Articles | Volume 27, issue 18
https://doi.org/10.5194/hess-27-3375-2023
© Author(s) 2023. 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-27-3375-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Sep 2023
Research article |
| 22 Sep 2023
| 22 Sep 2023
On the visual detection of non-natural records in streamflow time series: challenges and impacts
Laurent Strohmenger
CORRESPONDING AUTHOR
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Eric Sauquet
INRAE, UR RiverLy, Villeurbanne, France
Claire Bernard
Chambre d'agriculture du Vaucluse, Avignon, France
Jérémie Bonneau
INRAE, UR RiverLy, Villeurbanne, France
Flora Branger
INRAE, UR RiverLy, Villeurbanne, France
Amélie Bresson
EPIDOR, Castelnaud-la-Chapelle, France
Pierre Brigode
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Observatoire de la Côte d'Azur, CNRS, OCA, IRD, Géoazur, Université Côte d'Azur, Sophia-Antipolis, France
Rémy Buzier
URA IRSTEA, University of Limoges, Limoges, France
Olivier Delaigue
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Alexandre Devers
INRAE, UR RiverLy, Villeurbanne, France
Guillaume Evin
INRAE, CNRS, IRD, Grenoble INP, IGE, Univ. Grenoble Alpes, Grenoble, France
Maïté Fournier
ACTeon – Environment, Research & Consultancy, Grenoble, France
Shu-Chen Hsu
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Sandra Lanini
BRGM, unité EAU-RMD, Montpellier, France
G-EAU, UMR 183, INRAE, CIRAD, IRD, AgroParisTech, Supagro, BRGM, Montpellier, France
Alban de Lavenne
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Thibault Lemaitre-Basset
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
UMR 7619 METIS, Sorbonne Université, CNRS, EPHE, Paris, France
Claire Magand
Office français de la biodiversité (OFB), Vincennes, France
Guilherme Mendoza Guimarães
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Max Mentha
Safege-Suez Consulting, Paris, France
Simon Munier
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Charles Perrin
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Tristan Podechard
CEREG, Montpellier, France
Léo Rouchy
INRAE, UR RiverLy, Villeurbanne, France
Malak Sadki
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Myriam Soutif-Bellenger
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
AgroParisTech, 75005, Paris, France
François Tilmant
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Yves Tramblay
HSM, University of Montpellier, CNRS, IRD, IMT, Montpellier, France
Anne-Lise Véron
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
Jean-Philippe Vidal
INRAE, UR RiverLy, Villeurbanne, France
Guillaume Thirel
CORRESPONDING AUTHOR
INRAE, HYCAR Research Unit, Université Paris-Saclay, Antony, France
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Samuel Morin, Hugues François, Marion Réveillet, Eric Sauquet, Louise Crochemore, Flora Branger, Étienne Leblois, and Marie Dumont
Hydrol. Earth Syst. Sci., 27, 4257–4277, https://doi.org/10.5194/hess-27-4257-2023, https://doi.org/10.5194/hess-27-4257-2023, 2023
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Isabelle Ousset, Guillaume Evin, Damien Raynaud, and Thierry Faug
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Erwan Le Roux, Guillaume Evin, Raphaëlle Samacoïts, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
The Cryosphere, 17, 4691–4704, https://doi.org/10.5194/tc-17-4691-2023, https://doi.org/10.5194/tc-17-4691-2023, 2023
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Julia Pfeffer, Anny Cazenave, Alejandro Blazquez, Bertrand Decharme, Simon Munier, and Anne Barnoud
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Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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Juliette Blanchet, Alix Reverdy, Antoine Blanc, Jean-Dominique Creutin, Périne Kiennemann, and Guillaume Evin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-197, https://doi.org/10.5194/hess-2023-197, 2023
Revised manuscript not accepted
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Olivier Delaigue, Pierre Brigode, Guillaume Thirel, and Laurent Coron
Hydrol. Earth Syst. Sci., 27, 3293–3327, https://doi.org/10.5194/hess-27-3293-2023, https://doi.org/10.5194/hess-27-3293-2023, 2023
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Yves Tramblay, Patrick Arnaud, Guillaume Artigue, Michel Lang, Emmanuel Paquet, Luc Neppel, and Eric Sauquet
Hydrol. Earth Syst. Sci., 27, 2973–2987, https://doi.org/10.5194/hess-27-2973-2023, https://doi.org/10.5194/hess-27-2973-2023, 2023
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Hanieh Seyedhashemi, Florentina Moatar, Jean-Philippe Vidal, and Dominique Thiéry
Earth Syst. Sci. Data, 15, 2827–2839, https://doi.org/10.5194/essd-15-2827-2023, https://doi.org/10.5194/essd-15-2827-2023, 2023
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This paper presents a past and future dataset of daily time series of discharge and stream temperature for 52 278 reaches over the Loire River basin (100 000 km2) in France, using thermal and hydrological models. Past data are provided over 1963–2019. Future data are available over the 1976–2100 period under different future climate change models (warm and wet, intermediate, and hot and dry) and scenarios (optimistic, intermediate, and pessimistic).
Maxime Morel, Guillaume Piton, Damien Kuss, Guillaume Evin, and Caroline Le Bouteiller
Nat. Hazards Earth Syst. Sci., 23, 1769–1787, https://doi.org/10.5194/nhess-23-1769-2023, https://doi.org/10.5194/nhess-23-1769-2023, 2023
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In mountain catchments, damage during floods is generally primarily driven by the supply of a massive amount of sediment. Predicting how much sediment can be delivered by frequent and infrequent events is thus important in hazard studies. This paper uses data gathered during the maintenance operation of about 100 debris retention basins to build simple equations aiming at predicting sediment supply from simple parameters describing the upstream catchment.
Cécile Duvillier, Nicolas Eckert, Guillaume Evin, and Michael Deschâtres
Nat. Hazards Earth Syst. Sci., 23, 1383–1408, https://doi.org/10.5194/nhess-23-1383-2023, https://doi.org/10.5194/nhess-23-1383-2023, 2023
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This study develops a method that identifies individual potential release areas (PRAs) of snow avalanches based on terrain analysis and watershed delineation and demonstrates its efficiency in the French Alps context using an extensive cadastre of past avalanche limits. Results may contribute to better understanding local avalanche hazard. The work may also foster the development of more efficient PRA detection methods based on a rigorous evaluation scheme.
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.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
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Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Juliette Blanchet, Alix Reverdy, Antoine Blanc, Jean-Dominique Creutin, Périne Kiennemann, and Guillaume Evin
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-276, https://doi.org/10.5194/nhess-2022-276, 2023
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We study the atmospheric conditions at the origin of damaging torrential events in the Northern French Alps over the long run. We consider seven atmospheric variables that describe the nature of the air masses involved and the possible triggers of precipitation and we try to isolate the most discriminating variables. The results show that humidity and particularly humidity transport plays the greatest role under westerly flows while instability potential is mostly at play under southerly flows.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
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Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Reyhaneh Hashemi, Pierre Brigode, Pierre-André Garambois, and Pierre Javelle
Hydrol. Earth Syst. Sci., 26, 5793–5816, https://doi.org/10.5194/hess-26-5793-2022, https://doi.org/10.5194/hess-26-5793-2022, 2022
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Hydrologists have long dreamed of a tool that could adequately predict runoff in catchments. Data-driven long short-term memory (LSTM) models appear very promising to the hydrology community in this respect. Here, we have sought to benefit from traditional practices in hydrology to improve the effectiveness of LSTM models. We discovered that one LSTM parameter has a hydrologic interpretation and that there is a need to increase the data and to tune two parameters, thereby improving predictions.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
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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.
Daniel Viviroli, Anna E. Sikorska-Senoner, Guillaume Evin, Maria Staudinger, Martina Kauzlaric, Jérémy Chardon, Anne-Catherine Favre, Benoit Hingray, Gilles Nicolet, Damien Raynaud, Jan Seibert, Rolf Weingartner, and Calvin Whealton
Nat. Hazards Earth Syst. Sci., 22, 2891–2920, https://doi.org/10.5194/nhess-22-2891-2022, https://doi.org/10.5194/nhess-22-2891-2022, 2022
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Estimating the magnitude of rare to very rare floods is a challenging task due to a lack of sufficiently long observations. The challenge is even greater in large river basins, where precipitation patterns and amounts differ considerably between individual events and floods from different parts of the basin coincide. We show that a hydrometeorological model chain can provide plausible estimates in this setting and can thus inform flood risk and safety assessments for critical infrastructure.
