Articles | Volume 12, issue 6
https://doi.org/10.5194/gmd-12-2501-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-2501-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
28 Jun 2019
Model description paper |
| 28 Jun 2019
| 28 Jun 2019
The multiscale routing model mRM v1.0: simple river routing at resolutions from 1 to 50 km
Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Matthias Cuntz
Université de Lorraine, Institut National de la Recherche Agronomique (INRA), AgroParisTech, Unité Mixte de Recherche Silva, 54000 Nancy, France
Matthias Kelbling
Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Rohini Kumar
Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Juliane Mai
Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, Ontario, Canada
Luis Samaniego
Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Related authors
Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Omar Abdelazim Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2198, https://doi.org/10.5194/egusphere-2025-2198, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of climate projections. The system produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
Sebastian Müller, Martin Lange, Thomas Fischer, Sara König, Matthias Kelbling, Jeisson Javier Leal Rojas, and Stephan Thober
Geosci. Model Dev., 18, 4483–4498, https://doi.org/10.5194/gmd-18-4483-2025, https://doi.org/10.5194/gmd-18-4483-2025, 2025
Short summary
Short summary
This study presents FINAM (
FINAM is not a model), a new coupling framework written in Python to dynamically connect independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.
Maria Staudinger, Anna Herzog, Ralf Loritz, Tobias Houska, Sandra Pool, Diana Spieler, Paul D. Wagner, Juliane Mai, Jens Kiesel, Stephan Thober, Björn Guse, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2025-1076, https://doi.org/10.5194/egusphere-2025-1076, 2025
Short summary
Short summary
Four process-based and four data-driven hydrological models are compared using different training data. We found process-based models to perform better with small data sets but stop learning soon, while data-driven models learn longer. The study highlights the importance of memory in data and the impact of different data sampling methods on model performance. The direct comparison of these models is novel and provides a clear understanding of their performance under various data conditions.
Katherine Grayson, Stephan Thober, Aleksander Lacima-Nadolnik, Ehsan Sharifi, Llorenç Lledó, and Francisco Doblas-Reyes
EGUsphere, https://doi.org/10.5194/egusphere-2025-28, https://doi.org/10.5194/egusphere-2025-28, 2025
Short summary
Short summary
To provide the most accurate climate adaptation information, climate models are being run with finer grid resolution, resulting in larger data output. This paper presents intelligent data reduction algorithms that act on streamed data, a novel way of processing climate data as soon as it is produced. Using these algorithms to calculate statistics, we show that the accuracy provided is well within acceptable bounds while still providing memory savings that bypass unfeasible storage requirements.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024, https://doi.org/10.5194/bg-21-5277-2024, 2024
Short summary
Short summary
Plants at the land surface mediate between soil and the atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to consider these dynamics. Two models that predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness, which is caused by a mismatch between implemented physical relations and observable connections.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
Short summary
Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
Short summary
Short summary
The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
Michael Peichl, Stephan Thober, Luis Samaniego, Bernd Hansjürgens, and Andreas Marx
Hydrol. Earth Syst. Sci., 25, 6523–6545, https://doi.org/10.5194/hess-25-6523-2021, https://doi.org/10.5194/hess-25-6523-2021, 2021
Short summary
Short summary
Using a statistical model that can also take complex systems into account, the most important factors affecting wheat yield in Germany are determined. Different spatial damage potentials are taken into account. In many parts of Germany, yield losses are caused by too much soil water in spring. Negative heat effects as well as damaging soil drought are identified especially for north-eastern Germany. The model is able to explain years with exceptionally high yields (2014) and losses (2003, 2018).
Miao Jing, Rohini Kumar, Falk Heße, Stephan Thober, Oldrich Rakovec, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 24, 1511–1526, https://doi.org/10.5194/hess-24-1511-2020, https://doi.org/10.5194/hess-24-1511-2020, 2020
Short summary
Short summary
This study investigates the response of regional groundwater system to the climate change under three global warming levels (1.5, 2, and 3 °C) in a central German basin. A comprehensive uncertainty analysis is also presented. This study indicates that the variability of responses increases with the amount of global warming, which might affect the cost of managing the groundwater system.
Michael Peichl, Stephan Thober, Volker Meyer, and Luis Samaniego
Nat. Hazards Earth Syst. Sci., 18, 889–906, https://doi.org/10.5194/nhess-18-889-2018, https://doi.org/10.5194/nhess-18-889-2018, 2018
Short summary
Short summary
Crop yields are routinely derived from meteorological variables, especially temperature. However, the primary water source for plant growth (soil moisture) is neglected. In this study, the predictability of maize yield is investigated using soil moisture or meteorological variables in Germany. The effects of soil moisture dominate those of temperature and are time-dependent. For example, comparatively moist soil conditions in June reduce crop yields, while in August they increase yields.
Andreas Marx, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Niko Wanders, Matthias Zink, Eric F. Wood, Ming Pan, Justin Sheffield, and Luis Samaniego
Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, https://doi.org/10.5194/hess-22-1017-2018, 2018
Short summary
Short summary
Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.
