Articles | Volume 18, issue 2
https://doi.org/10.5194/hess-18-511-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-511-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 Feb 2014
Research article |
| 10 Feb 2014
Contribution of snow and glacier melt to discharge for highly glacierised catchments in Norway
M. Engelhardt
Department of Geosciences, University of Oslo, Oslo, Norway
T. V. Schuler
Department of Geosciences, University of Oslo, Oslo, Norway
L. M. Andreassen
Norwegian Water Resources and Energy Directorate, Oslo, Norway
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Livia Piermattei, Michael Zemp, Christian Sommer, Fanny Brun, Matthias H. Braun, Liss M. Andreassen, Joaquín M. C. Belart, Etienne Berthier, Atanu Bhattacharya, Laura Boehm Vock, Tobias Bolch, Amaury Dehecq, Inés Dussaillant, Daniel Falaschi, Caitlyn Florentine, Dana Floricioiu, Christian Ginzler, Gregoire Guillet, Romain Hugonnet, Matthias Huss, Andreas Kääb, Owen King, Christoph Klug, Friedrich Knuth, Lukas Krieger, Jeff La Frenierre, Robert McNabb, Christopher McNeil, Rainer Prinz, Louis Sass, Thorsten Seehaus, David Shean, Désirée Treichler, Anja Wendt, and Ruitang Yang
The Cryosphere, 18, 3195–3230, https://doi.org/10.5194/tc-18-3195-2024, https://doi.org/10.5194/tc-18-3195-2024, 2024
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Satellites have made it possible to observe glacier elevation changes from all around the world. In the present study, we compared the results produced from two different types of satellite data between different research groups and against validation measurements from aeroplanes. We found a large spread between individual results but showed that the group ensemble can be used to reliably estimate glacier elevation changes and related errors from satellite data.
Mette Kusk Gillespie, Liss Marie Andreassen, Matthias Huss, Simon de Villiers, Kamilla Hauknes Sjursen, Jostein Aasen, Jostein Bakke, Jan Magne Cederstrøm, Halgeir Elvehøy, Bjarne Kjøllmoen, Even Loe, Marte Meland, Kjetil Melvold, Sigurd Daniel Nerhus, Torgeir Opeland Røthe, Eivind Nagel Wilhelm Støren, Kåre Øst, and Jacob Clement Yde
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-167, https://doi.org/10.5194/essd-2024-167, 2024
Revised manuscript accepted for ESSD
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Here we present an extensive new ice thickness dataset from Jostedalsbreen ice cap which will serve as baseline for future studies of regional climate-induced change. Results show that Jostedalsbreen currently (~2020) has a maximum ice thickness of ~630 m, a mean ice thickness of 154 m ± 22 m and an ice volume of 70.6 ± 10.2 km3. Ice of less than 50 m thickness covers two narrow regions of the ice cap, and Jostedalsbreen is likely to separate into three smaller ice caps in a warming climate.
Coline Bouchayer, Ugo Nanni, Pierre-Marie Lefeuvre, John Hult, Louise Steffensen Schmidt, Jack Kohler, François Renard, and Thomas V. Schuler
The Cryosphere, 18, 2939–2968, https://doi.org/10.5194/tc-18-2939-2024, https://doi.org/10.5194/tc-18-2939-2024, 2024
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We explore the interplay between surface runoff and subglacial conditions. We focus on Kongsvegen glacier in Svalbard. We drilled 350 m down to the glacier base to measure water pressure, till strength, seismic noise, and glacier surface velocity. In the low-melt season, the drainage system adapted gradually, while the high-melt season led to a transient response, exceeding drainage capacity and enhancing sliding. Our findings contribute to discussions on subglacial hydro-mechanical processes.
