Articles | Volume 26, issue 21
https://doi.org/10.5194/hess-26-5605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-5605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Nov 2022
Research article |
| 09 Nov 2022
| 09 Nov 2022
Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies
Eva Sebok
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Ernesto Pastén-Zapata
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Department of Geographical and Historical Studies, University of Eastern Finland, Joensuu, Finland
Peter Berg
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
Guillaume Thirel
HYCAR Research Unit, Université Paris-Saclay, INRAE, Antony,
France
Anthony Lemoine
HYCAR Research Unit, Université Paris-Saclay, INRAE, Antony,
France
Andrea Lira-Loarca
Andalusian Earth Sciences Institute, University of Granada, Granada, Spain
Christiana Photiadou
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
European Environment Agency, Copenhagen, Denmark
Rafael Pimentel
Fluvial Dynamics and Hydrology Research Group, Andalusian Institute
for Earth System Research (IISTA), University of Córdoba, Córdoba, Spain
Department of Agronomy, María de Maeztu Unit of Excellence
(DAUCO), University of Córdoba, Córdoba, Spain
Paul Royer-Gaspard
HYCAR Research Unit, Université Paris-Saclay, INRAE, Antony,
France
Erik Kjellström
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
Jens Hesselbjerg Christensen
Physics of Ice, Climate and Earth, Niels Bohr Institute, University of
Copenhagen, Copenhagen, Denmark
Bjerknes Centre for Climate
Research, NORCE Norwegian Research Centre, Bergen, Norway
Danish Meteorological Institute, Copenhagen, Denmark
Jean Philippe Vidal
RiverLy Research Unit, INRAE, Villeurbanne CEDEX, France
Philippe Lucas-Picher
Groupe de Météorologie de Grande Échelle et Climat,
Centre National de Recherches Météorologiques, Météo-France,
Toulouse, France
Département des sciences de la Terre et de l'atmosphère,
Université du Québec à Montréal, Montréal, Quebec,
Canada
Markus G. Donat
Barcelona Supercomputing Center, Barcelona, Spain
ICREA, Pg. Lluís Companys 23, Barcelona, Spain
Giovanni Besio
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy
María José Polo
Fluvial Dynamics and Hydrology Research Group, Andalusian Institute
for Earth System Research (IISTA), University of Córdoba, Córdoba, Spain
Department of Agronomy, María de Maeztu Unit of Excellence
(DAUCO), University of Córdoba, Córdoba, Spain
Simon Stisen
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Yvan Caballero
BRGM, University of Montpellier, Montpellier, France
Ilias G. Pechlivanidis
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
Lars Troldborg
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Jens Christian Refsgaard
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
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Laurent Strohmenger, Eric Sauquet, Claire Bernard, Jérémie Bonneau, Flora Branger, Amélie Bresson, Pierre Brigode, Rémy Buzier, Olivier Delaigue, Alexandre Devers, Guillaume Evin, Maïté Fournier, Shu-Chen Hsu, Sandra Lanini, Alban de Lavenne, Thibault Lemaitre-Basset, Claire Magand, Guilherme Mendoza Guimarães, Max Mentha, Simon Munier, Charles Perrin, Tristan Podechard, Léo Rouchy, Malak Sadki, Myriam Soutif-Bellenger, François Tilmant, Yves Tramblay, Anne-Lise Véron, Jean-Philippe Vidal, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 27, 3375–3391, https://doi.org/10.5194/hess-27-3375-2023, https://doi.org/10.5194/hess-27-3375-2023, 2023
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Gustav Strandberg, Jie Chen, Ralph Fyfe, Erik Kjellström, Johan Lindström, Anneli Poska, Qiong Zhang, and Marie-José Gaillard
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Hanieh Seyedhashemi, Florentina Moatar, Jean-Philippe Vidal, and Dominique Thiéry
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Søren J. Kragh, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 27, 2463–2478, https://doi.org/10.5194/hess-27-2463-2023, https://doi.org/10.5194/hess-27-2463-2023, 2023
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This study investigates the precision of irrigation estimates from a global hotspot of unsustainable irrigation practice, the Indus and Ganges basins. We show that irrigation water use can be estimated with high precision by comparing satellite and rainfed hydrological model estimates of evapotranspiration. We believe that our work can support sustainable water resource management, as it addresses the uncertainty of a key component of the water balance that remains challenging to quantify.
Julian Koch, Lars Elsgaard, Mogens H. Greve, Steen Gyldenkærne, Cecilie Hermansen, Gregor Levin, Shubiao Wu, and Simon Stisen
Biogeosciences, 20, 2387–2403, https://doi.org/10.5194/bg-20-2387-2023, https://doi.org/10.5194/bg-20-2387-2023, 2023
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Utilizing peatlands for agriculture leads to large emissions of greenhouse gases worldwide. The emissions are triggered by lowering the water table, which is a necessary step in order to make peatlands arable. Many countries aim at reducing their emissions by restoring peatlands, which can be achieved by stopping agricultural activities and thereby raising the water table. We estimate a total emission of 2.6 Mt CO2-eq for organic-rich peatlands in Denmark and a potential reduction of 77 %.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
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Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
EGUsphere, https://doi.org/10.5194/egusphere-2023-775, https://doi.org/10.5194/egusphere-2023-775, 2023
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We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows, but show poor performance outside the range of the targeted streamflows and are less robust. We show that no a priori assumption on transformations must be taken as warranted.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-78, https://doi.org/10.5194/hess-2023-78, 2023
Publication in HESS not foreseen
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The recent development of the a new meteorological dataset providing precipitation and temperature over France – FYRE Climate – has been transformed to streamflow time series over 1871–2012 through the used of a hydrological model. This led to the creation of the daily hydrological reconstructions called HyDRE and HyDRE. These two reconstructions are evaluated allow to better understand the variability of past hydrology over France.
Raphael Schneider, Julian Koch, Lars Troldborg, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci., 26, 5859–5877, https://doi.org/10.5194/hess-26-5859-2022, https://doi.org/10.5194/hess-26-5859-2022, 2022
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Hydrological models at high spatial resolution are computationally expensive. However, outputs from such models, such as the depth of the groundwater table, are often desired in high resolution. We developed a downscaling algorithm based on machine learning that allows us to increase spatial resolution of hydrological model outputs, alleviating computational burden. We successfully applied the downscaling algorithm to the climate-change-induced impacts on the groundwater table across Denmark.
Rashed Mahmood, Markus G. Donat, Pablo Ortega, Francisco J. Doblas-Reyes, Carlos Delgado-Torres, Margarida Samsó, and Pierre-Antoine Bretonnière
Earth Syst. Dynam., 13, 1437–1450, https://doi.org/10.5194/esd-13-1437-2022, https://doi.org/10.5194/esd-13-1437-2022, 2022
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Near-term climate change projections are strongly affected by the uncertainty from internal climate variability. Here we present a novel approach to reduce such uncertainty by constraining decadal-scale variability in the projections using observations. The constrained ensembles show significant added value over the unconstrained ensemble in predicting global climate 2 decades ahead. We also show the applicability of regional constraints for attributing predictability to certain ocean regions.
Changgui Lin, Erik Kjellström, Renate Anna Irma Wilcke, and Deliang Chen
Earth Syst. Dynam., 13, 1197–1214, https://doi.org/10.5194/esd-13-1197-2022, https://doi.org/10.5194/esd-13-1197-2022, 2022
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This study endorses RCMs' added value on the driving GCMs in representing observed heat wave magnitudes. The future increase of heat wave magnitudes projected by GCMs is attenuated when downscaled by RCMs. Within the downscaling, uncertainties can be attributed almost equally to choice of RCMs and to the driving data associated with different GCMs. Uncertainties of GCMs in simulating heat wave magnitudes are transformed by RCMs in a complex manner rather than simply inherited.
Peter Berg, Thomas Bosshard, Wei Yang, and Klaus Zimmermann
Geosci. Model Dev., 15, 6165–6180, https://doi.org/10.5194/gmd-15-6165-2022, https://doi.org/10.5194/gmd-15-6165-2022, 2022
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When performing impact analyses with climate models, one is often confronted with the issue that the models have significant bias. Commonly, the modelled climatological temperature deviates from the observed climate by a few degrees or it rains excessively in the model. MIdAS employs a novel statistical model to translate the model climatology toward that observed using novel methodologies and modern tools. The coding platform allows opportunities to develop methods for high-resolution models.
N. Hempelmann, C. Ehbrecht, E. Plesiat, G. Hobona, J. Simoes, D. Huard, T. J. Smith, U. S. McKnight, I. G. Pechlivanidis, and C. Alvarez-Castro
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 187–194, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-187-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-187-2022, 2022
Rena Meyer, Wenmin Zhang, Søren Julsgaard Kragh, Mie Andreasen, Karsten Høgh Jensen, Rasmus Fensholt, Simon Stisen, and Majken C. Looms
Hydrol. Earth Syst. Sci., 26, 3337–3357, https://doi.org/10.5194/hess-26-3337-2022, https://doi.org/10.5194/hess-26-3337-2022, 2022
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The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of great relevance for agriculture and water management. Here, we investigate whether the established downscaling algorithm combining different satellite products to estimate medium-scale soil moisture is applicable to higher resolutions and whether results can be improved by accounting for land cover types. Original satellite data and downscaled soil moisture are compared with ground observations.
Veit Blauhut, Michael Stoelzle, Lauri Ahopelto, Manuela I. Brunner, Claudia Teutschbein, Doris E. Wendt, Vytautas Akstinas, Sigrid J. Bakke, Lucy J. Barker, Lenka Bartošová, Agrita Briede, Carmelo Cammalleri, Ksenija Cindrić Kalin, Lucia De Stefano, Miriam Fendeková, David C. Finger, Marijke Huysmans, Mirjana Ivanov, Jaak Jaagus, Jiří Jakubínský, Svitlana Krakovska, Gregor Laaha, Monika Lakatos, Kiril Manevski, Mathias Neumann Andersen, Nina Nikolova, Marzena Osuch, Pieter van Oel, Kalina Radeva, Renata J. Romanowicz, Elena Toth, Mirek Trnka, Marko Urošev, Julia Urquijo Reguera, Eric Sauquet, Aleksandra Stevkov, Lena M. Tallaksen, Iryna Trofimova, Anne F. Van Loon, Michelle T. H. van Vliet, Jean-Philippe Vidal, Niko Wanders, Micha Werner, Patrick Willems, and Nenad Živković
Nat. Hazards Earth Syst. Sci., 22, 2201–2217, https://doi.org/10.5194/nhess-22-2201-2022, https://doi.org/10.5194/nhess-22-2201-2022, 2022
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Recent drought events caused enormous damage in Europe. We therefore questioned the existence and effect of current drought management strategies on the actual impacts and how drought is perceived by relevant stakeholders. Over 700 participants from 28 European countries provided insights into drought hazard and impact perception and current management strategies. The study concludes with an urgent need to collectively combat drought risk via a European macro-level drought governance approach.
Hanieh Seyedhashemi, Jean-Philippe Vidal, Jacob S. Diamond, Dominique Thiéry, Céline Monteil, Frédéric Hendrickx, Anthony Maire, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 2583–2603, https://doi.org/10.5194/hess-26-2583-2022, https://doi.org/10.5194/hess-26-2583-2022, 2022
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Stream temperature appears to be increasing globally, but its rate remains poorly constrained due to a paucity of long-term data. Using a thermal model, this study provides a large-scale understanding of the evolution of stream temperature over a long period (1963–2019). This research highlights that air temperature and streamflow can exert joint influence on stream temperature trends, and riparian shading in small mountainous streams may mitigate warming in stream temperatures.
Thibault Lemaitre-Basset, Ludovic Oudin, Guillaume Thirel, and Lila Collet
Hydrol. Earth Syst. Sci., 26, 2147–2159, https://doi.org/10.5194/hess-26-2147-2022, https://doi.org/10.5194/hess-26-2147-2022, 2022
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Increasing temperature will impact evaporation and water resource management. Hydrological models are fed with an estimation of the evaporative demand of the atmosphere, called potential evapotranspiration (PE). The objectives of this study were (1) to compute the future PE anomaly over France and (2) to determine the impact of the choice of the method to estimate PE. Our results show that all methods present similar future trends. No method really stands out from the others.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
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Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Erika Médus, Emma D. Thomassen, Danijel Belušić, Petter Lind, Peter Berg, Jens H. Christensen, Ole B. Christensen, Andreas Dobler, Erik Kjellström, Jonas Olsson, and Wei Yang
Nat. Hazards Earth Syst. Sci., 22, 693–711, https://doi.org/10.5194/nhess-22-693-2022, https://doi.org/10.5194/nhess-22-693-2022, 2022
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We evaluate the skill of a regional climate model, HARMONIE-Climate, to capture the present-day characteristics of heavy precipitation in the Nordic region and investigate the added value provided by a convection-permitting model version. The higher model resolution improves the representation of hourly heavy- and extreme-precipitation events and their diurnal cycle. The results indicate the benefits of convection-permitting models for constructing climate change projections over the region.