Luis Samaniego, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Matthias Zink, Niko Wanders, Stephanie Eisner, Hannes Müller Schmied, Edwin H. Sutanudjaja, Kirsten Warrach-Sagi, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, https://doi.org/10.5194/hess-21-4323-2017, 2017
Short summary
Short summary
We inspect the state-of-the-art of several land surface (LSMs) and hydrologic models (HMs) and show that most do not have consistent and realistic parameter fields for land surface geophysical properties. We propose to use the multiscale parameter regionalization (MPR) technique to solve, at least partly, the scaling problem in LSMs/HMs. A general model protocol is presented to describe how MPR can be applied to a specific model.
Remko C. Nijzink, Luis Samaniego, Juliane Mai, Rohini Kumar, Stephan Thober, Matthias Zink, David Schäfer, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, https://doi.org/10.5194/hess-20-1151-2016, 2016
Short summary
Short summary
The heterogeneity of landscapes in river basins strongly affects the hydrological response. In this study, the distributed mesoscale Hydrologic Model (mHM) was equipped with additional processes identified by landscapes within one modelling cell. Seven study catchments across Europe were selected to test the value of this additional sub-grid heterogeneity. In addition, the models were constrained based on expert knowledge. Generally, the modifications improved the representation of low flows.
Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Omar Abdelazim Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2198, https://doi.org/10.5194/egusphere-2025-2198, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of climate projections. The system produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, Yannis Markonis, and Miroslav Trnka
Hydrol. Earth Syst. Sci., 29, 3341–3358, https://doi.org/10.5194/hess-29-3341-2025, https://doi.org/10.5194/hess-29-3341-2025, 2025
Short summary
Short summary
We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, with clusters of 775 and 630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Sebastian Müller, Martin Lange, Thomas Fischer, Sara König, Matthias Kelbling, Jeisson Javier Leal Rojas, and Stephan Thober
Geosci. Model Dev., 18, 4483–4498, https://doi.org/10.5194/gmd-18-4483-2025, https://doi.org/10.5194/gmd-18-4483-2025, 2025
Short summary
Short summary
This study presents FINAM (
FINAM is not a model), a new coupling framework written in Python to dynamically connect independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.
Gabriel Destouet, Nikola Besic, Emilie Joetzjer, and Matthias Cuntz
Atmos. Meas. Tech., 18, 3193–3215, https://doi.org/10.5194/amt-18-3193-2025, https://doi.org/10.5194/amt-18-3193-2025, 2025
Short summary
Short summary
Over the past two decades, global flux tower networks have provided valuable insights into ecosystem functioning. However, the standard eddy-covariance method used for processing flux data has limitations, leading to data loss and limited resolution due to fixed time steps. This paper introduces a new method using wavelet analysis to increase temporal resolution and improve data retention. Applied at the Hesse forest flux tower in France, this approach provides high-resolution flux estimates, enhancing the accuracy of flux measurements.
Pia Ebeling, Andreas Musolff, Rohini Kumar, Andreas Hartmann, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 29, 2925–2950, https://doi.org/10.5194/hess-29-2925-2025, https://doi.org/10.5194/hess-29-2925-2025, 2025
Short summary
Short summary
Groundwater is a crucial resource at risk due to droughts. To understand drought effects on groundwater levels in Germany, we grouped 6626 wells into six regional and two national patterns. Weather explained half of the level variations with varied response times. Shallow groundwater responds fast and is more vulnerable to short droughts (a few months). Dampened deep heads buffer short droughts but suffer from long droughts and recoveries. Two nationwide trend patterns were linked to human water use.
Mansi Nagpal, Jasmin Heilemann, Luis Samaniego, Bernd Klauer, Erik Gawel, and Christian Klassert
Nat. Hazards Earth Syst. Sci., 25, 2115–2135, https://doi.org/10.5194/nhess-25-2115-2025, https://doi.org/10.5194/nhess-25-2115-2025, 2025
Short summary
Short summary
This study measures the direct effects of droughts in association with other extreme weather events on agriculture in Germany at the district level. Using a statistical yield model, we quantify the direct damage of extremes on crop yields and farm revenue. Extreme events during drought cause an average annual damage of EUR 781 million, accounting for 45 % of reported revenue losses. The insights herein can help develop better strategies for managing and mitigating the effects of future climate extremes.
Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 25, 2007–2029, https://doi.org/10.5194/nhess-25-2007-2025, https://doi.org/10.5194/nhess-25-2007-2025, 2025
Short summary
Short summary
The July 2021 flood in central Europe was one of the deadliest floods in Europe in the recent decades and the most expensive flood in Germany. In this paper, we show that the hydrological impact of this event in the Ahr valley could have been even worse if the rainfall footprint trajectory had been only slightly different. The presented methodology of spatial counterfactuals generates plausible unprecedented events and helps to better prepare for future extreme floods.
