Articles | Volume 29, issue 17
https://doi.org/10.5194/hess-29-4199-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-4199-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Sep 2025
Research article |
| 09 Sep 2025
| 09 Sep 2025
Rain-on-snow events in mountainous catchments under climate change
Ondrej Hotovy
Department of Physical Geography and Geoecology, Charles University, Prague, Czechia
Ondrej Nedelcev
Department of Physical Geography and Geoecology, Charles University, Prague, Czechia
Czech Hydrometeorological Institute, Prague, Czechia
Jan Seibert
Department of Geography, University of Zurich, Zurich, Switzerland
Michal Jenicek
CORRESPONDING AUTHOR
Department of Physical Geography and Geoecology, Charles University, Prague, Czechia
Related authors
No articles found.
Inhye Kong, Jan Seibert, and Ross S. Purves
Hydrol. Earth Syst. Sci., 29, 3795–3808, https://doi.org/10.5194/hess-29-3795-2025, https://doi.org/10.5194/hess-29-3795-2025, 2025
Short summary
Short summary
This study examines the timing and topics of newspaper coverage of droughts in England. Media attention correlated with drought-prone hydroclimatic conditions, particularly low precipitation and low groundwater levels, but also showed a seasonality bias, with more coverage in spring and summer, as exemplified by the 2022 summer drought. The findings reveal complex media dynamics in science communication, suggesting potential gaps in how droughts are framed by scientists versus the media.
Ondřej Nedělčev, Michael Matějka, Kamil Láska, Zbyněk Engel, Jan Kavan, and Michal Jenicek
The Cryosphere, 19, 2457–2473, https://doi.org/10.5194/tc-19-2457-2025, https://doi.org/10.5194/tc-19-2457-2025, 2025
Short summary
Short summary
The annual variability of runoff has not been analysed in the maritime Antarctic. Thus, we simulated and analysed rain, snow and glacier contributions to runoff related to climate variability in a small catchment over 11 years. The majority of the runoff came from snowmelt. Inter-annual variability in total runoff was associated with large variability in glacier runoff. Between October and May, 92 % of the runoff occurred, with significant runoff events outside the usual measurement season.
Thiago Victor Medeiros do Nascimento, Julia Rudlang, Sebastian Gnann, Jan Seibert, Markus Hrachowitz, and Fabrizio Fenicia
EGUsphere, https://doi.org/10.5194/egusphere-2025-739, https://doi.org/10.5194/egusphere-2025-739, 2025
Short summary
Short summary
Large-sample hydrological studies often overlook the importance of detailed landscape data in explaining river flow variability. Analyzing over 4,000 European catchments, we found that geology becomes a dominant factor—especially for baseflow—when using detailed regional maps. This highlights the need for high-resolution geological data to improve river flow regionalization, particularly in non-monitored areas.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
Short summary
Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Mijael Rodrigo Vargas Godoy, Yannis Markonis, Oldrich Rakovec, Michal Jenicek, Riya Dutta, Rajani Kumar Pradhan, Zuzana Bešťáková, Jan Kyselý, Roman Juras, Simon Michael Papalexiou, and Martin Hanel
Hydrol. Earth Syst. Sci., 28, 1–19, https://doi.org/10.5194/hess-28-1-2024, https://doi.org/10.5194/hess-28-1-2024, 2024
Short summary
Short summary
The study introduces a novel benchmarking method based on the water cycle budget for hydroclimate data fusion. Using this method and multiple state-of-the-art datasets to assess the spatiotemporal patterns of water cycle changes in Czechia, we found that differences in water availability distribution are dominated by evapotranspiration. Furthermore, while the most significant temporal changes in Czechia occur during spring, the median spatial patterns stem from summer changes in the water cycle.