Ida Karlsson Seidenfaden, Torben Obel Sonnenborg, Jens Christian Refsgaard, Christen Duus Børgesen, Jørgen Eivind Olesen, and Dennis Trolle
Hydrol. Earth Syst. Sci., 26, 955–973, https://doi.org/10.5194/hess-26-955-2022, https://doi.org/10.5194/hess-26-955-2022, 2022
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This study investigates how the spatial nitrate reduction in the subsurface may shift under changing climate and land use conditions. This change is investigated by comparing maps showing the spatial nitrate reduction in an agricultural catchment for current conditions, with maps generated for future projected climate and land use conditions. Results show that future climate flow paths may shift the catchment reduction noticeably, while implications of land use changes were less substantial.
Anna Rutgersson, Erik Kjellström, Jari Haapala, Martin Stendel, Irina Danilovich, Martin Drews, Kirsti Jylhä, Pentti Kujala, Xiaoli Guo Larsén, Kirsten Halsnæs, Ilari Lehtonen, Anna Luomaranta, Erik Nilsson, Taru Olsson, Jani Särkkä, Laura Tuomi, and Norbert Wasmund
Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, https://doi.org/10.5194/esd-13-251-2022, 2022
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A natural hazard is a naturally occurring extreme event with a negative effect on people, society, or the environment; major events in the study area include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. In the future, an increase in sea level, extreme precipitation, heat waves, and phytoplankton blooms is expected, and a decrease in cold spells and severe ice winters is anticipated.
H. E. Markus Meier, Christian Dieterich, Matthias Gröger, Cyril Dutheil, Florian Börgel, Kseniia Safonova, Ole B. Christensen, and Erik Kjellström
Earth Syst. Dynam., 13, 159–199, https://doi.org/10.5194/esd-13-159-2022, https://doi.org/10.5194/esd-13-159-2022, 2022
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In addition to environmental pressures such as eutrophication, overfishing and contaminants, climate change is believed to have an important impact on the marine environment in the future, and marine management should consider the related risks. Hence, we have compared and assessed available scenario simulations for the Baltic Sea and found considerable uncertainties of the projections caused by the underlying assumptions and model biases, in particular for the water and biogeochemical cycles.
Ole Bøssing Christensen, Erik Kjellström, Christian Dieterich, Matthias Gröger, and Hans Eberhard Markus Meier
Earth Syst. Dynam., 13, 133–157, https://doi.org/10.5194/esd-13-133-2022, https://doi.org/10.5194/esd-13-133-2022, 2022
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The Baltic Sea Region is very sensitive to climate change, whose impacts could easily exacerbate biodiversity stress from society and eutrophication of the Baltic Sea. Therefore, there has been a focus on estimations of future climate change and its impacts in recent research. Models show a strong warming, in particular in the north in winter. Precipitation is projected to increase in the whole region apart from the south during summer. New results improve estimates of future climate change.
Ruud T. W. L. Hurkmans, Bart van den Hurk, Maurice J. Schmeits, Fredrik Wetterhall, and Ilias G. Pechlivanidis
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-604, https://doi.org/10.5194/hess-2021-604, 2022
Manuscript not accepted for further review
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Seasonal forecasts can help in safely and efficiently managing a fresh water reservoir in the Netherlands. We compare hydrological forecast systems of the river Rhine, the lakes most important source and analyze forecast skill for over 1993–2016 and for specific extreme years. On average, forecast skill is high in spring due to Alpine snow and smaller in summer. Dry summers appear to be more predictable, skill increases with event extremity. In those cases, seasonal forecasts are valuable tools.
Marcus Reckermann, Anders Omstedt, Tarmo Soomere, Juris Aigars, Naveed Akhtar, Magdalena Bełdowska, Jacek Bełdowski, Tom Cronin, Michał Czub, Margit Eero, Kari Petri Hyytiäinen, Jukka-Pekka Jalkanen, Anders Kiessling, Erik Kjellström, Karol Kuliński, Xiaoli Guo Larsén, Michelle McCrackin, H. E. Markus Meier, Sonja Oberbeckmann, Kevin Parnell, Cristian Pons-Seres de Brauwer, Anneli Poska, Jarkko Saarinen, Beata Szymczycha, Emma Undeman, Anders Wörman, and Eduardo Zorita
Earth Syst. Dynam., 13, 1–80, https://doi.org/10.5194/esd-13-1-2022, https://doi.org/10.5194/esd-13-1-2022, 2022
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As part of the Baltic Earth Assessment Reports (BEAR), we present an inventory and discussion of different human-induced factors and processes affecting the environment of the Baltic Sea region and their interrelations. Some are naturally occurring and modified by human activities, others are completely human-induced, and they are all interrelated to different degrees. The findings from this study can largely be transferred to other comparable marginal and coastal seas in the world.
Paul Royer-Gaspard, Vazken Andréassian, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 25, 5703–5716, https://doi.org/10.5194/hess-25-5703-2021, https://doi.org/10.5194/hess-25-5703-2021, 2021
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Most evaluation studies based on the differential split-sample test (DSST) endorse the consensus that rainfall–runoff models lack climatic robustness. In this technical note, we propose a new performance metric to evaluate model robustness without applying the DSST and which can be used with a single hydrological model calibration. Our work makes it possible to evaluate the temporal transferability of any hydrological model, including uncalibrated models, at a very low computational cost.
Manuel Fossa, Bastien Dieppois, Nicolas Massei, Matthieu Fournier, Benoit Laignel, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 25, 5683–5702, https://doi.org/10.5194/hess-25-5683-2021, https://doi.org/10.5194/hess-25-5683-2021, 2021
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Hydro-climate observations (such as precipitation, temperature, and river discharge time series) reveal very complex behavior inherited from complex interactions among the physical processes that drive hydro-climate viability. This study shows how even small perturbations of a physical process can have large consequences on some others. Those interactions vary spatially, thus showing the importance of both temporal and spatial dimensions in better understanding hydro-climate variability.
Alexis Jeantet, Hocine Henine, Cédric Chaumont, Lila Collet, Guillaume Thirel, and Julien Tournebize
Hydrol. Earth Syst. Sci., 25, 5447–5471, https://doi.org/10.5194/hess-25-5447-2021, https://doi.org/10.5194/hess-25-5447-2021, 2021
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The hydrological subsurface drainage model SIDRA-RU is assessed at the French national scale, using a unique database representing the large majority of the French drained areas. The model is evaluated following its capacity to simulate the drainage discharge variability and the annual drained water balance. Eventually, the temporal robustness of SIDRA-RU is assessed to demonstrate the utility of this model as a long-term management tool.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, and Olivier Vannier
Clim. Past, 17, 1857–1879, https://doi.org/10.5194/cp-17-1857-2021, https://doi.org/10.5194/cp-17-1857-2021, 2021
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This article presents FYRE Climate, a dataset providing daily precipitation and temperature spanning the 1871–2012 period at 8 km resolution over France. FYRE Climate has been obtained through the combination of daily and yearly observations and a gridded reconstruction already available through a statistical technique called data assimilation. Results highlight the quality of FYRE Climate in terms of both long-term variations and reproduction of extreme events.
Pierre Nicolle, Vazken Andréassian, Paul Royer-Gaspard, Charles Perrin, Guillaume Thirel, Laurent Coron, and Léonard Santos
Hydrol. Earth Syst. Sci., 25, 5013–5027, https://doi.org/10.5194/hess-25-5013-2021, https://doi.org/10.5194/hess-25-5013-2021, 2021
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In this note, a new method (RAT) is proposed to assess the robustness of hydrological models. The RAT method is particularly interesting because it does not require multiple calibrations (it is therefore applicable to uncalibrated models), and it can be used to determine whether a hydrological model may be safely used for climate change impact studies. Success at the robustness assessment test is a necessary (but not sufficient) condition of model robustness.
Simon Ricard, Philippe Lucas-Picher, and François Anctil
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-451, https://doi.org/10.5194/hess-2021-451, 2021
Revised manuscript not accepted
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We propose a simplified hydroclimatic modelling workflow for producing hydrologic scenarios without resorting to meteorological observations. This innovative approach preserves trends and physical consistency between simulated climate variables, allows the implementation of modelling cascades despite observation scarcity, and supports the participation of end-users in producing and interpreting climate change impacts on water resources.
Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven
Hydrol. Earth Syst. Sci., 25, 3937–3973, https://doi.org/10.5194/hess-25-3937-2021, https://doi.org/10.5194/hess-25-3937-2021, 2021
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The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Jonas Olsson, Peter Berg, and Remco van de Beek
Adv. Sci. Res., 18, 59–64, https://doi.org/10.5194/asr-18-59-2021, https://doi.org/10.5194/asr-18-59-2021, 2021
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We have developed a tool to visualize rainfall observations, based on a combination of meteorological stations and weather radars, over Sweden in near real-time. By accumulating the rainfall in time (1–12 h) and space (hydrological basins), the tool is designed mainly for hydrological applications, e.g. to support flood forecasters and to facilitate post-event analyses. Despite evident uncertainties, different users have confirmed an added value of the tool in case studies.
Peter Berg, Fredrik Almén, and Denica Bozhinova
Earth Syst. Sci. Data, 13, 1531–1545, https://doi.org/10.5194/essd-13-1531-2021, https://doi.org/10.5194/essd-13-1531-2021, 2021
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HydroGFD3.0 (Hydrological Global Forcing Data) is a data set of daily precipitation and temperature intended for use in hydrological modelling. The method uses different observational data sources to correct the variables from a model estimation of precipitation and temperature. An openly available data set covers the years 1979–2019, and times after this are available by request.
Cristina Aguilar, Rafael Pimentel, and María J. Polo
Earth Syst. Sci. Data, 13, 1335–1359, https://doi.org/10.5194/essd-13-1335-2021, https://doi.org/10.5194/essd-13-1335-2021, 2021
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This work presents the reconstruction of 19 years of daily, monthly, and annual global radiation maps in Sierra Nevada (Spain) derived using daily historical records from weather stations in the area and a modeling scheme that captures the topographic effects that constitute the main sources of the spatial and temporal variability of solar radiation. The generated datasets are valuable in different fields, such as hydrology, ecology, or energy production systems downstream.
Martin Le Mesnil, Roger Moussa, Jean-Baptiste Charlier, and Yvan Caballero
Hydrol. Earth Syst. Sci., 25, 1259–1282, https://doi.org/10.5194/hess-25-1259-2021, https://doi.org/10.5194/hess-25-1259-2021, 2021
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We present an innovative approach consisting of the statistical analysis and comparison of 15 hydrological descriptors, characterizing catchment response to rainfall events. The distribution of these descriptors is analysed according to the occurrence of karst areas inside 108 catchments. It shows that karst impacts on storm events mainly result in river losses and that interbasin groundwater flows can represent a significant part of the catchment water budget ah the event timescale.
Marc Girons Lopez, Louise Crochemore, and Ilias G. Pechlivanidis
Hydrol. Earth Syst. Sci., 25, 1189–1209, https://doi.org/10.5194/hess-25-1189-2021, https://doi.org/10.5194/hess-25-1189-2021, 2021
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The Swedish hydrological warning service is extending its use of seasonal forecasts, which requires an analysis of the available methods. We evaluate the simple ESP method and find out how and why forecasts vary in time and space. We find that forecasts are useful up to 3 months into the future, especially during winter and in northern Sweden. They tend to be good in slow-reacting catchments and bad in flashy and highly regulated ones. We finally link them with areas of similar behaviour.
Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, https://doi.org/10.5194/hess-25-1069-2021, 2021
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We quantify the differences in internal states and fluxes of 12 process-based models with similar streamflow performance and assess their plausibility using remotely sensed estimates of evaporation, snow cover, soil moisture and total storage anomalies. The dissimilarities in internal process representation imply that these models cannot all simultaneously be close to reality. Therefore, we invite modelers to evaluate their models using multiple variables and to rely on multi-model studies.
