts of climate change in catchments covered by snow or glaciers (including a shift from snow to rain, earlier snowmelt, and a decrease in peak snow accumulation) will reflect both on water resources availability and water uses at multiple scales, with potential implications for energy and food production.
The generation of runoff in catchments that are impacted by snow or ice, profoundly differs from rainfed catchments. And yet, our knowledge of snow/ice accumulation and melt patterns and their impact on runoff is highly uncertain, because of both limited availability and inherently large spatial variability of hydrological and weather data in such areas. This translates into limited process understanding, especially in a warming climate.
This session aims at bringing together those scientists that define themselves to some extent as cold region hydrologists, as large as this field can be. Contributions addressing the following topics are welcome:
- Experimental research on snow-melt & ice-melt runoff processes and potential implementation in hydrological models;
- Development of novel strategies for snowmelt runoff modelling in various (or changing) climatic and land-cover conditions;
- Evaluation of remote-sensing or in-situ snow products and application for snowmelt runoff calibration, data assimilation, streamflow forecasting or snow and ice physical properties quantification;
- Observational and modelling studies that shed new light on hydrological processes in glacier-covered catchments, e.g. impacts of glacier retreat on water resources and water storage dynamics or the application of techniques for tracing water flow paths;
- Studies on cryosphere-influenced mountain hydrology, such as landforms at high elevations and their relationship with streamflow, water balance of snow/ice-dominated mountain regions;
- Studies addressing the impact of climate change on the water cycle of snow and ice affected catchments.
Tue, 24 May, 08:30–10:00
Chairpersons: Francesco Avanzi, Doris Duethmann, Giulia Mazzotti
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.
The climate emergency will drive changes in the cryosphere and hydrology of high mountain catchments, with subsequent influences on water resources availability. Process-based hydrological and glaciological models require significant amounts of data which are often unavailable in high mountainous catchments, especially in developing countries, and are unable to explicitly integrate human-induced factors on river flows (Momblanch et al. 2019). This can be overcome by water resources systems models that take a more conceptual approach. However, they currently have limited capability to represent glacier evolution and thus river discharge dynamics, especially in long-term simulations required for climate change impact and adaptation analysis. There is, therefore, a clear need for improved representation of the spatio-temporal response of glaciers within water resources systems models to support the strategic water resources planning and management and ensure future water security.
The Water and Evaluation and Planning system (WEAP; Yates et al. 2005) is widely used in water resources management studies by both the scientific and decision-making communities around the world. WEAP includes a glacier module which accounts for ice accumulation and melt using the enhanced temperature-index method, but overlooks other processes such as glacier area change, snow redistribution, sublimation and ice flow. These omissions will severely impact the validity and utility of long-term simulations, especially in regions with very rough topography such as the Himalayas.
This research reports the development and application of an enhanced glacier modelling capability in the WEAP software that introduces ice flow dynamics. Through the integration of elevation bands and remote sensing-derived glacier velocities, a ‘plug-in’ extension into WEAP’s Application Programming Interface allows glacier routing to be represented. The Aleo catchment in the upper reaches of the Indus basin in the Western Himalayas is used as a case study to showcase the ‘plug-in’ and to compare outputs with other process-based models. The results show that the enhanced glacier model significantly improves the simulation of the main glacier variables, i.e. mass balance, depth and volume, with respect to the original glacier model in WEAP. The research outputs contribute to a better understanding of climate change impacts on high mountain hydrology, which is key for regional development.
Momblanch, A., Holman, I., Jain, S., 2019. Current Practice and Recommendations for Modelling Global Change Impacts on Water Resource in the Himalayas. Water 11, 1303. doi:10.3390/w11061303
Yates, D., Purkey, D., Sieber, J., Huber-Lee, A., Galbraith, H., 2005. WEAP21—A Demand-, Priority-, and Preference-Driven Water Planning Model. Water Int. 30, 501–512. doi:10.1080/02508060508691894
How to cite: Momblanch, A., Shirsat, T., Kulkarni, A., and Holman, I. P.: Integrating glacier flow in hydrological modelling for water resources management, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6025, https://doi.org/10.5194/egusphere-egu22-6025, 2022.