Thomas J. Barnes, Thomas V. Schuler, Simon Filhol, and Karianne S. Lilleøren
Earth Surf. Dynam., 12, 801–818, https://doi.org/10.5194/esurf-12-801-2024, https://doi.org/10.5194/esurf-12-801-2024, 2024
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In this paper, we use machine learning to automatically outline landforms based on their characteristics. We test several methods to identify the most accurate and then proceed to develop the most accurate to improve its accuracy further. We manage to outline landforms with 65 %–75 % accuracy, at a resolution of 10 m, thanks to high-quality/high-resolution elevation data. We find that it is possible to run this method at a country scale to quickly produce landform inventories for future studies.
Etienne Berthier, Jérôme Lebreton, Delphine Fontannaz, Steven Hosford, Joaquin Munoz Cobo Belart, Fanny Brun, Liss Marie Andreassen, Brian Menounos, and Charlotte Blondel
EGUsphere, https://doi.org/10.5194/egusphere-2024-250, https://doi.org/10.5194/egusphere-2024-250, 2024
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Repeat elevation measurements are crucial for monitoring glacier health and how they affect river flows and sea levels. Until recently, high resolution elevation data were mostly available for polar regions and High Mountain Asia. Our project, the Pléiades Glacier Observatory (PGO), now provides high-resolution topographies of 140 glacier sites worldwide. This is a novel and open dataset to monitor the impact of climate change on glacier at high resolution and accuracy.
Andrea Spolaor, Federico Scoto, Catherine Larose, Elena Barbaro, Francois Burgay, Mats P. Bjorkman, David Cappelletti, Federico Dallo, Fabrizio de Blasi, Dmitry Divine, Giuliano Dreossi, Jacopo Gabrieli, Elisabeth Isaksson, Jack Kohler, Tonu Martma, Louise S. Schmidt, Thomas V. Schuler, Barbara Stenni, Clara Turetta, Bartłomiej Luks, Mathieu Casado, and Jean-Charles Gallet
The Cryosphere, 18, 307–320, https://doi.org/10.5194/tc-18-307-2024, https://doi.org/10.5194/tc-18-307-2024, 2024
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We evaluate the impact of the increased snowmelt on the preservation of the oxygen isotope (δ18O) signal in firn records recovered from the top of the Holtedahlfonna ice field located in the Svalbard archipelago. Thanks to a multidisciplinary approach we demonstrate a progressive deterioration of the isotope signal in the firn core. We link the degradation of the δ18O signal to the increased occurrence and intensity of melt events associated with the rapid warming occurring in the archipelago.
Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Erin Emily Thomas, and Sebastian Westermann
The Cryosphere, 17, 2941–2963, https://doi.org/10.5194/tc-17-2941-2023, https://doi.org/10.5194/tc-17-2941-2023, 2023
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Here, we present high-resolution simulations of glacier mass balance (the gain and loss of ice over a year) and runoff on Svalbard from 1991–2022, one of the fastest warming regions in the Arctic. The simulations are created using the CryoGrid community model. We find a small overall loss of mass over the simulation period of −0.08 m yr−1 but with no statistically significant trend. The average runoff was found to be 41 Gt yr−1, with a significant increasing trend of 6.3 Gt per decade.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev., 16, 2607–2647, https://doi.org/10.5194/gmd-16-2607-2023, https://doi.org/10.5194/gmd-16-2607-2023, 2023
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The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
Anirudha Mahagaonkar, Geir Moholdt, and Thomas V. Schuler
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-4, https://doi.org/10.5194/tc-2023-4, 2023
Revised manuscript not accepted
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Surface meltwater lakes along the margins of the Antarctic Ice Sheet can be important for ice shelf dynamics and stability. We used optical satellite imagery to study seasonal evolution of meltwater lakes in Dronning Maud Land. We found large interannual variability in lake extents, but with consistent seasonal patterns. Although correlation with summer air temperature was strong locally, other climatic and environmental factors need to be considered to explain the large regional variability.