Aurélien Beaufort, Jacob S. Diamond, Eric Sauquet, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 3477–3495, https://doi.org/10.5194/hess-26-3477-2022, https://doi.org/10.5194/hess-26-3477-2022, 2022
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We developed one of the largest stream temperature databases to calculate a simple, ecologically relevant metric – the thermal peak – that captures the magnitude of summer thermal extremes. Using statistical models, we extrapolated the thermal peak to nearly every stream in France, finding the hottest thermal peaks along large rivers without forested riparian zones and groundwater inputs. Air temperature was a poor proxy for the thermal peak, highlighting the need to grow monitoring networks.
Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
Earth Syst. Dynam., 13, 1059–1075, https://doi.org/10.5194/esd-13-1059-2022, https://doi.org/10.5194/esd-13-1059-2022, 2022
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Anticipating risks related to climate extremes is critical for societal adaptation to climate change. In this study, we propose a statistical method in order to estimate future climate extremes from past observations and an ensemble of climate change simulations. We apply this approach to snow load data available in the French Alps at 1500 m elevation and find that extreme snow load is projected to decrease by −2.9 kN m−2 (−50 %) between 1986–2005 and 2080–2099 for a high-emission scenario.
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.
Alban de Lavenne, Vazken Andréassian, Louise Crochemore, Göran Lindström, and Berit Arheimer
Hydrol. Earth Syst. Sci., 26, 2715–2732, https://doi.org/10.5194/hess-26-2715-2022, https://doi.org/10.5194/hess-26-2715-2022, 2022
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A watershed remembers the past to some extent, and this memory influences its behavior. This memory is defined by the ability to store past rainfall for several years. By releasing this water into the river or the atmosphere, it tends to forget. We describe how this memory fades over time in France and Sweden. A few watersheds show a multi-year memory. It increases with the influence of groundwater or dry conditions. After 3 or 4 years, they behave independently of the past.
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.
Simon Munier and Bertrand Decharme
Earth Syst. Sci. Data, 14, 2239–2258, https://doi.org/10.5194/essd-14-2239-2022, https://doi.org/10.5194/essd-14-2239-2022, 2022
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This paper presents a new global-scale river network at 1/12°, generated automatically and assessed over the 69 largest basins of the world. A set of hydro-geomorphological parameters are derived at the same spatial resolution, including a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography). The dataset may be useful for hydrology modelling or climate studies.
Małgorzata Chmiel, Maxime Godano, Marco Piantini, Pierre Brigode, Florent Gimbert, Maarten Bakker, Françoise Courboulex, Jean-Paul Ampuero, Diane Rivet, Anthony Sladen, David Ambrois, and Margot Chapuis
Nat. Hazards Earth Syst. Sci., 22, 1541–1558, https://doi.org/10.5194/nhess-22-1541-2022, https://doi.org/10.5194/nhess-22-1541-2022, 2022
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On 2 October 2020, the French Maritime Alps were struck by an extreme rainfall event caused by Storm Alex. Here, we show that seismic data provide the timing and velocity of the propagation of flash-flood waves along the Vésubie River. We also detect 114 small local earthquakes triggered by the rainwater weight and/or its infiltration into the ground. This study paves the way for future works that can reveal further details of the impact of Storm Alex on the Earth’s surface and subsurface.
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.
Yves Tramblay and Pere Quintana Seguí
Nat. Hazards Earth Syst. Sci., 22, 1325–1334, https://doi.org/10.5194/nhess-22-1325-2022, https://doi.org/10.5194/nhess-22-1325-2022, 2022
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Monitoring soil moisture is important during droughts, but very few measurements are available. Consequently, land-surface models are essential tools for reproducing soil moisture dynamics. In this study, a hybrid approach allowed for regionalizing soil water content using a machine learning method. This approach proved to be efficient, compared to the use of soil property maps, to run a simple soil moisture accounting model, and therefore it can be applied in various regions.
Guillaume Evin, Samuel Somot, and Benoit Hingray
Earth Syst. Dynam., 12, 1543–1569, https://doi.org/10.5194/esd-12-1543-2021, https://doi.org/10.5194/esd-12-1543-2021, 2021
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This research paper proposes an assessment of mean climate change responses and related uncertainties over Europe for mean seasonal temperature and total seasonal precipitation. An advanced statistical approach is applied to a large ensemble of 87 high-resolution EURO-CORDEX projections. For the first time, we provide a comprehensive estimation of the relative contribution of GCMs and RCMs, RCP scenarios, and internal variability to the total variance of a very large ensemble.
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.
Guillaume Evin, Matthieu Lafaysse, Maxime Taillardat, and Michaël Zamo
Nonlin. Processes Geophys., 28, 467–480, https://doi.org/10.5194/npg-28-467-2021, https://doi.org/10.5194/npg-28-467-2021, 2021
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Forecasting the height of new snow is essential for avalanche hazard surveys, road and ski resort management, tourism attractiveness, etc. Météo-France operates a probabilistic forecasting system using a numerical weather prediction system and a snowpack model. It provides better forecasts than direct diagnostics but exhibits significant biases. Post-processing methods can be applied to provide automatic forecasting products from this system.
Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
The Cryosphere, 15, 4335–4356, https://doi.org/10.5194/tc-15-4335-2021, https://doi.org/10.5194/tc-15-4335-2021, 2021
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Extreme snowfall can cause major natural hazards (avalanches, winter storms) that can generate casualties and economic damage. In the French Alps, we show that between 1959 and 2019 extreme snowfall mainly decreased below 2000 m of elevation and increased above 2000 m. At 2500 m, we find a contrasting pattern: extreme snowfall decreased in the north, while it increased in the south. This pattern might be related to increasing trends in extreme snowfall observed near the Mediterranean Sea.
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.
Stella Guillemot, Ophelie Fovet, Chantal Gascuel-Odoux, Gérard Gruau, Antoine Casquin, Florence Curie, Camille Minaudo, Laurent Strohmenger, and Florentina Moatar
Hydrol. Earth Syst. Sci., 25, 2491–2511, https://doi.org/10.5194/hess-25-2491-2021, https://doi.org/10.5194/hess-25-2491-2021, 2021
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This study investigates the drivers of spatial variations in stream water quality in poorly studied headwater catchments and includes multiple elements involved in major water quality issues, such as eutrophication. We used a regional public dataset of monthly stream water concentrations monitored for 10 years over 185 agricultural catchments. We found a spatial and seasonal opposition between carbon and nitrogen concentrations, while phosphorus concentrations showed another spatial pattern.
Yves Tramblay, Nathalie Rouché, Jean-Emmanuel Paturel, Gil Mahé, Jean-François Boyer, Ernest Amoussou, Ansoumana Bodian, Honoré Dacosta, Hamouda Dakhlaoui, Alain Dezetter, Denis Hughes, Lahoucine Hanich, Christophe Peugeot, Raphael Tshimanga, and Patrick Lachassagne
Earth Syst. Sci. Data, 13, 1547–1560, https://doi.org/10.5194/essd-13-1547-2021, https://doi.org/10.5194/essd-13-1547-2021, 2021
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This dataset provides a set of hydrometric indices for about 1500 stations across Africa with daily discharge data. These indices represent mean flow characteristics and extremes (low flows and floods), allowing us to study the long-term evolution of hydrology in Africa and support the modeling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.
Thibault Guinaldo, Simon Munier, Patrick Le Moigne, Aaron Boone, Bertrand Decharme, Margarita Choulga, and Delphine J. Leroux
Geosci. Model Dev., 14, 1309–1344, https://doi.org/10.5194/gmd-14-1309-2021, https://doi.org/10.5194/gmd-14-1309-2021, 2021
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Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services such as freshwater supply. Despite the impact of lakes on the water cycle, they are generally not considered in global hydrological studies. Based on a model called MLake, we assessed both the importance of lakes in simulating river flows at global scale and the value of their level variations for water resource management.
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
Louise Mimeau, Yves Tramblay, Luca Brocca, Christian Massari, Stefania Camici, and Pascal Finaud-Guyot
Hydrol. Earth Syst. Sci., 25, 653–669, https://doi.org/10.5194/hess-25-653-2021, https://doi.org/10.5194/hess-25-653-2021, 2021
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Soil moisture is a key variable related to droughts and flood genesis, but little is known about the evolution of soil moisture under climate change. Here, using a simulation approach, we show that changes in soil moisture are driven by changes in precipitation intermittence rather than changes in precipitation intensity or in temperature.
Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
Nat. Hazards Earth Syst. Sci., 20, 2961–2977, https://doi.org/10.5194/nhess-20-2961-2020, https://doi.org/10.5194/nhess-20-2961-2020, 2020
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To minimize the risk of structure collapse due to extreme snow loads, structure standards rely on 50-year return levels of ground snow load (GSL), i.e. levels exceeded once every 50 years on average, that do not account for climate change. We study GSL data in the French Alps massifs from 1959 and 2019 and find that these 50-year return levels are decreasing with time between 900 and 4800 m of altitude, but they still exceed return levels of structure standards for half of the massifs at 1800 m.
El Mahdi El Khalki, Yves Tramblay, Christian Massari, Luca Brocca, Vincent Simonneaux, Simon Gascoin, and Mohamed El Mehdi Saidi
Nat. Hazards Earth Syst. Sci., 20, 2591–2607, https://doi.org/10.5194/nhess-20-2591-2020, https://doi.org/10.5194/nhess-20-2591-2020, 2020
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In North Africa, the vulnerability to floods is high, and there is a need to improve the flood-forecasting systems. Remote-sensing and reanalysis data can palliate the lack of in situ measurements, in particular for soil moisture, which is a crucial parameter to consider when modeling floods. In this study we provide an evaluation of recent globally available soil moisture products for flood modeling in Morocco.
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.
Pierre Nicolle, François Besson, Olivier Delaigue, Pierre Etchevers, Didier François, Matthieu Le Lay, Charles Perrin, Fabienne Rousset, Dominique Thiéry, François Tilmant, Claire Magand, Timothée Leurent, and Élise Jacob
Proc. IAHS, 383, 381–389, https://doi.org/10.5194/piahs-383-381-2020, https://doi.org/10.5194/piahs-383-381-2020, 2020
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.
Damien Raynaud, Benoit Hingray, Guillaume Evin, Anne-Catherine Favre, and Jérémy Chardon
Hydrol. Earth Syst. Sci., 24, 4339–4352, https://doi.org/10.5194/hess-24-4339-2020, https://doi.org/10.5194/hess-24-4339-2020, 2020
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This research paper proposes a weather generator combining two sampling approaches. A first generator recombines large-scale atmospheric situations. A second generator is applied to these atmospheric trajectories in order to simulate long time series of daily regional precipitation and temperature. The method is applied to daily time series in Switzerland. It reproduces adequately the observed climatology and improves the reproduction of extreme precipitation values.
Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, https://doi.org/10.5194/hess-24-4291-2020, 2020
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LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
Yongjun Zheng, Clément Albergel, Simon Munier, Bertrand Bonan, and Jean-Christophe Calvet
Geosci. Model Dev., 13, 3607–3625, https://doi.org/10.5194/gmd-13-3607-2020, https://doi.org/10.5194/gmd-13-3607-2020, 2020
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This study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framework for high-dimensional ensemble Kalman filters. The offline and online modes of ensemble Kalman filters are built to comprehensively assess their time to solution efficiencies. The offline mode is substantially faster than the online mode in terms of time to solution, especially for large-scale assimilation problems.
Victor Pellet, Filipe Aires, Fabrice Papa, Simon Munier, and Bertrand Decharme
Hydrol. Earth Syst. Sci., 24, 3033–3055, https://doi.org/10.5194/hess-24-3033-2020, https://doi.org/10.5194/hess-24-3033-2020, 2020
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The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.
Lionel Berthet, François Bourgin, Charles Perrin, Julie Viatgé, Renaud Marty, and Olivier Piotte
Hydrol. Earth Syst. Sci., 24, 2017–2041, https://doi.org/10.5194/hess-24-2017-2020, https://doi.org/10.5194/hess-24-2017-2020, 2020
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An increasing number of flood forecasting services assess and communicate the uncertainty associated with their forecasts. We present a crash-testing framework that evaluates the quality of hydrological forecasts in an extrapolation context. Overall, the results highlight the challenge of uncertainty quantification when forecasting high flows. They show a significant drop in reliability when forecasting high flows and considerable variability among catchments and across lead times.
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.
Jordi Bolibar, Antoine Rabatel, Isabelle Gouttevin, Clovis Galiez, Thomas Condom, and Eric Sauquet
The Cryosphere, 14, 565–584, https://doi.org/10.5194/tc-14-565-2020, https://doi.org/10.5194/tc-14-565-2020, 2020
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We introduce a novel approach for simulating glacier mass balances using a deep artificial neural network (i.e. deep learning) from climate and topographical data. This has been added as a component of a new open-source parameterized glacier evolution model. Deep learning is found to outperform linear machine learning methods, mainly due to its nonlinearity. Potential applications range from regional mass balance reconstructions from observations to simulations for past and future climates.
Bertrand Bonan, Clément Albergel, Yongjun Zheng, Alina Lavinia Barbu, David Fairbairn, Simon Munier, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 325–347, https://doi.org/10.5194/hess-24-325-2020, https://doi.org/10.5194/hess-24-325-2020, 2020
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This paper introduces an ensemble square root filter (EnSRF), a deterministic ensemble Kalman filter, for jointly assimilating observations of the surface soil moisture and leaf area index in the Land Data Assimilation System LDAS-Monde. LDAS-Monde constrains the Interaction between Soil, Biosphere and Atmosphere (ISBA) land surface model to improve the reanalysis of land surface variables. EnSRF is compared with the simplified extended Kalman filter over the European Mediterranean region.
Yves Tramblay, Louise Mimeau, Luc Neppel, Freddy Vinet, and Eric Sauquet
Hydrol. Earth Syst. Sci., 23, 4419–4431, https://doi.org/10.5194/hess-23-4419-2019, https://doi.org/10.5194/hess-23-4419-2019, 2019
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In the present study the flood trends have been assessed for a large sample of 171 basins located in southern France, which has a Mediterranean climate. Results show that, despite the increase in rainfall intensity previously observed in this area, there is no general increase in flood magnitude. Instead, a reduction in the annual number of floods is found, linked to a decrease in soil moisture caused by the increase in temperature observed in recent decades.
Jari-Pekka Nousu, Matthieu Lafaysse, Matthieu Vernay, Joseph Bellier, Guillaume Evin, and Bruno Joly
Nonlin. Processes Geophys., 26, 339–357, https://doi.org/10.5194/npg-26-339-2019, https://doi.org/10.5194/npg-26-339-2019, 2019
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Forecasting the height of new snow is crucial for avalanche hazard, road viability, ski resorts and tourism. The numerical models suffer from systematic and significant errors which are misleading for the final users. Here, we applied for the first time a state-of-the-art statistical method to correct ensemble numerical forecasts of the height of new snow from their statistical link with measurements in French Alps and Pyrenees. Thus the realism of automatic forecasts can be quickly improved.
Eric Sauquet, Bastien Richard, Alexandre Devers, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 23, 3683–3710, https://doi.org/10.5194/hess-23-3683-2019, https://doi.org/10.5194/hess-23-3683-2019, 2019
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This study aims to identify catchments and the associated water uses vulnerable to climate change. Vulnerability is considered here to be the likelihood of water restrictions which are unacceptable for agricultural uses. This study provides the first regional analysis of the stated water restrictions, highlighting heterogeneous decision-making processes; data from a national system of compensation to farmers for uninsurable damages were used to characterize past failure events.
Pauline Rivoire, Yves Tramblay, Luc Neppel, Elke Hertig, and Sergio M. Vicente-Serrano
Nat. Hazards Earth Syst. Sci., 19, 1629–1638, https://doi.org/10.5194/nhess-19-1629-2019, https://doi.org/10.5194/nhess-19-1629-2019, 2019
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In order to define a dry period, a threshold for wet days is usually considered to account for measurement errors and evaporation. In the present study, we compare the threshold of 1 mm d−1, the most commonly used threshold, to a time-varying threshold describing evapotranspiration to compare how the risk of extreme dry spells is estimated with both thresholds. Results indicate that considering a fixed threshold can underestimate extreme dry spells during the extended summer.
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.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, https://doi.org/10.5194/hess-23-1973-2019, 2019
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This study investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modeling, in global water resource reanalysis. Analysis is based on ensemble hydrologic simulations for a period of 11 years based on six global hydrologic models and five precipitation datasets. Results show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure.