Water resources in Central Asia strongly depend on glaciers, which in turn adjust their size in response to climate variations. We investigate glacier runoff in the period 1981–2019 in the upper Naryn basin, Kyrgyzstan. The basins contain more than 1000 glaciers, which cover a total area of 776 km2. We model the mass balance and runoff contribution of all glaciers with a simplified energy balance melt model and distributed accumulation model driven by ERA5 LAND re-analysis data for the time period of 1981 - 2019. The results are evaluated against discharge records, satellite-derived snow cover, stake readings from individual glaciers, and geodetic mass balances. Modelled glacier volume decreased by approximately 6.7 km3 or 14%, and the majority of the mass loss took place from 1996 until 2019. The decreasing trend is the result of increasingly negative summer mass balances whereas winter mass balances show no substantial trend. Analysis of the discharge data suggests an increasing runoff for the past two decades, which is, however only partly reflected in an increase of glacier melt. Moreover, the strongest increase in discharge is observed in winter, suggesting either a prolonged melting period and/or increased groundwater discharge. The average runoff from the glacierized areas in summer months (June to August) constitutes approximately 23% of the total contributions to the basin's runoff. The results highlight the strong regional variability in glacier-climate interactions in Central Asia.
How to cite: Saks, T., Pohl, E., Machguth, H., Dehecq, A., Barandun, M., Kenzhebaev, R., Kalashnikova, O., and Hoelzle, M.: Glacier runoff variation since 1981 in the upper Naryn river catchments, Central Tien Shan, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4317, https://doi.org/10.5194/egusphere-egu22-4317, 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.
Changes in surface runoff from permafrost thaw in mountain catchments can be estimated using numerical cryo-hydrogeology models. However, such models can be complex from a numerical standpoint due to the need to simulate transient thermo-hydrologic feedbacks in highly heterogenous geological settings. Models that also seek to quantify water movement and water-budget contributions from ground-ice thaw must further account for changes in water/ice saturation to continually estimate and update the physical properties that control heat and water transfer in the ground (i.e., thermal and hydraulic conductivity) during the model execution. This has important implications for permafrost hydrology modelling efforts in arid mountain watersheds like the High Andes, where water security is threatened by climate change and the role of permafrost in the hydrologic cycle is unclear.
In this contribution the coupled finite element codes TEMP/W and SEEP/W are used to illustrate ground thermal and hydrologic dynamics for different geological scenarios within a hypothetical mountain slope, characteristic of the High Andes at an altitude of up to 6000 m. The 3 km-long, two dimensional cross-sectional model was developed based on a simplified topography, and ground temperatures and climate data collected within the region. In the first scenario, a uniform hydraulic conductivity is applied to the full model domain. A second scenario simulates a case where the hydraulic conductivity of the ground in the upper 200 m is an order of magnitude higher than for the rest of the model (i.e., as in fractured bedrock or unconsolidated sediment). The scenarios were subjected to a 1,000-yr seasonally cyclic climate forcing, followed by 1,000 years of warming superimposed on inter-annual variability at an average warming rate of 4 deg/100 year.
Model experiments show that the applied variations in hydraulic conductivity support vastly different permafrost and ground ice-content distributions under identical climate forcing. Compared to the uniform hydraulic conductivity case, the scenario with high hydraulic conductivity upper layer produces an increase in the heterogeneity of ice-rich permafrost under the stable climate forcing, and a slightly accelerated rate of permafrost thaw under climate warming. Higher recharge and discharge fluxes across the model surface are also predicted for the high hydraulic conductivity scenario.