Jana Erdbrügger, Ilja van Meerveld, Jan Seibert, and Kevin Bishop
Earth Syst. Sci. Data, 15, 1779–1800, https://doi.org/10.5194/essd-15-1779-2023, https://doi.org/10.5194/essd-15-1779-2023, 2023
Short summary
Short summary
Groundwater can respond quickly to precipitation and is the main source of streamflow in most catchments in humid, temperate climates. To better understand shallow groundwater dynamics, we installed a network of groundwater wells in two boreal headwater catchments in Sweden. We recorded groundwater levels in 75 wells for 2 years and sampled the water and analyzed its chemical composition in one summer. This paper describes these datasets.
Rosanna A. Lane, Gemma Coxon, Jim Freer, Jan Seibert, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 26, 5535–5554, https://doi.org/10.5194/hess-26-5535-2022, https://doi.org/10.5194/hess-26-5535-2022, 2022
Short summary
Short summary
This study modelled the impact of climate change on river high flows across Great Britain (GB). Generally, results indicated an increase in the magnitude and frequency of high flows along the west coast of GB by 2050–2075. In contrast, average flows decreased across GB. All flow projections contained large uncertainties; the climate projections were the largest source of uncertainty overall but hydrological modelling uncertainties were considerable in some regions.
Daniel Viviroli, Anna E. Sikorska-Senoner, Guillaume Evin, Maria Staudinger, Martina Kauzlaric, Jérémy Chardon, Anne-Catherine Favre, Benoit Hingray, Gilles Nicolet, Damien Raynaud, Jan Seibert, Rolf Weingartner, and Calvin Whealton
Nat. Hazards Earth Syst. Sci., 22, 2891–2920, https://doi.org/10.5194/nhess-22-2891-2022, https://doi.org/10.5194/nhess-22-2891-2022, 2022
Short summary
Short summary
Estimating the magnitude of rare to very rare floods is a challenging task due to a lack of sufficiently long observations. The challenge is even greater in large river basins, where precipitation patterns and amounts differ considerably between individual events and floods from different parts of the basin coincide. We show that a hydrometeorological model chain can provide plausible estimates in this setting and can thus inform flood risk and safety assessments for critical infrastructure.
Jan Seibert and Sten Bergström
Hydrol. Earth Syst. Sci., 26, 1371–1388, https://doi.org/10.5194/hess-26-1371-2022, https://doi.org/10.5194/hess-26-1371-2022, 2022
Short summary
Short summary
Hydrological catchment models are commonly used as the basis for water resource management planning. The HBV model, which is a typical example of such a model, was first applied about 50 years ago in Sweden. We describe and reflect on the model development and applications. The aim is to provide an understanding of the background of model development and a basis for addressing the balance between model complexity and data availability that will continue to face hydrologists in the future.
Marit Van Tiel, Anne F. Van Loon, Jan Seibert, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 25, 3245–3265, https://doi.org/10.5194/hess-25-3245-2021, https://doi.org/10.5194/hess-25-3245-2021, 2021
Short summary
Short summary
Glaciers can buffer streamflow during dry and warm periods, but under which circumstances can melt compensate precipitation deficits? Streamflow responses to warm and dry events were analyzed using
long-term observations of 50 glacierized catchments in Norway, Canada, and the European Alps. Region, timing of the event, relative glacier cover, and antecedent event conditions all affect the level of compensation during these events. This implies that glaciers do not compensate straightforwardly.
Camila Alvarez-Garreton, Juan Pablo Boisier, René Garreaud, Jan Seibert, and Marc Vis
Hydrol. Earth Syst. Sci., 25, 429–446, https://doi.org/10.5194/hess-25-429-2021, https://doi.org/10.5194/hess-25-429-2021, 2021
Short summary
Short summary
The megadrought experienced in Chile (2010–2020) has led to larger than expected water deficits. By analysing 106 basins with snow-/rainfall regimes, we relate such intensification with the hydrological memory of the basins, explained by snow and groundwater. Snow-dominated basins have larger memory and thus accumulate the effect of persistent precipitation deficits more strongly than pluvial basins. This notably affects central Chile, a water-limited region where most of the population lives.