Manon Cassagnole, Maria-Helena Ramos, Ioanna Zalachori, Guillaume Thirel, Rémy Garçon, Joël Gailhard, and Thomas Ouillon
Hydrol. Earth Syst. Sci., 25, 1033–1052, https://doi.org/10.5194/hess-25-1033-2021, https://doi.org/10.5194/hess-25-1033-2021, 2021
Roberto Bilbao, Simon Wild, Pablo Ortega, Juan Acosta-Navarro, Thomas Arsouze, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Rubén Cruz-García, Ivana Cvijanovic, Francisco Javier Doblas-Reyes, Markus Donat, Emanuel Dutra, Pablo Echevarría, An-Chi Ho, Saskia Loosveldt-Tomas, Eduardo Moreno-Chamarro, Núria Pérez-Zanon, Arthur Ramos, Yohan Ruprich-Robert, Valentina Sicardi, Etienne Tourigny, and Javier Vegas-Regidor
Earth Syst. Dynam., 12, 173–196, https://doi.org/10.5194/esd-12-173-2021, https://doi.org/10.5194/esd-12-173-2021, 2021
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This paper presents and evaluates a set of retrospective decadal predictions with the EC-Earth3 climate model. These experiments successfully predict past changes in surface air temperature but show poor predictive capacity in the subpolar North Atlantic, a well-known source region of decadal climate variability. The poor predictive capacity is linked to an initial shock affecting the Atlantic Ocean circulation, ultimately due to a suboptimal representation of the Labrador Sea density.
Aslak Grinsted and Jens Hesselbjerg Christensen
Ocean Sci., 17, 181–186, https://doi.org/10.5194/os-17-181-2021, https://doi.org/10.5194/os-17-181-2021, 2021
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As we warm our planet, oceans expand, ice on land melts, and sea levels rise. On century timescales, we find that the sea level response to warming can be characterized by a single metric: the transient sea level sensitivity. Historical sea level exhibits substantially higher sensitivity than model-based estimates of future climates in authoritative climate assessments, implying recent projections could well underestimate the likely sea level rise by the end of this century.
Torben Schmith, Peter Thejll, Peter Berg, Fredrik Boberg, Ole Bøssing Christensen, Bo Christiansen, Jens Hesselbjerg Christensen, Marianne Sloth Madsen, and Christian Steger
Hydrol. Earth Syst. Sci., 25, 273–290, https://doi.org/10.5194/hess-25-273-2021, https://doi.org/10.5194/hess-25-273-2021, 2021
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European extreme precipitation is expected to change in the future; this is based on climate model projections. But, since climate models have errors, projections are uncertain. We study this uncertainty in the projections by comparing results from an ensemble of 19 climate models. Results can be used to give improved estimates of future extreme precipitation for Europe.
Matteo Giuliani, Louise Crochemore, Ilias Pechlivanidis, and Andrea Castelletti
Hydrol. Earth Syst. Sci., 24, 5891–5902, https://doi.org/10.5194/hess-24-5891-2020, https://doi.org/10.5194/hess-24-5891-2020, 2020
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This paper aims at quantifying the value of hydroclimatic forecasts in terms of potential economic benefit to end users in the Lake Como basin (Italy), which allows the inference of a relation between gains in forecast skill and gains in end user profit. We also explore the sensitivity of this benefit to both the forecast system setup and end user behavioral factors, showing that the estimated forecast value is potentially undermined by different levels of end user risk aversion.
Renate Anna Irma Wilcke, Erik Kjellström, Changgui Lin, Daniela Matei, Anders Moberg, and Evangelos Tyrlis
Earth Syst. Dynam., 11, 1107–1121, https://doi.org/10.5194/esd-11-1107-2020, https://doi.org/10.5194/esd-11-1107-2020, 2020
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Two long-lasting high-pressure systems in summer 2018 led to heat waves over Scandinavia and an extended summer period with devastating impacts on both agriculture and human life. Using five climate model ensembles, the unique 263-year Stockholm temperature time series and a composite 150-year time series for the whole of Sweden, we found that anthropogenic climate change has strongly increased the probability of a warm summer, such as the one observed in 2018, occurring in Sweden.
Valentin Dall'Alba, Philippe Renard, Julien Straubhaar, Benoit Issautier, Cédric Duvail, and Yvan Caballero
Hydrol. Earth Syst. Sci., 24, 4997–5013, https://doi.org/10.5194/hess-24-4997-2020, https://doi.org/10.5194/hess-24-4997-2020, 2020
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Due to climate and population evolution, increased pressure is put on the groundwater resource, which calls for better understanding and models. In this paper, we describe a novel workflow to model the geological heterogeneity of coastal aquifers and apply it to the Roussillon plain (southern France). The main strength of the workflow is its capability to model aquifer heterogeneity when only sparse data are available while honoring the local geological trends and quantifying uncertainty.
Nicolas Massei, Daniel G. Kingston, David M. Hannah, Jean-Philippe Vidal, Bastien Dieppois, Manuel Fossa, Andreas Hartmann, David A. Lavers, and Benoit Laignel
Proc. IAHS, 383, 141–149, https://doi.org/10.5194/piahs-383-141-2020, https://doi.org/10.5194/piahs-383-141-2020, 2020
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This paper presents recent thoughts by members of EURO-FRIEND Water project 3 “Large-scale-variations in hydrological characteristics” about research needed to characterize and understand large-scale hydrology under global changes. Emphasis is put on the necessary efforts to better understand 1 – the impact of low-frequency climate variability on hydrological trends and extremes, 2 – the role of basin properties on modulating the climate signal producing hydrological responses on the basin scale.
Kerstin Stahl, Jean-Philippe Vidal, Jamie Hannaford, Erik Tijdeman, Gregor Laaha, Tobias Gauster, and Lena M. Tallaksen
Proc. IAHS, 383, 291–295, https://doi.org/10.5194/piahs-383-291-2020, https://doi.org/10.5194/piahs-383-291-2020, 2020
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Numerous indices exist for the description of hydrological drought, some are based on absolute thresholds of overall streamflows or water levels and some are based on relative anomalies with respect to the season. This article discusses paradigms and experiences with such index uses in drought monitoring and drought analysis to raise awareness of the different interpretations of drought severity.
Marc Schleiss, Jonas Olsson, Peter Berg, Tero Niemi, Teemu Kokkonen, Søren Thorndahl, Rasmus Nielsen, Jesper Ellerbæk Nielsen, Denica Bozhinova, and Seppo Pulkkinen
Hydrol. Earth Syst. Sci., 24, 3157–3188, https://doi.org/10.5194/hess-24-3157-2020, https://doi.org/10.5194/hess-24-3157-2020, 2020
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A multinational assessment of radar's ability to capture heavy rain events is conducted. In total, six different radar products in Denmark, the Netherlands, Finland and Sweden were considered. Results show a fair agreement, with radar underestimating by 17 %-44 % on average compared with gauges. Despite being adjusted for bias, five of six radar products still exhibited strong conditional biases with intensities of 1–2% per mm/h. Median peak intensity bias was significantly higher, reaching 44 %–67%.
Francesco De Leo, Sebastián Solari, and Giovanni Besio
Nat. Hazards Earth Syst. Sci., 20, 1233–1246, https://doi.org/10.5194/nhess-20-1233-2020, https://doi.org/10.5194/nhess-20-1233-2020, 2020
Minchao Wu, Grigory Nikulin, Erik Kjellström, Danijel Belušić, Colin Jones, and David Lindstedt
Earth Syst. Dynam., 11, 377–394, https://doi.org/10.5194/esd-11-377-2020, https://doi.org/10.5194/esd-11-377-2020, 2020
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Regional Climate Models constitute a downscaling tool to provide high-resolution data for impact and adaptation studies. However, there is no unique definition of the added value of downscaling as it depends on many factors. We investigate the impact of spatial resolution and model formulation on downscaled rainfall in Africa. Our results show that improvements in downscaled rainfall compared to the driving reanalysis are often related to model formulation and not always to higher resolution.
Danijel Belušić, Hylke de Vries, Andreas Dobler, Oskar Landgren, Petter Lind, David Lindstedt, Rasmus A. Pedersen, Juan Carlos Sánchez-Perrino, Erika Toivonen, Bert van Ulft, Fuxing Wang, Ulf Andrae, Yurii Batrak, Erik Kjellström, Geert Lenderink, Grigory Nikulin, Joni-Pekka Pietikäinen, Ernesto Rodríguez-Camino, Patrick Samuelsson, Erik van Meijgaard, and Minchao Wu
Geosci. Model Dev., 13, 1311–1333, https://doi.org/10.5194/gmd-13-1311-2020, https://doi.org/10.5194/gmd-13-1311-2020, 2020
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A new regional climate modelling system, HCLIM38, is presented and shown to be applicable in different regions ranging from the tropics to the Arctic. The main focus is on climate simulations at horizontal resolutions between 1 and 4 km, the so-called convection-permitting scales, even though the model can also be used at coarser resolutions. The benefits of simulating climate at convection-permitting scales are shown and are particularly evident for climate extremes.
Steefan Contractor, Markus G. Donat, Lisa V. Alexander, Markus Ziese, Anja Meyer-Christoffer, Udo Schneider, Elke Rustemeier, Andreas Becker, Imke Durre, and Russell S. Vose
Hydrol. Earth Syst. Sci., 24, 919–943, https://doi.org/10.5194/hess-24-919-2020, https://doi.org/10.5194/hess-24-919-2020, 2020
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This paper provides the documentation of the REGEN dataset, a global land-based daily observational precipitation dataset from 1950 to 2016 at a gridded resolution of 1° × 1°. REGEN is currently the longest-running global dataset of daily precipitation and is expected to facilitate studies looking at changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity.
Jean-Pierre Vergnes, Nicolas Roux, Florence Habets, Philippe Ackerer, Nadia Amraoui, François Besson, Yvan Caballero, Quentin Courtois, Jean-Raynald de Dreuzy, Pierre Etchevers, Nicolas Gallois, Delphine J. Leroux, Laurent Longuevergne, Patrick Le Moigne, Thierry Morel, Simon Munier, Fabienne Regimbeau, Dominique Thiéry, and Pascal Viennot
Hydrol. Earth Syst. Sci., 24, 633–654, https://doi.org/10.5194/hess-24-633-2020, https://doi.org/10.5194/hess-24-633-2020, 2020
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The AquiFR hydrogeological modelling platform aims to provide
short-term-to-seasonal hydrological forecasts over France for daily water management and long-term simulations for climate impact studies. The results described in this study confirm the feasibility of gathering independent groundwater models into the same numerical tool. This new tool encourages the development of groundwater modelling, and it has the potential to be valuable for many operational and research applications.
Mia H. Gross, Markus G. Donat, Lisa V. Alexander, and Steven C. Sherwood
Earth Syst. Dynam., 11, 97–111, https://doi.org/10.5194/esd-11-97-2020, https://doi.org/10.5194/esd-11-97-2020, 2020
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This study explores the amplified warming of cold extremes relative to average temperatures for both the recent past and future in the Northern Hemisphere and the possible physical processes that are driving this. We find that decreases in snow cover and
warmer-than-usual winds are driving the disproportionate rates of warming in cold extremes relative to average temperatures. These accelerated warming rates in cold extremes have implications for tourism, insect longevity and human health.
Berit Arheimer, Rafael Pimentel, Kristina Isberg, Louise Crochemore, Jafet C. M. Andersson, Abdulghani Hasan, and Luis Pineda
Hydrol. Earth Syst. Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, https://doi.org/10.5194/hess-24-535-2020, 2020
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How far can we reach in predicting river flow globally, using integrated catchment modelling and open global data? For the first time, a catchment model was applied world-wide, covering the entire globe with a relatively high resolution. The results show that stepwise calibration provided better performance than traditional modelling of the globe. The study highlights that open data and models are crucial to advance hydrological sciences by sharing knowledge and enabling transparent evaluation.
Raphael Schneider, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-685, https://doi.org/10.5194/hess-2019-685, 2020
Revised manuscript not accepted
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For groundwater models to deliver reliable results, their parameters often have to be estimated in an optimization process guided by some measure of model performance. In this context, we suggest the use of a novel performance metric, which is less prone to a fit to inadequate observations than the most frequently used metrics based on squared errors. Hence, calibration is more robust to deficiencies in model and observational data, which are common especially in larger scale models.
Julian Koch, Helen Berger, Hans Jørgen Henriksen, and Torben Obel Sonnenborg
Hydrol. Earth Syst. Sci., 23, 4603–4619, https://doi.org/10.5194/hess-23-4603-2019, https://doi.org/10.5194/hess-23-4603-2019, 2019
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This study explores novel modelling avenues using machine learning in combination with process-based models to predict the shallow water table at high spatial resolution. Due to climate change and anthropogenic impacts, the shallow groundwater is rising in many parts of the world. In order to adapt to risks induced by groundwater flooding, new modelling tools need to emerge. In this study, we found that machine learning is capable of reaching the required accuracy and resolution.