The divergence in the results is attributed to preferential flow paths that develop near the model surface in the higher hydraulic conductivity case, which in turn leads to increased spatial complexity in advective heat transfer. This can have profound effects on predictive models aiming to estimate rates of permafrost thaw and discharge behaviour under climate warming, and highlights the need for awareness of uncertainties associated with estimated or assumed thermal and hydrologic properties in modelling large mountain catchments.
How to cite: Koenig, C., Hauck, C., Arenson, L., and Hilbich, C.: Effects of Geologic Heterogeneity on Permafrost Distribution and Catchment Hydrology in Mountain Environments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12146, https://doi.org/10.5194/egusphere-egu22-12146, 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.
Tue, 24 May, 10:20–11:50
Chairpersons: Abror Gafurov, Doris Duethmann, Giulia Mazzotti
The snow and glacier reservoirs of High Mountain Asia play a key role in sustaining water supply to mountain communities and downstream ecosystems, populations and economic activities. However, little is known about how rain, snow- and ice melt vary sub-seasonally and along the altitudinal gradient in high-elevation watersheds.
We generate detailed simulations of catchment hydrology using a land surface model that constrains energy and mass fluxes using advanced physical representations of both cryospheric and biospheric processes in high detail at 100 m spatial resolution. We use the model to study how snow and glacier processes affect the hydrological cycle and how vegetation can mediate water yield from the high mountains of a glacierized Himalayan catchment downstream. This bridges the modelling gap between snow- and glacier dynamics, which generate the runoff, and vegetation processes, which interfere with runoff production and water uses at lower elevations.
We study the upper Langtang catchment (~4000-7000 m a.s.l.) in the Nepalese Himalayas, and simulate catchment runoff for two hydrological years (2017-2019), revealing the relative importance of precipitation, snow, ice, soil moisture and vegetation for different elevations and seasons. The land surface model is forced with hourly meteorological input data based on the main weather station in the basin and air temperature and precipitation were spatially distributed using observed elevational gradients.
We calibrate a minimal set of parameters (physical properties of supraglacial debris) and use integrative variables such as catchment runoff or glacier mass balance only for validation. The availability of a rich dataset of field- and remote sensing observations allows validation of numerous physical processes simulated by the model and drastically reduces the probability of internal error compensation.
The model provides detailed insights into the importance of each of the energy and mass balance components in the catchment water budget and shows that evaporative fluxes are non-negligible contributors to mass loss at very high elevations (especially from snow) and in the lower part of the catchment (transpiration from vegetation). Often neglected or derived as a bulk quantity in simpler model approaches, evaporation accounts for about 15% of the water leaving the basin. We show precipitation to be the major source of uncertainty in the simulations and that vegetation is relevant in determining the amount of runoff transferred further downstream even for high elevation, extensively glacierized Himalayan catchments.
How to cite: Buri, P., Fatichi, S., Shaw, T. E., Miles, E. S., McCarthy, M., Fyffe, C., Fugger, S., Ren, S., Kneib, M., Fujita, K., and Pellicciotti, F.: Dissecting the subseasonal and altitudinal water balance of a high-elevation Himalayan catchment using a land surface model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6871, https://doi.org/10.5194/egusphere-egu22-6871, 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 high altitude Hindukush Karakorum Himalaya (HKH) mountainous region, the complex weather and terrain and sparse measurements make the precipitation distribution and hydrological regime significant unknowns. Recent advances in remote-sensing and reanalysis-based global precipitation products and numerical models may provide more insights on the hydro-climatic regimes for such regions. This study examined the precipitation distribution and snow and glacier melt contributions to river flow in the highly glaciated and snow-fed Hunza basin of the Karakorum mountains. The Distance Distribution Dynamics (DDD), a rainfall-runoff model with its temperature index and an energy balance approach for glacial melt, was used. The model was forced with precipitation estimates based on a newly developed and fine resolution (0.1°×0.1°) gridded product of ERA5-Land. The model calibration and validation were performed from 1997–2005 and 2006–2010, respectively. The mean annual precipitation of the Hunza basin was estimated as 947 mm from 1997–2010. The precipitation distribution analysis showed more precipitation at lower elevations than at higher. The simulated snow cover area (SCA) was in good agreement with MODIS satellite-based SCA. The flow analysis indicated that the Hunza’s flow is strongly controlled by glacier melt (44–47 %) followed by snowmelt (31–32 %) and rainfall (22–23 %). The simulations showed that the DDD model has good potential to simulate hydrological processes satisfactorily for data-scarce basins.