Anna E. Sikorska-Senoner, Bettina Schaefli, and Jan Seibert
Nat. Hazards Earth Syst. Sci., 20, 3521–3549, https://doi.org/10.5194/nhess-20-3521-2020, https://doi.org/10.5194/nhess-20-3521-2020, 2020
Short summary
Short summary
This work proposes methods for reducing the computational requirements of hydrological simulations for the estimation of very rare floods that occur on average less than once in 1000 years. These methods enable the analysis of long streamflow time series (here for example 10 000 years) at low computational costs and with modelling uncertainty. They are to be used within continuous simulation frameworks with long input time series and are readily transferable to similar simulation tasks.
Maria Staudinger, Stefan Seeger, Barbara Herbstritt, Michael Stoelzle, Jan Seibert, Kerstin Stahl, and Markus Weiler
Earth Syst. Sci. Data, 12, 3057–3066, https://doi.org/10.5194/essd-12-3057-2020, https://doi.org/10.5194/essd-12-3057-2020, 2020
Short summary
Short summary
The data set CH-IRP provides isotope composition in precipitation and streamflow from 23 Swiss catchments, being unique regarding its long-term multi-catchment coverage along an alpine–pre-alpine gradient. CH-IRP contains fortnightly time series of stable water isotopes from streamflow grab samples complemented by time series in precipitation. Sampling conditions, catchment and climate information, lab standards and errors are provided together with areal precipitation and catchment boundaries.
Marc Girons Lopez, Marc J. P. Vis, Michal Jenicek, Nena Griessinger, and Jan Seibert
Hydrol. Earth Syst. Sci., 24, 4441–4461, https://doi.org/10.5194/hess-24-4441-2020, https://doi.org/10.5194/hess-24-4441-2020, 2020
Short summary
Short summary
Snow processes are crucial for runoff in mountainous areas, but their complexity makes water management difficult. Temperature models are widely used as they are simple and do not require much data, but not much thought is usually given to which model to use, which may lead to bad predictions. We studied the impact of many model alternatives and found that a more complex model does not necessarily perform better. Finding which processes are most important in each area is a much better strategy.
Cited articles
Addor, N., Rössler, O., Köplin, N., Huss, M., Weingartner, R., and Seibert, J.: Robust changes and sources of uncertainty in the projected hydrological regimes of Swiss catchments, Water Resour. Res., 50, 7541–7562, https://doi.org/10.1002/2014WR015549, 2014.
Bartsch, A., Kumpula, T., Forbes, B. C., and Stammler, F.: Detection of snow surface thawing and refreezing in the Eurasian arctic with QuikSCAT: Implications for reindeer herding, Ecol. Appl., 20, 2346–2358, https://doi.org/10.1890/09-1927.1, 2010.
Bartsch, A., Bergstedt, H., Pointner, G., Muri, X., Rautiainen, K., Leppänen, L., Joly, K., Sokolov, A., Orekhov, P., Ehrich, D., and Soininen, E. M.: Towards long-term records of rain-on-snow events across the Arctic from satellite data, The Cryosphere, 17, 889–915, https://doi.org/10.5194/tc-17-889-2023, 2023.
Beniston, M. and Stoffel, M.: Rain-on-snow events, floods and climate change in the Alps: Events may increase with warming up to 4 °C and decrease thereafter, Sci. Total Environ., 571, 228–236, https://doi.org/10.1016/j.scitotenv.2016.07.146, 2016.
Berghuijs, W. R., Harrigan, S., Molnar, P., Slater, L. J., and Kirchner, J. W.: The Relative Importance of Different Flood-Generating Mechanisms Across Europe, Water Resour. Res., 55, 4582–4593, https://doi.org/10.1029/2019WR024841, 2019.
Beven, K.: An epistemically uncertain walk through the rather fuzzy subject of observation and model uncertainties1, Hydrol. Process., 35, 1–9, https://doi.org/10.1002/hyp.14012, 2021.
Bieniek, P. A., Bhatt, U. S., Walsh, J. E., Lader, R., Griffith, B., Roach, J. K., and Thoman, R. L.: Assessment of Alaska rain-on-snow events using dynamical downscaling, J. Appl. Meteorol. Climatol., 57, 1847–1863, https://doi.org/10.1175/JAMC-D-17-0276.1, 2018.