Eva Sebok and Sascha Müller
Hydrol. Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/hess-23-3305-2019, https://doi.org/10.5194/hess-23-3305-2019, 2019
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Exchange fluxes between groundwater and surface waters can be quantified using temperature measurements from the upper sediment layers of streams and lakes assuming the thermal properties of sediments. This study quantified the natural variabiilty in sediment thermal conductivity in the vertical direction at the bed of surface waters and showed that fluxes can change by up to +/-75 % depending on using standard literature values or in situ measurements for sediment thermal conductivity.
Louise J. Slater, Guillaume Thirel, Shaun Harrigan, Olivier Delaigue, Alexander Hurley, Abdou Khouakhi, Ilaria Prosdocimi, Claudia Vitolo, and Katie Smith
Hydrol. Earth Syst. Sci., 23, 2939–2963, https://doi.org/10.5194/hess-23-2939-2019, https://doi.org/10.5194/hess-23-2939-2019, 2019
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This paper explores the benefits and advantages of R's usage in hydrology. We provide an overview of a typical hydrological workflow based on reproducible principles and packages for retrieval of hydro-meteorological data, spatial analysis, hydrological modelling, statistics, and the design of static and dynamic visualizations and documents. We discuss some of the challenges that arise when using R in hydrology as well as a roadmap for R’s future within the discipline.
Peter Berg, Ole B. Christensen, Katharina Klehmet, Geert Lenderink, Jonas Olsson, Claas Teichmann, and Wei Yang
Nat. Hazards Earth Syst. Sci., 19, 957–971, https://doi.org/10.5194/nhess-19-957-2019, https://doi.org/10.5194/nhess-19-957-2019, 2019
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A state-of-the-art regional climate model ensemble for Europe is investigated for extreme precipitation intensities. The models poorly reproduce short duration events of less than a few hours. Further, there is poor connection to some known hotspots for extreme cases. The model performance is much improved at 12 h durations. Projected future increases scale with seasonal mean temperature change, within a range from a few percent to over 10 percent per degree Celsius.
María J. Polo, Javier Herrero, Rafael Pimentel, and María J. Pérez-Palazón
Earth Syst. Sci. Data, 11, 393–407, https://doi.org/10.5194/essd-11-393-2019, https://doi.org/10.5194/essd-11-393-2019, 2019
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This work presents the Guadalfeo Monitoring Network in the Sierra Nevada (Spain), a snow monitoring network in the Guadalfeo Experimental Catchment, a semiarid area in southern Europe representative of snowpacks with highly variable dynamics on both annual and seasonal scales and significant topographic gradients. The network includes weather stations and time-lapse cameras to capture the variability of the ablation phases on different spatial scales.
Laurie Caillouet, Jean-Philippe Vidal, Eric Sauquet, Benjamin Graff, and Jean-Michel Soubeyroux
Earth Syst. Sci. Data, 11, 241–260, https://doi.org/10.5194/essd-11-241-2019, https://doi.org/10.5194/essd-11-241-2019, 2019
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SCOPE Climate is a 25-member ensemble of 142-year daily high-resolution reconstructions of precipitation, temperature, and Penman–Monteith reference evapotranspiration over France. It is the first century-long gridded high-resolution homogeneous dataset available over France. It thus paves the way for studying local historical meteorological events and for assessing the local climate variability from the end of the 19th century.
Francesco De Leo, Giovanni Besio, Guido Zolezzi, and Marco Bezzi
Nat. Hazards Earth Syst. Sci., 19, 287–298, https://doi.org/10.5194/nhess-19-287-2019, https://doi.org/10.5194/nhess-19-287-2019, 2019
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This paper reviews the computation of vulnerability levels (VLs) of a coast to inundation with a known model. We refer to the original proposal, detailing the VL computation through an accurate investigation of the local wave climate. We prove that the resulting vulnerability is very sensitive due to the wave features taken into account, which have to be properly assessed. The research is the follow-up of a wider project set along the Bay of Lalzit (Albania).
Theano Iliopoulou, Cristina Aguilar, Berit Arheimer, María Bermúdez, Nejc Bezak, Andrea Ficchì, Demetris Koutsoyiannis, Juraj Parajka, María José Polo, Guillaume Thirel, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 73–91, https://doi.org/10.5194/hess-23-73-2019, https://doi.org/10.5194/hess-23-73-2019, 2019
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We investigate the seasonal memory properties of a large sample of European rivers in terms of high and low flows. We compute seasonal correlations between peak and low flows and average flows in the previous seasons and explore the links with various physiographic and hydro-climatic catchment descriptors. Our findings suggest that there is a traceable physical basis for river memory which in turn can be employed to reduce uncertainty and improve probabilistic predictions of floods and droughts.
Diana Lucatero, Henrik Madsen, Jens C. Refsgaard, Jacob Kidmose, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 22, 6591–6609, https://doi.org/10.5194/hess-22-6591-2018, https://doi.org/10.5194/hess-22-6591-2018, 2018
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The present study evaluates the skill of a seasonal forecasting system for hydrological relevant variables in Denmark. Linear scaling and quantile mapping were used to correct the forecasts. Uncorrected forecasts tend to be more skillful than climatology, in general, for the first month lead time only. Corrected forecasts show a reduced bias in the mean; are more consistent; and show a level of accuracy that is closer to, although no higher than, that of ensemble climatology, in general.
Rafael Pimentel, Carlo Marín, Ludovica De Gregorio, Mattia Callegari, María J. Pérez-Palazón, Claudia Notarnicola, and María J. Polo
Proc. IAHS, 380, 67–72, https://doi.org/10.5194/piahs-380-67-2018, https://doi.org/10.5194/piahs-380-67-2018, 2018
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In Mediterranean regions, the spatiotemporal evolution of the snow cover can experiment quick changes and high frequency sensors are required to adequately monitor such shifts. This work presents a methodological approach to validate the improved MODIS daily snow cover maps, in a Sierra Nevada (southern Spain), from a reference data set obtained by Landsat TM data. The results show a significantly high correlation between the two snow map products at differents spatial scale.
María J. Polo, Maria P. González-Dugo, and Christopher Neale
Proc. IAHS, 380, 1–2, https://doi.org/10.5194/piahs-380-1-2018, https://doi.org/10.5194/piahs-380-1-2018, 2018
Léonard Santos, Guillaume Thirel, and Charles Perrin
Hydrol. Earth Syst. Sci., 22, 4583–4591, https://doi.org/10.5194/hess-22-4583-2018, https://doi.org/10.5194/hess-22-4583-2018, 2018
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The Kling and Gupta efficiency (KGE) is a score used in hydrology to evaluate flow simulation compared to observations. In order to force the evaluation on the low flows, some authors used the log-transformed flow to calculate the KGE. In this technical note, we show that this transformation should be avoided because it produced numerical flaws that lead to difficulties in the score value interpretation.
Rafael Pimentel and Berit Arheimer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-387, https://doi.org/10.5194/hess-2018-387, 2018
Revised manuscript not accepted
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The Västmanland wildfire, Sweden, burned 14 000 hectares and removed the Boreal forest in this area during the summer 2014. This empirical study evaluates the hydrological effects of this wildfire. A paired catchment methodology is used to evaluate 23 catchment characteristics of flow and physiography defined using in situ and remote sensing data. The results show a change in the snow dynamics over the burnt areas with shorter duration of the snow season and a higher stream flow during autumn.
Gaia Piazzi, Guillaume Thirel, Lorenzo Campo, and Simone Gabellani
The Cryosphere, 12, 2287–2306, https://doi.org/10.5194/tc-12-2287-2018, https://doi.org/10.5194/tc-12-2287-2018, 2018
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The study focuses on the development of a multivariate particle filtering data assimilation scheme into a point-scale snow model. One of the main challenging issues concerns the impoverishment of the particle sample, which is addressed by jointly perturbing meteorological data and model parameters. An additional snow density model is introduced to reduce sensitivity to the availability of snow mass-related observations. In this configuration, the system reveals a satisfying performance.
Diana Lucatero, Henrik Madsen, Jens C. Refsgaard, Jacob Kidmose, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 22, 3601–3617, https://doi.org/10.5194/hess-22-3601-2018, https://doi.org/10.5194/hess-22-3601-2018, 2018
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The skill of an experimental streamflow forecast system in the Ahlergaarde catchment, Denmark, is analyzed. Inputs to generate the forecasts are taken from the ECMWF System 4 seasonal forecasting system and an ensemble of observations (ESP). Reduction of biases is achieved by processing the meteorological and/or streamflow forecasts. In general, this is not sufficient to ensure a higher level of accuracy than the ESP, indicating a modest added value of a seasonal meteorological system.
Stephen Blenkinsop, Hayley J. Fowler, Renaud Barbero, Steven C. Chan, Selma B. Guerreiro, Elizabeth Kendon, Geert Lenderink, Elizabeth Lewis, Xiao-Feng Li, Seth Westra, Lisa Alexander, Richard P. Allan, Peter Berg, Robert J. H. Dunn, Marie Ekström, Jason P. Evans, Greg Holland, Richard Jones, Erik Kjellström, Albert Klein-Tank, Dennis Lettenmaier, Vimal Mishra, Andreas F. Prein, Justin Sheffield, and Mari R. Tye
Adv. Sci. Res., 15, 117–126, https://doi.org/10.5194/asr-15-117-2018, https://doi.org/10.5194/asr-15-117-2018, 2018
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Measurements of sub-daily (e.g. hourly) rainfall totals are essential if we are to understand short, intense bursts of rainfall that cause flash floods. We might expect the intensity of such events to increase in a warming climate but these are poorly realised in projections of future climate change. The INTENSE project is collating a global dataset of hourly rainfall measurements and linking with new developments in climate models to understand the characteristics and causes of these events.
Julian Koch, Mehmet Cüneyd Demirel, and Simon Stisen
Geosci. Model Dev., 11, 1873–1886, https://doi.org/10.5194/gmd-11-1873-2018, https://doi.org/10.5194/gmd-11-1873-2018, 2018
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Our work addresses a key challenge in earth system modelling: how to optimally exploit the information contained in satellite remote sensing observations in the calibration of such models. For this we thoroughly test a number of measures that quantify the fit between an observed and a simulated spatial pattern. We acknowledge the difficulties associated with such a comparison and suggest using measures that regard multiple aspects of spatial information, i.e. magnitude and variability.
Erik Kjellström, Grigory Nikulin, Gustav Strandberg, Ole Bøssing Christensen, Daniela Jacob, Klaus Keuler, Geert Lenderink, Erik van Meijgaard, Christoph Schär, Samuel Somot, Silje Lund Sørland, Claas Teichmann, and Robert Vautard
Earth Syst. Dynam., 9, 459–478, https://doi.org/10.5194/esd-9-459-2018, https://doi.org/10.5194/esd-9-459-2018, 2018
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Based on high-resolution regional climate models we investigate European climate change at 1.5 and 2 °C of global warming compared to pre-industrial levels. Considerable near-surface warming exceeding that of the global mean is found for most of Europe, already at the lower 1.5 °C of warming level. Changes in precipitation and near-surface wind speed are identified. The 1.5 °C of warming level shows significantly less change compared to the 2 °C level, indicating the importance of mitigation.
Léonard Santos, Guillaume Thirel, and Charles Perrin
Geosci. Model Dev., 11, 1591–1605, https://doi.org/10.5194/gmd-11-1591-2018, https://doi.org/10.5194/gmd-11-1591-2018, 2018
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Many rainfall–runoff models are based on stores. However, the differential equations that describe the stores' evolution are rarely presented in literature.
This represents an issue when the temporal resolution changes. In this work, we propose and evaluate a state-space version of a simple rainfall–runoff model within a robust resolution scheme. The results show that the proposed model performs equally well or slightly better than the original one and is independent of the temporal resolution.
Mehmet C. Demirel, Juliane Mai, Gorka Mendiguren, Julian Koch, Luis Samaniego, and Simon Stisen
Hydrol. Earth Syst. Sci., 22, 1299–1315, https://doi.org/10.5194/hess-22-1299-2018, https://doi.org/10.5194/hess-22-1299-2018, 2018
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Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
Peter Berg, Chantal Donnelly, and David Gustafsson
Hydrol. Earth Syst. Sci., 22, 989–1000, https://doi.org/10.5194/hess-22-989-2018, https://doi.org/10.5194/hess-22-989-2018, 2018
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A new product (Global Forcing Data, GFD) that provides bias-adjusted meteorological forcing data for impact models, such as hydrological models, is presented. The main novelty with the product is the near-real time updating of the data which allows more up-to-date impact modeling. This is performed by combining climatological data sets with climate monitoring data sets. The potential in using the data to initialize hydrological forecasts is further investigated.