Jonathan P. Conway, Jakob Abermann, Liss M. Andreassen, Mohd Farooq Azam, Nicolas J. Cullen, Noel Fitzpatrick, Rianne H. Giesen, Kirsty Langley, Shelley MacDonell, Thomas Mölg, Valentina Radić, Carleen H. Reijmer, and Jean-Emmanuel Sicart
The Cryosphere, 16, 3331–3356, https://doi.org/10.5194/tc-16-3331-2022, https://doi.org/10.5194/tc-16-3331-2022, 2022
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We used data from automatic weather stations on 16 glaciers to show how clouds influence glacier melt in different climates around the world. We found surface melt was always more frequent when it was cloudy but was not universally faster or slower than under clear-sky conditions. Also, air temperature was related to clouds in opposite ways in different climates – warmer with clouds in cold climates and vice versa. These results will help us improve how we model past and future glacier melt.
Chloé Scholzen, Thomas V. Schuler, and Adrien Gilbert
The Cryosphere, 15, 2719–2738, https://doi.org/10.5194/tc-15-2719-2021, https://doi.org/10.5194/tc-15-2719-2021, 2021
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We use a two-dimensional model of water flow below the glaciers in Kongsfjord, Svalbard, to investigate how different processes of surface-to-bed meltwater transfer affect subglacial hydraulic conditions. The latter are important for the sliding motion of glaciers, which in some cases exhibit huge variations. Our findings indicate that the glaciers in our study area undergo substantial sliding because water is poorly evacuated from their base, with limited influence from the surface hydrology.
Juditha Undine Schmidt, Bernd Etzelmüller, Thomas Vikhamar Schuler, Florence Magnin, Julia Boike, Moritz Langer, and Sebastian Westermann
The Cryosphere, 15, 2491–2509, https://doi.org/10.5194/tc-15-2491-2021, https://doi.org/10.5194/tc-15-2491-2021, 2021
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This study presents rock surface temperatures (RSTs) of steep high-Arctic rock walls on Svalbard from 2016 to 2020. The field data show that coastal cliffs are characterized by warmer RSTs than inland locations during winter seasons. By running model simulations, we analyze factors leading to that effect, calculate the surface energy balance and simulate different future scenarios. Both field data and model results can contribute to a further understanding of RST in high-Arctic rock walls.
Elena Barbaro, Krystyna Koziol, Mats P. Björkman, Carmen P. Vega, Christian Zdanowicz, Tonu Martma, Jean-Charles Gallet, Daniel Kępski, Catherine Larose, Bartłomiej Luks, Florian Tolle, Thomas V. Schuler, Aleksander Uszczyk, and Andrea Spolaor
Atmos. Chem. Phys., 21, 3163–3180, https://doi.org/10.5194/acp-21-3163-2021, https://doi.org/10.5194/acp-21-3163-2021, 2021
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This paper shows the most comprehensive seasonal snow chemistry survey to date, carried out in April 2016 across 22 sites on 7 glaciers across Svalbard. The dataset consists of the concentration, mass loading, spatial and altitudinal distribution of major ion species (Ca2+, K+,
Na2+, Mg2+,
NH4+, SO42−,
Br−, Cl− and
NO3−), together with its stable oxygen and hydrogen isotope composition (δ18O and
δ2H) in the snowpack. This study was part of the larger Community Coordinated Snow Study in Svalbard.
Christian Zdanowicz, Jean-Charles Gallet, Mats P. Björkman, Catherine Larose, Thomas Schuler, Bartłomiej Luks, Krystyna Koziol, Andrea Spolaor, Elena Barbaro, Tõnu Martma, Ward van Pelt, Ulla Wideqvist, and Johan Ström
Atmos. Chem. Phys., 21, 3035–3057, https://doi.org/10.5194/acp-21-3035-2021, https://doi.org/10.5194/acp-21-3035-2021, 2021
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Black carbon (BC) aerosols are soot-like particles which, when transported to the Arctic, darken snow surfaces, thus indirectly affecting climate. Information on BC in Arctic snow is needed to measure their impact and monitor the efficacy of pollution-reduction policies. This paper presents a large new set of BC measurements in snow in Svalbard collected between 2007 and 2018. It describes how BC in snow varies across the archipelago and explores some factors controlling these variations.