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.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
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.
Guillaume Evin, Thomas Curt, and Nicolas Eckert
Nat. Hazards Earth Syst. Sci., 18, 2641–2651, https://doi.org/10.5194/nhess-18-2641-2018, https://doi.org/10.5194/nhess-18-2641-2018, 2018
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Very large wildfires have high human, economic, and ecological impacts. Preventing such events is a major objective of the new fire policy set up in France in 1994, which is oriented towards fast and massive fire suppression. This study investigates the effect of this policy on the largest fires. We estimate the burned area corresponding to fires that occur every 5, 20, and 50 years on average (so-called return periods) in southern France.
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.
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.
Clement Albergel, Emanuel Dutra, Simon Munier, Jean-Christophe Calvet, Joaquin Munoz-Sabater, Patricia de Rosnay, and Gianpaolo Balsamo
Hydrol. Earth Syst. Sci., 22, 3515–3532, https://doi.org/10.5194/hess-22-3515-2018, https://doi.org/10.5194/hess-22-3515-2018, 2018
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ECMWF recently released the first 7-year segment of its latest atmospheric reanalysis: ERA-5 (2010–2016). ERA-5 has important changes relative to ERA-Interim including higher spatial and temporal resolutions as well as a more recent model and data assimilation system. ERA-5 is foreseen to replace ERA-Interim reanalysis. One of the main goals of this study is to assess whether ERA-5 can enhance the simulation performances with respect to ERA-Interim when it is used to force a land surface model.
Aurélien Beaufort, Nicolas Lamouroux, Hervé Pella, Thibault Datry, and Eric Sauquet
Hydrol. Earth Syst. Sci., 22, 3033–3051, https://doi.org/10.5194/hess-22-3033-2018, https://doi.org/10.5194/hess-22-3033-2018, 2018
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Streams which may stop flowing are poorly gauged. To improve their characterisation, we use an extended network providing monthly visual observations stating whether streams are flowing or not across France. These observations are combined with discharge and groundwater level in models to predict daily regional probability of drying. This approach allows identification of the most impacted regions by flow intermittence and estimation of the probability of drying dynamics over the last 27 years.
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.
Guillaume Evin, Anne-Catherine Favre, and Benoit Hingray
Hydrol. Earth Syst. Sci., 22, 655–672, https://doi.org/10.5194/hess-22-655-2018, https://doi.org/10.5194/hess-22-655-2018, 2018
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This research paper proposes a multi-site daily precipitation model, named GWEX, which aims to reproduce the statistical features of extremely rare events at different temporal and spatial scales. Recent advances and various statistical methods (regionalization, disaggregation) are considered in order to obtain a robust and appropriate representation of the most extreme precipitation fields. Performances are shown with an application to 105 stations, covering a large region in Switzerland.
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
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LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
Hélène Dewaele, Simon Munier, Clément Albergel, Carole Planque, Nabil Laanaia, Dominique Carrer, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4861–4878, https://doi.org/10.5194/hess-21-4861-2017, https://doi.org/10.5194/hess-21-4861-2017, 2017
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Soil maximum available water content (MaxAWC) is a key parameter in land surface models. Being difficult to measure, this parameter is usually unavailable. A 15-year time series of satellite-derived observations of leaf area index (LAI) is used to retrieve MaxAWC for rainfed straw cereals over France. Disaggregated LAI is sequentially assimilated into the ISBA LSM. MaxAWC is estimated minimising LAI analyses increments. Annual maximum LAI observations correlate with the MaxAWC estimates.
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.
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.
Guillaume Nord, Brice Boudevillain, Alexis Berne, Flora Branger, Isabelle Braud, Guillaume Dramais, Simon Gérard, Jérôme Le Coz, Cédric Legoût, Gilles Molinié, Joel Van Baelen, Jean-Pierre Vandervaere, Julien Andrieu, Coralie Aubert, Martin Calianno, Guy Delrieu, Jacopo Grazioli, Sahar Hachani, Ivan Horner, Jessica Huza, Raphaël Le Boursicaud, Timothy H. Raupach, Adriaan J. Teuling, Magdalena Uber, Béatrice Vincendon, and Annette Wijbrans
Earth Syst. Sci. Data, 9, 221–249, https://doi.org/10.5194/essd-9-221-2017, https://doi.org/10.5194/essd-9-221-2017, 2017
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A high space–time resolution dataset linking hydrometeorological forcing and hydro-sedimentary response in a mesoscale catchment (Auzon, 116 km2) of the Ardèche region (France) is presented. This region is subject to precipitating systems of Mediterranean origin, which can result in significant rainfall amount. The data presented cover a period of 4 years (2011–2014) and aim at improving the understanding of processes triggering flash floods.
Louise Crochemore, Maria-Helena Ramos, Florian Pappenberger, and Charles Perrin
Hydrol. Earth Syst. Sci., 21, 1573–1591, https://doi.org/10.5194/hess-21-1573-2017, https://doi.org/10.5194/hess-21-1573-2017, 2017
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The use of general circulation model outputs for streamflow forecasting has developed in the last decade. In parallel, traditional streamflow forecasting is commonly based on historical data. This study investigates the impact of conditioning historical data based on circulation model precipitation forecasts on seasonal streamflow forecast quality. Results highlighted a trade-off between the sharpness and reliability of forecasts.
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.
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.
Pierre Brigode, François Brissette, Antoine Nicault, Luc Perreault, Anna Kuentz, Thibault Mathevet, and Joël Gailhard
Clim. Past, 12, 1785–1804, https://doi.org/10.5194/cp-12-1785-2016, https://doi.org/10.5194/cp-12-1785-2016, 2016
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In this paper, we apply a new hydro-climatic reconstruction method on the Caniapiscau Reservoir (Canada), compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment, and study the natural streamflow variability over the 1881–2011 period. This new reconstruction is based on a historical reanalysis of global geopotential height fields and aims to produce daily streamflow time series (using a rainfall–runoff model).
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.
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.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 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
M. Adamovic, I. Braud, F. Branger, and J. W. Kirchner
Hydrol. Earth Syst. Sci., 19, 2427–2449, https://doi.org/10.5194/hess-19-2427-2015, https://doi.org/10.5194/hess-19-2427-2015, 2015
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This study explores how catchment heterogeneity and variability can be summarized in simplified models, representing the dominant hydrological processes. We apply simple dynamical system approach (Kirchner, 2009) in the Ardèche catchment (south-east France). The simple dynamical system hypothesis works especially well in wet conditions (peaks and recessions are well modelled) and for granite catchments, which are likely to be characterized by shallow subsurface flow.
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.
