Articles | Volume 20, issue 12
https://doi.org/10.5194/nhess-20-3521-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-3521-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
17 Dec 2020
Research article | Highlight paper |
| 17 Dec 2020
| 17 Dec 2020
Downsizing parameter ensembles for simulations of rare floods
Anna E. Sikorska-Senoner
CORRESPONDING AUTHOR
University of Zurich, Department of Geography, Zurich, Switzerland
Bettina Schaefli
University of Lausanne, Institute of Earth Surface Dynamics, Lausanne, Switzerland
University of Bern, Institute of Geography, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Jan Seibert
University of Zurich, Department of Geography, Zurich, Switzerland
Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment, Uppsala, Sweden
Related authors
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
Short summary
Short summary
CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
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.
Silja Stefnisdóttir, Anna E. Sikorska-Senoner, Eyjólfur I. Ásgeirsson, and David C. Finger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-325, https://doi.org/10.5194/hess-2021-325, 2021
Manuscript not accepted for further review
Short summary
Short summary
We combine multiple dataset calibration with metaheuristic calibration techniques, namely Mone Carlo (MC), Simulated Annealing (SA) and Genetic Algorithms (GA), to improve hydrological models. Our results demonstrate that GA improves the overall performance of hydrological models. This leads to precise scenario simulations and, accordingly, is a major achievement in hydrology.
Ondrej Hotovy, Ondrej Nedelcev, Jan Seibert, and Michal Jenicek
Hydrol. Earth Syst. Sci., 29, 4199–4217, https://doi.org/10.5194/hess-29-4199-2025, https://doi.org/10.5194/hess-29-4199-2025, 2025
Short summary
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.
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.
Florentin Hofmeister, Xinyang Fan, Madlene Pfeiffer, Ben Marzeion, Bettina Schaefli, and Gabriele Chiogna
EGUsphere, https://doi.org/10.5194/egusphere-2025-3256, https://doi.org/10.5194/egusphere-2025-3256, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
We use the WRF model for dynamically downscaling a global reanalysis product for the period 1850 to 2015 for the central European Alps. We demonstrate a workflow for transferring coarse-resolution (2 km) WRF temperature and precipitation to a much finer spatial resolution (25 m) of a physics-based hydrological model (WaSiM) and evaluate the results in a multi-data approach covering different simulation periods. Our results highlight the need for plausible and consistent elevation gradients.
Xinyang Fan, Florentin Hofmeister, Bettina Schaefli, and Gabriele Chiogna
EGUsphere, https://doi.org/10.5194/egusphere-2025-1500, https://doi.org/10.5194/egusphere-2025-1500, 2025
Preprint archived
Short summary
Short summary
We adopt a fully-distributed, physics-based hydrological modeling approach, to understand streamflow variations and their interactions with groundwater in a high-elevation glaciated environment. We demonstrate opportunities and challenges of integrating point-scale groundwater observations into a distributed model. This study sheds new lights on surface-subsurface processes in high alpine environments and highlights the importance of improving subsurface representation in hydrological modeling.
Malve Heinz, Maria Eliza Turek, Bettina Schaefli, Andreas Keiser, and Annelie Holzkämper
Hydrol. Earth Syst. Sci., 29, 1807–1827, https://doi.org/10.5194/hess-29-1807-2025, https://doi.org/10.5194/hess-29-1807-2025, 2025
Short summary
Short summary
Potato farmers in Switzerland are facing drier conditions and water restrictions. We explored how improving soil health and planting early-maturing potato varieties might help them to adapt. Using a computer model, we simulated potato yields and irrigation water needs under water scarcity. Our results show that earlier-maturing potato varieties reduce the reliance on irrigation but result in lower yields. However, improving soil health can significantly reduce yield losses.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025, https://doi.org/10.5194/hess-29-1725-2025, 2025
Short summary
Short summary
In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until we observe overparameterization.
Adrià Fontrodona-Bach, Bettina Schaefli, Ross Woods, and Joshua R. Larsen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1214, https://doi.org/10.5194/egusphere-2025-1214, 2025
Short summary
Short summary
Investigating changing snow in response to global warming can be done with a simple model and only temperature and precipitation data, simplifying snow dynamics with assumptions and parameters. We provide a large-scale and long-term evaluation of this approach and its performance across diverse climates. Temperature thresholds are more robust over cold climates but melt parameters are more robust over warmer climates with deep snow. The model performs well across climates despite its simplicity.