Blahušiaková, A., Matoušková, M., Jenicek, M., Ledvinka, O., Kliment, Z., Podolinská, J., and Snopková, Z.: Snow and climate trends and their impact on seasonal runoff and hydrological drought types in selected mountain catchments in Central Europe, Hydrol. Sci. J., 65, 2083–2096, https://doi.org/10.1080/02626667.2020.1784900, 2020.
Brunner, M. I. and Fischer, S.: Snow-influenced floods are more strongly connected in space than purely rainfall-driven floods, Environ. Res. Lett., 17, 104038, https://doi.org/10.1088/1748-9326/ac948f, 2022.
Crawford, A. D., Alley, K. E., Cooke, A. M., and Serreze, M. C.: Synoptic climatology of rain-on-snow events in Alaska, Mon. Weather Rev., 148, 1275–1295, https://doi.org/10.1175/MWR-D-19-0311.1, 2020.
Cui, G., Anderson, M., and Bales, R.: Runoff response to the uncertainty from key water-budget variables in a seasonally snow-covered mountain basin, J. Hydrol. Reg. Stud., 50, 101601, https://doi.org/10.1016/j.ejrh.2023.101601, 2023.
Earman, S., Campbell, A. R., Phillips, F. M., and Newman, B. D.: Isotopic exchange between snow and atmospheric water vapor: Estimation of the snowmelt component of groundwater recharge in the southwestern United States, J. Geophys. Res., 111, D09302, https://doi.org/10.1029/2005JD006470, 2006.
Etter, S., Addor, N., Huss, M., and Finger, D.: Climate change impacts on future snow, ice and rain runoff in a Swiss mountain catchment using multi-dataset calibration, J. Hydrol. Reg. Stud., 13, 222–239, https://doi.org/10.1016/j.ejrh.2017.08.005, 2017.
Freudiger, D., Kohn, I., Stahl, K., and Weiler, M.: Large-scale analysis of changing frequencies of rain-on-snow events with flood-generation potential, Hydrol. Earth Syst. Sci., 18, 2695–2709, https://doi.org/10.5194/hess-18-2695-2014, 2014.
Garvelmann, J., Pohl, S., and Weiler, M.: Variability of Observed Energy Fluxes during Rain-on-Snow and Clear Sky Snowmelt in a Midlatitude Mountain Environment, J. Hydrometeorol., 15, 1220–1237, https://doi.org/10.1175/JHM-D-13-0187.1, 2014.
Garvelmann, J., Pohl, S., and Weiler, M.: Spatio-temporal controls of snowmelt and runoff generation during rain-on-snow events in a mid-latitude mountain catchment, Hydrol. Process., 29, 3649–3664, https://doi.org/10.1002/hyp.10460, 2015.
Girons Lopez, M., Vis, M. J. P., Jenicek, M., Griessinger, N., and Seibert, J.: Assessing the degree of detail of temperature-based snow routines for runoff modelling in mountainous areas in central Europe, Hydrol. Earth Syst. Sci., 24, 4441–4461, https://doi.org/10.5194/hess-24-4441-2020, 2020.
Grenfell, T. C. and Putkonen, J.: A method for the detection of the severe rain-on-snow event on Banks Island, October 2003, using passive microwave remote sensing, Water Resour. Res., 44, 3425, https://doi.org/10.1029/2007WR005929, 2008.
Gutiérrez, J. M., Jones, R. G., Narisma, G. T., Alves, L. M., Amjad, M., Gorodetskaya, I. V., Grose, M., Klutse, N. A. B., Krakovska, S., Li, J., Martinez-Castro, D., Mearns, L. O., Mernild, S. H., Ngo-Duc, T., van den Hurk, B., and Yoon, J. H.: Atlas, in: Climate Change 2021 – The Physical Science Basis, Cambridge University Press, 1927–2058, https://doi.org/10.1017/9781009157896.021, 2021.