Andreas Alexander, Jaroslav Obu, Thomas V. Schuler, Andreas Kääb, and Hanne H. Christiansen
The Cryosphere, 14, 4217–4231, https://doi.org/10.5194/tc-14-4217-2020, https://doi.org/10.5194/tc-14-4217-2020, 2020
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In this study we present subglacial air, ice and sediment temperatures from within the basal drainage systems of two cold-based glaciers on Svalbard during late spring and the summer melt season. We put the data into the context of air temperature and rainfall at the glacier surface and show the importance of surface events on the subglacial thermal regime and erosion around basal drainage channels. Observed vertical erosion rates thereby reachup to 0.9 m d−1.
Ethan Welty, Michael Zemp, Francisco Navarro, Matthias Huss, Johannes J. Fürst, Isabelle Gärtner-Roer, Johannes Landmann, Horst Machguth, Kathrin Naegeli, Liss M. Andreassen, Daniel Farinotti, Huilin Li, and GlaThiDa Contributors
Earth Syst. Sci. Data, 12, 3039–3055, https://doi.org/10.5194/essd-12-3039-2020, https://doi.org/10.5194/essd-12-3039-2020, 2020
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Knowing the thickness of glacier ice is critical for predicting the rate of glacier loss and the myriad downstream impacts. To facilitate forecasts of future change, we have added 3 million measurements to our worldwide database of glacier thickness: 14 % of global glacier area is now within 1 km of a thickness measurement (up from 6 %). To make it easier to update and monitor the quality of our database, we have used automated tools to check and track changes to the data over time.
Aynom T. Teweldebrhan, Thomas V. Schuler, John F. Burkhart, and Morten Hjorth-Jensen
Hydrol. Earth Syst. Sci., 24, 4641–4658, https://doi.org/10.5194/hess-24-4641-2020, https://doi.org/10.5194/hess-24-4641-2020, 2020
Ankit Pramanik, Jack Kohler, Katrin Lindbäck, Penelope How, Ward Van Pelt, Glen Liston, and Thomas V. Schuler
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-197, https://doi.org/10.5194/tc-2020-197, 2020
Revised manuscript not accepted
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Freshwater discharge from tidewater glaciers influences fjord circulation and fjord ecosystem. Glacier hydrology plays crucial role in transporting water underneath glacier ice. We investigated hydrology beneath the tidewater glaciers of Kongsfjord basin in Northwest Svalbard and found that subglacial water flow differs substantially from surface flow of glacier ice. Furthermore, we derived freshwater discharge time-series from all the glaciers to the fjord.
Thomas Vikhamar Schuler and Torbjørn Ims Østby
Earth Syst. Sci. Data, 12, 875–885, https://doi.org/10.5194/essd-12-875-2020, https://doi.org/10.5194/essd-12-875-2020, 2020
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Atmospheric variables needed to force terrestrial process models (permafrost, glacier mass balance, seasonal snow, surface energy balance) have been downscaled from the ERA-40 and ERA-Interim reanalyses using methodology described in the accompanying paper. The gridded dataset has a horizontal resolution of 1 km and covers the entire Svalbard archipelago. The data have a temporal resolution of 6 h and cover the entire ERA-40 period (1957–2002) and the ERA-Interim period (1979–2017).
Andreas Alexander, Maarja Kruusmaa, Jeffrey A. Tuhtan, Andrew J. Hodson, Thomas V. Schuler, and Andreas Kääb
The Cryosphere, 14, 1009–1023, https://doi.org/10.5194/tc-14-1009-2020, https://doi.org/10.5194/tc-14-1009-2020, 2020
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This work shows the potential of pressure and inertia sensing drifters to measure flow parameters along glacial channels. The technology allows us to record the spatial distribution of water pressures, as well as an estimation of the flow velocity along the flow path in the channels. The measurements show a high repeatability and the potential to identify channel morphology from sensor readings.