Tanguy Postic, François de Coligny, Isabelle Chuine, Louis Devresse, Daniel Berveiller, Hervé Cochard, Matthias Cuntz, Nicolas Delpierre, Émilie Joetzjer, Jean-Marc Limousin, Jean-Marc Ourcival, François Pimont, Julien Ruffault, Guillaume Simioni, Nicolas K. Martin-StPaul, and Xavier Morin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2110, https://doi.org/10.5194/egusphere-2025-2110, 2025
Short summary
Short summary
PHOREAU is a forest dynamic model that links plant traits with water use, growth, and climate responses to explore how species diversity affects productivity and resilience. Validated across European forests, PHOREAU simulates how tree communities function under drought and warming. Our findings support the use of trait-based modeling to guide forest adaptation strategies under future climate scenarios.
Hannes Müller Schmied, Simon Newland Gosling, Marlo Garnsworthy, Laura Müller, Camelia-Eliza Telteu, Atiq Kainan Ahmed, Lauren Seaby Andersen, Julien Boulange, Peter Burek, Jinfeng Chang, He Chen, Lukas Gudmundsson, Manolis Grillakis, Luca Guillaumot, Naota Hanasaki, Aristeidis Koutroulis, Rohini Kumar, Guoyong Leng, Junguo Liu, Xingcai Liu, Inga Menke, Vimal Mishra, Yadu Pokhrel, Oldrich Rakovec, Luis Samaniego, Yusuke Satoh, Harsh Lovekumar Shah, Mikhail Smilovic, Tobias Stacke, Edwin Sutanudjaja, Wim Thiery, Athanasios Tsilimigkras, Yoshihide Wada, Niko Wanders, and Tokuta Yokohata
Geosci. Model Dev., 18, 2409–2425, https://doi.org/10.5194/gmd-18-2409-2025, https://doi.org/10.5194/gmd-18-2409-2025, 2025
Short summary
Short summary
Global water models contribute to the evaluation of important natural and societal issues but are – as all models – simplified representation of reality. So, there are many ways to calculate the water fluxes and storages. This paper presents a visualization of 16 global water models using a standardized visualization and the pathway towards this common understanding. Next to academic education purposes, we envisage that these diagrams will help researchers, model developers, and data users.
Robert Reinecke, Annemarie Bäthge, Ricarda Dietrich, Sebastian Gnann, Simon N. Gosling, Danielle Grogan, Andreas Hartmann, Stefan Kollet, Rohini Kumar, Richard Lammers, Sida Liu, Yan Liu, Nils Moosdorf, Bibi Naz, Sara Nazari, Chibuike Orazulike, Yadu Pokhrel, Jacob Schewe, Mikhail Smilovic, Maryna Strokal, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
EGUsphere, https://doi.org/10.5194/egusphere-2025-1181, https://doi.org/10.5194/egusphere-2025-1181, 2025
Short summary
Short summary
Here we describe a collaborative effort to improve predictions of how climate change will affect groundwater. The ISIMIP groundwater sector combines multiple global groundwater models to capture a range of possible outcomes and reduce uncertainty. Initial comparisons reveal significant differences between models in key metrics like water table depth and recharge rates, highlighting the need for structured model intercomparisons.
Maria Staudinger, Anna Herzog, Ralf Loritz, Tobias Houska, Sandra Pool, Diana Spieler, Paul D. Wagner, Juliane Mai, Jens Kiesel, Stephan Thober, Björn Guse, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2025-1076, https://doi.org/10.5194/egusphere-2025-1076, 2025
Short summary
Short summary
Four process-based and four data-driven hydrological models are compared using different training data. We found process-based models to perform better with small data sets but stop learning soon, while data-driven models learn longer. The study highlights the importance of memory in data and the impact of different data sampling methods on model performance. The direct comparison of these models is novel and provides a clear understanding of their performance under various data conditions.
Masooma Batool, Fanny J. Sarrazin, and Rohini Kumar
Earth Syst. Sci. Data, 17, 881–916, https://doi.org/10.5194/essd-17-881-2025, https://doi.org/10.5194/essd-17-881-2025, 2025
Short summary
Short summary
Our paper presents a reconstruction and analysis of the gridded P surplus in European landscapes from 1850 to 2019 at a 5 arcmin resolution. By utilizing 48 different estimates, we account for uncertainties in major components of the P surplus. Our findings highlight substantial historical changes, with the total P surplus in the EU 27 tripling over 170 years. Our dataset enables flexible aggregation at various spatial scales, providing critical insights for land and water management strategies.
Katherine Grayson, Stephan Thober, Aleksander Lacima-Nadolnik, Ehsan Sharifi, Llorenç Lledó, and Francisco Doblas-Reyes
EGUsphere, https://doi.org/10.5194/egusphere-2025-28, https://doi.org/10.5194/egusphere-2025-28, 2025
Short summary
Short summary
To provide the most accurate climate adaptation information, climate models are being run with finer grid resolution, resulting in larger data output. This paper presents intelligent data reduction algorithms that act on streamed data, a novel way of processing climate data as soon as it is produced. Using these algorithms to calculate statistics, we show that the accuracy provided is well within acceptable bounds while still providing memory savings that bypass unfeasible storage requirements.
