Articles | Volume 27, issue 1
https://doi.org/10.5194/hess-27-191-2023
© 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-27-191-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Jan 2023
Research article |
| 10 Jan 2023
| 10 Jan 2023
Impact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchment
Aniket Gupta
CORRESPONDING AUTHOR
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Alix Reverdy
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Jean-Martial Cohard
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Basile Hector
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Marc Descloitres
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Jean-Pierre Vandervaere
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Catherine Coulaud
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Romain Biron
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Lucie Liger
Univ. Grenoble Alpes, CNRS, Lautaret Garden, 38000, Grenoble, France
Reed Maxwell
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
Jean-Gabriel Valay
Univ. Grenoble Alpes, CNRS, Lautaret Garden, 38000, Grenoble, France
Didier Voisin
Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, France
Related authors
No articles found.
Benjamin D. West, Reed M. Maxwell, and Laura E. Condon
EGUsphere, https://doi.org/10.5194/egusphere-2024-965, https://doi.org/10.5194/egusphere-2024-965, 2024
Short summary
Short summary
This article describes the addition of reservoirs to the hydrologic model, ParFlow. ParFlow is particularly good at helping us understand some of the broader drivers behind different parts of the water cycle. By having reservoirs in such a model we hope to be better able to understand both our impacts on the environment, and how to adjust our management of reservoirs to changing conditions.
Max Berkelhammer, Gerald F. Page, Frank Zurek, Christopher Still, Mariah S. Carbone, William Talavera, Laura Hildebrand, James Byron, Kyle Inthabandith, Angellica Kucinski, Melissa Carter, Kelsey Foss, Wendy Brown, Rosemary W. H. Carroll, Austin Simonpietri, Marshall Worsham, Ian Breckheimer, Anna Ryken, Reed Maxwell, David Gochis, Mark Raleigh, Eric Small, and Kenneth H. Williams
EGUsphere, https://doi.org/10.5194/egusphere-2023-3063, https://doi.org/10.5194/egusphere-2023-3063, 2024
Short summary
Short summary
Warming in montane systems is affecting the amount of snowmelt inputs. This will affect subalpine forests globally that rely on spring snowmelt to support their water demands. We use a network of sensors across in the Upper Colorado Basin to show that changing spring primarily impacts dense forest stands that have high peak water demands. On the other hand, open forest stands show a higher reliance on summer rain and were minimally sensitive to even historically low snow conditions like 2019.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-264, https://doi.org/10.5194/hess-2023-264, 2024
Preprint under review for HESS
Short summary
Short summary
Large-scale hydrologic a needed tool to explore complex watershed processes and how they may evolve under a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration with a set of experiments in the Upper Colorado River Basin.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
Short summary
Short summary
Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
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 under review for HESS
Short summary
Short summary
The Alpine region is strongly affected by torrential floods, sometimes leading to severe negative impacts on society, economy, and the environment. Understanding such natural hazards and their drivers is essential to mitigate related risks. In this article we study the atmospheric conditions at the origin of damaging torrential events in the Northern French Alps over the long run, using a database of reported occurrence of damaging torrential flooding in the Grenoble conurbation since 1851.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
Short summary
Short summary
Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
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
Manuscript not accepted for further review
Short summary
Short summary
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.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-345, https://doi.org/10.5194/hess-2022-345, 2022
Publication in HESS not foreseen
Short summary
Short summary
As the stress on water resources from climate change grows, we need models that represent water processes at the scale of counties, states, and even countries in order to make viable predictions about things will change. While such models are powerful, they can be cumbersome to deal with because they are so large. This research explores a novel way of increasing the efficiency of large-scale hydrologic models using an approach called Simulation-Based Inference.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
Short summary
Short summary
Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Mary M. F. O'Neill, Danielle T. Tijerina, Laura E. Condon, and Reed M. Maxwell
Geosci. Model Dev., 14, 7223–7254, https://doi.org/10.5194/gmd-14-7223-2021, https://doi.org/10.5194/gmd-14-7223-2021, 2021
Short summary
Short summary
Modeling the hydrologic cycle at high resolution and at large spatial scales is an incredible opportunity and challenge for hydrologists. In this paper, we present the results of a high-resolution hydrologic simulation configured over the contiguous United States. We discuss simulated water fluxes through groundwater, soil, plants, and over land, and we compare model results to in situ observations and satellite products in order to build confidence and guide future model development.
Jun Zhang, Laura E. Condon, Hoang Tran, and Reed M. Maxwell
Earth Syst. Sci. Data, 13, 3263–3279, https://doi.org/10.5194/essd-13-3263-2021, https://doi.org/10.5194/essd-13-3263-2021, 2021
Short summary
Short summary
Existing national topographic datasets for the US may not be compatible with gridded hydrologic models. A national topographic dataset developed to support physically based hydrologic models at 1 km and 250 m over the contiguous US is provided. We used a Priority Flood algorithm to ensure hydrologically consistent drainage networks and evaluated the performance with an integrated hydrologic model. Datasets and scripts are available for direct data usage or modification of processing as desired.
Jaber Rahimi, Expedit Evariste Ago, Augustine Ayantunde, Sina Berger, Jan Bogaert, Klaus Butterbach-Bahl, Bernard Cappelaere, Jean-Martial Cohard, Jérôme Demarty, Abdoul Aziz Diouf, Ulrike Falk, Edwin Haas, Pierre Hiernaux, David Kraus, Olivier Roupsard, Clemens Scheer, Amit Kumar Srivastava, Torbern Tagesson, and Rüdiger Grote
Geosci. Model Dev., 14, 3789–3812, https://doi.org/10.5194/gmd-14-3789-2021, https://doi.org/10.5194/gmd-14-3789-2021, 2021
Short summary
Short summary
West African Sahelian and Sudanian ecosystems are important regions for global carbon exchange, and they provide valuable food and fodder resources. Therefore, we simulated net ecosystem exchange and aboveground biomass of typical ecosystems in this region with an improved process-based biogeochemical model, LandscapeDNDC. Carbon stocks and exchange rates were particularly correlated with the abundance of trees. Grass and crop yields increased under humid climatic conditions.
François Tuzet, Marie Dumont, Ghislain Picard, Maxim Lamare, Didier Voisin, Pierre Nabat, Mathieu Lafaysse, Fanny Larue, Jesus Revuelto, and Laurent Arnaud
The Cryosphere, 14, 4553–4579, https://doi.org/10.5194/tc-14-4553-2020, https://doi.org/10.5194/tc-14-4553-2020, 2020
Short summary
Short summary
This study presents a field dataset collected over 30 d from two snow seasons at a Col du Lautaret site (French Alps). The dataset compares different measurements or estimates of light-absorbing particle (LAP) concentrations in snow, highlighting a gap in the current understanding of the measurement of these quantities. An ensemble snowpack model is then evaluated for this dataset estimating that LAPs shorten each snow season by around 10 d despite contrasting meteorological conditions.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-378, https://doi.org/10.5194/hess-2020-378, 2020
Revised manuscript not accepted
Stephen R. Maples, Laura Foglia, Graham E. Fogg, and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 24, 2437–2456, https://doi.org/10.5194/hess-24-2437-2020, https://doi.org/10.5194/hess-24-2437-2020, 2020
Short summary
Short summary
In this study, we use a combination of local- and global-sensitivity analyses to evaluate the relative importance of (1) the configuration of subsurface alluvial geology and (2) the hydraulic properties of geologic facies on recharge processes. Results show that there is a large variation of recharge rates possible in a typical alluvial aquifer system and that the configuration proportion of sand and gravel deposits in the subsurface have a large impact on recharge rates.