Ward van Pelt, Veijo Pohjola, Rickard Pettersson, Sergey Marchenko, Jack Kohler, Bartłomiej Luks, Jon Ove Hagen, Thomas V. Schuler, Thorben Dunse, Brice Noël, and Carleen Reijmer
The Cryosphere, 13, 2259–2280, https://doi.org/10.5194/tc-13-2259-2019, https://doi.org/10.5194/tc-13-2259-2019, 2019
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The climate in Svalbard is undergoing amplified change compared to the global mean, which has a strong impact on the climatic mass balance of glaciers and the state of seasonal snow in land areas. In this study we analyze a coupled energy balance–subsurface model dataset, which provides detailed information on distributed climatic mass balance, snow conditions, and runoff across Svalbard between 1957 and 2018.
Aynom T. Teweldebrhan, John F. Burkhart, and Thomas V. Schuler
Hydrol. Earth Syst. Sci., 22, 5021–5039, https://doi.org/10.5194/hess-22-5021-2018, https://doi.org/10.5194/hess-22-5021-2018, 2018
Solveig H. Winsvold, Andreas Kääb, Christopher Nuth, Liss M. Andreassen, Ward J. J. van Pelt, and Thomas Schellenberger
The Cryosphere, 12, 867–890, https://doi.org/10.5194/tc-12-867-2018, https://doi.org/10.5194/tc-12-867-2018, 2018
Martin Beniston, Daniel Farinotti, Markus Stoffel, Liss M. Andreassen, Erika Coppola, Nicolas Eckert, Adriano Fantini, Florie Giacona, Christian Hauck, Matthias Huss, Hendrik Huwald, Michael Lehning, Juan-Ignacio López-Moreno, Jan Magnusson, Christoph Marty, Enrique Morán-Tejéda, Samuel Morin, Mohamed Naaim, Antonello Provenzale, Antoine Rabatel, Delphine Six, Johann Stötter, Ulrich Strasser, Silvia Terzago, and Christian Vincent
The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, https://doi.org/10.5194/tc-12-759-2018, 2018
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This paper makes a rather exhaustive overview of current knowledge of past, current, and future aspects of cryospheric issues in continental Europe and makes a number of reflections of areas of uncertainty requiring more attention in both scientific and policy terms. The review paper is completed by a bibliography containing 350 recent references that will certainly be of value to scholars engaged in the fields of glacier, snow, and permafrost research.
Kristoffer Aalstad, Sebastian Westermann, Thomas Vikhamar Schuler, Julia Boike, and Laurent Bertino
The Cryosphere, 12, 247–270, https://doi.org/10.5194/tc-12-247-2018, https://doi.org/10.5194/tc-12-247-2018, 2018
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We demonstrate how snow cover data from satellites can be used to constrain estimates of snow distributions at sites in the Arctic. In this effort, we make use of data assimilation to combine the information contained in the snow cover data with a simple snow model. By comparing our snow distribution estimates to independent observations, we find that this method performs favorably. Being modular, this method could be applied to other areas as a component of a larger reanalysis system.
Christopher J. L. D'Amboise, Karsten Müller, Laurent Oxarango, Samuel Morin, and Thomas V. Schuler
Geosci. Model Dev., 10, 3547–3566, https://doi.org/10.5194/gmd-10-3547-2017, https://doi.org/10.5194/gmd-10-3547-2017, 2017
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We present a new water percolation routine added to the Crocus model. The new routine is physically based, describing motion of water through a layered snowpack considering capillary-driven and gravity flow. We tested the routine on two data sets. Wet-snow layers were able to reach higher saturations than the empirical routine. Meaningful applicability is limited until new and better parameterizations of water retention are developed, and feedbacks are adjusted to handle higher saturations.