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.
Tom Müller, Mauro Fischer, Stuart N. Lane, and Bettina Schaefli
The Cryosphere, 19, 423–458, https://doi.org/10.5194/tc-19-423-2025, https://doi.org/10.5194/tc-19-423-2025, 2025
Short summary
Short summary
Based on extensive field observations in a highly glacierized catchment in the Swiss Alps, we develop a combined isotopic and glacio-hydrological model. We show that water stable isotopes may help to better constrain model parameters, especially those linked to water transfer. However, we highlight that separating snow and ice melt for temperate glaciers based on isotope mixing models alone is not advised and should only be considered if their isotopic signatures have clearly different values.
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.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Proc. IAHS, 385, 121–127, https://doi.org/10.5194/piahs-385-121-2024, https://doi.org/10.5194/piahs-385-121-2024, 2024
Short summary
Short summary
This study assesses the impact of climate change on the timing, seasonality and magnitude of mean annual minimum (MAM) flows and annual maximum flows (AMF) in the Volta River basin (VRB). Several climate change projection data are use to simulate river flow under multiple greenhouse gas emission scenarios. Future projections show that AMF could increase with various magnitude but negligible shift in time across the VRB, while MAM could decrease with up to 14 days of delay in occurrence.
Tom Müller, Matteo Roncoroni, Davide Mancini, Stuart N. Lane, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 28, 735–759, https://doi.org/10.5194/hess-28-735-2024, https://doi.org/10.5194/hess-28-735-2024, 2024
Short summary
Short summary
We investigate the role of a newly formed floodplain in an alpine glaciated catchment to store and release water. Based on field measurements, we built a numerical model to simulate the water fluxes and show that recharge occurs mainly due to the ice-melt-fed river. We identify three future floodplains, which could emerge from glacier retreat, and show that their combined storage leads to some additional groundwater storage but contributes little additional baseflow for the downstream river.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
Short summary
Short summary
CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Adrià Fontrodona-Bach, Bettina Schaefli, Ross Woods, Adriaan J. Teuling, and Joshua R. Larsen
Earth Syst. Sci. Data, 15, 2577–2599, https://doi.org/10.5194/essd-15-2577-2023, https://doi.org/10.5194/essd-15-2577-2023, 2023
Short summary
Short summary
We provide a dataset of snow water equivalent, the depth of liquid water that results from melting a given depth of snow. The dataset contains 11 071 sites over the Northern Hemisphere, spans the period 1950–2022, and is based on daily observations of snow depth on the ground and a model. The dataset fills a lack of accessible historical ground snow data, and it can be used for a variety of applications such as the impact of climate change on global and regional snow and water resources.
Alessio Gentile, Davide Canone, Natalie Ceperley, Davide Gisolo, Maurizio Previati, Giulia Zuecco, Bettina Schaefli, and Stefano Ferraris
Hydrol. Earth Syst. Sci., 27, 2301–2323, https://doi.org/10.5194/hess-27-2301-2023, https://doi.org/10.5194/hess-27-2301-2023, 2023
Short summary
Short summary
What drives young water fraction, F*yw (i.e., the fraction of water in streamflow younger than 2–3 months), variations with elevation? Why is F*yw counterintuitively low in high-elevation catchments, in spite of steeper topography? In this paper, we present a perceptual model explaining how the longer low-flow duration at high elevations, driven by the persistence of winter snowpacks, increases the proportion of stored (old) water contributing to the stream, thus reducing F*yw.
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.
Anthony Michelon, Natalie Ceperley, Harsh Beria, Joshua Larsen, Torsten Vennemann, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 27, 1403–1430, https://doi.org/10.5194/hess-27-1403-2023, https://doi.org/10.5194/hess-27-1403-2023, 2023
Short summary
Short summary
Streamflow generation processes in high-elevation catchments are largely influenced by snow accumulation and melt. For this work, we collected and analyzed more than 2800 water samples (temperature, electric conductivity, and stable isotopes of water) to characterize the hydrological processes in such a high Alpine environment. Our results underline the critical role of subsurface flow during all melt periods and the presence of snowmelt even during the winter periods.
Tom Müller, Stuart N. Lane, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 6029–6054, https://doi.org/10.5194/hess-26-6029-2022, https://doi.org/10.5194/hess-26-6029-2022, 2022
Short summary
Short summary
This research provides a comprehensive analysis of groundwater storage in Alpine glacier forefields, a zone rapidly evolving with glacier retreat. Based on data analysis of a case study, it provides a simple perceptual model showing where and how groundwater is stored and released in a high Alpine environment. It especially points out the presence of groundwater storages in both fluvial and bedrock aquifers, which may become more important with future glacier retreat.