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
Short summary
Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
Short summary
Short summary
This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024, https://doi.org/10.5194/bg-21-5277-2024, 2024
Short summary
Short summary
Plants at the land surface mediate between soil and the atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to consider these dynamics. Two models that predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness, which is caused by a mismatch between implemented physical relations and observable connections.
Vishal Thakur, Yannis Markonis, Rohini Kumar, Johanna Ruth Thomson, Mijael Rodrigo Vargas Godoy, Martin Hanel, and Oldrich Rakovec
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-341, https://doi.org/10.5194/hess-2024-341, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Understanding the changes in water movement in earth is crucial for everyone. To quantify this water movement there are several techniques. We examined how different methods of estimating evaporation impact predictions of various types of water movement across Europe. We found that, while these methods generally agree on whether changes are increasing or decreasing, they differ in magnitude. This means selecting the right evaporation method is crucial for accurate predictions of water movement.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
Short summary
Short summary
Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
Short summary
Short summary
It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Kingsley Nnaemeka Ogbu, Oldrich Rakovec, Luis Samaniego, Gloria Chinwendu Okafor, Bernhard Tischbein, and Hadush Meresa
Proc. IAHS, 385, 211–218, https://doi.org/10.5194/piahs-385-211-2024, https://doi.org/10.5194/piahs-385-211-2024, 2024
Short summary
Short summary
In this study, the MPR-mHM technique was applied in four data-scarce basins in Nigeria. Remotely sensed rainfall datasets were used as model forcings to evaluate the mHM capability in reproducing observed stream discharge under single and multivariable model calibration frameworks. Overall, model calibration performances displayed satisfactory outputs as evident in the Kling-Gupta Efficiency (KGE) scores across most basins.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
Short summary
Short summary
A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Samah Larabi, Juliane Mai, Markus Schnorbus, Bryan A. Tolson, and Francis Zwiers
Hydrol. Earth Syst. Sci., 27, 3241–3263, https://doi.org/10.5194/hess-27-3241-2023, https://doi.org/10.5194/hess-27-3241-2023, 2023
Short summary
Short summary
The computational cost of sensitivity analysis (SA) becomes prohibitive for large hydrologic modeling domains. Here, using a large-scale Variable Infiltration Capacity (VIC) deployment, we show that watershed classification helps identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. Findings reveal the opportunity to leverage climate and land cover attributes to reduce the cost of SA and facilitate more rapid deployment of large-scale land surface models.
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.
Robert Chlumsky, Juliane Mai, James R. Craig, and Bryan A. Tolson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-69, https://doi.org/10.5194/hess-2023-69, 2023
Revised manuscript not accepted
Short summary
Short summary
A blended model allows multiple hydrologic processes to be represented in a single model, which allows for a model to achieve high performance without the need to modify its structure for different catchments. Here, we improve upon the initial blended version by testing more than 30 blended models in twelve catchments to improve the overall model performance. We validate our proposed, updated blended model version with independent catchments, and make this version available for open use.
Carolin Winter, Tam V. Nguyen, Andreas Musolff, Stefanie R. Lutz, Michael Rode, Rohini Kumar, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 27, 303–318, https://doi.org/10.5194/hess-27-303-2023, https://doi.org/10.5194/hess-27-303-2023, 2023
Short summary
Short summary
The increasing frequency of severe and prolonged droughts threatens our freshwater resources. While we understand drought impacts on water quantity, its effects on water quality remain largely unknown. Here, we studied the impact of the unprecedented 2018–2019 drought in Central Europe on nitrate export in a heterogeneous mesoscale catchment in Germany. We show that severe drought can reduce a catchment's capacity to retain nitrogen, intensifying the internal pollution and export of nitrate.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
Short summary
Short summary
Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
Short summary
Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel
Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, https://doi.org/10.5194/essd-14-4035-2022, 2022
Short summary
Short summary
This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff
Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, https://doi.org/10.5194/essd-14-3715-2022, 2022
Short summary
Short summary
Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
Short summary
Short summary
Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Michelle Viswanathan, Tobias K. D. Weber, Sebastian Gayler, Juliane Mai, and Thilo Streck
Biogeosciences, 19, 2187–2209, https://doi.org/10.5194/bg-19-2187-2022, https://doi.org/10.5194/bg-19-2187-2022, 2022
Short summary
Short summary
We analysed the evolution of model parameter uncertainty and prediction error as we updated parameters of a maize phenology model based on yearly observations, by sequentially applying Bayesian calibration. Although parameter uncertainty was reduced, prediction quality deteriorated when calibration and prediction data were from different maize ripening groups or temperature conditions. The study highlights that Bayesian methods should account for model limitations and inherent data structures.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
Short summary
Short summary
The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
Michael Peichl, Stephan Thober, Luis Samaniego, Bernd Hansjürgens, and Andreas Marx
Hydrol. Earth Syst. Sci., 25, 6523–6545, https://doi.org/10.5194/hess-25-6523-2021, https://doi.org/10.5194/hess-25-6523-2021, 2021
Short summary
Short summary
Using a statistical model that can also take complex systems into account, the most important factors affecting wheat yield in Germany are determined. Different spatial damage potentials are taken into account. In many parts of Germany, yield losses are caused by too much soil water in spring. Negative heat effects as well as damaging soil drought are identified especially for north-eastern Germany. The model is able to explain years with exceptionally high yields (2014) and losses (2003, 2018).