I. Braud, P.-A. Ayral, C. Bouvier, F. Branger, G. Delrieu, J. Le Coz, G. Nord, J.-P. Vandervaere, S. Anquetin, M. Adamovic, J. Andrieu, C. Batiot, B. Boudevillain, P. Brunet, J. Carreau, A. Confoland, J.-F. Didon-Lescot, J.-M. Domergue, J. Douvinet, G. Dramais, R. Freydier, S. Gérard, J. Huza, E. Leblois, O. Le Bourgeois, R. Le Boursicaud, P. Marchand, P. Martin, L. Nottale, N. Patris, B. Renard, J.-L. Seidel, J.-D. Taupin, O. Vannier, B. Vincendon, and A. Wijbrans
Hydrol. Earth Syst. Sci., 18, 3733–3761, https://doi.org/10.5194/hess-18-3733-2014, https://doi.org/10.5194/hess-18-3733-2014, 2014
P. Nicolle, R. Pushpalatha, C. Perrin, D. François, D. Thiéry, T. Mathevet, M. Le Lay, F. Besson, J.-M. Soubeyroux, C. Viel, F. Regimbeau, V. Andréassian, P. Maugis, B. Augeard, and E. Morice
Hydrol. Earth Syst. Sci., 18, 2829–2857, https://doi.org/10.5194/hess-18-2829-2014, https://doi.org/10.5194/hess-18-2829-2014, 2014
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
L. Coron, V. Andréassian, C. Perrin, M. Bourqui, and F. Hendrickx
Hydrol. Earth Syst. Sci., 18, 727–746, https://doi.org/10.5194/hess-18-727-2014, https://doi.org/10.5194/hess-18-727-2014, 2014
K. Kochanek, B. Renard, P. Arnaud, Y. Aubert, M. Lang, T. Cipriani, and E. Sauquet
Nat. Hazards Earth Syst. Sci., 14, 295–308, https://doi.org/10.5194/nhess-14-295-2014, https://doi.org/10.5194/nhess-14-295-2014, 2014
F. Lobligeois, V. Andréassian, C. Perrin, P. Tabary, and C. Loumagne
Hydrol. Earth Syst. Sci., 18, 575–594, https://doi.org/10.5194/hess-18-575-2014, https://doi.org/10.5194/hess-18-575-2014, 2014
H. V. Gupta, C. Perrin, G. Blöschl, A. Montanari, R. Kumar, M. Clark, and V. Andréassian
Hydrol. Earth Syst. Sci., 18, 463–477, https://doi.org/10.5194/hess-18-463-2014, https://doi.org/10.5194/hess-18-463-2014, 2014
Y. Tramblay, S. El Adlouni, and E. Servat
Nat. Hazards Earth Syst. Sci., 13, 3235–3248, https://doi.org/10.5194/nhess-13-3235-2013, https://doi.org/10.5194/nhess-13-3235-2013, 2013
W. R. van Esse, C. Perrin, M. J. Booij, D. C. M. Augustijn, F. Fenicia, D. Kavetski, and F. Lobligeois
Hydrol. Earth Syst. Sci., 17, 4227–4239, https://doi.org/10.5194/hess-17-4227-2013, https://doi.org/10.5194/hess-17-4227-2013, 2013
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
Y. Tramblay, D. Ruelland, S. Somot, R. Bouaicha, and E. Servat
Hydrol. Earth Syst. Sci., 17, 3721–3739, https://doi.org/10.5194/hess-17-3721-2013, https://doi.org/10.5194/hess-17-3721-2013, 2013
T. H. Snelder, T. Datry, N. Lamouroux, S. T. Larned, E. Sauquet, H. Pella, and C. Catalogne
Hydrol. Earth Syst. Sci., 17, 2685–2699, https://doi.org/10.5194/hess-17-2685-2013, https://doi.org/10.5194/hess-17-2685-2013, 2013
P. Brigode, Z. Mićović, P. Bernardara, E. Paquet, F. Garavaglia, J. Gailhard, and P. Ribstein
Hydrol. Earth Syst. Sci., 17, 1455–1473, https://doi.org/10.5194/hess-17-1455-2013, https://doi.org/10.5194/hess-17-1455-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Uncertainty analysis
Historical rainfall data in northern Italy predict larger meteorological drought hazard than climate projections
Daytime-only mean data enhance understanding of land–atmosphere coupling
Quantifying the uncertainty of precipitation forecasting using probabilistic deep learning
Unraveling the contribution of potential evaporation formulation to uncertainty under climate change
Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II
Choosing between post-processing precipitation forecasts or chaining several uncertainty quantification tools in hydrological forecasting systems
Performance of the Global Forecast System's medium-range precipitation forecasts in the Niger river basin using multiple satellite-based products
Uncertainties and their interaction in flood hazard assessment with climate change
Bias-correcting input variables enhances forecasting of reference crop evapotranspiration
Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies
At which timescale does the complementary principle perform best in evaporation estimation?
Uncertainty in nonstationary frequency analysis of South Korea's daily rainfall peak over threshold excesses associated with covariates
Assessment of extreme flows and uncertainty under climate change: disentangling the uncertainty contribution of representative concentration pathways, global climate models and internal climate variability
The accuracy of weather radar in heavy rain: a comparative study for Denmark, the Netherlands, Finland and Sweden
A new uncertainty estimation approach with multiple datasets and implementation for various precipitation products
A crash-testing framework for predictive uncertainty assessment when forecasting high flows in an extrapolation context
Required sampling density of ground-based soil moisture and brightness temperature observations for calibration and validation of L-band satellite observations based on a virtual reality
Response of global evaporation to major climate modes in historical and future Coupled Model Intercomparison Project Phase 5 simulations
Cross-validating precipitation datasets in the Indus River basin
Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics
Assessment of spatial uncertainty of heavy rainfall at catchment scale using a dense gauge network
Influence of three phases of El Niño–Southern Oscillation on daily precipitation regimes in China
Dual-polarized quantitative precipitation estimation as a function of range
Reconstruction of droughts in India using multiple land-surface models (1951–2015)
Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system
Exploratory studies into seasonal flow forecasting potential for large lakes
Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China
Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate
Providing a non-deterministic representation of spatial variability of precipitation in the Everest region
Inter-comparison of daily precipitation products for large-scale hydro-climatic applications over Canada
Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones
Characteristics of rainfall events in regional climate model simulations for the Czech Republic
The rainfall erosivity factor in the Czech Republic and its uncertainty
Hierarchy of climate and hydrological uncertainties in transient low-flow projections
Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game
Assessment of small-scale variability of rainfall and multi-satellite precipitation estimates using measurements from a dense rain gauge network in Southeast India
Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands
Uncertainties in calculating precipitation climatology in East Asia
Measurement and interpolation uncertainties in rainfall maps from cellular communication networks
Characterization of precipitation product errors across the United States using multiplicative triple collocation
Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework
Evaluation of land surface model simulations of evapotranspiration over a 12-year crop succession: impact of soil hydraulic and vegetation properties
Multi-objective parameter optimization of common land model using adaptive surrogate modeling
Testing gridded land precipitation data and precipitation and runoff reanalyses (1982–2010) between 45° S and 45° N with normalised difference vegetation index data
Evaluation of high-resolution precipitation analyses using a dense station network
Prediction of extreme floods based on CMIP5 climate models: a case study in the Beijiang River basin, South China
Estimating the water needed to end the drought or reduce the drought severity in the Carpathian region
Alternative configurations of quantile regression for estimating predictive uncertainty in water level forecasts for the upper Severn River: a comparison
Comparison of drought indicators derived from multiple data sets over Africa
The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps
Rui Guo and Alberto Montanari
Hydrol. Earth Syst. Sci., 27, 2847–2863, https://doi.org/10.5194/hess-27-2847-2023, https://doi.org/10.5194/hess-27-2847-2023, 2023
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The present study refers to the region of Bologna, where the availability of a 209-year-long daily rainfall series allows us to make a unique assessment of global climate models' reliability and their predicted changes in rainfall and multiyear droughts. Our results suggest carefully considering the impact of uncertainty when designing climate change adaptation policies for droughts. Rigorous use and comprehensive interpretation of the available information are needed to avoid mismanagement.
Zun Yin, Kirsten L. Findell, Paul Dirmeyer, Elena Shevliakova, Sergey Malyshev, Khaled Ghannam, Nina Raoult, and Zhihong Tan
Hydrol. Earth Syst. Sci., 27, 861–872, https://doi.org/10.5194/hess-27-861-2023, https://doi.org/10.5194/hess-27-861-2023, 2023
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Land–atmosphere (L–A) interactions typically focus on daytime processes connecting the land state with the overlying atmospheric boundary layer. However, much prior L–A work used monthly or daily means due to the lack of daytime-only data products. Here we show that monthly smoothing can significantly obscure the L–A coupling signal, and including nighttime information can mute or mask the daytime processes of interest. We propose diagnosing L–A coupling within models or archiving subdaily data.
Lei Xu, Nengcheng Chen, Chao Yang, Hongchu Yu, and Zeqiang Chen
Hydrol. Earth Syst. Sci., 26, 2923–2938, https://doi.org/10.5194/hess-26-2923-2022, https://doi.org/10.5194/hess-26-2923-2022, 2022
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Precipitation forecasting has potential uncertainty due to data and model uncertainties. Here, an integrated predictive uncertainty modeling framework is proposed by jointly considering data and model uncertainties through an uncertainty propagation theorem. The results indicate an effective predictive uncertainty estimation for precipitation forecasting, indicating the great potential for uncertainty quantification of numerous predictive applications.
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.
Jing Xu, François Anctil, and Marie-Amélie Boucher
Hydrol. Earth Syst. Sci., 26, 1001–1017, https://doi.org/10.5194/hess-26-1001-2022, https://doi.org/10.5194/hess-26-1001-2022, 2022
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The performance of the non-dominated sorting genetic algorithm II (NSGA-II) is compared with a conventional post-processing method of affine kernel dressing. NSGA-II showed its superiority in improving the forecast skill and communicating trade-offs with end-users. It allows the enhancement of the forecast quality since it allows for setting multiple specific objectives from scratch. This flexibility should be considered as a reason to implement hydrologic ensemble prediction systems (H-EPSs).