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.
Feiko Bernard van Zadelhoff, Adel Albaba, Denis Cohen, Chris Phillips, Bettina Schaefli, Luuk Dorren, and Massimiliano Schwarz
Nat. Hazards Earth Syst. Sci., 22, 2611–2635, https://doi.org/10.5194/nhess-22-2611-2022, https://doi.org/10.5194/nhess-22-2611-2022, 2022
Short summary
Short summary
Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard and the impact of protective measures can reduce losses. We developed a model (SlideforMAP) that can assess the shallow-landslide risk on a regional scale for specific rainfall events. Trees are an effective and cheap protective measure on a regional scale. Our model can assess their hazard reduction down to the individual tree level.
Alexandre Tuel, Bettina Schaefli, Jakob Zscheischler, and Olivia Martius
Hydrol. Earth Syst. Sci., 26, 2649–2669, https://doi.org/10.5194/hess-26-2649-2022, https://doi.org/10.5194/hess-26-2649-2022, 2022
Short summary
Short summary
River discharge is strongly influenced by the temporal structure of precipitation. Here, we show how extreme precipitation events that occur a few days or weeks after a previous event have a larger effect on river discharge than events occurring in isolation. Windows of 2 weeks or less between events have the most impact. Similarly, periods of persistent high discharge tend to be associated with the occurrence of several extreme precipitation events in close succession.
Stefan Brönnimann, Peter Stucki, Jörg Franke, Veronika Valler, Yuri Brugnara, Ralf Hand, Laura C. Slivinski, Gilbert P. Compo, Prashant D. Sardeshmukh, Michel Lang, and Bettina Schaefli
Clim. Past, 18, 919–933, https://doi.org/10.5194/cp-18-919-2022, https://doi.org/10.5194/cp-18-919-2022, 2022
Short summary
Short summary
Floods in Europe vary on time scales of several decades. Flood-rich and flood-poor periods alternate. Recently floods have again become more frequent. Long time series of peak stream flow, precipitation, and atmospheric variables reveal that until around 1980, these changes were mostly due to changes in atmospheric circulation. However, in recent decades the role of increasing atmospheric moisture due to climate warming has become more important and is now the main driver of flood changes.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022, https://doi.org/10.5194/hess-26-1481-2022, 2022
Short summary
Short summary
Climate change impacts on water resources in the Volta River basin are investigated under various global warming scenarios. Results reveal contrasting changes in future hydrological processes and water availability, depending on greenhouse gas emission scenarios, with implications for floods and drought occurrence over the 21st century. These findings provide insights for the elaboration of regional adaptation and mitigation strategies for climate change.
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.
Adrien Michel, Bettina Schaefli, Nander Wever, Harry Zekollari, Michael Lehning, and Hendrik Huwald
Hydrol. Earth Syst. Sci., 26, 1063–1087, https://doi.org/10.5194/hess-26-1063-2022, https://doi.org/10.5194/hess-26-1063-2022, 2022
Short summary
Short summary
This study presents an extensive study of climate change impacts on river temperature in Switzerland. Results show that, even for low-emission scenarios, water temperature increase will lead to adverse effects for both ecosystems and socio-economic sectors throughout the 21st century. For high-emission scenarios, the effect will worsen. This study also shows that water seasonal warming will be different between the Alpine regions and the lowlands. Finally, efficiency of models is assessed.
Silja Stefnisdóttir, Anna E. Sikorska-Senoner, Eyjólfur I. Ásgeirsson, and David C. Finger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-325, https://doi.org/10.5194/hess-2021-325, 2021
Manuscript not accepted for further review
Short summary
Short summary
We combine multiple dataset calibration with metaheuristic calibration techniques, namely Mone Carlo (MC), Simulated Annealing (SA) and Genetic Algorithms (GA), to improve hydrological models. Our results demonstrate that GA improves the overall performance of hydrological models. This leads to precise scenario simulations and, accordingly, is a major achievement in hydrology.
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.
Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 25, 2301–2325, https://doi.org/10.5194/hess-25-2301-2021, https://doi.org/10.5194/hess-25-2301-2021, 2021
Short summary
Short summary
Rainfall observation remains a challenge, particularly in mountain environments. Unlike most studies which are model based, this analysis of the rainfall–runoff response of a 13.4 km2 alpine catchment is purely data based and relies on measurements from a network of 12 low-cost rain gauges over 3 months. It assesses the importance of high-density rainfall observations in informing hydrological processes and helps in designing a permanent rain gauge network.
Elvira Mächler, Anham Salyani, Jean-Claude Walser, Annegret Larsen, Bettina Schaefli, Florian Altermatt, and Natalie Ceperley
Hydrol. Earth Syst. Sci., 25, 735–753, https://doi.org/10.5194/hess-25-735-2021, https://doi.org/10.5194/hess-25-735-2021, 2021
Short summary
Short summary
In this study, we collected water from an Alpine catchment in Switzerland and compared the genetic information of eukaryotic organisms conveyed by eDNA with the hydrologic information conveyed by naturally occurring hydrologic tracers. At the intersection of two disciplines, our study provides complementary knowledge gains and identifies the next steps to be addressed for using eDNA to achieve complementary insights into Alpine water sources.
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.
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.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406, https://doi.org/10.5194/hess-24-5379-2020, https://doi.org/10.5194/hess-24-5379-2020, 2020
Short summary
Short summary
This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
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. a
American Society of Civil Engineers: Hydrology Handbook, 2nd Edn., American Society of Civil Engineers, New York, https://doi.org/10.1061/9780784401385, 1996.
a
Arnaud, P. and Lavabre, J.: Coupled rainfall model and discharge model for
flood frequency estimation, Water Resour. Res., 38, 1075, https://doi.org/10.1029/2001WR000474, 2002. a, b
Arnaud, P., Cantet, P., and Odry, J.: Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling, J. Hydrol., 554, 360–369, https://doi.org/10.1016/j.jhydrol.2017.09.011, 2017. a, b
BAFU: Hochwasserstatistik Stationsbericht Dünnern – Olten,
Hammermüuhle, BAFU Bericht, available at:
https://www.hydrodaten.admin.ch/lhg/sdi/hq_studien/hq_statistics/2434_hq_Bericht.pdf (last access: 16 December 2020), 2017. a
Beauchamp, J., Leconte, R., Trudel, M., and Brissette, F.: Estimation of the
summer–fall PMP and PMF of a northern watershed under a changed climate, Water Resour. Res., 49, 3852–3862, https://doi.org/10.1002/wrcr.20336, 2013. a
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty
estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, https://doi.org/10.1016/S0022-1694(01)00421-8, 2001. a, b, c
Blazkova, S. and Beven, K.: Flood frequency estimation by continuous simulation for a catchment treated as ungauged (with uncertainty), Water Resour. Res., 38, 14–1–14–14, https://doi.org/10.1029/2001WR000500, 2002. a, b
Blazkova, S. and Beven, K.: Flood frequency estimation by continuous simulation of subcatchment rainfalls and discharges with the aim of improving dam safety assessment in a large basin in the Czech Republic, J. Hydrol., 292, 153–172, https://doi.org/10.1016/j.jhydrol.2003.12.025, 2004. a, b
Boughton, W. and Droop, O.: Continuous simulation for design flood estimation – a review, Environ. Model. Softw., 18, 309–318, https://doi.org/10.1016/S1364-8152(03)00004-5, 2003. a
Breinl, K.: Driving a lumped hydrological model with precipitation output from weather generators of different complexity, Hydrolog. Sci. J., 61, 1395–1414, https://doi.org/10.1080/02626667.2015.1036755, 2016. a