How to cite: Nazeer, A., Maskey, S., Skaugen, T., and E. McClain, M.: Evaluating the hydrological regime of the snow-fed and glaciated Hunza basin in the Hindukush Karakorum Himalaya (HKH) region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1338, https://doi.org/10.5194/egusphere-egu22-1338, 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.
Monitoring the state of the cryosphere in real time is a key to improved risk and water resources management, especially in a warming climate. All around the world, this goal is achieved through forecasting chains combining models with in-situ and remote-sensing measurements. Here, we discuss lessons learned while developing S3M Italy, one such chain delivering hourly estimates of snow water equivalent, density, snow and glacier melt, and bulk liquid water content across the Italian territory (300k+ km2, 200 m resolution, 1.5 hour turnaround). S3M Italy includes downloaders to ingest input data from automatic weather stations, spatialization tools to convert these data into weather-input maps, blending routines for deriving daily snow-covered-area maps from ESA Sentinel 2, NASA MODIS, and EUMETSAT H-SAF products, mapping algorithms based on multilinear regressions for assimilating on-the-ground snow-depth data, as well as algorithms to manage parallelized runs and then mosaic model outputs. S3M Italy has been developed to support decisions by the Italian Civil Protection Agency and is fully open source, not only in terms of underlying models (https://github.com/c-hydro/s3m-dev), but also in terms of all pre-processing routines (https://github.com/c-hydro/fp-hyde, https://github.com/c-hydro/fp-s3m).
How to cite: Avanzi, F., Gabellani, S., Delogu, F., Silvestro, F., Puca, S., Toniazzo, A., Giordano, P., Falzacappa, M., Ratto, S., Stevenin, H., Cardillo, A., Cremonese, E., and Morra di Cella, U.: S3M Italy: a real-time, open-source cryospheric-forecasting chain for applications on a large scale , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-528, https://doi.org/10.5194/egusphere-egu22-528, 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.
In Alpine regions, forests that overlap with seasonal snow mostly reside in complex terrain. Due to major observational challenges in these environments, the combined impact of forest structure and topography on seasonal snow cover dynamics is still poorly understood. However, recent advances in forest snow process representation and increasing availability of detailed canopy structure datasets now allow for hyper-resolution (<5 m) snow model simulations capable of resolving tree-scale processes. These simulations can shed light on the complex process interactions that govern forest snow cover dynamics.
We present multi-year simulations at 2 m resolution obtained with FSM2, a mass- and energy-balance based forest snow model specifically developed and validated for meter-scale applications. Our 3km2 model domain encompasses forested slopes of a sub-alpine valley in the Eastern Swiss Alps. Simulations thus span a wide range of canopy structures, terrain characteristics, and meteorological conditions typical for the region. We analyze spatial and temporal variations in forest snow energy balance partitioning, aiming to quantify and understand the contribution of individual energy exchange processes at different locations and times.
Our results suggest that snow cover evolution is equally affected by fine-scale canopy structure, terrain characteristics and meteorological conditions. We show that the interaction of these three factors can lead to snow distribution and melt patterns that vary between years. Generally, we find higher snow distribution variability and complexity in slopes that receive solar radiation early in winter. Our process-level insights corroborate and complement existing empirical findings that are largely based on snow distribution datasets only. Hyper-resolution simulations as presented here will thus help us to better understand how ecohydrological regimes sub-alpine regions may evolve as a result of forest disturbances and a warming climate.