Gorka Mendiguren, Julian Koch, and Simon Stisen
Hydrol. Earth Syst. Sci., 21, 5987–6005, https://doi.org/10.5194/hess-21-5987-2017, https://doi.org/10.5194/hess-21-5987-2017, 2017
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The present study is focused on the spatial pattern evaluation of two models and describes the similarities and dissimilarities. It also discusses the factors that generate these patterns and proposes similar new approaches to minimize the differences. The study points towards a new approach in which the spatial component of the hydrological model is also calibrated and taken into account.
Richard Wartenburger, Martin Hirschi, Markus G. Donat, Peter Greve, Andy J. Pitman, and Sonia I. Seneviratne
Geosci. Model Dev., 10, 3609–3634, https://doi.org/10.5194/gmd-10-3609-2017, https://doi.org/10.5194/gmd-10-3609-2017, 2017
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This article analyses regional changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. Readers are encouraged to use the online tool for visualization of specific indices of interest, e.g. to assess their response to 1.5 or 2 °C global warming.
Philippe Riboust, Nicolas Le Moine, Guillaume Thirel, and Pierre Ribstein
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-539, https://doi.org/10.5194/hess-2017-539, 2017
Revised manuscript not accepted
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In hydrological modelling complex forcing data are often needed to reproduce the energy balance, mainly for simulating snowmelt and evapotranspiration processes. Incoming radiation data are not widely measured and are often derived from reanalyses. We provide a method for simulating these radiations in mountainous areas using only daily temperature range data and a digital elevation model. The method has been validated on 105 weather stations and a simple snow surface temperature model.
Cristina Aguilar, Alberto Montanari, and María-José Polo
Hydrol. Earth Syst. Sci., 21, 3687–3700, https://doi.org/10.5194/hess-21-3687-2017, https://doi.org/10.5194/hess-21-3687-2017, 2017
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Assuming that floods are driven by both short- (meteorological forcing) and long-term perturbations (higher-than-usual moisture), we propose a technique for updating a season in advance the flood frequency distribution. Its application in the Po and Danube rivers helped to reduce the uncertainty in the estimation of floods and thus constitutes a promising tool for real-time management of flood risk mitigation. This study is the result of the stay of the first author at the University of Bologna.
Gregor Laaha, Tobias Gauster, Lena M. Tallaksen, Jean-Philippe Vidal, Kerstin Stahl, Christel Prudhomme, Benedikt Heudorfer, Radek Vlnas, Monica Ionita, Henny A. J. Van Lanen, Mary-Jeanne Adler, Laurie Caillouet, Claire Delus, Miriam Fendekova, Sebastien Gailliez, Jamie Hannaford, Daniel Kingston, Anne F. Van Loon, Luis Mediero, Marzena Osuch, Renata Romanowicz, Eric Sauquet, James H. Stagge, and Wai K. Wong
Hydrol. Earth Syst. Sci., 21, 3001–3024, https://doi.org/10.5194/hess-21-3001-2017, https://doi.org/10.5194/hess-21-3001-2017, 2017
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In 2015 large parts of Europe were affected by a drought. In terms of low flow magnitude, a region around the Czech Republic was most affected, with return periods > 100 yr. In terms of deficit volumes, the drought was particularly severe around S. Germany where the event lasted notably long. Meteorological and hydrological events developed differently in space and time. For an assessment of drought impacts on water resources, hydrological data are required in addition to meteorological indices.
Laurie Caillouet, Jean-Philippe Vidal, Eric Sauquet, Alexandre Devers, and Benjamin Graff
Hydrol. Earth Syst. Sci., 21, 2923–2951, https://doi.org/10.5194/hess-21-2923-2017, https://doi.org/10.5194/hess-21-2923-2017, 2017
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The historical depth of streamflow observations in France is extended through daily hydrometeorogical reconstructions from 1871 onwards over a large set of near-natural catchments. Innovative approaches are proposed to identify and intercompare extreme low-flow events from these reconstructions, both in time and across France in a homogeneous way over more than 140 years. Analyses bring forward recent well-known events like 1976 and 1989–1990 but also much older ones like 1878 and 1893.
Giovanni Besio, Riccardo Briganti, Alessandro Romano, Lorenzo Mentaschi, and Paolo De Girolamo
Nat. Hazards Earth Syst. Sci., 17, 505–514, https://doi.org/10.5194/nhess-17-505-2017, https://doi.org/10.5194/nhess-17-505-2017, 2017
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Results of 36-years of hindcast in the Mediterranean Sea are analysed to detect time clustering of wave storms using the Allan factor. The analysis reveals that some areas of the basin are characterized by storm clustering for timescales t < 50 days, while seasonality is dominant at large scales. The findings highlight a deviation from the Poisson distribution in some sub-basins of the Mediterranean Sea. Implications for coastal erosion/flooding need to be studied further.
Rafael Pimentel, Javier Herrero, and María José Polo
Hydrol. Earth Syst. Sci., 21, 805–820, https://doi.org/10.5194/hess-21-805-2017, https://doi.org/10.5194/hess-21-805-2017, 2017
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This study analyses the subgrid variability of the snow distribution in a Mediterranean region and formulates a parametric approach that includes these scale effects in the physical modelling of snow by means of accumulation–depletion curves associated with snow evolution patterns, by means of terrestrial photography. The results confirm that the use of these on a cell scale provides a solid foundation for the extension of point snow models to larger areas.
Tanja de Boer-Euser, Laurène Bouaziz, Jan De Niel, Claudia Brauer, Benjamin Dewals, Gilles Drogue, Fabrizio Fenicia, Benjamin Grelier, Jiri Nossent, Fernando Pereira, Hubert Savenije, Guillaume Thirel, and Patrick Willems
Hydrol. Earth Syst. Sci., 21, 423–440, https://doi.org/10.5194/hess-21-423-2017, https://doi.org/10.5194/hess-21-423-2017, 2017
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In this study, the rainfall–runoff models of eight international research groups were compared for a set of subcatchments of the Meuse basin to investigate the influence of certain model components on the modelled discharge. Although the models showed similar performances based on general metrics, clear differences could be observed for specific events. The differences during drier conditions could indeed be linked to differences in model structures.
Javier Herrero and María José Polo
The Cryosphere, 10, 2981–2998, https://doi.org/10.5194/tc-10-2981-2016, https://doi.org/10.5194/tc-10-2981-2016, 2016
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We present 7 years of field work and modelling to assess the importance of the loss of water from the snow by means of evaposublimation in the Mediterranean mountains of Sierra Nevada. The actual evaposublimation rates were detected through detailed measurement of the mass fluxes from the snow. These data have led to some improvements in the modelling of the snow dynamics in this kind of mountainous semiarid regions. Evaposublimation is estimated to range 24–33% of total annual snowfall.
Remko Nijzink, Christopher Hutton, Ilias Pechlivanidis, René Capell, Berit Arheimer, Jim Freer, Dawei Han, Thorsten Wagener, Kevin McGuire, Hubert Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 4775–4799, https://doi.org/10.5194/hess-20-4775-2016, https://doi.org/10.5194/hess-20-4775-2016, 2016
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The core component of many hydrological systems, the moisture storage capacity available to vegetation, is typically treated as a calibration parameter in hydrological models and often considered to remain constant in time. In this paper we test the potential of a recently introduced method to robustly estimate catchment-scale root-zone storage capacities exclusively based on climate data to reproduce the temporal evolution of root-zone storage under change (deforestation).
Donghua Zhang, Henrik Madsen, Marc E. Ridler, Jacob Kidmose, Karsten H. Jensen, and Jens C. Refsgaard
Hydrol. Earth Syst. Sci., 20, 4341–4357, https://doi.org/10.5194/hess-20-4341-2016, https://doi.org/10.5194/hess-20-4341-2016, 2016
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We present a method to assimilate observed groundwater head and soil moisture profiles into an integrated hydrological model. The study uses the ensemble transform Kalman filter method and the MIKE SHE hydrological model code. The proposed method is shown to be more robust and provide better results for two cases in Denmark, and is also validated using real data. The hydrological model with assimilation overall improved performance compared to the model without assimilation.
Jean-Philippe Vidal, Benoît Hingray, Claire Magand, Eric Sauquet, and Agnès Ducharne
Hydrol. Earth Syst. Sci., 20, 3651–3672, https://doi.org/10.5194/hess-20-3651-2016, https://doi.org/10.5194/hess-20-3651-2016, 2016
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Possible transient futures of winter and summer low flows for two snow-influenced catchments in the southern French Alps show a strong decrease signal. It is however largely masked by the year-to-year variability, which should be the main target for defining adaptation strategies. Responses of different hydrological models strongly diverge in the future, suggesting to carefully check the robustness of evapotranspiration and snowpack components under a changing climate.
Lorenzo Mentaschi, Michalis Vousdoukas, Evangelos Voukouvalas, Ludovica Sartini, Luc Feyen, Giovanni Besio, and Lorenzo Alfieri
Hydrol. Earth Syst. Sci., 20, 3527–3547, https://doi.org/10.5194/hess-20-3527-2016, https://doi.org/10.5194/hess-20-3527-2016, 2016
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The climate is subject to variations which must be considered
studying the intensity and frequency of extreme events.
We introduce in this paper a new methodology
for the study of variable extremes, which consists in detecting
the pattern of variability of a time series, and applying these patterns
to the analysis of the extreme events.
This technique comes with advantages with respect to the previous ones
in terms of accuracy, simplicity, and robustness.
Jørn Rasmussen, Henrik Madsen, Karsten Høgh Jensen, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 20, 2103–2118, https://doi.org/10.5194/hess-20-2103-2016, https://doi.org/10.5194/hess-20-2103-2016, 2016
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In the paper, observations are assimilated into a hydrological model in order to improve the model performance. Two methods for detecting and correcting systematic errors (bias) in groundwater head observations are used leading to improved results compared to standard assimilation methods which ignores any bias. This is demonstrated using both synthetic (user generated) observations and real-world observations.
Alban de Lavenne, Guillaume Thirel, Vazken Andréassian, Charles Perrin, and Maria-Helena Ramos
Proc. IAHS, 373, 87–94, https://doi.org/10.5194/piahs-373-87-2016, https://doi.org/10.5194/piahs-373-87-2016, 2016
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Developing modelling tools that help to understand the spatial distribution of water resources is a key issue for better management. Ideally, hydrological models which discretise catchment space into sub-catchments should offer better streamflow simulations than lumped models, along with spatially-relevant water resources management solutions. However we demonstrate that those model raise other issues related to the calibration strategy and to the identifiability of the parameters.
María J. Polo, Albert Rovira, Darío García-Contreras, Eva Contreras, Agustín Millares, Cristina Aguilar, and Miguel A. Losada
Proc. IAHS, 373, 45–49, https://doi.org/10.5194/piahs-373-45-2016, https://doi.org/10.5194/piahs-373-45-2016, 2016
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Regulation by reservoirs affects both the freshwater regime and the sediment delivery downstream. Spain is one the countries with more water storage capacity by reservoirs in the world. The spatial redistribution of the seasonal and annual water storage in reservoirs mainly for irrigation and urban supply has resulted in significant environmental impacts downstream. This work shows these effects in the Guadalquivir and the Ebro River basins, two of the largest regulated areas in Spain.
Cristina Aguilar, Alberto Montanari, and María José Polo
Proc. IAHS, 373, 189–192, https://doi.org/10.5194/piahs-373-189-2016, https://doi.org/10.5194/piahs-373-189-2016, 2016
Laurie Caillouet, Jean-Philippe Vidal, Eric Sauquet, and Benjamin Graff
Clim. Past, 12, 635–662, https://doi.org/10.5194/cp-12-635-2016, https://doi.org/10.5194/cp-12-635-2016, 2016
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This paper describes a daily high-resolution reconstruction of precipitation and temperature fields in France from 1871 onwards. A statistical method linking atmospheric circulation to local precipitation is refined for taking advantage of recently published global long-term atmospheric and oceanic reconstructions. The resulting data set allows filling in the spatial and temporal data gaps in historical surface observations, and improving our knowledge on the local-scale climate variability.
I. G. Pechlivanidis and B. Arheimer
Hydrol. Earth Syst. Sci., 19, 4559–4579, https://doi.org/10.5194/hess-19-4559-2015, https://doi.org/10.5194/hess-19-4559-2015, 2015
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We modify the recommendations for flow predictions in ungauged catchments to address the challenges at the large scale. We use examples from the HYPE hydrological model set-up across 6000 subbasins for the Indian subcontinent. Multi-basin modelling reveals the spatial patterns of catchment functioning and dominant flow processes across the hydroclimatic gradient. The model set-up procedure according to the PUB recommendations brought insights into where the single model structure is inadequate.