Brunner, M. I. and Sikorska-Senoner, A. E.: Dependence of flood peaks and
volumes in modeled discharge time series: Effect of different uncertainty
sources, J. Hydrol., 572, 620–629, https://doi.org/10.1016/j.jhydrol.2019.03.024, 2019. a, b
Brunner, M. I., Seibert, J., and Favre, A.-C.: Bivariate return periods and
their importance for flood peak and volume estimation, WIREs Water, 3, 819–833, https://doi.org/10.1002/wat2.1173, 2016. a
Brunner, M. I., Viviroli, D., Sikorska, A. E., Vannier, O., Favre, A.-C., and
Seibert, J.: Flood type specific construction of synthetic design hydrographs, Water Resour. Res., 53, 1390–1406, https://doi.org/10.1002/2016WR019535,
2017. a, b
Brunner, M. I., Furrer, R., Sikorska, A. E., Viviroli, D., Seibert, J., and
Favre, A. C.: Synthetic design hydrographs for ungauged catchments: a
comparison of regionalization methods, Stoch. Environ. Res. Risk A., 32, 1993–2023, https://doi.org/10.1007/s00477-018-1523-3, 2018a. a, b
Brunner, M. I., Sikorska, A. E., Furrer, R., and Favre, A.-C.: Uncertainty
Assessment of Synthetic Design Hydrographs for Gauged and Ungauged
Catchments, Water Resour. Res., 54, 1493–1512, https://doi.org/10.1002/2017WR021129, 2018b. a
Brunner, M. I., Sikorska, A. E., and Seibert, J.: Bivariate analysis of floods in climate impact assessments, Sci. Total Environ., 616–617, 1392–1403, https://doi.org/10.1016/j.scitotenv.2017.10.176, 2018c. a, b
Calver, A. and Lamb, R.: Flood frequency estimation using continuous
rainfall-runoff modelling, Phys. Chem. Earth, 20, 479–483, https://doi.org/10.1016/S0079-1946(96)00010-9, 1995. a
Cameron, D., Beven, K., Tawn, J., Blazkova, S., and Naden, P.: Flood frequency estimation by continuous simulation for a gauged upland catchment (with uncertainty), J. Hydrol., 219, 169–187, https://doi.org/10.1016/S0022-1694(99)00057-8, 1999. a, b
Cameron, D., Beven, K., Tawn, J., and Naden, P.: Flood frequency estimation by continuous simulation (with likelihood based uncertainty estimation), Hydrol. Earth Syst. Sci., 4, 23–34, https://doi.org/10.5194/hess-4-23-2000, 2000. a, b
Chow, V. T., Maidment, D. R., and Mays, L. W.: Applied Hydrology, Mc Graw-Hill, New York, 1988. a
Dawson, C., Abrahart, R., and See, L.: Hydrotest: a web-based toolbox of
evaluation metrics for the standardised assessment of hydrological forecasts,
Environ. Model. Softw., 22, 1034–1052, https://doi.org/10.1016/j.envsoft.2006.06.008, 2007. a
De Michele, C., Salvadori, G., Canossi, M., Petaccia, A., and Rosso, R.:
Bivariate Statistical Approach to Check Adequacy of Dam Spillway, J. Hydrol. Eng., 10, 50–57, https://doi.org/10.1061/(ASCE)1084-0699(2005)10:1(50), 2005. a
Eagleson, P.: Dynamics of flood frequency, Water Resour. Res., 8, 878–898, https://doi.org/10.1029/WR008i004p00878, 1972. a
Evin, G., Favre, A.-C., and Hingray, B.: Stochastic generation of multi-site
daily precipitation focusing on extreme events, Hydrol. Earth Syst. Sci., 22, 655–672, https://doi.org/10.5194/hess-22-655-2018, 2018. a, b, c, d
Evin, G., Favre, A.-C., and Hingray, B.: Stochastic generators of multi-site
daily temperature: comparison of performances in various applications,
Theor. App. Climatol., 135, 811–824, https://doi.org/10.1007/s00704-018-2404-x, 2019. a, b
Favre, A. C., El Adlouni, S., Luc Perreault, L., Thiémonge, N., and Bobé, B.: Multivariate hydrological frequency analysis using copulas, Water Resour. Res., 40, W01101, https://doi.org/10.1029/2003WR002456, 2004. a
Filipova, V., Lawrence, D., and Skaugen, T.: A stochastic event-based approach for flood estimation in catchments with mixed rainfall and snowmelt flood regimes, Nat. Hazards Earth Syst. Sci., 19, 1–18,
https://doi.org/10.5194/nhess-19-1-2019, 2019. a
Fischer, S.: A seasonal mixed-POT model to estimate high flood quantiles from
different event types and seasons, J. Appl. Stat., 45, 2831–2847, https://doi.org/10.1080/02664763.2018.1441385, 2018. a