Daniel Farinotti, Douglas J. Brinkerhoff, Garry K. C. Clarke, Johannes J. Fürst, Holger Frey, Prateek Gantayat, Fabien Gillet-Chaulet, Claire Girard, Matthias Huss, Paul W. Leclercq, Andreas Linsbauer, Horst Machguth, Carlos Martin, Fabien Maussion, Mathieu Morlighem, Cyrille Mosbeux, Ankur Pandit, Andrea Portmann, Antoine Rabatel, RAAJ Ramsankaran, Thomas J. Reerink, Olivier Sanchez, Peter A. Stentoft, Sangita Singh Kumari, Ward J. J. van Pelt, Brian Anderson, Toby Benham, Daniel Binder, Julian A. Dowdeswell, Andrea Fischer, Kay Helfricht, Stanislav Kutuzov, Ivan Lavrentiev, Robert McNabb, G. Hilmar Gudmundsson, Huilin Li, and Liss M. Andreassen
The Cryosphere, 11, 949–970, https://doi.org/10.5194/tc-11-949-2017, https://doi.org/10.5194/tc-11-949-2017, 2017
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ITMIX – the Ice Thickness Models Intercomparison eXperiment – was the first coordinated performance assessment for models inferring glacier ice thickness from surface characteristics. Considering 17 different models and 21 different test cases, we show that although solutions of individual models can differ considerably, an ensemble average can yield uncertainties in the order of 10 ± 24 % the mean ice thickness. Ways forward for improving such estimates are sketched.
Thomas Schellenberger, Thorben Dunse, Andreas Kääb, Thomas Vikhamar Schuler, Jon Ove Hagen, and Carleen H. Reijmer
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-5, https://doi.org/10.5194/tc-2017-5, 2017
Preprint withdrawn
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Basin-3, NE-Svalbard, was still surging with 10 m d-1 in July 2016. After a speed peak of 18.8 m d-1 in Dec 2012/Jan 2013, speed-ups are overlying the fast flow every summer. The glacier is massively calving icebergs (5.2 Gt yr-1 ~ 2 L drinking water for every human being daily!) which in the same order of magnitude as all other Svalbard glaciers together.
Since autumn 2015 also Basin-2 is surging with maximum velocities of 8.7 m d-1, an advance of more than 2 km and a mass loss of 0.7 Gt yr-1.
Torbjørn Ims Østby, Thomas Vikhamar Schuler, Jon Ove Hagen, Regine Hock, Jack Kohler, and Carleen H. Reijmer
The Cryosphere, 11, 191–215, https://doi.org/10.5194/tc-11-191-2017, https://doi.org/10.5194/tc-11-191-2017, 2017
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We present modelled climatic mass balance for all glaciers in Svalbard for the period 1957–2014 at 1 km resolution using a coupled surface energy balance and snowpack model, thereby closing temporal and spatial gaps in direct and geodetic mass balance estimates.
Supporting previous studies, our results indicate increased mass loss over the period.
A detailed analysis of the involved energy fluxes reveals that increased mass loss is caused by atmospheric warming further amplified by feedbacks.
Walter Immerzeel, Philip Kraaijenbrink, and Liss Andreassen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-292, https://doi.org/10.5194/tc-2016-292, 2017
Revised manuscript not accepted
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Unmanned Aerial Vehicles (UAV) have become increasingly popular in environmental monitoring. In this study we use a UAV to derive a very detailed digital elevation model (DEM) of Storbreen in Norway. We compare our results with a past DEM to derive the mass balance of this glacier. Our results confirm strong mass loss and retreat of continental glaciers in southern Norway and we conclude that UAVs are effective tools in stuyding mountain glaciers at a high level of detail.
Rune Strand Ødegård, Atle Nesje, Ketil Isaksen, Liss Marie Andreassen, Trond Eiken, Margit Schwikowski, and Chiara Uglietti
The Cryosphere, 11, 17–32, https://doi.org/10.5194/tc-11-17-2017, https://doi.org/10.5194/tc-11-17-2017, 2017
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Despite numerous spectacular archaeological discoveries worldwide related to melting ice, governing processes related to ice patch development are still largely unexplored. We present new results from Jotunheimen in central southern Norway showing that the Juvfonne ice patch has existed continuously since ca. 7600 cal years BP. This is the oldest dating of ice in mainland Norway. Moss mats along the margin of Juvfonne in 2014 were covered by the expanding ice patch about 2000 years ago.