How to cite: Mazzotti, G., Webster, C., Quéno, L., Cluzet, B., Essery, R., and Jonas, T.: Unraveling energy balance partitioning in sub-alpine forests: interplay of canopy structure, topography, and meteorological conditions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11913, https://doi.org/10.5194/egusphere-egu22-11913, 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.
Estimating snowfall over mountain regions is an extremely challenging task due to the high variability of spatial and temporal precipitation gradients. Traditional methods to estimate snowfall include in-situ gauges, doppler weather radars, satellite radars and radiometers, numerical modeling and reanalysis products. Each of these methods, alone, is unable to capture the complex orographic precipitation. For example, in-situ gauges are often too sparse and lead to significant interpolation errors; radar beams are shielded by the complex mountainous terrains; satellite estimates are sub-optimal over snowy mountains regions; while the physical parameterization of mountainous orography remains challenging for estimating precipitation in numerical models. A potential method to overcome model and observational shortcomings in precipitation estimation is land surface data assimilation, which leverages the information content in both land surface observations and models while minimizing their limitations due to uncertainty. Recently, the ESA and Copernicus Sentinel-1 constellation has been used to map snow-depth across the Northern Hemisphere mountains with 1 km spatial resolution by exploiting C-band cross-polarized backscatter radar measurements. This work aims at characterizing and estimating snowfall precipitation errors over an alpine watershed located in Trentino Alto Adige, Italy. We derive the snowfall errors via the data assimilation of 1 km Sentinel-1 snow-depth observations within a numerical model. The data assimilation applies a particle batch smoother to the coupled snow-17 and Sacramento hydrological models.
How to cite: Girotto, M., Formetta, G., Azimi, S., Modanesi, S., De Lannoy, G., Lievens, H., Rigon, R., and Massari, C.: A Novel Approach to Estimate Snowfall over an Alpine Terrain via the Assimilation of Sentinel-1 Snow Depth Observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10582, https://doi.org/10.5194/egusphere-egu22-10582, 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.
Tue, 24 May, 13:20–14:50
Chairpersons: Giulia Mazzotti, Francesco Avanzi, Abror Gafurov
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.
Precipitation and temperature changes across the Vakhsh and Panj basins are of great importance for Tajikistan, Afghanistan, Turkmenistan, and Uzbekistan for consumption, agricultural, and energy purposes. While studies of precipitation and temperature trends have been conducted in these basins, attention to their heterogenous topography and nature have not been considered and analyzed together with glacial and permafrost melt. Here, we assessed the trends of precipitation and temperature over the last 20 years using remote sensing products. For precipitation, we used research grade daily GPM IMERG V06 Final Run from 2001 to 2020. Similarly, temperature MODIS Land Surface Temperature & Emissivity (LST&E) (MOD11A1) was used to assess temperature trends and separate liquid from solid precipitation. Annual precipitation and temperature trends were also assessed in three elevation bands: low (317-2225m), middle (2225-4500m) and high (4500-7543m).
Positive significant trends for solid precipitation mainly arise in the northern parts of the basins, while slightly positive with more negative trends occurred over the central and southern parts of the Panj basin. A significant solid precipitation trend of +1.30mm y-1 below 2225 m a.s.l. occurred in late spring. Many of the pixels (1 x 1 km) across the study region that exhibited significant trends were increases in temperature, especially in the high elevations in the eastern portion of the basins. There was a significant annual increase of liquid precipitation coupled with a decrease in solid precipitation and an increase in temperature trend in the central Pamirs, implying a shift from solid to liquid precipitation. An increase in rainfall below 4500 m a.s.l. was observed, where the largest increases occurred in the western portions of these basins with nearly no significant temperature trends; thus, potentially having a positive influence on agricultural and community water supplies. However, long-term water supplies in the dry regions of the central and eastern parts of the basins may create supply vulnerabilities.