Joni Dehaspe, Fanny Sarrazin, Rohini Kumar, Jan H. Fleckenstein, and Andreas Musolff
Hydrol. Earth Syst. Sci., 25, 6437–6463, https://doi.org/10.5194/hess-25-6437-2021, https://doi.org/10.5194/hess-25-6437-2021, 2021
Short summary
Short summary
Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low-frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
Nicolas Gasset, Vincent Fortin, Milena Dimitrijevic, Marco Carrera, Bernard Bilodeau, Ryan Muncaster, Étienne Gaborit, Guy Roy, Nedka Pentcheva, Maxim Bulat, Xihong Wang, Radenko Pavlovic, Franck Lespinas, Dikra Khedhaouiria, and Juliane Mai
Hydrol. Earth Syst. Sci., 25, 4917–4945, https://doi.org/10.5194/hess-25-4917-2021, https://doi.org/10.5194/hess-25-4917-2021, 2021
Short summary
Short summary
In this paper, we highlight the importance of including land-data assimilation as well as offline precipitation analysis components in a regional reanalysis system. We also document the performance of the first multidecadal 10 km reanalysis performed with the GEM atmospheric model that can be used for seamless land-surface and hydrological modelling in North America. It is of particular interest for transboundary basins, as existing datasets often show discontinuities at the border.
Camelia-Eliza Telteu, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, Lauren Seaby Andersen, Manolis Grillakis, Simon Newland Gosling, Yusuke Satoh, Oldrich Rakovec, Tobias Stacke, Jinfeng Chang, Niko Wanders, Harsh Lovekumar Shah, Tim Trautmann, Ganquan Mao, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Luis Samaniego, Yoshihide Wada, Vimal Mishra, Junguo Liu, Petra Döll, Fang Zhao, Anne Gädeke, Sam S. Rabin, and Florian Herz
Geosci. Model Dev., 14, 3843–3878, https://doi.org/10.5194/gmd-14-3843-2021, https://doi.org/10.5194/gmd-14-3843-2021, 2021
Short summary
Short summary
We analyse water storage compartments, water flows, and human water use sectors included in 16 global water models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b. We develop a standard writing style for the model equations. We conclude that even though hydrologic processes are often based on similar equations, in the end these equations have been adjusted, or the models have used different values for specific parameters or specific variables.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
Short summary
Short summary
Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Juliane Mai, James R. Craig, and Bryan A. Tolson
Hydrol. Earth Syst. Sci., 24, 5835–5858, https://doi.org/10.5194/hess-24-5835-2020, https://doi.org/10.5194/hess-24-5835-2020, 2020
Miao Jing, Rohini Kumar, Falk Heße, Stephan Thober, Oldrich Rakovec, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 24, 1511–1526, https://doi.org/10.5194/hess-24-1511-2020, https://doi.org/10.5194/hess-24-1511-2020, 2020
Short summary
Short summary
This study investigates the response of regional groundwater system to the climate change under three global warming levels (1.5, 2, and 3 °C) in a central German basin. A comprehensive uncertainty analysis is also presented. This study indicates that the variability of responses increases with the amount of global warming, which might affect the cost of managing the groundwater system.
Sophie Ehrhardt, Rohini Kumar, Jan H. Fleckenstein, Sabine Attinger, and Andreas Musolff
Hydrol. Earth Syst. Sci., 23, 3503–3524, https://doi.org/10.5194/hess-23-3503-2019, https://doi.org/10.5194/hess-23-3503-2019, 2019
Short summary
Short summary
This study shows quantitative and temporal offsets between nitrogen input and riverine output, using time series of three nested catchments in central Germany. The riverine concentrations show lagged reactions to the input, but at the same time exhibit strong inter-annual changes in the relationship between riverine discharge and concentration. The study found a strong retention of nitrogen that is dominantly assigned to a hydrological N legacy, which will affect future stream concentrations.