Kjersti Gisnås, Sebastian Westermann, Thomas Vikhamar Schuler, Kjetil Melvold, and Bernd Etzelmüller
The Cryosphere, 10, 1201–1215, https://doi.org/10.5194/tc-10-1201-2016, https://doi.org/10.5194/tc-10-1201-2016, 2016
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In wind exposed areas snow redistribution results in large spatial variability in ground temperatures. In these areas, the ground temperature of a grid cell must be determined based on the distribution, and not the average, of snow depths. We employ distribution functions of snow in a regional permafrost model, showing highly improved representation of ground temperatures. By including snow distributions, we find the permafrost area to be nearly twice as large as what is modelled without.
Kjetil S. Aas, Thorben Dunse, Emily Collier, Thomas V. Schuler, Terje K. Berntsen, Jack Kohler, and Bartłomiej Luks
The Cryosphere, 10, 1089–1104, https://doi.org/10.5194/tc-10-1089-2016, https://doi.org/10.5194/tc-10-1089-2016, 2016
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A high-resolution, coupled atmosphere--climatic mass balance (CMB) model is applied to Svalbard for the period 2003 to 2013. The mean CMB during this period is negative but displays large spatial and temporal variations. Comparison with observations on different scales shows a good overall model performance except for one particular glacier, where wind strongly affects the spatial patterns of CMB. The model also shows considerable sensitivity to model resolution, especially on local scales.
Liss M. Andreassen, Hallgeir Elvehøy, Bjarne Kjøllmoen, and Rune V. Engeset
The Cryosphere, 10, 535–552, https://doi.org/10.5194/tc-10-535-2016, https://doi.org/10.5194/tc-10-535-2016, 2016
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This study provides homogenised and partly calibrated data series of glaciological and geodetic mass balance for the 10 Norwegian glaciers with long-term observations. In total, 21 periods of data were compared. Uncertainties were quantified for relevant sources of errors, both in the glaciological and geodetic series. The reanalysis processes altered seasonal, annual, and cumulative as well as ELA and AAR values for many of the years for the 10 glaciers presented.
L. Gray, D. Burgess, L. Copland, M. N. Demuth, T. Dunse, K. Langley, and T. V. Schuler
The Cryosphere, 9, 1895–1913, https://doi.org/10.5194/tc-9-1895-2015, https://doi.org/10.5194/tc-9-1895-2015, 2015
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We show that the Cryosat (CS) radar altimeter can measure elevation change on a variety of Arctic ice caps. With the frequent coverage of Cryosat it is even possible to track summer surface height loss due to extensive melt; no other satellite altimeter has been able to do this. However, we also show that under cold conditions there is a bias between the surface and Cryosat detected elevation which varies with the conditions of the upper snow and firn layers.
S. Westermann, T. I. Østby, K. Gisnås, T. V. Schuler, and B. Etzelmüller
The Cryosphere, 9, 1303–1319, https://doi.org/10.5194/tc-9-1303-2015, https://doi.org/10.5194/tc-9-1303-2015, 2015
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We use remotely sensed land surface temperature and land cover in conjunction with air temperature and snowfall from a reanalysis product as input for a simple permafrost model. The scheme is applied to the permafrost regions bordering the North Atlantic. A comparison with ground temperatures in boreholes suggests a modeling accuracy of 2 to 2.5 °C.