Y. Caballero and B. Ladouche
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-10109-2015, https://doi.org/10.5194/hessd-12-10109-2015, 2015
Revised manuscript has not been submitted
T. O. Sonnenborg, D. Seifert, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 19, 3891–3901, https://doi.org/10.5194/hess-19-3891-2015, https://doi.org/10.5194/hess-19-3891-2015, 2015
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The impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Geology is the dominating uncertainty source for travel time and capture zones, while climate dominates for hydraulic heads and steam flow.
P. A. Marker, N. Foged, X. He, A. V. Christiansen, J. C. Refsgaard, E. Auken, and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 19, 3875–3890, https://doi.org/10.5194/hess-19-3875-2015, https://doi.org/10.5194/hess-19-3875-2015, 2015
J. Rasmussen, H. Madsen, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 19, 2999–3013, https://doi.org/10.5194/hess-19-2999-2015, https://doi.org/10.5194/hess-19-2999-2015, 2015
M. Egüen, M. J. Polo, Z. Gulliver, E. Contreras, C. Aguilar, and M. A. Losada
Proc. IAHS, 370, 51–56, https://doi.org/10.5194/piahs-370-51-2015, https://doi.org/10.5194/piahs-370-51-2015, 2015
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This work shows the change on flood risk in the coastal areas of three hydrographic basins in South Spain during the reservoir expansion period. The results differentiate the impact of the regulation level on both the cumulative distribution functions of the fluvial discharge near the river mouth, and the associated damage related to the enhanced soil occupation during this period.
M. J. Pérez-Palazón, R. Pimentel, J. Herrero, C. Aguilar, J. M. Perales, and M. J. Polo
Proc. IAHS, 369, 157–162, https://doi.org/10.5194/piahs-369-157-2015, https://doi.org/10.5194/piahs-369-157-2015, 2015
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Sierra Nevada National Park (South Spain) constitute a key monitoring point for climate variability and its impacts. This work presents the local trend analysis of weather variables at this area together with additional snow-related variables. The joint analysis of weather and snow variables showed a decrease trend in the extent and persistence of the snow covered area over the area. The precipitation regime seems to be the most relevant driver on the snow regime forcing in Mediterranean areas.
B. Eggert, P. Berg, J. O. Haerter, D. Jacob, and C. Moseley
Atmos. Chem. Phys., 15, 5957–5971, https://doi.org/10.5194/acp-15-5957-2015, https://doi.org/10.5194/acp-15-5957-2015, 2015
I. Giuntoli, J.-P. Vidal, C. Prudhomme, and D. M. Hannah
Earth Syst. Dynam., 6, 267–285, https://doi.org/10.5194/esd-6-267-2015, https://doi.org/10.5194/esd-6-267-2015, 2015
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We assessed future changes in high and low flows globally using runoff projections from global hydrological models (GHMs) driven by global climate models (GCMs) under the RCP8.5 scenario. Further, we quantified the relative size of uncertainty from GHMs and from GCMs using ANOVA. We show that GCMs are the major contributors to uncertainty overall, but GHMs increase their contribution for low flows and can equal or outweigh GCM uncertainty in snow-dominated areas for both high and low flows.
R. Guzinski, H. Nieto, S. Stisen, and R. Fensholt
Hydrol. Earth Syst. Sci., 19, 2017–2036, https://doi.org/10.5194/hess-19-2017-2015, https://doi.org/10.5194/hess-19-2017-2015, 2015
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The study compared evapotranspiration (ET) modelled by two remote sensing models and one hydrological model in a river catchment in Denmark. The results show that the spatial patterns of ET produced by the remote sensing models are more similar to each other than to the fluxes produced by the hydrological model. This indicates potential benefits to the hydrological modelling community from integrating spatial information derived through remote sensing methodology into the hydrological models.
J. R. Poulsen, E. Sebok, C. Duque, D. Tetzlaff, and P. K. Engesgaard
Hydrol. Earth Syst. Sci., 19, 1871–1886, https://doi.org/10.5194/hess-19-1871-2015, https://doi.org/10.5194/hess-19-1871-2015, 2015
R. J. H. Dunn, M. G. Donat, and L. V. Alexander
Clim. Past, 10, 2171–2199, https://doi.org/10.5194/cp-10-2171-2014, https://doi.org/10.5194/cp-10-2171-2014, 2014
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Observational data sets contain uncertainties, e.g. from the instrument accuracy, as well as from the fact that usually only a single method is used in processing. We have performed an assessment of the size of the uncertainties associated with choices in the method used. The largest effects come from changes which affect the station network or the gridding method used. However, for the temperature indices in places with many stations, these changes have little effect on the long-term behaviour.
H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen
Hydrol. Earth Syst. Sci., 18, 5169–5179, https://doi.org/10.5194/hess-18-5169-2014, https://doi.org/10.5194/hess-18-5169-2014, 2014
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A new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical depth-to-water table function. Results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater--surface water--land surface model (ParFlow.CLM) by up to 50%. The methodology is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
M. A. D. Larsen, J. C. Refsgaard, M. Drews, M. B. Butts, K. H. Jensen, J. H. Christensen, and O. B. Christensen
Hydrol. Earth Syst. Sci., 18, 4733–4749, https://doi.org/10.5194/hess-18-4733-2014, https://doi.org/10.5194/hess-18-4733-2014, 2014
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The paper presents results from a novel dynamical coupling between a hydrology model and a regional climate model developed to include a wider range of processes, land-surface/atmosphere interaction and finer spatio-temporal scales. The coupled performance was largely dependent on the data exchange frequency between the two model components, and longer-term precipitation was somewhat improved by the coupled system whereas the short-term dynamics for a range of variables was less accurate.
J. Koch, X. He, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 18, 2907–2923, https://doi.org/10.5194/hess-18-2907-2014, https://doi.org/10.5194/hess-18-2907-2014, 2014
R. Lorenz, A. J. Pitman, M. G. Donat, A. L. Hirsch, J. Kala, E. A. Kowalczyk, R. M. Law, and J. Srbinovsky
Geosci. Model Dev., 7, 545–567, https://doi.org/10.5194/gmd-7-545-2014, https://doi.org/10.5194/gmd-7-545-2014, 2014
G. Strandberg, E. Kjellström, A. Poska, S. Wagner, M.-J. Gaillard, A.-K. Trondman, A. Mauri, B. A. S. Davis, J. O. Kaplan, H. J. B. Birks, A. E. Bjune, R. Fyfe, T. Giesecke, L. Kalnina, M. Kangur, W. O. van der Knaap, U. Kokfelt, P. Kuneš, M. Lata\l owa, L. Marquer, F. Mazier, A. B. Nielsen, B. Smith, H. Seppä, and S. Sugita
Clim. Past, 10, 661–680, https://doi.org/10.5194/cp-10-661-2014, https://doi.org/10.5194/cp-10-661-2014, 2014
I. B. Karlsson, T. O. Sonnenborg, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 18, 595–610, https://doi.org/10.5194/hess-18-595-2014, https://doi.org/10.5194/hess-18-595-2014, 2014
K. Steffens, M. Larsbo, J. Moeys, E. Kjellström, N. Jarvis, and E. Lewan
Hydrol. Earth Syst. Sci., 18, 479–491, https://doi.org/10.5194/hess-18-479-2014, https://doi.org/10.5194/hess-18-479-2014, 2014
S. Radanovics, J.-P. Vidal, E. Sauquet, A. Ben Daoud, and G. Bontron
Hydrol. Earth Syst. Sci., 17, 4189–4208, https://doi.org/10.5194/hess-17-4189-2013, https://doi.org/10.5194/hess-17-4189-2013, 2013
H. Qin, G. Cao, M. Kristensen, J. C. Refsgaard, M. O. Rasmussen, X. He, J. Liu, Y. Shu, and C. Zheng
Hydrol. Earth Syst. Sci., 17, 3759–3778, https://doi.org/10.5194/hess-17-3759-2013, https://doi.org/10.5194/hess-17-3759-2013, 2013
P. Berg, R. Döscher, and T. Koenigk
Geosci. Model Dev., 6, 849–859, https://doi.org/10.5194/gmd-6-849-2013, https://doi.org/10.5194/gmd-6-849-2013, 2013
J. Kidmose, J. C. Refsgaard, L. Troldborg, L. P. Seaby, and M. M. Escrivà
Hydrol. Earth Syst. Sci., 17, 1619–1634, https://doi.org/10.5194/hess-17-1619-2013, https://doi.org/10.5194/hess-17-1619-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Uncertainty analysis
Technical note: Complexity–uncertainty curve (c-u-curve) – a method to analyse, classify and compare dynamical systems
Technical note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty
Why do our rainfall–runoff models keep underestimating the peak flows?
Pitfalls and a feasible solution for using KGE as an informal likelihood function in MCMC methods: DREAM(ZS) as an example
Benchmarking global hydrological and land surface models against GRACE in a medium-sized tropical basin
Guidance on evaluating parametric model uncertainty at decision-relevant scales
Quantifying input uncertainty in the calibration of water quality models: reordering errors via the secant method
Sequential data assimilation for real-time probabilistic flood inundation mapping
Key challenges facing the application of the conductivity mass balance method: a case study of the Mississippi River basin
Coupled machine learning and the limits of acceptability approach applied in parameter identification for a distributed hydrological model
A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors – a case study for Kenya and Uganda
Technical note: Uncertainty in multi-source partitioning using large tracer data sets
Assessment of climate change impact and difference on the river runoff in four basins in China under 1.5 and 2.0 °C global warming
A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation
Technical note: Analytical sensitivity analysis and uncertainty estimation of baseflow index calculated by a two-component hydrograph separation method with conductivity as a tracer
Understanding the water cycle over the upper Tarim Basin: retrospecting the estimated discharge bias to atmospheric variables and model structure
The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed
Parameter uncertainty analysis for an operational hydrological model using residual-based and limits of acceptability approaches
Technical note: Pitfalls in using log-transformed flows within the KGE criterion
Improvement of model evaluation by incorporating prediction and measurement uncertainty
Transferability of climate simulation uncertainty to hydrological impacts
Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (upper Clutha River, New Zealand)
Mapping (dis)agreement in hydrologic projections
Consistency assessment of rating curve data in various locations using Bidirectional Reach (BReach)
The critical role of uncertainty in projections of hydrological extremes
Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting
Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding
Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales
Extending flood forecasting lead time in a large watershed by coupling WRF QPF with a distributed hydrological model
Quantifying uncertainty on sediment loads using bootstrap confidence intervals
Event-scale power law recession analysis: quantifying methodological uncertainty
Disentangling timing and amplitude errors in streamflow simulations
Reliability of lumped hydrological modeling in a semi-arid mountainous catchment facing water-use changes
Using dry and wet year hydroclimatic extremes to guide future hydrologic projections
Uncertainty contributions to low-flow projections in Austria
Accounting for dependencies in regionalized signatures for predictions in ungauged catchments
Climate change and its impacts on river discharge in two climate regions in China
Uncertainty in hydrological signatures
Climate model uncertainty versus conceptual geological uncertainty in hydrological modeling
Estimation of predictive hydrologic uncertainty using the quantile regression and UNEEC methods and their comparison on contrasting catchments
Transferring global uncertainty estimates from gauged to ungauged catchments
Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model
Uncertainty reduction and parameter estimation of a distributed hydrological model with ground and remote-sensing data
The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models
Flow pathways and nutrient transport mechanisms drive hydrochemical sensitivity to climate change across catchments with different geology and topography
The importance of hydrological uncertainty assessment methods in climate change impact studies
Regional water balance modelling using flow-duration curves with observational uncertainties
Climate change impacts on the hydrologic regime of a Canadian river: comparing uncertainties arising from climate natural variability and lumped hydrological model structures
From maps to movies: high-resolution time-varying sensitivity analysis for spatially distributed watershed models
Bridging the gap between GLUE and formal statistical approaches: approximate Bayesian computation
Uwe Ehret and Pankaj Dey
Hydrol. Earth Syst. Sci., 27, 2591–2605, https://doi.org/10.5194/hess-27-2591-2023, https://doi.org/10.5194/hess-27-2591-2023, 2023
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We propose the
c-u-curvemethod to characterize dynamical (time-variable) systems of all kinds.
Uis for uncertainty and expresses how well a system can be predicted in a given period of time.
Cis for complexity and expresses how predictability differs between different periods, i.e. how well predictability itself can be predicted. The method helps to better classify and compare dynamical systems across a wide range of disciplines, thus facilitating scientific collaboration.