Emixi Sthefany Valdez, François Anctil, and Maria-Helena Ramos
Hydrol. Earth Syst. Sci., 26, 197–220, https://doi.org/10.5194/hess-26-197-2022, https://doi.org/10.5194/hess-26-197-2022, 2022
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We investigated how a precipitation post-processor interacts with other tools for uncertainty quantification in a hydrometeorological forecasting chain. Four systems were implemented to generate 7 d ensemble streamflow forecasts, which vary from partial to total uncertainty estimation. Overall analysis showed that post-processing and initial condition estimation ensure the most skill improvements, in some cases even better than a system that considers all sources of uncertainty.
Haowen Yue, Mekonnen Gebremichael, and Vahid Nourani
Hydrol. Earth Syst. Sci., 26, 167–181, https://doi.org/10.5194/hess-26-167-2022, https://doi.org/10.5194/hess-26-167-2022, 2022
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The development of high-resolution global precipitation forecasts and the lack of reliable precipitation forecasts over Africa motivates this work to evaluate the precipitation forecasts from the Global Forecast System (GFS) over the Niger river basin in Africa. The GFS forecasts, at a 15 d accumulation timescale, have an acceptable performance; however, the forecasts are highly biased. It is recommended to apply bias correction to GFS forecasts before their application.
Hadush Meresa, Conor Murphy, Rowan Fealy, and Saeed Golian
Hydrol. Earth Syst. Sci., 25, 5237–5257, https://doi.org/10.5194/hess-25-5237-2021, https://doi.org/10.5194/hess-25-5237-2021, 2021
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The assessment of future impacts of climate change is associated with a cascade of uncertainty linked to the modelling chain employed in assessing local-scale changes. Understanding and quantifying this cascade is essential for developing effective adaptation actions. We find that not only do the contributions of different sources of uncertainty vary by catchment, but that the dominant sources of uncertainty can be very different on a catchment-by-catchment basis.
Qichun Yang, Quan J. Wang, Kirsti Hakala, and Yating Tang
Hydrol. Earth Syst. Sci., 25, 4773–4788, https://doi.org/10.5194/hess-25-4773-2021, https://doi.org/10.5194/hess-25-4773-2021, 2021
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Forecasts of water losses from land surface to the air are highly valuable for water resource management and planning. In this study, we aim to fill a critical knowledge gap in the forecasting of evaporative water loss. Model experiments across Australia clearly suggest the necessity of correcting errors in input variables for more reliable water loss forecasting. We anticipate that the strategy developed in our work will benefit future water loss forecasting and lead to more skillful forecasts.
Mostafa Tarek, François Brissette, and Richard Arsenault
Hydrol. Earth Syst. Sci., 25, 3331–3350, https://doi.org/10.5194/hess-25-3331-2021, https://doi.org/10.5194/hess-25-3331-2021, 2021
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It is not known how much uncertainty the choice of a reference data set may bring to impact studies. This study compares precipitation and temperature data sets to evaluate the uncertainty contribution to the results of climate change studies. Results show that all data sets provide good streamflow simulations over the reference period. The reference data sets also provided uncertainty that was equal to or larger than that related to general circulation models over most of the catchments.
Liming Wang, Songjun Han, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 25, 375–386, https://doi.org/10.5194/hess-25-375-2021, https://doi.org/10.5194/hess-25-375-2021, 2021
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It remains unclear at which timescale the complementary principle performs best in estimating evaporation. In this study, evaporation estimation was assessed over 88 eddy covariance monitoring sites at multiple timescales. The results indicate that the generalized complementary functions perform best in estimating evaporation at the monthly scale. This study provides a reference for choosing a suitable time step for evaporation estimations in relevant studies.
Okjeong Lee, Jeonghyeon Choi, Jeongeun Won, and Sangdan Kim
Hydrol. Earth Syst. Sci., 24, 5077–5093, https://doi.org/10.5194/hess-24-5077-2020, https://doi.org/10.5194/hess-24-5077-2020, 2020
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The uncertainty of the model interpreting rainfall extremes with temperature is analyzed. The performance of the model focuses on the reliability of the output. It has been found that the selection of temperatures suitable for extreme levels plays an important role in improving model reliability. Based on this, a methodology is proposed to quantify the degree of uncertainty inherent in the change in rainfall extremes due to global warming.
Chao Gao, Martijn J. Booij, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 24, 3251–3269, https://doi.org/10.5194/hess-24-3251-2020, https://doi.org/10.5194/hess-24-3251-2020, 2020
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This paper studies the impact of climate change on high and low flows and quantifies the contribution of uncertainty sources from representative concentration pathways (RCPs), global climate models (GCMs) and internal climate variability in extreme flows. Internal climate variability was reflected in a stochastic rainfall model. The results show the importance of internal climate variability and GCM uncertainty in high flows and GCM and RCP uncertainty in low flows especially for the far future.
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%.
Xudong Zhou, Jan Polcher, Tao Yang, and Ching-Sheng Huang
Hydrol. Earth Syst. Sci., 24, 2061–2081, https://doi.org/10.5194/hess-24-2061-2020, https://doi.org/10.5194/hess-24-2061-2020, 2020
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This article proposes a new estimation approach for assessing the uncertainty with multiple datasets by fully considering all variations in temporal and spatial dimensions. Comparisons demonstrate that classical metrics may underestimate the uncertainties among datasets due to an averaging process in their algorithms. This new approach is particularly suitable for overall assessment of multiple climatic products, but can be easily applied to other spatiotemporal products in related fields.
Lionel Berthet, François Bourgin, Charles Perrin, Julie Viatgé, Renaud Marty, and Olivier Piotte
Hydrol. Earth Syst. Sci., 24, 2017–2041, https://doi.org/10.5194/hess-24-2017-2020, https://doi.org/10.5194/hess-24-2017-2020, 2020
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An increasing number of flood forecasting services assess and communicate the uncertainty associated with their forecasts. We present a crash-testing framework that evaluates the quality of hydrological forecasts in an extrapolation context. Overall, the results highlight the challenge of uncertainty quantification when forecasting high flows. They show a significant drop in reliability when forecasting high flows and considerable variability among catchments and across lead times.
Shaoning Lv, Bernd Schalge, Pablo Saavedra Garfias, and Clemens Simmer
Hydrol. Earth Syst. Sci., 24, 1957–1973, https://doi.org/10.5194/hess-24-1957-2020, https://doi.org/10.5194/hess-24-1957-2020, 2020
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Passive remote sensing of soil moisture has good potential to improve weather forecasting via data assimilation in theory. We use the virtual reality data set (VR01) to infer the impact of sampling density on soil moisture ground cal/val activity. It shows how the sampling error is growing with an increasing sampling distance for a SMOS–SMAP scale footprint in about 40 km, 9 km, and 3 km. The conclusion will help in understanding the passive remote sensing soil moisture products.
Thanh Le and Deg-Hyo Bae
Hydrol. Earth Syst. Sci., 24, 1131–1143, https://doi.org/10.5194/hess-24-1131-2020, https://doi.org/10.5194/hess-24-1131-2020, 2020
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Here we investigate the response of global evaporation to main climate modes, including the Indian Ocean Dipole (IOD), the North Atlantic Oscillation (NAO) and the El Niño–Southern Oscillation (ENSO). Our results indicate that ENSO is an important driver of evaporation for many regions, while the impacts of NAO and IOD are substantial. This study allows us to obtain insight about the predictability of evaporation and, hence, may help to improve the early-warning systems of climate extremes.
Jean-Philippe Baudouin, Michael Herzog, and Cameron A. Petrie
Hydrol. Earth Syst. Sci., 24, 427–450, https://doi.org/10.5194/hess-24-427-2020, https://doi.org/10.5194/hess-24-427-2020, 2020
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The amount of precipitation falling in the Indus River basin remains uncertain while its variability impacts 100 million inhabitants. A comparison of datasets from diverse sources (ground remote observations, model outputs) reduces this uncertainty significantly. Grounded observations offer the most reliable long-term variability but with important underestimation in winter over the mountains. By contrast, recent model outputs offer better estimations of total amount and short-term variability.