Benjamin N. O. Kuffour, Nicholas B. Engdahl, Carol S. Woodward, Laura E. Condon, Stefan Kollet, and Reed M. Maxwell
Geosci. Model Dev., 13, 1373–1397, https://doi.org/10.5194/gmd-13-1373-2020, https://doi.org/10.5194/gmd-13-1373-2020, 2020
Short summary
Short summary
Integrated hydrologic models (IHMs) were developed in order to allow for more accurate simulations of real-world ecohydrologic conditions. Many IHMs exist, and the literature can be dense, so it is often difficult to understand what a specific model can and cannot do. We provide a review of the current core capabilities, solution techniques, communication structure with other models, some limitations, and potential future improvements of one such open-source integrated model called ParFlow.
Pascal Hagenmuller, Frederic Flin, Marie Dumont, François Tuzet, Isabel Peinke, Philippe Lapalus, Anne Dufour, Jacques Roulle, Laurent Pézard, Didier Voisin, Edward Ando, Sabine Rolland du Roscoat, and Pascal Charrier
The Cryosphere, 13, 2345–2359, https://doi.org/10.5194/tc-13-2345-2019, https://doi.org/10.5194/tc-13-2345-2019, 2019
Short summary
Short summary
Light–absorbing particles (LAPs, e.g. dust or black carbon) in snow are a potent climate forcing agent. Their presence darkens the snow surface and leads to higher solar energy absorption. Several studies have quantified this radiative impact by assuming that LAPs were motionless in dry snow, without any clear evidence of this assumption. Using time–lapse X–ray tomography, we show that temperature gradient metamorphism of snow induces downward motion of LAPs, leading to self–cleaning of snow.
Francois Tuzet, Marie Dumont, Laurent Arnaud, Didier Voisin, Maxim Lamare, Fanny Larue, Jesus Revuelto, and Ghislain Picard
The Cryosphere, 13, 2169–2187, https://doi.org/10.5194/tc-13-2169-2019, https://doi.org/10.5194/tc-13-2169-2019, 2019
Short summary
Short summary
Here we present a novel method to estimate the impurity content (e.g. black carbon or mineral dust) in Alpine snow based on measurements of light extinction profiles. This method is proposed as an alternative to chemical measurements, allowing rapid retrievals of vertical concentrations of impurities in the snowpack. In addition, the results provide a better understanding of the impact of impurities on visible light extinction in snow.
Annette Hein, Laura Condon, and Reed Maxwell
Hydrol. Earth Syst. Sci., 23, 1931–1950, https://doi.org/10.5194/hess-23-1931-2019, https://doi.org/10.5194/hess-23-1931-2019, 2019
Short summary
Short summary
Drought is a natural disaster that can result from changes to temperature, precipitation and/or vegetation. Here we apply a
high-resolution computer model to explore the relative importance of each factor on the North American High Plains, one of the most important agricultural regions of the USA. Decreased precipitation caused larger changes in hydrologic variables (evapotranspiration, soil moisture, stream flow and water table levels) than increased temperature or disturbed vegetation did.
Magdalena Uber, Jean-Pierre Vandervaere, Isabella Zin, Isabelle Braud, Maik Heistermann, Cédric Legoût, Gilles Molinié, and Guillaume Nord
Hydrol. Earth Syst. Sci., 22, 6127–6146, https://doi.org/10.5194/hess-22-6127-2018, https://doi.org/10.5194/hess-22-6127-2018, 2018
Short summary
Short summary
We investigate how rivers in a flash-flood-prone region in southern France respond to rainfall depending on initial soil moisture. Therefore, high-resolution data of rainfall, river discharge and soil moisture were used. We find that during dry initial conditions, the rivers hardly respond even for heavy rain events, but for wet initial conditions, the response remains unpredictable: for some rain events almost all rainfall is transformed to discharge, whereas this is not the case for others.
Basile Hector, Jean-Martial Cohard, Luc Séguis, Sylvie Galle, and Christophe Peugeot
Hydrol. Earth Syst. Sci., 22, 5867–5888, https://doi.org/10.5194/hess-22-5867-2018, https://doi.org/10.5194/hess-22-5867-2018, 2018
Short summary
Short summary
The hydrological functioning of western African headwater wetlands remains poorly understood, despite their potential for small-scale farming and their role in streamflow production. We found that land cover changes significantly affect water budgets, and pedo-geological features control dry season baseflow. These are the results of virtual experiments with a physically based critical zone model evaluated against streamflow, evapotranspiration, soil moisture, water table and water storage data.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
Short summary
Short summary
This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Francois Tuzet, Marie Dumont, Matthieu Lafaysse, Ghislain Picard, Laurent Arnaud, Didier Voisin, Yves Lejeune, Luc Charrois, Pierre Nabat, and Samuel Morin
The Cryosphere, 11, 2633–2653, https://doi.org/10.5194/tc-11-2633-2017, https://doi.org/10.5194/tc-11-2633-2017, 2017
Short summary
Short summary
Light-absorbing impurities deposited on snow, such as soot or dust, strongly modify its evolution. We implemented impurity deposition and evolution in a detailed snowpack model, thereby expanding the reach of such models into addressing the subtle interplays between snow physics and impurities' optical properties. Model results were evaluated based on innovative field observations at an Alpine site. This allows future investigations in the fields of climate, hydrology and avalanche prediction.
Marie Dumont, Laurent Arnaud, Ghislain Picard, Quentin Libois, Yves Lejeune, Pierre Nabat, Didier Voisin, and Samuel Morin
The Cryosphere, 11, 1091–1110, https://doi.org/10.5194/tc-11-1091-2017, https://doi.org/10.5194/tc-11-1091-2017, 2017
Short summary
Short summary
Snow spectral albedo in the visible/near-infrared range has been continuously measured during a winter season at Col de Porte alpine site (French Alps; 45.30° N, 5.77°E; 1325 m a.s.l.). This study highlights that the variations of spectral albedo can be successfully explained by variations of the following snow surface variables: snow-specific surface area, effective light-absorbing impurities content, presence of liquid water and slope.
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
Short summary
Short summary
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.
Laura E. Condon and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 21, 1117–1135, https://doi.org/10.5194/hess-21-1117-2017, https://doi.org/10.5194/hess-21-1117-2017, 2017
Short summary
Short summary
We evaluate the impact of groundwater–surface water exchanges on the fraction of precipitation that leaves a watershed as either surface runoff or evapotranspiration. Results show that groundwater storage can systematically influence watershed behavior at the land surface. This is an important finding because most studies of tradeoffs between runoff and evapotranspiration assume that watersheds are in a steady-state condition where there are no net exchanges between the surface and subsurface.
James M. Gilbert and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 21, 923–947, https://doi.org/10.5194/hess-21-923-2017, https://doi.org/10.5194/hess-21-923-2017, 2017
Short summary
Short summary
Understanding how groundwater and streamflow interact over large areas is a challenge. In this study we use a computer simulation that calculates water movement and storage at the land surface and in the subsurface within California's San Joaquin River basin to analyze different parts of the watershed. Results show that the mountains may be an important source of groundwater to the Central Valley while differences in relative speed of groundwater and river flow affect their connection patterns.
Wolfgang Kurtz, Guowei He, Stefan J. Kollet, Reed M. Maxwell, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 9, 1341–1360, https://doi.org/10.5194/gmd-9-1341-2016, https://doi.org/10.5194/gmd-9-1341-2016, 2016
Short summary
Short summary
This paper describes the development of a modular data assimilation (DA) system for the integrated Earth system model TerrSysMP with the help of the PDAF data assimilation library.