How to cite: Khojazoda, Z., Sidle, R., and Caiserman, A.: Water Towers of the Pamirs: I. Precipitation and temperature trends, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3798, https://doi.org/10.5194/egusphere-egu22-3798, 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.
Cryosphere components in the Pamirs play an important role in the release of water to the Vakhsh and Panj river systems where both mountain and downstream communities rely on sustainable water supplies for their agriculture, potable water, and hydropower. Of the three primary cryosphere sources of water (glacial, snow, and permafrost melt), glacial melt is the most predictable and constitutes and intermediate supply of runoff to streams, while almost no estimates of permafrost contributions are available. Snowmelt is highly variable from year to year and because it is the largest water supply to these rivers, understanding the potential amount and timing of snowmelt is critical for local communities.
Based on our remote sensing investigations during the past 20 years, we water found wide interannual variations in snow water, snowline elevation, and snow persistence throughout the Vakhsh and Paji basins, but no clear evidence of basin-wide climate change trends. Specific locations of the central Pamirs appear to be shifting from snow to rain due to climate warming, approximately offsetting each other, but likely producing more runoff in late spring to early summer and less in mid to late summer. In the high, glaciated Vakhsh basin, temperature increases have been offset by higher snowfall, resulting in little glacial ice change. By overlaying maps of glaciers on a digital elevation model (Alos Palsar 12.5 m) containing stream networks, we estimated that about 75% of the glaciers were closely connected to first-order or larger channels; however, this may be a liberal estimate because some first-order streams are not connected to major river systems. Based on the TTOP model nearly 24,000 km2 of continuous permafrost terrain exists throughout the Panj and Vakhsh basins, the majority of which is located at elevations > 3577 m. Streamflow contributions from permafrost thaw during the summer were estimated as subsurface flux from streambanks; ≈ 638 x 106 m3 each summer, which represents about 1.5% of the average annual river discharge for both basins.
The climate variability and localized changes we observed pose challenges for predicting runoff from high elevation cold regions due to the altered patterns of the timing of snow, glacier, and permafrost accumulation and melt, including temporal changes, interannual variability, and hydrological connectivity of sources. The various water sources will respond differently in a changing climate, generating complex runoff scenarios and socioeconomic consequences downstream.
How to cite: Sidle, R. C., Caiserman, A., Salazar, Á., and Khojazoda, Z. T.: Water Towers of the Pamirs: II. Cryosphere dynamics and implications for runoff and livelihoods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4705, https://doi.org/10.5194/egusphere-egu22-4705, 2022.
In this paper we analyse the future hydrology of the Lake Como catchment under climate change scenarios. The management of the lake is extremely important because it is needed both to supply water for the irrigation demand of the Po Valley, and to prevent flood risk along the lake shores. The climate variations are affecting the lake operation with negative impacts both on agriculture and hydropower production. The lake dynamics are link to the cryospheric driven upstream basin, and so the use of a model able to assess the water input as related to snow cover processes is a key issue. Accordingly, we use the physically based hydrological model Poli-hydro able to represent the most important process in the cryospheric driven catchment. We set up and calibrated the model against lake inflows during 2002-2018, resulting in a mean error Bias = +2.15%, and a monthly/daily Nash-Sutcliff efficiency, NSE = 0.77/0.64. We then performed a stochastic disaggregation of 3 Global Circulation Models (GCMs) of the most recent Assessment report 6 (AR6) of the IPCC, under 4 different socio-economic pathways (SSPs), from which we derived daily series of rainfall and temperature to be used as inputs for the hydrological model Poli-Hydro. The climate projections show a potential increase of temperature at the end of the century between +0.61°C and +5.96°C, which would lead to a decrease of the total ice volume in the catchment of -50% and -77%, respectively. Future projections show generally an increase of discharge in autumn and winter (November-March) and a reduction in spring and summer (May-September). This is due to the increase of temperature with an increase of liquid precipitation instead of solid precipitation in winter and an anticipation of the snow melt peak at the beginning of spring. Possible consequences are the increase of flood hazard in the winter period and a scarcity of water availability in summer. A new regulation of Lake Como is essential to satisfy stakeholders requests.