Fischer, S., Schumann, A., and Schulte, M.: Characterisation of seasonal flood types according to timescales in mixed probability distributions, J. Hydrol., 539, 38–56, https://doi.org/10.1016/j.jhydrol.2016.05.005, 2016. a
FOEN: Historical data from the hydrometric stations on Swiss watercourses and lakes, Switzerland, available at: https://www.bafu.admin.ch, last access: 12 February 2020. a
Gaál, L., Szolgay, J., Kohnová, S., Hlavčová, K., Parajka, J., Viglione, A., Merz, R., and Blöschl, G.: Dependence between flood peaks and volumes: a case study on climate and hydrological controls, Hydrolog. Sci. J., 60, 968–984, https://doi.org/10.1080/02626667.2014.951361, 2015. a
Gabriel-Martin, I., Sordo-Ward, A., Garrote, L., and García, J. T.: Dependence Between Extreme Rainfall Events and the Seasonality and Bivariate Properties of Floods. A Continuous Distributed Physically-Based Approach, Water, 11, 1896, https://doi.org/10.3390/w11091896, 2019. a
Gangrade, S., Kao, S. C., Dullo, T. T., Kalyanapu, A. J., and Preston, B. L.:
Ensemble-based flood vulnerability assessment for probable maximum flood in a
changing environment, J. Hydrol., 576, 342–355, https://doi.org/10.1016/j.jhydrol.2019.06.027, 2019. a
Graler, B., van den Berg, M. J., Vandenberghe, S., Petroselli, A., Grimaldi,
S., De Baets, B., and Verhoest, N. E. C.: Multivariate return periods in
hydrology: a critical and practical review focusing on synthetic design
hydrograph estimation, Hydrol. Earth Syst. Sci., 17, 1281–1296,
https://doi.org/10.5194/hess-17-1281-2013, 2013. a
Griessinger, N., Seibert, J., Magnusson, J., and Jonas, T.: Assessing the
benefit of snow data assimilation for runoff modeling in Alpine catchments, Hydrol. Earth Syst. Sci., 20, 3895–3905, https://doi.org/10.5194/hess-20-3895-2016, 2016. a
Grimaldi, S., Petroselli, A., and Serinaldi, F.: Design hydrograph estimation
in small and ungauged watersheds: continuous simulation method versus
event-based approach, Hydrol. Process., 26, 3124–3134,
https://doi.org/10.1002/hyp.8384, 2012a. a
Grimaldi, S., Petroselli, A., and Serinaldi, F.: A continuous simulation model for design-hydrograph estimation in small and ungauged watersheds,
Hydrolog. Sci. J., 57, 1035–1051, https://doi.org/10.1080/02626667.2012.702214, 2012b. a
Grimaldi, S., Petroselli, A., Arcangeletti, E., and Nardi, F.: Flood mapping in ungauged basins using fully continuous hydrologic–hydraulic modeling, J. Hydrol., 487, 39–47, https://doi.org/10.1016/j.jhydrol.2013.02.023, 2013. a, b
Gringorten, I. I.: A plotting rule for extreme probability paper, J. Geophys. Res., 68, 813–814, https://doi.org/10.1029/JZ068i003p00813, 1963. a
Gupta, H., Kling, H., Yilmaz, K., and Martinez, G.: Decomposition of the mean
squared error and NSE performance criteria: Implications for improving
hydrological modelling, J. Hydrol., 377, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009. a
Hartigan, J. A. and Wong, M. A.: Algorithm AS 136: A K-Means Clustering
Algorithm, J. Roy. Stat. Soc. Ser. C, 28, 100–108, 1979. a
Hazewinkel, M.: Upper and lower bounds, In: Encyclopedia of Mathematics, edited by: Hazewinkel, M., Springer Science + Business Media B.V./Kluwer Academic Publishers, the Netherlands, 1994. a
Hoes, O. and Nelen, F.: Continuous simulation or event-based modelling to
estimate flood probabilities?, WIT Trans. Ecol. Environ., 80, 3–10, https://doi.org/10.2495/WRM050011, 2005. a
Jost, G., Moore, R. D., Menounos, B., and Wheate, R.: Quantifying the
contribution of glacier runoff to streamflow in the upper Columbia River
Basin, Canada, Hydrol. Earth Syst. Sci., 16, 849–860, https://doi.org/10.5194/hess-16-849-2012, 2012. a
Katz, R. W., Parlange, M. B., and Naveau, P.: Statistics of extremes in
hydrology, Adv. Water Resour., 25, 1287–1304, 2002. a
Kavetski, D., Fenicia, F., Reichert, P., and Albert, C.: Signature-Domain