Kamal Ahmed, Dhanapala A. Sachindra, Shamsuddin Shahid, Mehmet C. Demirel, and Eun-Sung Chung
Hydrol. Earth Syst. Sci., 23, 4803–4824, https://doi.org/10.5194/hess-23-4803-2019, https://doi.org/10.5194/hess-23-4803-2019, 2019
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This study evaluated the performance of 36 CMIP5 GCMs in simulating seasonal precipitation and maximum and minimum temperature over Pakistan using spatial metrics (SPAtial EFficiency, fractions skill score, Goodman–Kruskal's lambda, Cramer's V, Mapcurves, and Kling–Gupta efficiency) for the period 1961–2005. NorESM1-M, MIROC5, BCC-CSM1-1, and ACCESS1-3 were identified as the most suitable GCMs for simulating all three climate variables over Pakistan.
Sungmin O and Ulrich Foelsche
Hydrol. Earth Syst. Sci., 23, 2863–2875, https://doi.org/10.5194/hess-23-2863-2019, https://doi.org/10.5194/hess-23-2863-2019, 2019
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We analyze heavy local rainfall to address questions regarding the spatial uncertainty due to the approximation of areal rainfall using point measurements. Ten years of rainfall data from a dense network of 150 rain gauges in southeastern Austria are employed, which permits robust examination of small-scale rainfall at various horizontal resolutions. Quantitative uncertainty information from the study can guide both data users and producers to estimate uncertainty in their own rainfall dataset.
Aifeng Lv, Bo Qu, Shaofeng Jia, and Wenbin Zhu
Hydrol. Earth Syst. Sci., 23, 883–896, https://doi.org/10.5194/hess-23-883-2019, https://doi.org/10.5194/hess-23-883-2019, 2019
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ENSO-related changes in daily precipitation regimes are currently ignored by the scientific community. We analyzed the anomalies of daily precipitation and hydrological extremes caused by different phases of ENSO events, as well as the possible driving mechanisms, to reveal the influence of ENSO on China's daily precipitation regimes. Our results provide a valuable tool for daily precipitation prediction and enable the prioritization of adaptation efforts ahead of extreme events in China.
Micheal J. Simpson and Neil I. Fox
Hydrol. Earth Syst. Sci., 22, 3375–3389, https://doi.org/10.5194/hess-22-3375-2018, https://doi.org/10.5194/hess-22-3375-2018, 2018
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Many researchers have expressed that one of the main difficulties in modeling watershed hydrology is that of obtaining continuous, widespread weather input data, especially precipitation. The overarching objective of this study was to provide a comprehensive study of three weather radars as a function of range. We found that radar-estimated precipitation was best at ranges between 100 and 150 km from the radar, with different radar parameters being superior at varying distances from the radar.
Vimal Mishra, Reepal Shah, Syed Azhar, Harsh Shah, Parth Modi, and Rohini Kumar
Hydrol. Earth Syst. Sci., 22, 2269–2284, https://doi.org/10.5194/hess-22-2269-2018, https://doi.org/10.5194/hess-22-2269-2018, 2018
Sanjib Sharma, Ridwan Siddique, Seann Reed, Peter Ahnert, Pablo Mendoza, and Alfonso Mejia
Hydrol. Earth Syst. Sci., 22, 1831–1849, https://doi.org/10.5194/hess-22-1831-2018, https://doi.org/10.5194/hess-22-1831-2018, 2018
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We investigate the relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1–7). For this purpose, we develop and implement a regional hydrologic ensemble prediction system (RHEPS). Overall analysis shows that implementing both preprocessing and postprocessing ensures the most skill improvements, but postprocessing alone can often be a competitive alternative.
Kevin Sene, Wlodek Tych, and Keith Beven
Hydrol. Earth Syst. Sci., 22, 127–141, https://doi.org/10.5194/hess-22-127-2018, https://doi.org/10.5194/hess-22-127-2018, 2018
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The theme of the paper is exploration of the potential for seasonal flow forecasting for large lakes using a range of stochastic transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes.
Fan Yang, Hui Lu, Kun Yang, Jie He, Wei Wang, Jonathon S. Wright, Chengwei Li, Menglei Han, and Yishan Li
Hydrol. Earth Syst. Sci., 21, 5805–5821, https://doi.org/10.5194/hess-21-5805-2017, https://doi.org/10.5194/hess-21-5805-2017, 2017
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In this paper, we show that CLDAS has the highest spatial and temporal resolution, and it performs best in terms of precipitation, while it overestimates the shortwave radiation. CMFD also has high resolution and its shortwave radiation data match well with the station data; its annual-mean precipitation is reliable but its monthly precipitation needs improvements. Both GLDAS and CN05.1 over mainland China need to be improved. The results can benefit researchers for forcing data selection.
Rachel Bazile, Marie-Amélie Boucher, Luc Perreault, and Robert Leconte
Hydrol. Earth Syst. Sci., 21, 5747–5762, https://doi.org/10.5194/hess-21-5747-2017, https://doi.org/10.5194/hess-21-5747-2017, 2017
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Meteorological forecasting agencies constantly work on pushing the limit of predictability farther in time. However, some end users need proof that climate model outputs are ready to be implemented operationally. We show that bias correction is crucial for the use of ECMWF System4 forecasts for the studied area and there is a potential for the use of 1-month-ahead forecasts. Beyond this, forecast performance is equivalent to using past climatology series as inputs to the hydrological model.
Judith Eeckman, Pierre Chevallier, Aaron Boone, Luc Neppel, Anneke De Rouw, Francois Delclaux, and Devesh Koirala
Hydrol. Earth Syst. Sci., 21, 4879–4893, https://doi.org/10.5194/hess-21-4879-2017, https://doi.org/10.5194/hess-21-4879-2017, 2017
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The central part of the Himalayan Range presents tremendous heterogeneity in terms of topography and climatology, but the representation of hydro-climatic processes for Himalayan catchments is limited due to a lack of knowledge in such poorly instrumented environments. The proposed approach is to characterize the effect of altitude on precipitation by considering ensembles of acceptable altitudinal factors. Ensembles of acceptable values for the components of the water cycle are then provided.
Jefferson S. Wong, Saman Razavi, Barrie R. Bonsal, Howard S. Wheater, and Zilefac E. Asong
Hydrol. Earth Syst. Sci., 21, 2163–2185, https://doi.org/10.5194/hess-21-2163-2017, https://doi.org/10.5194/hess-21-2163-2017, 2017
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This study was conducted to quantify the spatial and temporal variability of the errors associated with various gridded precipitation products in Canada. Overall, WFDEI [GPCC] and CaPA performed best with respect to different performance measures, followed by ANUSPLIN and WEDEI [CRU]. Princeton and NARR demonstrated the lowest quality. Comparing the climate model-simulated products, PCIC ensembles generally performed better than NA-CORDEX ensembles in terms of reliability in four seasons.
Danlu Guo, Seth Westra, and Holger R. Maier
Hydrol. Earth Syst. Sci., 21, 2107–2126, https://doi.org/10.5194/hess-21-2107-2017, https://doi.org/10.5194/hess-21-2107-2017, 2017
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This study assessed the impact of baseline climate conditions on the sensitivity of potential evapotranspiration (PET) to a large range of plausible changes in temperature, relative humidity, solar radiation and wind speed at 30 Australian locations. Around 2-fold greater PET changes were observed at cool and humid locations compared to others, indicating potential for elevated water loss in the future. These impacts can be useful to inform the selection of PET models under a changing climate.
Vojtěch Svoboda, Martin Hanel, Petr Máca, and Jan Kyselý
Hydrol. Earth Syst. Sci., 21, 963–980, https://doi.org/10.5194/hess-21-963-2017, https://doi.org/10.5194/hess-21-963-2017, 2017
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The study presents validation of precipitation events as simulated by an ensemble of regional climate models for the Czech Republic. While the number of events per season, seasonal total precipitation due to heavy events and the distribution of rainfall depths are simulated relatively well, event maximum precipitation and event intensity are strongly underestimated. This underestimation cannot be explained by scale mismatch between point observations and area average (climate model simulations).
Martin Hanel, Petr Máca, Petr Bašta, Radek Vlnas, and Pavel Pech
Hydrol. Earth Syst. Sci., 20, 4307–4322, https://doi.org/10.5194/hess-20-4307-2016, https://doi.org/10.5194/hess-20-4307-2016, 2016
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The paper is focused on assessment of the contribution of various sources of uncertainty to the estimated rainfall erosivity factor. It is shown that the rainfall erosivity factor can be estimated with reasonable precision even from records shorter than recommended, provided good spatial coverage and reasonable explanatory variables are available. The research was done as an update of the R factor estimates for the Czech Republic, which were later used for climate change assessment.