Trevor Page, Paul Smith, Keith Beven, Francesca Pianosi, Fanny Sarrazin, Susana Almeida, Liz Holcombe, Jim Freer, Nick Chappell, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 27, 2523–2534, https://doi.org/10.5194/hess-27-2523-2023, https://doi.org/10.5194/hess-27-2523-2023, 2023
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This publication provides an introduction to the CREDIBLE Uncertainty Estimation (CURE) toolbox. CURE offers workflows for a variety of uncertainty estimation methods. One of its most important features is the requirement that all of the assumptions on which a workflow analysis depends be defined. This facilitates communication with potential users of an analysis. An audit trail log is produced automatically from a workflow for future reference.
András Bárdossy and Faizan Anwar
Hydrol. Earth Syst. Sci., 27, 1987–2000, https://doi.org/10.5194/hess-27-1987-2023, https://doi.org/10.5194/hess-27-1987-2023, 2023
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This study demonstrates the fact that the large river flows forecasted by the models show an underestimation that is inversely related to the number of locations where precipitation is recorded, which is independent of the model. The higher the number of points where the amount of precipitation is recorded, the better the estimate of the river flows.
Yan Liu, Jaime Fernández-Ortega, Matías Mudarra, and Andreas Hartmann
Hydrol. Earth Syst. Sci., 26, 5341–5355, https://doi.org/10.5194/hess-26-5341-2022, https://doi.org/10.5194/hess-26-5341-2022, 2022
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We adapt the informal Kling–Gupta efficiency (KGE) with a gamma distribution to apply it as an informal likelihood function in the DiffeRential Evolution Adaptive Metropolis DREAM(ZS) method. Our adapted approach performs as well as the formal likelihood function for exploring posterior distributions of model parameters. The adapted KGE is superior to the formal likelihood function for calibrations combining multiple observations with different lengths, frequencies and units.
Silvana Bolaños Chavarría, Micha Werner, Juan Fernando Salazar, and Teresita Betancur Vargas
Hydrol. Earth Syst. Sci., 26, 4323–4344, https://doi.org/10.5194/hess-26-4323-2022, https://doi.org/10.5194/hess-26-4323-2022, 2022
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Using total water storage (TWS) from GRACE satellites, we assess the reliability of global hydrological and land surface models over a medium-sized tropical basin with a well-developed gauging network. We find the models poorly represent TWS for the monthly series, but they improve in representing seasonality and long-term trends. We conclude that GRACE provides a valuable dataset to benchmark global simulations of TWS change, offering a useful tool to improve global models in tropical basins.
Jared D. Smith, Laurence Lin, Julianne D. Quinn, and Lawrence E. Band
Hydrol. Earth Syst. Sci., 26, 2519–2539, https://doi.org/10.5194/hess-26-2519-2022, https://doi.org/10.5194/hess-26-2519-2022, 2022
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Watershed models are used to simulate streamflow and water quality, and to inform siting and sizing decisions for runoff and nutrient control projects. Data are limited for many watershed processes that are represented in such models, which requires selecting the most important processes to be calibrated. We show that this selection should be based on decision-relevant metrics at the spatial scales of interest for the control projects. This should enable more robust project designs.
Xia Wu, Lucy Marshall, and Ashish Sharma
Hydrol. Earth Syst. Sci., 26, 1203–1221, https://doi.org/10.5194/hess-26-1203-2022, https://doi.org/10.5194/hess-26-1203-2022, 2022
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Decomposing parameter and input errors in model calibration is a considerable challenge. This study transfers the direct estimation of an input error series to their rank estimation and develops a new algorithm, i.e., Bayesian error analysis with reordering (BEAR). In the context of a total suspended solids simulation, two synthetic studies and a real study demonstrate that the BEAR method is effective for improving the input error estimation and water quality model calibration.
Keighobad Jafarzadegan, Peyman Abbaszadeh, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 25, 4995–5011, https://doi.org/10.5194/hess-25-4995-2021, https://doi.org/10.5194/hess-25-4995-2021, 2021
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In this study, daily observations are assimilated into a hydrodynamic model to update the performance of modeling and improve the flood inundation mapping skill. Results demonstrate that integrating data assimilation with a hydrodynamic model improves the performance of flood simulation and provides more reliable inundation maps. A flowchart provides the overall steps for applying this framework in practice and forecasting probabilistic flood maps before the onset of upcoming floods.
Hang Lyu, Chenxi Xia, Jinghan Zhang, and Bo Li
Hydrol. Earth Syst. Sci., 24, 6075–6090, https://doi.org/10.5194/hess-24-6075-2020, https://doi.org/10.5194/hess-24-6075-2020, 2020
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Baseflow separation plays a critical role in science-based management of water resources. This study addressed key challenges hindering the application of the generally accepted conductivity mass balance (CMB). Monitoring data for over 200 stream sites of the Mississippi River basin were collected to answer the following questions. What are the characteristics of a watershed that determine the method suitability? What length of monitoring data is needed? How can the parameters be more accurate?
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
Christoph Schürz, Bano Mehdi, Jens Kiesel, Karsten Schulz, and Mathew Herrnegger
Hydrol. Earth Syst. Sci., 24, 4463–4489, https://doi.org/10.5194/hess-24-4463-2020, https://doi.org/10.5194/hess-24-4463-2020, 2020
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The USLE is a commonly used model to estimate soil erosion by water. It quantifies soil loss as a product of six inputs representing rainfall erosivity, soil erodibility, slope length and steepness, plant cover, and support practices. Many methods exist to derive these inputs, which can, however, lead to substantial differences in the estimated soil loss. Here, we analyze the effect of different input representations on the estimated soil loss in a large-scale study in Kenya and Uganda.
Alicia Correa, Diego Ochoa-Tocachi, and Christian Birkel
Hydrol. Earth Syst. Sci., 23, 5059–5068, https://doi.org/10.5194/hess-23-5059-2019, https://doi.org/10.5194/hess-23-5059-2019, 2019
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The applications and availability of large tracer data sets have vastly increased in recent years leading to research into the contributions of multiple sources to a mixture. We introduce a method based on Taylor series approximation to estimate the uncertainties of such sources' contributions. The method is illustrated with examples of hydrology (14 tracers) and a MATLAB code is provided for reproducibility. This method can be generalized to any number of tracers across a range of disciplines.
Hongmei Xu, Lüliu Liu, Yong Wang, Sheng Wang, Ying Hao, Jingjin Ma, and Tong Jiang
Hydrol. Earth Syst. Sci., 23, 4219–4231, https://doi.org/10.5194/hess-23-4219-2019, https://doi.org/10.5194/hess-23-4219-2019, 2019
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1.5 and 2 °C have become targets in the discussion of climate change impacts. However, climate research is also challenged to provide more robust information on the impact of climate change at local and regional scales to assist the development of sound scientific adaptation and mitigation measures. This study assessed the impacts and differences of 1.5 and 2.0 °C global warming on basin-scale river runoff by examining four river basins covering a wide hydroclimatic setting in China.
Lorenz Ammann, Fabrizio Fenicia, and Peter Reichert
Hydrol. Earth Syst. Sci., 23, 2147–2172, https://doi.org/10.5194/hess-23-2147-2019, https://doi.org/10.5194/hess-23-2147-2019, 2019
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The uncertainty of hydrological models can be substantial, and its quantification and realistic description are often difficult. We propose a new flexible probabilistic framework to describe and quantify this uncertainty. It is show that the correlation of the errors can be non-stationary, and that accounting for temporal changes in correlation can lead to strongly improved probabilistic predictions. This is a promising avenue for improving uncertainty estimation in hydrological modelling.
Weifei Yang, Changlai Xiao, and Xiujuan Liang
Hydrol. Earth Syst. Sci., 23, 1103–1112, https://doi.org/10.5194/hess-23-1103-2019, https://doi.org/10.5194/hess-23-1103-2019, 2019
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This paper analyzed the sensitivity of the baseflow index to the parameters of the conductivity two-component hydrograph separation method. The results indicated that the baseflow index is more sensitive to the conductivity of baseflow and the separation method may be more suitable for the long time series in a small watershed. After considering the mutual offset of the measurement errors of conductivity and streamflow, the uncertainty in baseflow index was reduced by half.
Xudong Zhou, Jan Polcher, Tao Yang, Yukiko Hirabayashi, and Trung Nguyen-Quang
Hydrol. Earth Syst. Sci., 22, 6087–6108, https://doi.org/10.5194/hess-22-6087-2018, https://doi.org/10.5194/hess-22-6087-2018, 2018
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Model bias is commonly seen in discharge simulation by hydrological or land surface models. This study tested an approach with the Budyko hypothesis to retrospect the estimated discharge bias to different bias sources including the atmospheric variables and model structure. Results indicate that the bias is most likely caused by the forcing variables, and the forcing bias should firstly be assessed and reduced in order to perform pertinent analysis of the regional water cycle.
Linh Hoang, Rajith Mukundan, Karen E. B. Moore, Emmet M. Owens, and Tammo S. Steenhuis
Hydrol. Earth Syst. Sci., 22, 5947–5965, https://doi.org/10.5194/hess-22-5947-2018, https://doi.org/10.5194/hess-22-5947-2018, 2018
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The paper analyzes the effect of two input data (DEMs and the combination of soil and land use data) with different resolution and complexity on the uncertainty of model outputs (the predictions of streamflow and saturated areas) and parameter uncertainty using SWAT-HS. Results showed that DEM resolution has significant effect on the spatial pattern of saturated areas and using complex soil and land use data may not necessarily improve model performance or reduce model uncertainty.
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
Léonard Santos, Guillaume Thirel, and Charles Perrin
Hydrol. Earth Syst. Sci., 22, 4583–4591, https://doi.org/10.5194/hess-22-4583-2018, https://doi.org/10.5194/hess-22-4583-2018, 2018
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The Kling and Gupta efficiency (KGE) is a score used in hydrology to evaluate flow simulation compared to observations. In order to force the evaluation on the low flows, some authors used the log-transformed flow to calculate the KGE. In this technical note, we show that this transformation should be avoided because it produced numerical flaws that lead to difficulties in the score value interpretation.
Lei Chen, Shuang Li, Yucen Zhong, and Zhenyao Shen
Hydrol. Earth Syst. Sci., 22, 4145–4154, https://doi.org/10.5194/hess-22-4145-2018, https://doi.org/10.5194/hess-22-4145-2018, 2018
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In this study, the cumulative distribution function approach (CDFA) and the Monte Carlo approach (MCA) were used to develop two new approaches for model evaluation within an uncertainty framework. These proposed methods could be extended to watershed models to provide a substitution for traditional model evaluations within an uncertainty framework.
Hui-Min Wang, Jie Chen, Alex J. Cannon, Chong-Yu Xu, and Hua Chen
Hydrol. Earth Syst. Sci., 22, 3739–3759, https://doi.org/10.5194/hess-22-3739-2018, https://doi.org/10.5194/hess-22-3739-2018, 2018
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Facing a growing number of climate models, many selection methods were proposed to select subsets in the field of climate simulation, but the transferability of their performances to hydrological impacts remains doubtful. We investigate the transferability of climate simulation uncertainty to hydrological impacts using two selection methods, and conclude that envelope-based selection of about 10 climate simulations based on properly chosen climate variables is suggested for impact studies.
Andreas M. Jobst, Daniel G. Kingston, Nicolas J. Cullen, and Josef Schmid
Hydrol. Earth Syst. Sci., 22, 3125–3142, https://doi.org/10.5194/hess-22-3125-2018, https://doi.org/10.5194/hess-22-3125-2018, 2018
Lieke A. Melsen, Nans Addor, Naoki Mizukami, Andrew J. Newman, Paul J. J. F. Torfs, Martyn P. Clark, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 22, 1775–1791, https://doi.org/10.5194/hess-22-1775-2018, https://doi.org/10.5194/hess-22-1775-2018, 2018
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Long-term hydrological predictions are important for water management planning, but are also prone to uncertainty. This study investigates three sources of uncertainty for long-term hydrological predictions in the US: climate models, hydrological models, and hydrological model parameters. Mapping the results revealed spatial patterns in the three sources of uncertainty: different sources of uncertainty dominate in different regions.
Katrien Van Eerdenbrugh, Stijn Van Hoey, Gemma Coxon, Jim Freer, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5315–5337, https://doi.org/10.5194/hess-21-5315-2017, https://doi.org/10.5194/hess-21-5315-2017, 2017
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Consistency in stage–discharge data is investigated using a methodology called Bidirectional Reach (BReach). Various measurement stations in the UK, New Zealand and Belgium are selected based on their historical ratings information and their characteristics related to data consistency. When applying a BReach analysis on them, the methodology provides results that appear consistent with the available knowledge and thus facilitates a reliable assessment of (in)consistency in stage–discharge data.