Calibration of Hydrological Models Using Approximate Bayesian Computation:
Theory and Comparison to Existing Applications, Water Resour. Res., 54,
4059–4083, https://doi.org/10.1002/2017WR020528, 2018. a
Kochanek, K., Renard, B., Arnaud, P., Aubert, Y., Lang, M., Cipriani, T., and
Sauquet, E.: A data-based comparison of flood frequency analysis methods used
in France, Nat. Hazards Earth Syst. Sci., 14, 295–308,
https://doi.org/10.5194/nhess-14-295-2014, 2014. a, b
Kuchment, L. and Gelfan, A.: Assessment of extreme flood characteristics based on a dynamic-stochastic model of runoff generation and the probable maximum discharge, J. Flood Risk Manage., 4, 115–127,
https://doi.org/10.1111/j.1753-318X.2011.01096.x, 2011. a
Kundzewicz, Z. W., Krysanova, V., Dankers, R., Hirabayashi, Y., Kanae, S.,
Hattermann, F. F., Huang, S., Milly, P. C. D., Stoffel, M., Driessen, P. P. J., Matczak, P., Quevauviller, P., and Schellnhuber, H.-J.: Differences in
flood hazard projections in Europe – their causes and consequences for
decision making, Hydrolog. Sci. J., 62, 1–14, https://doi.org/10.1080/02626667.2016.1241398, 2017. a
Lamb, R. and Kay, A. L.: Confidence intervals for a spatially generalized,
continuous simulation flood frequency model for Great Britain, Water Resour. Res., 40, W07501, https://doi.org/10.1029/2003WR002428, 2004. a, b
Lamb, R., Faulkner, D., Wass, P., and Cameron, D.: Have applications of
continuous rainfall–runoff simulation realized the vision for process-based
flood frequency analysis?, Hydrol. Process., 30, 2463–2481,
https://doi.org/10.1002/hyp.10882, 2016. a
Mediero, L., Jimenez-Alvarez, A., and Garrote, L.: Design flood hydrographs
from the relationship between flood peak and volume, Hydrol. Earth Syst. Sci., 14, 2495–2505, https://doi.org/10.5194/hess-14-2495-2010, 2010. a
Merz, R. and Blöschl, G.: A process typology of regional floods, Water
Resour. Res., 39, W1340, https://doi.org/10.1029/2002WR001952, 2003. a, b
MeteoSwiss: MeteoSwiss ground level monitoring networks, Switzerland, available at: http://www.meteoswiss.ch, last access: 12 February 2020. a
Müller-Thomy, H. and Sikorska-Senoner, A. E.: Does the complexity in
temporal precipitation disaggregation matter for a lumped hydrological
model?, Hydrolog. Sci. J., 64, 1453–1471, https://doi.org/10.1080/02626667.2019.1638926, 2019. a
Paquet, E., Garavaglia, F., Garçon, R., and Gailhard, J.: The SCHADEX
method: A semi-continuous rainfall–runoff simulation for extreme flood
estimation, J. Hydrol., 495, 23–37, https://doi.org/10.1016/j.jhydrol.2013.04.045, 2013. a, b
Pramanik, N., Panda, R., and Sen, D.: Development of design flood hydrographs
using probability density functions, Hydrol. Process., 24, 415–428,
https://doi.org/10.1002/hyp.7494, 2010. a
Press, W., Teukolsky, S., Vetterling, W., and Flannery, B.: Numerical recipes
in C
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, available at: https://www.R-project.org/ (last access: 16 December 2020), 2019. a
Schumann, A. H., Nijssen, D., and Pahlow, M.: Handling uncertainties of
hydrological loads in flood retention planning, Int. J. River Basin Manage., 8, 281–294, https://doi.org/10.1080/15715124.2010.512561, 2010. a
Schürch, M., Kozel, R., Biaggi, D., and Weingartner, R.: Typisierung von
Grundwasserregimen in der Schweiz – Konzept und Fallbeispiele, Gas Wasser Abwasser, 11/2010, 955–965, 2010. a
Seibert, J.: Estimation of Parameter Uncertainty in the HBV Model, Hydrol. Res., 28, 247–262, https://doi.org/10.2166/nh.1998.15, 1997. a
Seibert, J.: Multi-criteria calibration of a conceptual runoff model using a
genetic algorithm, Hydrol. Earth Syst. Sci., 4, 215–224,
https://doi.org/10.5194/hess-4-215-2000, 2000. a
Seibert, J.: Reliability of model predictions outside calibration conditions,
Nord. Hydrol., 34, 477–492, https://doi.org/10.2166/nh.2003.0019, 2003. a