Currently, pressure and soil moisture data can be used to update model states and parameters in the subsurface compartment of TerrSysMP.
Results from an idealized twin experiment show that the developed DA system provides a good parallel performance and is also applicable for high-resolution modelling problems.
R. M. Maxwell, L. E. Condon, and S. J. Kollet
Geosci. Model Dev., 8, 923–937, https://doi.org/10.5194/gmd-8-923-2015, https://doi.org/10.5194/gmd-8-923-2015, 2015
Short summary
Short summary
A model that simulates groundwater and surface water flow has been developed for the major river basins of the continental United States. Fundamental data sets provide input to the model resulting in a natural organization of stream networks and groundwater flow that is compared to observations of surface water and groundwater. Model results show relationships between flow and area that are moderated by aridity and represent an important step toward integrated hydrological prediction.
I. El Haddad, B. D'Anna, B. Temime-Roussel, M. Nicolas, A. Boreave, O. Favez, D. Voisin, J. Sciare, C. George, J.-L. Jaffrezo, H. Wortham, and N. Marchand
Atmos. Chem. Phys., 13, 7875–7894, https://doi.org/10.5194/acp-13-7875-2013, https://doi.org/10.5194/acp-13-7875-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Toward interpretable LSTM-based modeling of hydrological systems
Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model
What controls the tail behaviour of flood series: rainfall or runoff generation?
Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California
Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
Impacts of climate and land-surface change on catchment evapotranspiration and runoff from 1951–2020 in Saxony, Germany
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes
Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling
Modelling flood frequency and magnitude in a glacially conditioned, heterogeneous landscape: testing the importance of land cover and land use
Enhancing LSTM-based streamflow prediction with a spatially distributed approach
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
Altitudinal Control of Isotopic Composition and Application in Understanding Hydrologic Processes in the mid Merced River Catchment, Sierra Nevada, California, USA
Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach
To what extent does river routing matter in hydrological modeling?
Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins
An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
airGRteaching: an open-source tool for teaching hydrological modeling with R
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 Large Ensemble
To What Extent Do Extreme Storm Events Change Future Flood Hazards?
Stable water isotopes and tritium tracers tell the same tale: no evidence for underestimation of catchment transit times inferred by stable isotopes in StorAge Selection (SAS)-function models
Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation
Changes in Mediterranean flood processes and seasonality
Metamorphic Testing of Machine Learning and Conceptual Hydrologic Models
Can the combining of wetlands with reservoir operation reduce the risk of future floods and droughts?
Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado
When best is the enemy of good – critical evaluation of performance criteria in hydrological models
The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment
Producing reliable hydrologic scenarios from raw climate model outputs without resorting to meteorological observations
Afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
Using normalised difference infrared index patterns to constrain semi-distributed rainfall–runoff models in tropical nested catchments
Revisiting the hydrological basis of the Budyko framework with the principle of hydrologically similar groups
Reconstructing five decades of sediment export from two glacierized high-alpine catchments in Tyrol, Austria, using nonparametric regression
Water and energy budgets over hydrological basins on short and long timescales
Hydrological response to climate change and human activities in the Three-River Source Region
Incorporating experimentally derived streamflow contributions into model parameterization to improve discharge prediction
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
Short summary
Short summary
Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
Short summary
Short summary
We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
Short summary
Short summary
Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
Short summary
Short summary
We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
Short summary
Short summary
Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
Short summary
Short summary
This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
Short summary
Short summary
To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
Short summary
Short summary
Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
Short summary
Short summary
Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
Short summary
Short summary
Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
Short summary
Short summary
In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
Short summary
Short summary
In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
Short summary
Short summary
This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
Short summary
Short summary
Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
Short summary
Short summary
We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
Short summary
Short summary
Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-6, https://doi.org/10.5194/hess-2024-6, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Climate and land-surface conditions influence the availability of fresh water resources. Their impact is quantified with data of 71 catchments in Saxony/Germany, for which distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff, that has not been seen in the observation records before.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
Short summary
Short summary
How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
Short summary
Short summary
Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
Short summary
Short summary
We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
Short summary
Short summary
Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
Short summary
Short summary
Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
Short summary
Short summary
Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Pamela E. Tetford and Joseph R. Desloges
Hydrol. Earth Syst. Sci., 27, 3977–3998, https://doi.org/10.5194/hess-27-3977-2023, https://doi.org/10.5194/hess-27-3977-2023, 2023
Short summary
Short summary
An efficient regional flood frequency model relates drainage area to discharge, with a major assumption of similar basin conditions. In a landscape with variable glacial deposits and land use, we characterize varying hydrological function using 28 explanatory variables. We demonstrate that (1) a heterogeneous landscape requires objective model selection criteria to optimize the fit of flow data, and (2) incorporating land use as a predictor variable improves the drainage area to discharge model.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-237, https://doi.org/10.5194/hess-2023-237, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
It is challenging to incorporate the spatial distribution information of input variables when implementing LSTM models for streamflow prediction. This paper presents a novel hybrid modeling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise in predicting streamflow at large ungauged basin.
Ana Ramos Oliveira, Tiago Brito Ramos, Lígia Pinto, and Ramiro Neves
Hydrol. Earth Syst. Sci., 27, 3875–3893, https://doi.org/10.5194/hess-27-3875-2023, https://doi.org/10.5194/hess-27-3875-2023, 2023
Short summary
Short summary
This paper intends to demonstrate the adequacy of a hybrid solution to overcome the difficulties related to the incorporation of human behavior when modeling hydrological processes. Two models were implemented, one to estimate the outflow of a reservoir and the other to simulate the hydrological processes of the watershed. With both models feeding each other, results show that the proposed approach significantly improved the streamflow estimation downstream of the reservoir.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-230, https://doi.org/10.5194/hess-2023-230, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of water falls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow-rain transition (2,000–2,500m) and very vulnerable to shift in the snow-rain ratio.
Zhihua He, Kevin Shook, Christopher Spence, John W. Pomeroy, and Colin Whitfield
Hydrol. Earth Syst. Sci., 27, 3525–3546, https://doi.org/10.5194/hess-27-3525-2023, https://doi.org/10.5194/hess-27-3525-2023, 2023
Short summary
Short summary
This study evaluated the impacts of climate change on snowmelt, soil moisture, and streamflow over the Canadian Prairies. The entire prairie region was divided into seven basin types. We found strong variations of hydrological sensitivity to precipitation and temperature changes in different land covers and basins, which suggests that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the prairies.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, https://doi.org/10.5194/hess-27-3505-2023, 2023
Short summary
Short summary
This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
Dung Trung Vu, Thanh Duc Dang, Francesca Pianosi, and Stefano Galelli
Hydrol. Earth Syst. Sci., 27, 3485–3504, https://doi.org/10.5194/hess-27-3485-2023, https://doi.org/10.5194/hess-27-3485-2023, 2023
Short summary
Short summary
The calibration of hydrological models over extensive spatial domains is often challenged by the lack of data on river discharge and the operations of hydraulic infrastructures. Here, we use satellite data to address the lack of data that could unintentionally bias the calibration process. Our study is underpinned by a computational framework that quantifies this bias and provides a safe approach to the calibration of models in poorly gauged and heavily regulated basins.