Hale, K. E., Jennings, K. S., Musselman, K. N., Livneh, B., and Molotch, N. P.: Recent decreases in snow water storage in western North America, Commun. Earth Environ., 4, 1–11, https://doi.org/10.1038/s43247-023-00751-3, 2023.
Hotovy, O. and Jenicek, M.: The impact of changing subcanopy radiation on snowmelt in a disturbed coniferous forest, Hydrol. Process., 34, 5298–5314, https://doi.org/10.1002/hyp.13936, 2020.
Hotovy, O., Nedelcev, O., and Jenicek, M.: Changes in rain-on-snow events in mountain catchments in the rain–snow transition zone, Hydrol. Sci. J., 68, 572–584, https://doi.org/10.1080/02626667.2023.2177544, 2023.
Jenicek, M. and Ledvinka, O.: Importance of snowmelt contribution to seasonal runoff and summer low flows in Czechia, Hydrol. Earth Syst. Sci., 24, 3475–3491, https://doi.org/10.5194/hess-24-3475-2020, 2020.
Jenicek, M., Hnilica, J., Nedelcev, O., and Sipek, V.: Future changes in snowpack will impact seasonal runoff and low flows in Czechia, J. Hydrol. Reg. Stud., 37, 100899, https://doi.org/10.1016/j.ejrh.2021.100899, 2021.
Jenicek, M., Nedelcev, O., and Hotovy, O.: Supplementary data: Rain-on-snow events in mountainous catchments under climate change, Zenodo [data set], https://doi.org/10.5281/zenodo.12772038, 2024.
Jennings, K. S., Winchell, T. S., Livneh, B., and Molotch, N. P.: Spatial variation of the rain-snow temperature threshold across the Northern Hemisphere, Nat. Commun., 9, 1–9, https://doi.org/10.1038/s41467-018-03629-7, 2018.
Il Jeong, D. and Sushama, L.: Rain-on-snow events over North America based on two Canadian regional climate models, Clim. Dynam., 50, 303–316, https://doi.org/10.1007/s00382-017-3609-x, 2017.
Juras, R., Blöcher, J. R., Jenicek, M., Hotovy, O., and Markonis, Y.: What affects the hydrological response of rain-on-snow events in low-altitude mountain ranges in Central Europe?, J. Hydrol., 603, 127002, https://doi.org/10.1016/j.jhydrol.2021.127002, 2021.
Kotlarski, S., Gobiet, A., Morin, S., Olefs, M., Rajczak, J., and Samacoïts, R.: 21st Century alpine climate change, Clim. Dynam., 60, 65–86, https://doi.org/10.1007/s00382-022-06303-3, 2023.
Li, D., Lettenmaier, D. P., Margulis, S. A., and Andreadis, K.: The Role of Rain-on-Snow in Flooding Over the Conterminous United States, Water Resour. Res., 55, 8492–8513, https://doi.org/10.1029/2019WR024950, 2019.
Li, Z., Chen, Y., Li, Y., and Wang, Y.: Declining snowfall fraction in the alpine regions, Central Asia, Sci. Rep., 10, 1–12, https://doi.org/10.1038/s41598-020-60303-z, 2020.
Lindström, G., Johansson, B., Persson, M., Gardelin, M., and Bergström, S.: Development and test of the distributed HBV-96 hydrological model, J. Hydrol., 201, 272–288, https://doi.org/10.1016/S0022-1694(97)00041-3, 1997.
López-Moreno, J. I., Pomeroy, J. W., Morán-Tejeda, E., Revuelto, J., Navarro-Serrano, F. M., Vidaller, I., and Alonso-González, E.: Changes in the frequency of global high mountain rain-on-snow events due to climate warming, Environ. Res. Lett., 16, 094021, https://doi.org/10.1088/1748-9326/ac0dde, 2021.
Magnusson, J., Gustafsson, D., Hüsler, F., and Jonas, T.: Assimilation of point SWE data into a distributed snow cover model comparing two contrasting methods, Water Resour. Res., 50, 7816–7835, https://doi.org/10.1002/2014WR015302, 2014.