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. a
Serinaldi, F. and Grimaldi, S.: Synthetic Design Hydrographs Based on
Distribution Functions with Finite Support, J. Hydrol. Eng., 16, 434–446, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000339, 2011. a
Sikorska, A. and Seibert, J.: Appropriate temporal resolution of precipitation data for discharge modelling in pre-alpine catchments, Hydrolog. Sci. J., 61, 1–16, https://doi.org/10.1080/02626667.2017.1410279, 2018a. a
Sikorska, A. E. and Seibert, J.: Value of different precipitation data for
flood prediction in an alpine catchment: A Bayesian approach, J. Hydrol., 556, 961–971, https://doi.org/10.1016/j.jhydrol.2016.06.031, 2018b. a, b
Sikorska, A., Viviroli, D., and Seibert, J.: Effective precipitation duration
for runoff peaks based on catchment modelling, J. Hydrol., 556, 510–522, https://doi.org/10.1016/j.jhydrol.2017.11.028, 2018. a
Sikorska, A. E. and Renard, B.: Calibrating a hydrological model in stage space to account for rating curve uncertainties: general framework and key
challenges, Adv. Water Resour., 105, 51–66, https://doi.org/10.1016/j.advwatres.2017.04.011, 2017. a
Sikorska-Senoner, A. E. and Seibert, J.: Flood-type trend analysis for alpine
catchments, Hydrolog. Sci. J., 65, 1281–1299, https://doi.org/10.1080/02626667.2020.1749761, 2020. a
Sikorska, A. E., Viviroli, D., and Seibert, J.: Flood-type classification in
mountainous catchments using crisp and fuzzy decision trees, Water Resour.
Res., 51, 7959–7976, https://doi.org/10.1002/2015WR017326, 2015. a, b
Tung, Y. K., Yeh, K. C., and Yang, J. C.: Regionalization of unit hydrograph
parameters: 1. Comparison of regression analysis techniques, Stoch. Hydrol. Hydraul., 11, 145–171, https://doi.org/10.1007/BF02427913, 1997. a
Viglione, A. and Blöschl, G.: On the role of storm duration in the mapping of rainfall to flood return periods, Hydrol. Earth Syst. Sci., 13, 205–216, https://doi.org/10.5194/hess-13-205-2009, 2009. a
Viviroli, D., Kauzlaric, M., Sikorska-Senoner, A. E., Staudinger, M., Keller,
L., Whealton, C., Nicolet, G., Evin, G., Raynaud, D., Chardon, J., Favre,
A.-C., Hingray, B., Weingartner, R., and Seibert, J.: Estimation of extremely
rare floods in a large river basin from continuous hydrometeorological
simulations, in: Proceedings of INTERPRAEVENT, 11–14 May 2020, Bergen, Norway, 2020. a
Weingartner, R. and Aschwanden, H.: Abflussregimes als Grundlage zur
Abschätzung von Mittelwerten des Abflusses in Hydrologischer Atlas der Schweiz, available at: https://hydrologischeratlas.ch/produkte/druckausgabe# (last access: 16 December 2020), 1992. a
Westerberg, I. K., Sikorska-Senoner, A. E., Viviroli, D., Vis, M., and Seibert, J.: Hydrologic Model Calibration with Uncertain Discharge Data, Hydrolog. Sci. J., https://doi.org/10.1080/02626667.2020.1735638, in press, 2020. a, b, c
Winter, B., Schneeberger, K., Dung, N., Huttenlau, M., Achleitner, S.,
Stötter, J., Merz, B., and Vorogushyn, S.: A continuous modelling approach for design flood estimation on sub-daily time scale, Hydrolog. Sci. J., 64, 539–554, https://doi.org/10.1080/02626667.2019.1593419, 2019.
a
Zeimetz, F., Schaefli, B., Artigue, G., García Hernández, J., and Schleiss,
A.: A new approach to identify critical initial conditions for extreme flood
simulations based on deterministic and stochastic simulation, J. Hydrol. Eng., 23, 04018031, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001652, 2018. a, b
Zhang, L. and Singh Vijay, P.: Trivariate Flood Frequency Analysis Using the
Gumbel–Hougaard Copula, J. Hydrol. Eng., 12, 431–439,
https://doi.org/10.1061/(ASCE)1084-0699(2007)12:4(431), 2007. a
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.
This work proposes methods for reducing the computational requirements of hydrological...
Altmetrics
Final-revised paper
Preprint