Francesco Fatone, Bartosz Szeląg, Przemysław Kowal, Arthur McGarity, Adam Kiczko, Grzegorz Wałek, Ewa Wojciechowska, Michał Stachura, and Nicolas Caradot
Hydrol. Earth Syst. Sci., 27, 3329–3349, https://doi.org/10.5194/hess-27-3329-2023, https://doi.org/10.5194/hess-27-3329-2023, 2023
Short summary
Short summary
A novel methodology for the development of a stormwater network performance simulator including advanced risk assessment was proposed. The applied tool enables the analysis of the influence of spatial variability in catchment and stormwater network characteristics on the relation between (SWMM) model parameters and specific flood volume, as an alternative approach to mechanistic models. The proposed method can be used at the stage of catchment model development and spatial planning management.
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
Short summary
Short summary
Teaching hydrological modeling is an important, but difficult, matter. It requires appropriate tools and teaching material. In this article, we present the airGRteaching package, which is an open-source software tool relying on widely used hydrological models. This tool proposes an interface and numerous hydrological modeling exercises representing a wide range of hydrological applications. We show how this tool can be applied to simple but real-life cases.
Florian Willkofer, Raul Roger Wood, and Ralf Ludwig
EGUsphere, https://doi.org/10.5194/egusphere-2023-2019, https://doi.org/10.5194/egusphere-2023-2019, 2023
Short summary
Short summary
Severe flood events pose threat to riverine areas, yet robust estimates about the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses and benefits from data from a RCM SMILE to drive a high-resolution hydrological model for 98 catchments of the Hydrological Bavaria to exploit the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
EGUsphere, https://doi.org/10.5194/egusphere-2023-1969, https://doi.org/10.5194/egusphere-2023-1969, 2023
Short summary
Short summary
Due to climate change, flooding is expected to become more frequent globally in the coming decades. Locally, storm-induced channel geometry changes can drastically affect flood hazards, yet rivers are mostly treated as static elements in flood studies. This study tried to gain an understanding of the effects of major storm events on future flood hazards, promoting a framework for incorporating channel conveyance adjustments into flood hazard assessment.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, https://doi.org/10.5194/hess-27-3083-2023, 2023
Short summary
Short summary
This study shows that previously reported underestimations of water ages are most likely not due to the use of seasonally variable tracers. Rather, these underestimations can be largely attributed to the choices of model approaches which rely on assumptions not frequently met in catchment hydrology. We therefore strongly advocate avoiding the use of this model type in combination with seasonally variable tracers and instead adopting StorAge Selection (SAS)-based or comparable model formulations.
Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz
Hydrol. Earth Syst. Sci., 27, 2989–3004, https://doi.org/10.5194/hess-27-2989-2023, https://doi.org/10.5194/hess-27-2989-2023, 2023
Short summary
Short summary
We analyzed the uncertainty of the water transit time distribution (TTD) arising from model input (interpolated tracer data) and structure (StorAge Selection, SAS, functions). We found that uncertainty was mainly associated with temporal interpolation, choice of SAS function, nonspatial interpolation, and low-flow conditions. It is important to characterize the specific uncertainty sources and their combined effects on TTD, as this has relevant implications for both water quantity and quality.
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
Short summary
Short summary
Mediterranean floods are causing major damage, and recent studies have shown that, despite the increase in intense rainfall, there has been no increase in river floods. This study reveals that the seasonality of floods changed in the Mediterranean Basin during 1959–2021. There was also an increased frequency of floods linked to short episodes of intense rain, associated with a decrease in soil moisture. These changes need to be taken into consideration to adapt flood warning systems.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-168, https://doi.org/10.5194/hess-2023-168, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine-learning hydrological models. We found that machine-learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Yanfeng Wu, Jingxuan Sun, Boting Hu, Y. Jun Xu, Alain N. Rousseau, and Guangxin Zhang
Hydrol. Earth Syst. Sci., 27, 2725–2745, https://doi.org/10.5194/hess-27-2725-2023, https://doi.org/10.5194/hess-27-2725-2023, 2023
Short summary
Short summary
Reservoirs and wetlands are important regulators of watershed hydrology, which should be considered when projecting floods and droughts. We first coupled wetlands and reservoir operations into a semi-spatially-explicit hydrological model and then applied it in a case study involving a large river basin in northeast China. We found that, overall, the risk of future floods and droughts will increase further even under the combined influence of reservoirs and wetlands.
Peishi Jiang, Pin Shuai, Alexander Sun, Maruti K. Mudunuru, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 27, 2621–2644, https://doi.org/10.5194/hess-27-2621-2023, https://doi.org/10.5194/hess-27-2621-2023, 2023
Short summary
Short summary
We developed a novel deep learning approach to estimate the parameters of a computationally expensive hydrological model on only a few hundred realizations. Our approach leverages the knowledge obtained by data-driven analysis to guide the design of the deep learning model used for parameter estimation. We demonstrate this approach by calibrating a state-of-the-art hydrological model against streamflow and evapotranspiration observations at a snow-dominated watershed in Colorado.
Guillaume Cinkus, Naomi Mazzilli, Hervé Jourde, Andreas Wunsch, Tanja Liesch, Nataša Ravbar, Zhao Chen, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 27, 2397–2411, https://doi.org/10.5194/hess-27-2397-2023, https://doi.org/10.5194/hess-27-2397-2023, 2023
Short summary
Short summary
The Kling–Gupta Efficiency (KGE) is a performance criterion extensively used to evaluate hydrological models. We conduct a critical study on the KGE and its variant to examine counterbalancing errors. Results show that, when assessing a simulation, concurrent over- and underestimation of discharge can lead to an overall higher criterion score without an associated increase in model relevance. We suggest that one carefully choose performance criteria and use scaling factors.
Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 27, 2357–2373, https://doi.org/10.5194/hess-27-2357-2023, https://doi.org/10.5194/hess-27-2357-2023, 2023
Short summary
Short summary
Powerful hybrid models (called δ or delta models) embrace the fundamental learning capability of AI and can also explain the physical processes. Here we test their performance when applied to regions not in the training data. δ models rivaled the accuracy of state-of-the-art AI models under the data-dense scenario and even surpassed them for the data-sparse one. They generalize well due to the physical structure included. δ models could be ideal candidates for global hydrologic assessment.
Simon Ricard, Philippe Lucas-Picher, Antoine Thiboult, and François Anctil
Hydrol. Earth Syst. Sci., 27, 2375–2395, https://doi.org/10.5194/hess-27-2375-2023, https://doi.org/10.5194/hess-27-2375-2023, 2023
Short summary
Short summary
A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. Results confirm that the proposed workflow produces equivalent projections of the seasonal mean flows in comparison to a conventional hydroclimatic modelling approach. The proposed approach supports the participation of end-users in interpreting the impact of climate change on water resources.
Marcus Edmund Henry Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-138, https://doi.org/10.5194/hess-2023-138, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
Afforestation has been proposed internationally, but the hydrological implications of such large increases in spatial extent of woodland are not fully understood. In this study we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Nutchanart Sriwongsitanon, Wasana Jandang, James Williams, Thienchart Suwawong, Ekkarin Maekan, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 2149–2171, https://doi.org/10.5194/hess-27-2149-2023, https://doi.org/10.5194/hess-27-2149-2023, 2023
Short summary
Short summary
We developed predictive semi-distributed rainfall–runoff models for nested sub-catchments in the upper Ping basin, which yielded better or similar performance compared to calibrated lumped models. The normalised difference infrared index proves to be an effective proxy for distributed root zone moisture capacity over sub-catchments and is well correlated with the percentage of evergreen forest. In validation, soil moisture simulations appeared to be highly correlated with the soil wetness index.