Maina, F. Z. and Kumar, S. V.: Diverging Trends in Rain-On-Snow Over High Mountain Asia, Earth's Futur., 11, e2022EF003009, https://doi.org/10.1029/2022EF003009, 2023.
Mccabe, G. J., Clark, M. P., and Hay, L. E.: Rain-on-snow events in the western United States, B. Am. Meteorol. Soc., 88, 319–328, https://doi.org/10.1175/BAMS-88-3-319, 2007.
Mooney, P. A. and Li, L.: Near future changes to rain-on-snow events in Norway, Environ. Res. Lett., 16, 064039, https://doi.org/10.1088/1748-9326/abfdeb, 2021.
Morán-Tejeda, E., López-Moreno, J. I., Stoffel, M., and Beniston, M.: Rain-on-snow events in Switzerland: Recent observations and projections for the 21st century, Clim. Res., 71, 111–125, https://doi.org/10.3354/cr01435, 2016.
Moriasi, D. N., Gitau, M. W., Pai, N., and Daggupati, P.: Hydrologic and water quality models: Performance measures and evaluation criteria, Trans. ASABE, 58, 1763–1785, https://doi.org/10.13031/trans.58.10715, 2015.
Mott, R., Winstral, A., Cluzet, B., Helbig, N., Magnusson, J., Mazzotti, G., Quéno, L., Schirmer, M., Webster, C., and Jonas, T.: Operational snow-hydrological modeling for Switzerland, Front. Earth Sci., 11, 1–20, https://doi.org/10.3389/feart.2023.1228158, 2023.
Musselman, K. N., Lehner, F., Ikeda, K., Clark, M. P., Prein, A. F., Liu, C., Barlage, M., and Rasmussen, R.: Projected increases and shifts in rain-on-snow flood risk over western North America, https://doi.org/10.1038/s41558-018-0236-4, 2018.
Myers, D. T., Ficklin, D. L., and Robeson, S. M.: Hydrologic implications of projected changes in rain-on-snow melt for Great Lakes Basin watersheds, Hydrol. Earth Syst. Sci., 27, 1755–1770, https://doi.org/10.5194/hess-27-1755-2023, 2023.
Nedelcev, O. and Jenicek, M.: Trends in seasonal snowpack and their relation to climate variables in mountain catchments in Czechia, Hydrol. Sci. J., 66, 2340–2356, https://doi.org/10.1080/02626667.2021.1990298, 2021.
Notarnicola, C.: Hotspots of snow cover changes in global mountain regions over 2000–2018, Remote Sens. Environ., 243, 111781, https://doi.org/10.1016/j.rse.2020.111781, 2020.
Ohba, M. and Kawase, H.: Rain-on-Snow events in Japan as projected by a large ensemble of regional climate simulations, Clim. Dynam., 55, 2785–2800, https://doi.org/10.1007/s00382-020-05419-8, 2020.
Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil, F., and Loumagne, C.: Which potential evapotranspiration input for a lumped rainfall-runoff model? Part 2 – Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling, J. Hydrol., 303, 290–306, https://doi.org/10.1016/j.jhydrol.2004.08.026, 2005.
Pall, P., Tallaksen, L. M., and Stordal, F.: A climatology of rain-on-snow events for Norway, J. Climate, 32, 6995–7016, https://doi.org/10.1175/JCLI-D-18-0529.1, 2019.
Parajka, J., Bezak, N., Burkhart, J., Hauksson, B., Holko, L., Hundecha, Y., Jenicek, M., Krajčí, P., Mangini, W., Molnar, P., Riboust, P., Rizzi, J., Sensoy, A., Thirel, G., and Viglione, A.: Modis snowline elevation changes during snowmelt runoff events in Europe, J. Hydrol. Hydromechanics, 67, 101–109, https://doi.org/10.2478/johh-2018-0011, 2019.