Naoki Mizukami, Oldrich Rakovec, Andrew J. Newman, Martyn P. Clark, Andrew W. Wood, Hoshin V. Gupta, and Rohini Kumar
Hydrol. Earth Syst. Sci., 23, 2601–2614, https://doi.org/10.5194/hess-23-2601-2019, https://doi.org/10.5194/hess-23-2601-2019, 2019
Short summary
Short summary
We find that Nash–Sutcliffe (NSE)-based model calibrations result in poor reproduction of high-flow events, such as the annual peak flows that are used for flood frequency estimation. The use of Kling–Gupta efficiency (KGE) results in annual peak flow estimates that are better than from NSE, with only a slight degradation in performance with respect to other related metrics.
Miao Jing, Falk Heße, Rohini Kumar, Olaf Kolditz, Thomas Kalbacher, and Sabine Attinger
Hydrol. Earth Syst. Sci., 23, 171–190, https://doi.org/10.5194/hess-23-171-2019, https://doi.org/10.5194/hess-23-171-2019, 2019
Short summary
Short summary
We evaluated the uncertainty propagation from the inputs (forcings) and parameters to the predictions of groundwater travel time distributions (TTDs) using a fully distributed numerical model (mHM-OGS) and the StorAge Selection (SAS) function. Through detailed numerical and analytical investigations, we emphasize the key role of recharge estimation in the reliable predictions of TTDs and the good interpretability of the SAS function.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Vanessa Haverd, Benjamin Smith, Lars Nieradzik, Peter R. Briggs, William Woodgate, Cathy M. Trudinger, Josep G. Canadell, and Matthias Cuntz
Geosci. Model Dev., 11, 2995–3026, https://doi.org/10.5194/gmd-11-2995-2018, https://doi.org/10.5194/gmd-11-2995-2018, 2018
Short summary
Short summary
CABLE is a terrestrial biosphere model that can be applied stand-alone and provides for land surface–atmosphere exchange within a climate model. We extend CABLE for regional and global carbon–climate simulations, accounting for land use and land cover change mediated by tree demography. A novel algorithm to simulate the coordination of rate-limiting photosynthetic processes is also implemented. Simulations satisfy multiple observational constraints on the global land carbon cycle.
Miao Jing, Falk Heße, Rohini Kumar, Wenqing Wang, Thomas Fischer, Marc Walther, Matthias Zink, Alraune Zech, Luis Samaniego, Olaf Kolditz, and Sabine Attinger
Geosci. Model Dev., 11, 1989–2007, https://doi.org/10.5194/gmd-11-1989-2018, https://doi.org/10.5194/gmd-11-1989-2018, 2018
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
Michael Peichl, Stephan Thober, Volker Meyer, and Luis Samaniego
Nat. Hazards Earth Syst. Sci., 18, 889–906, https://doi.org/10.5194/nhess-18-889-2018, https://doi.org/10.5194/nhess-18-889-2018, 2018
Short summary
Short summary
Crop yields are routinely derived from meteorological variables, especially temperature. However, the primary water source for plant growth (soil moisture) is neglected. In this study, the predictability of maize yield is investigated using soil moisture or meteorological variables in Germany. The effects of soil moisture dominate those of temperature and are time-dependent. For example, comparatively moist soil conditions in June reduce crop yields, while in August they increase yields.
Mehmet C. Demirel, Juliane Mai, Gorka Mendiguren, Julian Koch, Luis Samaniego, and Simon Stisen
Hydrol. Earth Syst. Sci., 22, 1299–1315, https://doi.org/10.5194/hess-22-1299-2018, https://doi.org/10.5194/hess-22-1299-2018, 2018
Short summary
Short summary
Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
Raneem Madi, Gerrit Huibert de Rooij, Henrike Mielenz, and Juliane Mai
Hydrol. Earth Syst. Sci., 22, 1193–1219, https://doi.org/10.5194/hess-22-1193-2018, https://doi.org/10.5194/hess-22-1193-2018, 2018
Short summary
Short summary
Water flows through soils with more difficulty when the soil is dried out. Scant rainfall in deserts may therefore result in a seemingly wet soil, but the water will often not penetrate deeply enough to replenish the groundwater. We compared the mathematical functions that describe how well different soils hold their water and found that only a few of them are realistic. The function one chooses to model the soil can have a large impact on the estimate of groundwater recharge.
Andreas Marx, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Niko Wanders, Matthias Zink, Eric F. Wood, Ming Pan, Justin Sheffield, and Luis Samaniego
Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, https://doi.org/10.5194/hess-22-1017-2018, 2018
Short summary
Short summary
Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.
Simon Höllering, Jan Wienhöfer, Jürgen Ihringer, Luis Samaniego, and Erwin Zehe
Hydrol. Earth Syst. Sci., 22, 203–220, https://doi.org/10.5194/hess-22-203-2018, https://doi.org/10.5194/hess-22-203-2018, 2018
Short summary
Short summary
Hydrological fingerprints are introduced as response targets for sensitivity analysis and combined with a conventional approach using streamflow data for a temporally resolved sensitivity analysis. The joint benefit of both approaches is presented for several headwater catchments. The approach allows discerning a clarified pattern for parameter influences pinpointed to diverse response characteristics and detecting even slight regional differences.
Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, https://doi.org/10.5194/hess-21-5009-2017, 2017
Short summary
Short summary
A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.
Luis Samaniego, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Matthias Zink, Niko Wanders, Stephanie Eisner, Hannes Müller Schmied, Edwin H. Sutanudjaja, Kirsten Warrach-Sagi, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, https://doi.org/10.5194/hess-21-4323-2017, 2017
Short summary
Short summary
We inspect the state-of-the-art of several land surface (LSMs) and hydrologic models (HMs) and show that most do not have consistent and realistic parameter fields for land surface geophysical properties. We propose to use the multiscale parameter regionalization (MPR) technique to solve, at least partly, the scaling problem in LSMs/HMs. A general model protocol is presented to describe how MPR can be applied to a specific model.
Christa D. Peters-Lidard, Martyn Clark, Luis Samaniego, Niko E. C. Verhoest, Tim van Emmerik, Remko Uijlenhoet, Kevin Achieng, Trenton E. Franz, and Ross Woods
Hydrol. Earth Syst. Sci., 21, 3701–3713, https://doi.org/10.5194/hess-21-3701-2017, https://doi.org/10.5194/hess-21-3701-2017, 2017
Short summary
Short summary
In this synthesis of hydrologic scaling and similarity, we assert that it is time for hydrology to embrace a fourth paradigm of data-intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modeling, have laid the foundation for a data-driven framework for scrutinizing hydrological hypotheses. We call upon the community to develop a focused effort towards a fourth paradigm for hydrology.
Martyn P. Clark, Marc F. P. Bierkens, Luis Samaniego, Ross A. Woods, Remko Uijlenhoet, Katrina E. Bennett, Valentijn R. N. Pauwels, Xitian Cai, Andrew W. Wood, and Christa D. Peters-Lidard
Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, https://doi.org/10.5194/hess-21-3427-2017, 2017
Short summary
Short summary
The diversity in hydrologic models has led to controversy surrounding the “correct” approach to hydrologic modeling. In this paper we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, summarize modeling advances that address these challenges, and define outstanding research needs.
Arndt Piayda, Maren Dubbert, Rolf Siegwolf, Matthias Cuntz, and Christiane Werner
Biogeosciences, 14, 2293–2306, https://doi.org/10.5194/bg-14-2293-2017, https://doi.org/10.5194/bg-14-2293-2017, 2017
Short summary
Short summary
Complex plant–soil interactions in the hydrological cycle of a Mediterranean cork oak ecosystem are investigated with stable water isotopes. Trees largely foster infiltration due to altered microclimatic conditions below crowns but compete with understorey plants for the same water source in deeper soil layers. The presence of understorey plants does not alter water losses compared to bare soil, but water utilization for carbon sequestration and nitrogen fixation is largely increased.
Gabriele Baroni, Matthias Zink, Rohini Kumar, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 2301–2320, https://doi.org/10.5194/hess-21-2301-2017, https://doi.org/10.5194/hess-21-2301-2017, 2017
Short summary
Short summary
Three methods are used to characterize the uncertainty in soil properties. The effect on simulated states and fluxes is quantified using a distributed hydrological model. Different impacts are identified as function of the perturbation method, of the model outputs and of the spatio-temporal resolution. The study underlines the importance of a proper characterization of the uncertainty in soil properties for a correct assessment of their role and further improvements in the model application.
Anne F. Van Loon, Rohini Kumar, and Vimal Mishra
Hydrol. Earth Syst. Sci., 21, 1947–1971, https://doi.org/10.5194/hess-21-1947-2017, https://doi.org/10.5194/hess-21-1947-2017, 2017
Short summary
Short summary
Summer 2015 was extremely dry in Europe, hampering groundwater supply to irrigation and drinking water. For effective management, the groundwater situation should be monitored in real time, but data are not available. We tested two methods to estimate groundwater in near-real time, based on satellite data and using the relationship between rainfall and historic groundwater levels. The second method gave a good spatially variable representation of the 2015 groundwater drought in Europe.
Matthias Zink, Rohini Kumar, Matthias Cuntz, and Luis Samaniego
Hydrol. Earth Syst. Sci., 21, 1769–1790, https://doi.org/10.5194/hess-21-1769-2017, https://doi.org/10.5194/hess-21-1769-2017, 2017
Short summary
Short summary
We discuss the estimation of a long-term, high-resolution, continuous and consistent dataset of hydro-meteorological variables for Germany. Here we describe the derivation of national-scale parameter sets and analyze the uncertainty of the estimated hydrologic variables (focusing on the parametric uncertainty). Our study highlights the role of accounting for the parametric uncertainty in model-derived hydrological datasets.
Falk Heße, Matthias Zink, Rohini Kumar, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 549–570, https://doi.org/10.5194/hess-21-549-2017, https://doi.org/10.5194/hess-21-549-2017, 2017
Short summary
Short summary
Travel-time distributions are a comprehensive tool for the characterization of hydrological systems. In our study, we used data that were simulated by virtue of a well-established hydrological model. This gave us a very large yet realistic dataset, both in time and space, from which we could infer the relative impact of different factors on travel-time behavior. These were, in particular, meteorological (precipitation), land surface (land cover, leaf-area index) and subsurface (soil) properties.