Yuchan Chen, Xiuzhi Chen, Meimei Xue, Chuanxun Yang, Wei Zheng, Jun Cao, Wenting Yan, and Wenping Yuan
Hydrol. Earth Syst. Sci., 27, 1929–1943, https://doi.org/10.5194/hess-27-1929-2023, https://doi.org/10.5194/hess-27-1929-2023, 2023
Short summary
Short summary
This study addresses the quantification and estimation of the watershed-characteristic-related parameter (Pw) in the Budyko framework with the principle of hydrologically similar groups. The results show that Pw is closely related to soil moisture and fractional vegetation cover, and the relationship varies across specific hydrologic similarity groups. The overall satisfactory performance of the Pw estimation model improves the applicability of the Budyko framework for global runoff estimation.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, Christoph Mayer, and Axel Bronstert
Hydrol. Earth Syst. Sci., 27, 1841–1863, https://doi.org/10.5194/hess-27-1841-2023, https://doi.org/10.5194/hess-27-1841-2023, 2023
Short summary
Short summary
We present a suitable method to reconstruct sediment export from decadal records of hydroclimatic predictors (discharge, precipitation, temperature) and shorter suspended sediment measurements. This lets us fill the knowledge gap on how sediment export from glacierized high-alpine areas has responded to climate change. We find positive trends in sediment export from the two investigated nested catchments with step-like increases around 1981 which are linked to crucial changes in glacier melt.
Samantha Petch, Bo Dong, Tristan Quaife, Robert P. King, and Keith Haines
Hydrol. Earth Syst. Sci., 27, 1723–1744, https://doi.org/10.5194/hess-27-1723-2023, https://doi.org/10.5194/hess-27-1723-2023, 2023
Short summary
Short summary
Gravitational measurements of water storage from GRACE (Gravity Recovery and Climate Experiment) can improve understanding of the water budget. We produce flux estimates over large river catchments based on observations that close the monthly water budget and ensure consistency with GRACE on short and long timescales. We use energy data to provide additional constraints and balance the long-term energy budget. These flux estimates are important for evaluating climate models.
Ting Su, Chiyuan Miao, Qingyun Duan, Jiaojiao Gou, Xiaoying Guo, and Xi Zhao
Hydrol. Earth Syst. Sci., 27, 1477–1492, https://doi.org/10.5194/hess-27-1477-2023, https://doi.org/10.5194/hess-27-1477-2023, 2023
Short summary
Short summary
The Three-River Source Region (TRSR) plays an extremely important role in water resources security and ecological and environmental protection in China and even all of Southeast Asia. This study used the variable infiltration capacity (VIC) land surface hydrologic model linked with the degree-day factor algorithm to simulate the runoff change in the TRSR. These results will help to guide current and future regulation and management of water resources in the TRSR.
Andreas Hartmann, Jean-Lionel Payeur-Poirier, and Luisa Hopp
Hydrol. Earth Syst. Sci., 27, 1325–1341, https://doi.org/10.5194/hess-27-1325-2023, https://doi.org/10.5194/hess-27-1325-2023, 2023
Short summary
Short summary
We advance our understanding of including information derived from environmental tracers into hydrological modeling. We present a simple approach that integrates streamflow observations and tracer-derived streamflow contributions for model parameter estimation. We consider multiple observed streamflow components and their variation over time to quantify the impact of their inclusion for streamflow prediction at the catchment scale.
Cited articles
Aguayo, M. A., Flores, A. N., McNamara, J. P., Marshall, H.-P., and Mead, J.: Examining cross-scale influences of forcing resolutions in a hillslope-resolving, integrated hydrologic model, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2020-451, 2020. a
Ajami, H., McCabe, M. F., Evans, J. P., and Stisen, S.: Assessing the impact of
model spin‐up on surface water‐groundwater interactions using an
integrated hydrologic model, Water Resour. Res., 50, 2636–2656, 2014. a
Arora, B., Briggs, M. A., Zarnetske, J. P., Stegen, J., Gomez-Velez, J. D.,
Dwivedi, D., and Steefel, C.: Hot spots and hot moments in the critical zone:
identification of and incorporation into reactive transport models, in:
Biogeochemistry of the Critical Zone, 9–47, Springer, https://doi.org/10.1007/978-3-030-95921-0_2, 2022. a
Ashby, S. F. and Falgout, R. D.: A parallel multigrid preconditioned conjugate
gradient algorithm for groundwater flow simulations, Nucl. Sci. Eng., 124, 145–159, 1996. a
Avanzi, F., Ercolani, G., Gabellani, S., Cremonese, E., Pogliotti, P., Filippa, G., Morra di Cella, U., Ratto, S., Stevenin, H., Cauduro, M., and Juglair, S.: Learning about precipitation lapse rates from snow course data improves water balance modeling, Hydrol. Earth Syst. Sci., 25, 2109–2131, https://doi.org/10.5194/hess-25-2109-2021, 2021. a
Baba, M. W., Gascoin, S., Kinnard, C., Marchane, A., and Hanich, L.: Effect of
Digital Elevation Model Resolution on the Simulation of the Snow
Cover Evolution in the High Atlas, Water Resour. Res., 55,
5360–5378, https://doi.org/10.1029/2018WR023789, 2019. a
Bertoldi, G., Della Chiesa, S., Notarnicola, C., Pasolli, L., Niedrist, G., and
Tappeiner, U.: Estimation of soil moisture patterns in mountain grasslands by
means of SAR RADARSAT2 images andhydrological modeling, J. Hydrol., 516, 245–257,
https://doi.org/10.1016/j.jhydrol.2014.02.018, 2014. a
Blöschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G.,
Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H. G., Sivapalan,
M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J.,
Széles, B., Viglione, A., Aksoy, H., Allen, S. T., Amin, A., Andréassian,
V., Arheimer, B., Aryal, S. K., Baker, V., Bardsley, E., Barendrecht, M. H.,
Bartosova, A., Batelaan, O., Berghuijs, W. R., Beven, K., Blume, T., Bogaard,
T., Amorim, P. B. d., Böttcher, M. E., Boulet, G., Breinl, K., Brilly, M.,
Brocca, L., Buytaert, W., Castellarin, A., Castelletti, A., Chen, X., Chen,
Y., Chen, Y., Chifflard, P., Claps, P., Clark, M. P., Collins, A. L., Croke,
B., Dathe, A., David, P. C., Barros, F. P. J. d., Rooij, G. d., Baldassarre,
G. D., Driscoll, J. M., Duethmann, D., Dwivedi, R., Eris, E., Farmer, W. H.,
Feiccabrino, J., Ferguson, G., Ferrari, E., Ferraris, S., Fersch, B., Finger,
D., Foglia, L., Fowler, K., Gartsman, B., Gascoin, S., Gaume, E., Gelfan, A.,
Geris, J., Gharari, S., Gleeson, T., Glendell, M., Bevacqua, A. G.,
González-Dugo, M. P., Grimaldi, S., Gupta, A. B., Guse, B., Han, D., Hannah,
D., Harpold, A., Haun, S., Heal, K., Helfricht, K., Herrnegger, M., Hipsey,
M., Hlaváčiková, H., Hohmann, C., Holko, L., Hopkinson, C., Hrachowitz,
M., Illangasekare, T. H., Inam, A., Innocente, C., Istanbulluoglu, E.,
Jarihani, B., Kalantari, Z., Kalvans, A., Khanal, S., Khatami, S., Kiesel,
J., Kirkby, M., Knoben, W., Kochanek, K., Kohnová, S., Kolechkina, A.,
Krause, S., Kreamer, D., Kreibich, H., Kunstmann, H., Lange, H., Liberato, M.