Poschlod, B., Zscheischler, J., Sillmann, J., Wood, R. R., and Ludwig, R.: Climate change effects on hydrometeorological compound events over southern Norway, Weather Clim. Extrem., 28, 100253, https://doi.org/10.1016/j.wace.2020.100253, 2020.
Schirmer, M., Winstral, A., Jonas, T., Burlando, P., and Peleg, N.: Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events, The Cryosphere, 16, 3469–3488, https://doi.org/10.5194/tc-16-3469-2022, 2022.
Seibert, J. and Bergström, S.: A retrospective on hydrological catchment modelling based on half a century with the HBV model, Hydrol. Earth Syst. Sci., 26, 1371–1388, https://doi.org/10.5194/hess-26-1371-2022, 2022.
Seibert, J. and Vis, M. J. P.: Teaching hydrological modeling with a user-friendly catchment-runoff-model software package, Hydrol. Earth Syst. Sci., 16, 3315–3325, https://doi.org/10.5194/hess-16-3315-2012, 2012.
Sezen, C., Sraj, M., Medved, A., and Bezak, N.: Investigation of rain-on-snow floods under climate change, Appl. Sci., 10, https://doi.org/10.3390/app10041242, 2020.
Sikorska-Senoner, A. E. and Seibert, J.: Flood-type trend analysis for alpine catchments, Hydrol. Sci. J., 65, 1281–1299, https://doi.org/10.1080/02626667.2020.1749761, 2020.
Surfleet, C. G. and Tullos, D.: Variability in effect of climate change on rain-on-snow peak flow events in a temperate climate, J. Hydrol., 479, 24–34, https://doi.org/10.1016/j.jhydrol.2012.11.021, 2013.
Suriano, Z. J.: North American rain-on-snow ablation climatology, Clim. Res., 87, 133–145, https://doi.org/10.3354/cr01687, 2022.
Trubilowicz, J. W. and Moore, R. D.: Quantifying the role of the snowpack in generating water available for run-off during rain-on-snow events from snow pillow records, Hydrol. Process., 31, 4136–4150, https://doi.org/10.1002/hyp.11310, 2017.
Urban, G., Richterová, D., Kliegrová, S., and Zusková, I.: Reasons for shortening snow cover duration in the Western Sudetes in light of global climate change, Int. J. Climatol., 43, 5485–5511, https://doi.org/10.1002/joc.8157, 2023.
Wayand, N. E., Lundquist, J. D., and Clark, M. P.: Modeling the influence of hypsometry, vegetation, and storm energy on snowmelt contributions to basins during rain-on-snow floods, Water Resour. Res., 51, 8551–8569, https://doi.org/10.1002/2014WR016576, 2015.
Würzer, S., Jonas, T., Wever, N., and Lehning, M.: Influence of Initial Snowpack Properties on Runoff Formation during Rain-on-Snow Events, J. Hydrometeorol., 17, 1801–1815, https://doi.org/10.1175/JHM-D-15-0181.1, 2016.
Yang, T., Li, Q., Hamdi, R., Chen, X., Zou, Q., Cui, F., De Maeyer, P., and Li, L.: Trends and spatial variations of rain-on-snow events over the high Mountain Asia, J. Hydrol., 614, 128593, https://doi.org/10.1016/j.jhydrol.2022.128593, 2022.
Yang, Z., Chen, R., Liu, Y., Zhao, Y., Liu, Z., and Liu, J.: The impact of rain-on-snow events on the snowmelt process: A field study, Hydrol. Process., 37, e15019, https://doi.org/10.1002/hyp.15019, 2023.
Short summary
Rain falling on snow (RoS) can accelerate snowmelt and affect runoff, potentially causing severe flooding. We assessed the regional and seasonal variations in the occurrence of RoS in mountainous catchments in central Europe under different perturbations of future climate. Our results showed that RoS changes driven by climate change vary greatly among regions, across elevations, and within the cold season. However, most projections suggested a decrease in RoS events and RoS-driven runoff.
Rain falling on snow (RoS) can accelerate snowmelt and affect runoff, potentially causing severe...