T. Dunse, T. Schellenberger, J. O. Hagen, A. Kääb, T. V. Schuler, and C. H. Reijmer
The Cryosphere, 9, 197–215, https://doi.org/10.5194/tc-9-197-2015, https://doi.org/10.5194/tc-9-197-2015, 2015
K. Gisnås, S. Westermann, T. V. Schuler, T. Litherland, K. Isaksen, J. Boike, and B. Etzelmüller
The Cryosphere, 8, 2063–2074, https://doi.org/10.5194/tc-8-2063-2014, https://doi.org/10.5194/tc-8-2063-2014, 2014
S. H. Winsvold, L. M. Andreassen, and C. Kienholz
The Cryosphere, 8, 1885–1903, https://doi.org/10.5194/tc-8-1885-2014, https://doi.org/10.5194/tc-8-1885-2014, 2014
M. Zemp, E. Thibert, M. Huss, D. Stumm, C. Rolstad Denby, C. Nuth, S. U. Nussbaumer, G. Moholdt, A. Mercer, C. Mayer, P. C. Joerg, P. Jansson, B. Hynek, A. Fischer, H. Escher-Vetter, H. Elvehøy, and L. M. Andreassen
The Cryosphere, 7, 1227–1245, https://doi.org/10.5194/tc-7-1227-2013, https://doi.org/10.5194/tc-7-1227-2013, 2013
S. Westermann, T. V. Schuler, K. Gisnås, and B. Etzelmüller
The Cryosphere, 7, 719–739, https://doi.org/10.5194/tc-7-719-2013, https://doi.org/10.5194/tc-7-719-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Simulation-based inference for parameter estimation of complex watershed simulators
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Catchment response to climatic variability: implications for root zone storage and streamflow predictions
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
Elevational control of isotopic composition and application in understanding hydrologic processes in the mid Merced River catchment, Sierra Nevada, California, USA
Lack of robustness of hydrological models: A large-sample diagnosis and an attempt to identify the hydrological and climatic drivers
The Significance of the Leaf-Area-Index on the Evapotranspiration Estimation in SWAT-T for Characteristic Land Cover Types of Western Africa
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Broadleaf afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Toward interpretable LSTM-based modeling of hydrological systems
Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model
What controls the tail behaviour of flood series: rainfall or runoff generation?
Learning Landscape Features from Streamflow with Autoencoders
Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California
Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
Improving the internal hydrological consistency of a process-based solute-transport model by simultaneous calibration of streamflow and stream concentrations
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
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We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
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This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
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This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
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A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
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Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
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
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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.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
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Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
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An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
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The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
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By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
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Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
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Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
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Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
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Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
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Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
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Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
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We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
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In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-80, https://doi.org/10.5194/hess-2024-80, 2024
Revised manuscript accepted for HESS
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This work aims at investigating how hydrological models can be transferred to a period in which climatic conditions are different to the ones of the period in which it was set up. The RAT method, built to detect dependencies between model error and climatic drivers, was applied to 3 different hydrological models on 352 catchments in Denmark, France and Sweden. Potential issues are detected for a significant number of catchments for the 3 models even though these catchments differ for each model.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-131, https://doi.org/10.5194/hess-2024-131, 2024
Revised manuscript accepted for HESS
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ET is computed from vegetation (plant transpiration) and soil (soil evaporation). In Western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented with the leaf-area-index (LAI). In this study, we evaluate the importance of LAI for the ET calculation. We take a close look at the LAI-ET interaction and show the relevance to consider both, LAI and ET. Our work contributes to the understanding of the processes of the terrestrial water cycle.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
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Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
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We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
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This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
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To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-57, https://doi.org/10.5194/hess-2024-57, 2024
Revised manuscript accepted for HESS
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. In this work we investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analysis indicate that adding two vegetation is enough to improve the representation of evaporation, and the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
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Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
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Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
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Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
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In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-47, https://doi.org/10.5194/hess-2024-47, 2024
Revised manuscript accepted for HESS
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature needed for challenging cases, associated with aridity and intermittent flow. Baseflow index, aridity, and soil/vegetation attributes strongly correlate with learned features, indicating their importance for streamflow prediction.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
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In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
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This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
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Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
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We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
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Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
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How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-292, https://doi.org/10.5194/hess-2023-292, 2024
Revised manuscript accepted for HESS
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To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their ability to reproduce observed system dynamics. Using a model to represent the dynamics of water, and nitrate and dissolved organic carbon concentrations in a catchment, we showed that using solute concentrations for calibration improved the consistency of the model. This study demonstrates that hydrochemical data are useful for improving the representation of hydrological systems.
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