L. R., Lindquist, E., Link, T., Liu, J., Loucks, D. P., Luce, C., Mahé, G.,
Makarieva, O., Malard, J., Mashtayeva, S., Maskey, S., Mas-Pla, J.,
Mavrova-Guirguinova, M., Mazzoleni, M., Mernild, S., Misstear, B. D.,
Montanari, A., Müller-Thomy, H., Nabizadeh, A., Nardi, F., Neale, C.,
Nesterova, N., Nurtaev, B., Odongo, V. O., Panda, S., Pande, S., Pang, Z.,
Papacharalampous, G., Perrin, C., Pfister, L., Pimentel, R., Polo, M. J.,
Post, D., Sierra, C. P., Ramos, M.-H., Renner, M., Reynolds, J. E., Ridolfi,
E., Rigon, R., Riva, M., Robertson, D. E., Rosso, R., Roy, T., Sá, J. H. M.,
Salvadori, G., Sandells, M., Schaefli, B., Schumann, A., Scolobig, A.,
Seibert, J., Servat, E., Shafiei, M., Sharma, A., Sidibe, M., Sidle, R. C.,
Skaugen, T., Smith, H., Spiessl, S. M., Stein, L., Steinsland, I., Strasser,
U., Su, B., Szolgay, J., Tarboton, D., Tauro, F., Thirel, G., Tian, F., Tong,
R., Tussupova, K., Tyralis, H., Uijlenhoet, R., Beek, R. v., Ent, R. J.
v. d., Ploeg, M. v. d., Loon, A. F. V., Meerveld, I. v., Nooijen, R. v., Oel,
P. R. v., Vidal, J.-P., Freyberg, J. v., Vorogushyn, S., Wachniew, P., Wade,
A. J., Ward, P., Westerberg, I. K., White, C., Wood, E. F., Woods, R., Xu,
Z., Yilmaz, K. K., and Zhang, Y.: Twenty-three unsolved problems in hydrology
(UPH) – a community perspective, Hydrolog. Sci. J., 64,
1141–1158, https://doi.org/10.1080/02626667.2019.1620507, 2019. a
Brutsaert, W.: The surface roughness parameterization, in: Evaporation into the
Atmosphere, 113–127, Springer, https://doi.org/10.1007/978-94-017-1497-6_5, 1982. a
Chen, L., Šimůnek, J., Bradford, S. A., Ajami, H., and Meles, M. B.: A
computationally efficient hydrologic modeling framework to simulate
surface-subsurface hydrological processes at the hillslope scale, J. Hydrol., 614, 128539, https://doi.org/10.1016/j.jhydrol.2022.128539, 2022. a
Clark, M. P., Fan, Y., Lawrence, D. M., Adam, J. C., Bolster, D., Gochis,
D. J., Hooper, R. P., Kumar, M., Leung, L. R., Mackay, D. S., Maxwell, R. M.,
Shen, C., Swenson, S. C., and Zeng, X.: Improving the representation of
hydrologic processes in Earth System Models, Water Resour. Res.,
51, 5929–5956, https://doi.org/10.1002/2015WR017096, 2015. a
Condon, L. E. and Maxwell, R. M.: Modified priority flood and global slope
enforcement algorithm for topographic processing in physically based
hydrologic modeling applications, Comput. Geosci., 126, 73–83,
https://doi.org/10.1016/j.cageo.2019.01.020, 2019. a, b
Costa, D., Shook, K., Spence, C., Elliott, J., Baulch, H., Wilson, H., and
Pomeroy, J. W.: Predicting Variable Contributing Areas, Hydrological
Connectivity, and Solute Transport Pathways for a Canadian
Prairie Basin, Water Resour. Res., 56, e2020WR027984,
https://doi.org/10.1029/2020WR027984, 2020. a
Dahri, Z. H., Ludwig, F., Moors, E., Ahmad, B., Khan, A., and Kabat, P.: An
appraisal of precipitation distribution in the high-altitude catchments of
the Indus basin, Sci. Total Environ., 548, 289–306, 2016. a
Dai, Y., Zeng, X., Dickinson, R. E., Baker, I., Bonan, G. B., Bosilovich,
M. G., Denning, A. S., Dirmeyer, P. A., Houser, P. R., Niu, G., Oleson,
K. W., Schlosser, C. A., and Yang, Z.-L.: The Common Land Model,
B. Am. Meteorol. Soc., 84, 1013–1024,
https://doi.org/10.1175/BAMS-84-8-1013, 2003. a
Dozier, J.: Spectral signature of alpine snow cover from the Landsat
Thematic Mapper, Remote Sens. Environ., 28, 9–22, 1989. a
Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F.,
Hoersch, B., Isola, C., Laberinti, P., and Martimort, P.: Sentinel-2: ESA's
optical high-resolution mission for GMES operational services, Remote Sens. Environ., 120, 25–36, 2012. a
Dunne, T.: Relation of field studies and modeling in the prediction of storm
runoff, J. Hydrol., 65, 25–48, https://doi.org/10.1016/0022-1694(83)90209-3,
1983. a
Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L.,
Brooks, P. D., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W.,
Mackay, D. S., McDonnell, J. J., Milly, P. C. D., Sullivan, P. L., Tague, C.,
Ajami, H., Chaney, N., Hartmann, A., Hazenberg, P., McNamara, J., Pelletier,
J., Perket, J., Rouholahnejad‐Freund, E., Wagener, T., Zeng, X., Beighley,
E., Buzan, J., Huang, M., Livneh, B., Mohanty, B. P., Nijssen, B., Safeeq,
M., Shen, C., Verseveld, W. v., Volk, J., and Yamazaki, D.: Hillslope
Hydrology in Global Change Research and Earth System Modeling,
Water Resour. Res., 55, 1737–1772,
https://doi.org/10.1029/2018WR023903, 2019. a, b, c, d
Fang, X. and Pomeroy, J. W.: Diagnosis of future changes in hydrology for a Canadian Rockies headwater basin, Hydrol. Earth Syst. Sci., 24, 2731–2754, https://doi.org/10.5194/hess-24-2731-2020, 2020. a, b
Gupta, A., Reverdy, A., Cohard, J.-M., Voisin, D., Hector, B., Descloitres, M., Vandervaere, J.-P., Coulaud, C., Biron, R., Liger, L., Valay, J.-G., and Maxwell, R.: Data from: Impact of distributed meteorological forcing on snow dynamic and induced water fluxes over a mid-elevation alpine micro-scale catchment, https://doi.org/10.18709/PERSCIDO.2022.09.DS375, 2022. a
Günther, D., Marke, T., Essery, R., and Strasser, U.: Uncertainties in
Snowpack Simulations – Assessing the Impact of Model Structure,
Parameter Choice, and Forcing Data Error on Point-Scale
Energy Balance Snow Model Performance, Water Resour. Res.,
55, 2779–2800, https://doi.org/10.1029/2018WR023403, 2019. a
Hellström, M., Vermeulen, A., Mirzov, O., Sabbatini, S., Vitale, D., Papale,
D., Tarniewicz, J., Hazan, L., Rivier, L., and Jones, S. D.: Near Real
Time Data Processing In ICOS RI, in: 2nd international workshop
on interoperable infrastructures for interdisciplinary big data sciences
(it4ris 16) in the context of ieee real-time system symposium (rtss), 29 November–2 December 2016, Porto, Portugal, 2016. a
Hofmeister, F., Arias-Rodriguez, L. F., Premier, V., Marin, C., Notarnicola,
C., Disse, M., and Chiogna, G.: Intercomparison of Sentinel-2 and modelled
snow cover maps in a high-elevation Alpine catchment, J. Hydrol., 15, 100123, https://doi.org/10.1016/j.hydroa.2022.100123, 2022. a
Hojatimalekshah, A., Uhlmann, Z., Glenn, N. F., Hiemstra, C. A., Tennant, C. J., Graham, J. D., Spaete, L., Gelvin, A., Marshall, H.-P., McNamara, J. P., and Enterkine, J.: Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning, The Cryosphere, 15, 2187–2209, https://doi.org/10.5194/tc-15-2187-2021, 2021. a