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.
Louise Arnal, Maria-Helena Ramos, Erin Coughlan de Perez, Hannah Louise Cloke, Elisabeth Stephens, Fredrik Wetterhall, Schalk Jan van Andel, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3109–3128, https://doi.org/10.5194/hess-20-3109-2016, https://doi.org/10.5194/hess-20-3109-2016, 2016
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Forecasts are produced as probabilities of occurrence of specific events, which is both an added value and a challenge for users. This paper presents a game on flood protection, "How much are you prepared to pay for a forecast?", which investigated how users perceive the value of forecasts and are willing to pay for them when making decisions. It shows that users are mainly influenced by the perceived quality of the forecasts, their need for the information and their degree of risk tolerance.
K. Sunilkumar, T. Narayana Rao, and S. Satheeshkumar
Hydrol. Earth Syst. Sci., 20, 1719–1735, https://doi.org/10.5194/hess-20-1719-2016, https://doi.org/10.5194/hess-20-1719-2016, 2016
Vincent Roth and Tatenda Lemann
Hydrol. Earth Syst. Sci., 20, 921–934, https://doi.org/10.5194/hess-20-921-2016, https://doi.org/10.5194/hess-20-921-2016, 2016
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The Soil and Water Assessment Tool (SWAT) suggests using the CFSR global rainfall data for modelling discharge and soil erosion in data-scarce parts of the world. These data are freely available and ready to use for SWAT modelling. However, simulations with the CFSR data in the Ethiopian Highlands were unable to represent the specific regional climates and showed high discrepancies. This article compares SWAT simulations with conventional rainfall data and with CFSR rainfall data.
J. Kim and S. K. Park
Hydrol. Earth Syst. Sci., 20, 651–658, https://doi.org/10.5194/hess-20-651-2016, https://doi.org/10.5194/hess-20-651-2016, 2016
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This study examined the uncertainty in climatological precipitation in East Asia, calculated from five gridded analysis data sets based on in situ rain gauge observations from 1980 to 2007. It is found that the regions of large uncertainties are typically lightly populated and are characterized by severe terrain and/or very high elevations. Thus, care must be taken in using long-term trends calculated from gridded precipitation analysis data for climate studies over such regions in East Asia.
M. F. Rios Gaona, A. Overeem, H. Leijnse, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 19, 3571–3584, https://doi.org/10.5194/hess-19-3571-2015, https://doi.org/10.5194/hess-19-3571-2015, 2015
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Commercial cellular networks are built for telecommunication purposes. These kinds of networks have lately been used to obtain rainfall maps at country-wide scales. From previous studies, we now quantify the uncertainties associated with such maps. To do so, we divided the sources or error into two categories: from microwave link measurements and from mapping. It was found that the former is the source that contributes the most to the overall error in rainfall maps from microwave link network.
S. H. Alemohammad, K. A. McColl, A. G. Konings, D. Entekhabi, and A. Stoffelen
Hydrol. Earth Syst. Sci., 19, 3489–3503, https://doi.org/10.5194/hess-19-3489-2015, https://doi.org/10.5194/hess-19-3489-2015, 2015
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This paper introduces a new variant of the triple collocation technique with multiplicative error model. The method is applied, for the first time, to precipitation products across the central part of continental USA. Results show distinctive patterns of error variance in each product that are estimated without a priori assumption of any of the error distributions. The correlation coefficients between each product and the truth are also estimated, which provides another performance perspective.
M. S. Raleigh, J. D. Lundquist, and M. P. Clark
Hydrol. Earth Syst. Sci., 19, 3153–3179, https://doi.org/10.5194/hess-19-3153-2015, https://doi.org/10.5194/hess-19-3153-2015, 2015
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A sensitivity analysis is used to examine how error characteristics (type, distributions, and magnitudes) in meteorological forcing data impact outputs from a physics-based snow model in four climates. Bias and error magnitudes were key factors in model sensitivity and precipitation bias often dominated. However, the relative importance of forcings depended somewhat on the selected model output. Forcing uncertainty was comparable to model structural uncertainty as found in other studies.
S. Garrigues, A. Olioso, J. C. Calvet, E. Martin, S. Lafont, S. Moulin, A. Chanzy, O. Marloie, S. Buis, V. Desfonds, N. Bertrand, and D. Renard
Hydrol. Earth Syst. Sci., 19, 3109–3131, https://doi.org/10.5194/hess-19-3109-2015, https://doi.org/10.5194/hess-19-3109-2015, 2015
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Land surface model simulations of evapotranspiration are assessed over a 12-year Mediterranean crop succession. Evapotranspiration mainly results from soil evaporation when it is simulated over a Mediterranean crop succession. This leads to a high sensitivity to the soil parameters. Errors on soil hydraulic properties can lead to a large bias in cumulative evapotranspiration over a long period of time. Accounting for uncertainties in soil properties is essential for land surface modelling.
W. Gong, Q. Duan, J. Li, C. Wang, Z. Di, Y. Dai, A. Ye, and C. Miao
Hydrol. Earth Syst. Sci., 19, 2409–2425, https://doi.org/10.5194/hess-19-2409-2015, https://doi.org/10.5194/hess-19-2409-2015, 2015
S. O. Los
Hydrol. Earth Syst. Sci., 19, 1713–1725, https://doi.org/10.5194/hess-19-1713-2015, https://doi.org/10.5194/hess-19-1713-2015, 2015
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The study evaluates annual precipitation (largely rainfall) amounts for the tropics and subtropics; precipitation was obtained from ground observations, satellite observations and numerical weather forecasting models.
- Annual precipitation amounts from ground and satellite observations were the most realistic.
- Newer weather forecasting models better predicted annual precipitation than older models.
- Weather forecasting models predicted inaccurate precipitation amounts for Africa.
A. Kann, I. Meirold-Mautner, F. Schmid, G. Kirchengast, J. Fuchsberger, V. Meyer, L. Tüchler, and B. Bica
Hydrol. Earth Syst. Sci., 19, 1547–1559, https://doi.org/10.5194/hess-19-1547-2015, https://doi.org/10.5194/hess-19-1547-2015, 2015
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The paper introduces a high resolution precipitation analysis system which operates on 1 km x 1 km resolution with high frequency updates of 5 minutes. The ability of such a system to adequately assess the convective precipitation distribution is evaluated by means of an independant, high resolution station network. This dense station network allows for a thorough evaluation of the analyses under different convective situations and of the representativeness error of raingaue measurements.
C. H. Wu, G. R. Huang, and H. J. Yu
Hydrol. Earth Syst. Sci., 19, 1385–1399, https://doi.org/10.5194/hess-19-1385-2015, https://doi.org/10.5194/hess-19-1385-2015, 2015
T. Antofie, G. Naumann, J. Spinoni, and J. Vogt
Hydrol. Earth Syst. Sci., 19, 177–193, https://doi.org/10.5194/hess-19-177-2015, https://doi.org/10.5194/hess-19-177-2015, 2015
P. López López, J. S. Verkade, A. H. Weerts, and D. P. Solomatine
Hydrol. Earth Syst. Sci., 18, 3411–3428, https://doi.org/10.5194/hess-18-3411-2014, https://doi.org/10.5194/hess-18-3411-2014, 2014
G. Naumann, E. Dutra, P. Barbosa, F. Pappenberger, F. Wetterhall, and J. V. Vogt
Hydrol. Earth Syst. Sci., 18, 1625–1640, https://doi.org/10.5194/hess-18-1625-2014, https://doi.org/10.5194/hess-18-1625-2014, 2014
K. Liechti, L. Panziera, U. Germann, and M. Zappa
Hydrol. Earth Syst. Sci., 17, 3853–3869, https://doi.org/10.5194/hess-17-3853-2013, https://doi.org/10.5194/hess-17-3853-2013, 2013
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Short summary
We present the results of a large visual inspection campaign of 674 streamflow time series in France. The objective was to detect non-natural records resulting from instrument failure or anthropogenic influences, such as hydroelectric power generation or reservoir management. We conclude that the identification of flaws in flow time series is highly dependent on the objectives and skills of individual evaluators, and we raise the need for better practices for data cleaning.
We present the results of a large visual inspection campaign of 674 streamflow time series in...