How to cite: Flavia, F., Francesca, C., Federico, G., and Daniele, B.: Future hydrology of the cryospheric driven Lake Como catchment in Italy under climate change scenarios, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1106, https://doi.org/10.5194/egusphere-egu22-1106, 2022.
Due to climate change, glaciers are retreating worldwide. Among different consequences, the decline of meltwater in rivers will lead to a reduction in runoff. The aim of this work is to quantify the changes in runoff and the impact on selected hydropower plants in different drainage basins in the Alps until 2100.
Outputs from the Global Glacier Evolution Model (GloGEM), which uses 14 General Circulation Models to compute the future evolution of the glaciers worldwide, were used to determine past and future runoff from glaciers individual hydropower plants’ catchments. Measured runoff data at selected locations along rivers was used to compute the share of glacier runoff in total discharge. The computed river runoff was subsequently applied to determine the reduced electricity production of the hydropower plants.
The results reveal a decrease in summer runoff at all investigated power plants by 2100. However, large differences occur among the different catchments. In particular, geographical characteristics, such as glacier size and altitude, determine the intensity and timing of the decline. Areas located further away from glaciers, particularly in the North of the Eastern Alps, show the strongest reduction in glacier runoff (up to 86% compared to 1986-2015). In contrast, mountainous catchments and the South of the Alps are mostly affected by a decrease in river discharge (up to 33% compared to 1986-2015). Due to the dry summer climate, the summer runoff in these areas is reliant on the glacier discharge. This is also evident in the impact on hydropower production. For the run-of-river plants along the Rhone, one has to expect a decrease in summer production of up to 20%, which corresponds to an annual loss of € 5.3 Million. The losses are even higher for storage power plants located in catchments with a big glacier cover. For these, annual losses of up to € 35.0 Million were determined for the period 2071-2100.
How to cite: Wallner, M., Abermann, J., Bachner, G., Frei, E., Schöner, W., and Steininger, K.: Future effects of glacier retreat on downstream runoff and hydropower generation in the Alps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7605, https://doi.org/10.5194/egusphere-egu22-7605, 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.
The change in climate, characterized by spatial and temporal variations in precipitation and temperature, significantly impacts the hydrological processes and water resources availability. Quantifying long-term changes in climatic variables and their effect on streamflow are crucial for understanding watershed hydrology and developing effective climate adaptation and water management strategies. In this study, we aim to quantify the changes in precipitation, temperature, and streamflow over the last 70 years (1950-2020) for two glacierized catchments in Nepal: Marsyangdi and Budigandaki River Basins. We utilize a distributed hydrological model (HYMOD_DS) forced by the most recent release of the ERA5 Land reanalysis product. Our investigation focuses on evaluating the impact of spatiotemporal changes in precipitation phases (either snow or rainfall) on streamflow characteristics. Specifically, we analyze the temporal trends and changes in the distribution of snow and rainfall and resulting streamflow separated into surface runoff and baseflow at daily and seasonal scales. The ERA5 Land reanalysis indicates a decrease in mean annual total precipitation for the period 1950-1980 and an increasing trend afterward. Annual mean temperature exhibits a rising trend for the entire period. Streamflow simulations for both basins revealed a significantly increased total flow over the last 20 years, primarily due to an increase in rainfall-induced streamflow. The results from this study will provide critical insight into the hydrology of glacierized basins and serve as a reference for water resources planning under climate change.
How to cite: Vijayan Nair, A., Wi, S., Gleason, C., Kayastha, R. B., and Nikolopoulos, E. I.: Climate change impact on precipitation-phase partitioning and streamflow for glacierized catchments in Nepal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10735, https://doi.org/10.5194/egusphere-egu22-10735, 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.
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