Horton, R. E.: The Rôle of infiltration in the hydrologic cycle, Eos,
Transactions American Geophysical Union, 14, 446–460,
https://doi.org/10.1029/TR014i001p00446, 1933. a
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner,
P. J., Lamarque, J.-F., Large, W. G., Lawrence, D., Lindsay, K., Lipscomb,
W. H., Long, M. C., Mahowald, N., Marsh, D. R., Neale, R. B., Rasch, P.,
Vavrus, S., Vertenstein, M., Bader, D., Collins, W. D., Hack, J. J., Kiehl,
J., and Marshall, S.: The Community Earth System Model: A
Framework for Collaborative Research, B. Am. Meteorol. Soc., 94, 1339–1360, https://doi.org/10.1175/BAMS-D-12-00121.1, 2013. a
Iseri, Y., Diaz, A. J., Trinh, T., Kavvas, M. L., Ishida, K., Anderson, M. L.,
Ohara, N., and Snider, E. D.: Dynamical downscaling of global reanalysis data
for high-resolution spatial modeling of snow accumulation/melting at the
central/southern Sierra Nevada watersheds, J. Hydrol., 598,
126445, https://doi.org/10.1016/j.jhydrol.2021.126445, 2021. a
Jabot, E., Zin, I., Lebel, T., Gautheron, A., and Obled, C.: Spatial
interpolation of sub-daily air temperatures for snow and hydrologic
applications in mesoscale Alpine catchments, Hydrol. Process., 26,
2618–2630, 2012. a
Jacobs, J. M., Hunsaker, A. G., Sullivan, F. B., Palace, M., Burakowski, E. A., Herrick, C., and Cho, E.: Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States, The Cryosphere, 15, 1485–1500, https://doi.org/10.5194/tc-15-1485-2021, 2021. a
Jefferson, J. L. and Maxwell, R. M.: Evaluation of simple to complex
parameterizations of bare ground evaporation, J. Adv. Model. Earth Sy., 7, 1075–1092, https://doi.org/10.1002/2014MS000398, 2015. a
Jones, J. E. and Woodward, C. S.: Newton–Krylov-multigrid solvers for
large-scale, highly heterogeneous, variably saturated flow problems, Adv. Water Resour., 24, 763–774, 2001. a
Kljun, N., Calanca, P., Rotach, M. W., and Schmid, H. P.: A simple
parameterisation for flux footprint predictions,
Bound.-Lay. Meteorol.,
112, 503–523, 2004. a
Klok, E. J., Jasper, K., Roelofsma, K. P., Gurtz, J., and Badoux, A.:
Distributed hydrological modelling of a heavily glaciated Alpine river
basin, Hydrolog. Sci. J., 46, 553–570, 2001. a
Kollet, S. J. and Maxwell, R. M.: Integrated surface–groundwater flow
modeling: A free-surface overland flow boundary condition in a parallel
groundwater flow model, Adv. Water Resour., 29, 945–958,
https://doi.org/10.1016/j.advwatres.2005.08.006, 2006. a, b, c
Kollet, S. J. and Maxwell, R. M.: Capturing the influence of groundwater
dynamics on land surface processes using an integrated, distributed watershed
model, Water Resour. Res., 44, W02402, https://doi.org/10.1029/2007WR006004, 2008. a
Kuffour, B. N. O., Engdahl, N. B., Woodward, C. S., Condon, L. E., Kollet, S., and Maxwell, R. M.: Simulating coupled surface–subsurface flows with ParFlow v3.5.0: capabilities, applications, and ongoing development of an open-source, massively parallel, integrated hydrologic model, Geosci. Model Dev., 13, 1373–1397, https://doi.org/10.5194/gmd-13-1373-2020, 2020. a, b, c
Liston, G. E. and Elder, K.: A Meteorological Distribution System for
High-Resolution Terrestrial Modeling (MicroMet),
J. Hydrometeorol., 7, 217–234, https://doi.org/10.1175/JHM486.1, 2006. a, b, c, d
Liston, G. E., Perham, C. J., Shideler, R. T., and Cheuvront, A. N.: Modeling
snowdrift habitat for polar bear dens, Ecol. Model., 320, 114–134,
https://doi.org/10.1016/j.ecolmodel.2015.09.010, 2016. a
Loritz, R., Hrachowitz, M., Neuper, M., and Zehe, E.: The role and value of distributed precipitation data in hydrological models, Hydrol. Earth Syst. Sci., 25, 147–167, https://doi.org/10.5194/hess-25-147-2021, 2021. a
Marsh, C. B., Pomeroy, J. W., Spiteri, R. J., and Wheater, H. S.: A Finite
Volume Blowing Snow Model for Use With Variable Resolution
Meshes, Water Resour. Res., 56, e2019WR025307,
https://doi.org/10.1029/2019WR025307, 2020. a
Maxwell, R. M.: A terrain-following grid transform and preconditioner for
parallel, large-scale, integrated hydrologic modeling, Adv. Water Resour., 53, 109–117, 2013. a
Maxwell, R. M. and Miller, N. L.: Development of a coupled land surface and
groundwater model, J. Hydrometeorol., 6, 233–247,
2005. a
Meerveld, H. J. T.-v., James, A. L., McDonnell, J. J., and Peters, N. E.: A
reference data set of hillslope rainfall-runoff response, Panola Mountain
Research Watershed, United States, Water Resour. Res., 44, W06502, https://doi.org/10.1029/2007WR006299, 2008. a
Melton, F. S., Huntington, J., Grimm, R., Herring, J., Hall, M., Rollison, D.,
Erickson, T., Allen, R., Anderson, M., and Fisher, J. B.: Openet: Filling a
critical data gap in water management for the western united states, J. Am. Water. Resour. As., 1–24, https://doi.org/10.1111/1752-1688.12956, 2021. a
Nijssen, B. and Lettenmaier, D. P.: A simplified approach for predicting
shortwave radiation transfer through boreal forest canopies, J. Geophys. Res.-Atmos., 104, 27859–27868,
https://doi.org/10.1029/1999JD900377, 1999. a
Oishi, A. C., Oren, R., and Stoy, P. C.: Estimating components of forest
evapotranspiration: a footprint approach for scaling sap flux measurements,
Agr. Forest Meteorol., 148, 1719–1732, 2008. a
Oleson, K. W., Dai, Y., Bonan, G., Bosilovich, M., Dickinson, R., Dirmeyer, P.,
Hoffman, F., Houser, P., Levis, S., and Niu, G.-Y.: Technical description of
the community land model (CLM), Tech. Note NCAR/TN-461+ STR, https://doi.org/10.5065/D6N877R0, 2004. a
Painter, T. H., Berisford, D. F., Boardman, J. W., Bormann, K. J., Deems,
J. S., Gehrke, F., Hedrick, A., Joyce, M., Laidlaw, R., and Marks, D.: The
Airborne Snow Observatory: Fusion of scanning lidar, imaging
spectrometer, and physically-based modeling for mapping snow water equivalent
and snow albedo, Remote Sens. Environ., 184, 139–152, 2016. a
Parsekian, A. D., Grana, D., Neves, F. d. A., Pleasants, M. S., Seyfried, M.,
Moravec, B. G., Chorover, J., Moraes, A. M., Smeltz, N. Y., and Westenhoff,
J. H.: Hydrogeophysical comparison of hillslope critical zone architecture
for different geologic substrates, Geophysics, 86, WB29–WB49, 2021. a
Pomeroy, J. W. and Li, L.: Prairie and arctic areal snow cover mass balance
using a blowing snow model, J. Geophys. Res.-Atmos.,
105, 26619–26634, https://doi.org/10.1029/2000JD900149, 2000. a
Pomeroy, J. W., Toth, B., Granger, R. J., Hedstrom, N. R., and Essery, R.