Hadush K. Meresa and Renata J. Romanowicz
Hydrol. Earth Syst. Sci., 21, 4245–4258, https://doi.org/10.5194/hess-21-4245-2017, https://doi.org/10.5194/hess-21-4245-2017, 2017
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Evaluation of the uncertainty in projections of future hydrological extremes in the mountainous catchment was performed. The uncertainty of the estimate of 1-in-100-year return maximum flow based on the 1971–2100 time series exceeds 200 % of its median value with the largest influence of the climate model uncertainty, while the uncertainty of the 1-in-100-year return minimum flow is of the same order (i.e. exceeds 200 %) but it is mainly influenced by the hydrological model parameter uncertainty.
Omar Wani, Joost V. L. Beckers, Albrecht H. Weerts, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 21, 4021–4036, https://doi.org/10.5194/hess-21-4021-2017, https://doi.org/10.5194/hess-21-4021-2017, 2017
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We generate uncertainty intervals for hydrologic model predictions using a simple instance-based learning scheme. Errors made by the model in some specific hydrometeorological conditions in the past are used to predict the probability distribution of its errors during forecasting. We test it for two different case studies in England. We find that this technique, even though conceptually simple and easy to implement, performs as well as some other sophisticated uncertainty estimation methods.
Christa Kelleher, Brian McGlynn, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 21, 3325–3352, https://doi.org/10.5194/hess-21-3325-2017, https://doi.org/10.5194/hess-21-3325-2017, 2017
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Models are tools for understanding how watersheds function and may respond to land cover and climate change. Before we can use models towards these purposes, we need to ensure that a model adequately represents watershed-wide observations. In this paper, we propose a new way to evaluate whether model simulations match observations, using a variety of information sources. We show how this information can reduce uncertainty in inputs to models, reducing uncertainty in hydrologic predictions.
Gabriele Baroni, Matthias Zink, Rohini Kumar, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 2301–2320, https://doi.org/10.5194/hess-21-2301-2017, https://doi.org/10.5194/hess-21-2301-2017, 2017
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Three methods are used to characterize the uncertainty in soil properties. The effect on simulated states and fluxes is quantified using a distributed hydrological model. Different impacts are identified as function of the perturbation method, of the model outputs and of the spatio-temporal resolution. The study underlines the importance of a proper characterization of the uncertainty in soil properties for a correct assessment of their role and further improvements in the model application.
Ji Li, Yangbo Chen, Huanyu Wang, Jianming Qin, Jie Li, and Sen Chiao
Hydrol. Earth Syst. Sci., 21, 1279–1294, https://doi.org/10.5194/hess-21-1279-2017, https://doi.org/10.5194/hess-21-1279-2017, 2017
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Quantitative precipitation forecast produced by the WRF model has a similar pattern to that estimated by rain gauges in a southern China large watershed, hydrological model parameters should be optimized with QPF produced by WRF, and simulating floods by coupling the WRF QPF with a distributed hydrological model provides a good reference for large watershed flood warning and could benefit the flood management communities due to its longer lead time.
Johanna I. F. Slaets, Hans-Peter Piepho, Petra Schmitter, Thomas Hilger, and Georg Cadisch
Hydrol. Earth Syst. Sci., 21, 571–588, https://doi.org/10.5194/hess-21-571-2017, https://doi.org/10.5194/hess-21-571-2017, 2017
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Determining measures of uncertainty on loads is not trivial, as a load is a product of concentration and discharge per time point, summed up over time. A bootstrap approach enables the calculation of confidence intervals on constituent loads. Ignoring the uncertainty on the discharge will typically underestimate the width of 95 % confidence intervals by around 10 %. Furthermore, confidence intervals are asymmetric, with the largest uncertainty on the upper limit.
David N. Dralle, Nathaniel J. Karst, Kyriakos Charalampous, Andrew Veenstra, and Sally E. Thompson
Hydrol. Earth Syst. Sci., 21, 65–81, https://doi.org/10.5194/hess-21-65-2017, https://doi.org/10.5194/hess-21-65-2017, 2017
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The streamflow recession is the period following rainfall during which flow declines. This paper examines a common method of recession analysis and identifies sensitivity of the technique's results to necessary, yet subjective, methodological choices. The results have implications for hydrology, sediment and solute transport, and geomorphology, as well as for testing numerous hydrologic theories which predict the mathematical form of the recession.
Simon Paul Seibert, Uwe Ehret, and Erwin Zehe
Hydrol. Earth Syst. Sci., 20, 3745–3763, https://doi.org/10.5194/hess-20-3745-2016, https://doi.org/10.5194/hess-20-3745-2016, 2016
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While the assessment of "vertical" (magnitude) errors of streamflow simulations is standard practice, "horizontal" (timing) errors are rarely considered. To assess their role, we propose a method to quantify both errors simultaneously which closely resembles visual hydrograph comparison. Our results reveal differences in time–magnitude error statistics for different flow conditions. The proposed method thus offers novel perspectives for model diagnostics and evaluation.
Paul Hublart, Denis Ruelland, Inaki García de Cortázar-Atauri, Simon Gascoin, Stef Lhermitte, and Antonio Ibacache
Hydrol. Earth Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, https://doi.org/10.5194/hess-20-3691-2016, 2016
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Our paper explores the reliability of conceptual catchment models in the dry Andes. First, we show that explicitly accounting for irrigation water use improves streamflow predictions during dry years. Second, we show that sublimation losses can be easily incorporated into temperature-based melt models without increasing model complexity too much. Our work also highlights areas requiring additional research, including the need for a better conceptualization of runoff generation processes.
Stephen Oni, Martyn Futter, Jose Ledesma, Claudia Teutschbein, Jim Buttle, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 20, 2811–2825, https://doi.org/10.5194/hess-20-2811-2016, https://doi.org/10.5194/hess-20-2811-2016, 2016
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This paper presents an important framework to improve hydrologic projections in cold regions. Hydrologic modelling/projections are often based on model calibration to long-term data. Here we used dry and wet years as a proxy to quantify uncertainty in projecting hydrologic extremes. We showed that projections based on long-term data could underestimate runoff by up to 35% in boreal regions. We believe the hydrologic modelling community will benefit from new insights derived from this study.
Juraj Parajka, Alfred Paul Blaschke, Günter Blöschl, Klaus Haslinger, Gerold Hepp, Gregor Laaha, Wolfgang Schöner, Helene Trautvetter, Alberto Viglione, and Matthias Zessner
Hydrol. Earth Syst. Sci., 20, 2085–2101, https://doi.org/10.5194/hess-20-2085-2016, https://doi.org/10.5194/hess-20-2085-2016, 2016
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Streamflow estimation during low-flow conditions is important for estimation of environmental flows, effluent water quality, hydropower operations, etc. However, it is not clear how the uncertainties in assumptions used in the projections translate into uncertainty of estimated future low flows. The objective of the study is to explore the relative role of hydrologic model calibration and climate scenarios in the uncertainty of low-flow projections in Austria.
Susana Almeida, Nataliya Le Vine, Neil McIntyre, Thorsten Wagener, and Wouter Buytaert
Hydrol. Earth Syst. Sci., 20, 887–901, https://doi.org/10.5194/hess-20-887-2016, https://doi.org/10.5194/hess-20-887-2016, 2016
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The absence of flow data to calibrate hydrologic models may reduce the ability of such models to reliably inform water resources management. To address this limitation, it is common to condition hydrological model parameters on regionalized signatures. In this study, we justify the inclusion of larger sets of signatures in the regionalization procedure if their error correlations are formally accounted for and thus enable a more complete use of all available information.
H. Xu and Y. Luo
Hydrol. Earth Syst. Sci., 19, 4609–4618, https://doi.org/10.5194/hess-19-4609-2015, https://doi.org/10.5194/hess-19-4609-2015, 2015
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This study quantified the climate impact on river discharge in the River Huangfuchuan in semi-arid northern China and the River Xiangxi in humid southern China. Climate projections showed trends toward warmer and wetter conditions, particularly for the River Huangfuchuan. The main projected hydrologic impact was a more pronounced increase in annual discharge in both catchments. Peak flows are projected to appear earlier than usual in the River Huangfuchuan and later than usual in River Xiangxi.
I. K. Westerberg and H. K. McMillan
Hydrol. Earth Syst. Sci., 19, 3951–3968, https://doi.org/10.5194/hess-19-3951-2015, https://doi.org/10.5194/hess-19-3951-2015, 2015
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This study investigated the effect of uncertainties in data and calculation methods on hydrological signatures. We present a widely applicable method to evaluate signature uncertainty and show results for two example catchments. The uncertainties were often large (i.e. typical intervals of ±10–40% relative uncertainty) and highly variable between signatures. It is therefore important to consider uncertainty when signatures are used for hydrological and ecohydrological analyses and modelling.
T. O. Sonnenborg, D. Seifert, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 19, 3891–3901, https://doi.org/10.5194/hess-19-3891-2015, https://doi.org/10.5194/hess-19-3891-2015, 2015
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The impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Geology is the dominating uncertainty source for travel time and capture zones, while climate dominates for hydraulic heads and steam flow.
N. Dogulu, P. López López, D. P. Solomatine, A. H. Weerts, and D. L. Shrestha
Hydrol. Earth Syst. Sci., 19, 3181–3201, https://doi.org/10.5194/hess-19-3181-2015, https://doi.org/10.5194/hess-19-3181-2015, 2015
F. Bourgin, V. Andréassian, C. Perrin, and L. Oudin
Hydrol. Earth Syst. Sci., 19, 2535–2546, https://doi.org/10.5194/hess-19-2535-2015, https://doi.org/10.5194/hess-19-2535-2015, 2015
T. Berezowski, J. Nossent, J. Chormański, and O. Batelaan
Hydrol. Earth Syst. Sci., 19, 1887–1904, https://doi.org/10.5194/hess-19-1887-2015, https://doi.org/10.5194/hess-19-1887-2015, 2015
F. Silvestro, S. Gabellani, R. Rudari, F. Delogu, P. Laiolo, and G. Boni
Hydrol. Earth Syst. Sci., 19, 1727–1751, https://doi.org/10.5194/hess-19-1727-2015, https://doi.org/10.5194/hess-19-1727-2015, 2015
M. C. Demirel, M. J. Booij, and A. Y. Hoekstra
Hydrol. Earth Syst. Sci., 19, 275–291, https://doi.org/10.5194/hess-19-275-2015, https://doi.org/10.5194/hess-19-275-2015, 2015
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This paper investigates the skill of 90-day low-flow forecasts using three models. From the results, it appears that all models are prone to over-predict runoff during low-flow periods using ensemble seasonal meteorological forcing. The largest range for 90-day low-flow forecasts is found for the GR4J model. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low-flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.
J. Crossman, M. N. Futter, P. G. Whitehead, E. Stainsby, H. M. Baulch, L. Jin, S. K. Oni, R. L. Wilby, and P. J. Dillon
Hydrol. Earth Syst. Sci., 18, 5125–5148, https://doi.org/10.5194/hess-18-5125-2014, https://doi.org/10.5194/hess-18-5125-2014, 2014
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We projected potential hydrochemical responses in four neighbouring catchments to a range of future climates. The highly variable responses in streamflow and total phosphorus (TP) were governed by geology and flow pathways, where larger catchment responses were proportional to greater soil clay content. This suggests clay content might be used as an indicator of catchment sensitivity to climate change, and highlights the need for catchment-specific management plans.
M. Honti, A. Scheidegger, and C. Stamm
Hydrol. Earth Syst. Sci., 18, 3301–3317, https://doi.org/10.5194/hess-18-3301-2014, https://doi.org/10.5194/hess-18-3301-2014, 2014
I. K. Westerberg, L. Gong, K. J. Beven, J. Seibert, A. Semedo, C.-Y. Xu, and S. Halldin
Hydrol. Earth Syst. Sci., 18, 2993–3013, https://doi.org/10.5194/hess-18-2993-2014, https://doi.org/10.5194/hess-18-2993-2014, 2014
G. Seiller and F. Anctil
Hydrol. Earth Syst. Sci., 18, 2033–2047, https://doi.org/10.5194/hess-18-2033-2014, https://doi.org/10.5194/hess-18-2033-2014, 2014
J. D. Herman, J. B. Kollat, P. M. Reed, and T. Wagener
Hydrol. Earth Syst. Sci., 17, 5109–5125, https://doi.org/10.5194/hess-17-5109-2013, https://doi.org/10.5194/hess-17-5109-2013, 2013
M. Sadegh and J. A. Vrugt
Hydrol. Earth Syst. Sci., 17, 4831–4850, https://doi.org/10.5194/hess-17-4831-2013, https://doi.org/10.5194/hess-17-4831-2013, 2013
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Short summary
Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus,...