L. H.: Variation in Surface Energetics during Snowmelt in a Subarctic
Mountain Catchment, J. Hydrometeorol., 4, 702–719,
https://doi.org/10.1175/1525-7541(2003)004<0702:VISEDS>2.0.CO;2, 2003. a
Pomeroy, J. W., Gray, D. M., Brown, T., Hedstrom, N. R., Quinton, W. L.,
Granger, R. J., and Carey, S. K.: The cold regions hydrological model: a
platform for basing process representation and model structure on physical
evidence, Hydrol. Process., 21, 2650–2667,
https://doi.org/10.1002/hyp.6787, 2007. a
Pradhananga, D. and Pomeroy, J. W.: Diagnosing changes in glacier hydrology
from physical principles using a hydrological model with snow redistribution,
sublimation, firnification and energy balance ablation algorithms, J. Hydrol., 608, 127545, https://doi.org/10.1016/j.jhydrol.2022.127545, 2022. a
Revuelto, J., Azorin-Molina, C., Alonso-González, E., Sanmiguel-Vallelado, A., Navarro-Serrano, F., Rico, I., and López-Moreno, J. I.: Meteorological and snow distribution data in the Izas Experimental Catchment (Spanish Pyrenees) from 2011 to 2017, Earth Syst. Sci. Data, 9, 993–1005, https://doi.org/10.5194/essd-9-993-2017, 2017. a
Revuelto, J., Billecocq, P., Tuzet, F., Cluzet, B., Lamare, M., Larue, F., and
Dumont, M.: Random forests as a tool to understand the snow depth
distribution and its evolution in mountain areas, Hydrol. Process., 34,
5384–5401, https://doi.org/10.1002/hyp.13951, 2020. a, b
Riggs, G., Hall, D., and Salomonson, V.: A snow index for the Landsat
Thematic Mapper and Moderate Resolution Imaging
Spectroradiometer, in: Proceedings of IGARSS '94 – 1994 IEEE
International Geoscience and Remote Sensing Symposium, vol. 4, 1942–1944, https://doi.org/10.1109/IGARSS.1994.399618, 1994. a
Rush, M., Rajaram, H., Anderson, R. S., and Anderson, S. P.: Modeling
Aspect‐Controlled Evolution of Ground Thermal Regimes on
Montane Hillslopes, J. Geophys. Res.-Earth, 126,
e2021JF006126, https://doi.org/10.1029/2021JF006126, 2021. a
Sampaio, R. J., Rodriguez, D. A., Von Randow, C., da Silva, F. P., de Araújo,
A. A. M., and Filho, O. C. R.: Sensible heat flux assessment in a complex
coastal-mountain urban area in the metropolitan area of Rio de Janeiro,
Brazil, Meteorol. Atmos. Phys., 133, 973–987, https://doi.org/10.1007/s00703-021-00812-2, 2021. a
Sevruk, B. and WMO, G.: Correction of precipitation
measurements(Proceedings), Zuerich (Switzerland) ETH, Zurich, Switzerland, Geographisches Inst., ETH/IAHS/WMO Workshop on the Correction of Precipitation
Measurements, 1986. a
Sidle, R. C.: Field observations and process understanding in hydrology:
essential components in scaling, Hydrol. Process., 20, 1439–1445, 2006. a
Sidle, R. C.: Strategies for smarter catchment hydrology models: incorporating
scaling and better process representation, Geoscience Letters, 8, 1–14, 2021. a
Smith, S., reedmaxwell, i-ferguson, Engdahl, N., Gasper, F., Chennault, C., Avery, P., Jourdain, S., grapp1, Condon, L., Bennett, A., Rigor, P., Kulkarni, K., Bansal, V., xy124, basileh, Thompson, D, DrewLazzeriKitware, Swilley, J., ... zperzan: aniketgupta2009/treeac-alp-parflow-ver-meteo: treeac-alp-parflow-ver-meteo (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.7470757, 2022. a
Song, J., Miller, G. R., Cahill, A. T., Aparecido, L. M. T., and Moore, G. W.: Modeling land surface processes over a mountainous rainforest in Costa Rica using CLM4.5 and CLM5, Geosci. Model Dev., 13, 5147–5173, https://doi.org/10.5194/gmd-13-5147-2020, 2020. a, b
Sun, N., Wigmosta, M., Zhou, T., Lundquist, J., Dickerson-Lange, S., and
Cristea, N.: Evaluating the functionality and streamflow impacts of
explicitly modelling forest–snow interactions and canopy gaps in a
distributed hydrologic model, Hydrol. Process., 32, 2128–2140,
https://doi.org/10.1002/hyp.13150, 2018. a, b
Tran, H., Zhang, J., Cohard, J.-M., Condon, L. E., and Maxwell, R. M.:
Simulating Groundwater-Streamflow Connections in the Upper Colorado
River Basin, Groundwater, 58, 392–405,
https://doi.org/10.1111/gwat.13000, 2020. a, b
van den Hurk, B., Best, M., Dirmeyer, P., Pitman, A., Polcher, J., and
Santanello, J.: Acceleration of land surface model development over a decade
of GLASS, B. Am. Meteorol. Soc., 92, 1593–1600, 2011. a
Van Genuchten, M. T.: A closed‐form equation for predicting the hydraulic
conductivity of unsaturated soils, Soil Sci. Soc. Am. J.,
44, 892–898, 1980. a
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012. a
Wlostowski, A. N., Molotch, N., Anderson, S. P., Brantley, S. L., Chorover, J.,
Dralle, D., Kumar, P., Li, L., Lohse, K. A., and Mallard, J. M.: Signatures
of hydrologic function across the critical zone observatory network, Water
Resour. Res., 57, e2019WR026635, https://doi.org/10.1029/2019WR026635, 2021. a
Yan, R., Zhang, X., Yan, S., Zhang, J., and Chen, H.: Spatial patterns of
hydrological responses to land use/cover change in a catchment on the Loess
Plateau, China, Ecol. Indic., 92, 151–160, 2018. a
Zhu, B., Xie, X., Lu, C., Lei, T., Wang, Y., Jia, K., and Yao, Y.: Extensive
evaluation of a continental-scale high-resolution hydrological model using
remote sensing and ground-based observations, Remote Sens., 13, 1247, https://doi.org/10.3390/rs13071247, 2021. a
Short summary
Patchy snow cover during spring impacts mountainous ecosystems on a large range of spatio-temporal scales. A hydrological model simulated such snow patchiness at 10 m resolution. Slope and orientation controls precipitation, radiation, and wind generate differences in snowmelt, subsurface storage, streamflow, and evapotranspiration. The snow patchiness increases the duration of the snowmelt to stream and subsurface storage, which sustains the plants and streamflow later in the summer.
Patchy snow cover during spring impacts mountainous ecosystems on a large range of...