Vanessa Haverd, Matthias Cuntz, Lars P. Nieradzik, and Ian N. Harman
Geosci. Model Dev., 9, 3111–3122, https://doi.org/10.5194/gmd-9-3111-2016, https://doi.org/10.5194/gmd-9-3111-2016, 2016
Short summary
Short summary
CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. We improve CABLE’s simulation of evaporation using a new scheme for drought response and a physically accurate representation of coupled energy and water fluxes in the soil. Marked improvements in predictions of evaporation are demonstrated globally. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.
Simon Höllering, Jürgen Ihringer, Luis Samaniego, and Erwin Zehe
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-249, https://doi.org/10.5194/hess-2016-249, 2016
Preprint withdrawn
Remko C. Nijzink, Luis Samaniego, Juliane Mai, Rohini Kumar, Stephan Thober, Matthias Zink, David Schäfer, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, https://doi.org/10.5194/hess-20-1151-2016, 2016
Short summary
Short summary
The heterogeneity of landscapes in river basins strongly affects the hydrological response. In this study, the distributed mesoscale Hydrologic Model (mHM) was equipped with additional processes identified by landscapes within one modelling cell. Seven study catchments across Europe were selected to test the value of this additional sub-grid heterogeneity. In addition, the models were constrained based on expert knowledge. Generally, the modifications improved the representation of low flows.
Rohini Kumar, Jude L. Musuuza, Anne F. Van Loon, Adriaan J. Teuling, Roland Barthel, Jurriaan Ten Broek, Juliane Mai, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 20, 1117–1131, https://doi.org/10.5194/hess-20-1117-2016, https://doi.org/10.5194/hess-20-1117-2016, 2016
Short summary
Short summary
In a maiden attempt, we performed a multiscale evaluation of the widely used SPI to characterize local- and regional-scale groundwater (GW) droughts using observations at 2040 groundwater wells in Germany and the Netherlands. From this data-based exploratory analysis, we provide sufficient evidence regarding the inability of the SPI to characterize GW drought events, and stress the need for more GW observations and accounting for regional hydrogeological characteristics in GW drought monitoring.
A. Piayda, M. Dubbert, C. Rebmann, O. Kolle, F. Costa e Silva, A. Correia, J. S. Pereira, C. Werner, and M. Cuntz
Biogeosciences, 11, 7159–7178, https://doi.org/10.5194/bg-11-7159-2014, https://doi.org/10.5194/bg-11-7159-2014, 2014
S. Gharari, M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4861–4870, https://doi.org/10.5194/hess-18-4861-2014, https://doi.org/10.5194/hess-18-4861-2014, 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
Related subject area
Hydrology
DECIPHeR-GW v1: a coupled hydrological model with improved representation of surface–groundwater interactions
Wastewater matters: incorporating wastewater treatment and reuse into a process-based hydrological model (CWatM v1.08)
A reach-integrated hydraulic modelling approach for large-scale and real-time inundation mapping
Graphical representation of global water models
LM4-SHARC v1.0: resolving the catchment-scale soil–hillslope aquifer–river continuum for the GFDL Earth system modeling framework
SWAT+MODFLOW: A New Hydrologic Model for Simulating Surface-Subsurface Flow in Managed Watersheds
The Process and Value of Reprogramming a Legacy Global Hydrological Model
Selecting a conceptual hydrological model using Bayes' factors computed with replica-exchange Hamiltonian Monte Carlo and thermodynamic integration
SMASH v1.0: A Differentiable and Regionalizable High-Resolution Hydrological Modeling and Data Assimilation Framework
The Water Table Model (WTM) (v2.0.1): coupled groundwater and dynamic lake modelling
Modelling rainfall with a Bartlett–Lewis process: pyBL (v1.0.0), a Python software package and an application with short records
Virtual Joint Field Campaign: a framework of synthetic landscapes to assess multiscale measurement methods of water storage
SERGHEI v2.0: introducing a performance-portable, high-performance, three-dimensional variably saturated subsurface flow solver (SERGHEI-RE)
A component based modular treatment of the soil-plant-atmosphere continuum: the GEOSPACE framework (v.1.2.9)
Fitting the junction model and other parameterizations for the unsaturated soil hydraulic conductivity curve: KRIAfitter version 1.0
The global water resources and use model WaterGAP v2.2e: description and evaluation of modifications and new features
Generalised drought index: a novel multi-scale daily approach for drought assessment
Development and performance of a high-resolution surface wave and storm surge forecast model: application to a large lake
Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models (δHBV-globe1.0-hydroDL)
PyEt v1.3.1: a Python package for the estimation of potential evapotranspiration
Prediction of hysteretic matric potential dynamics using artificial intelligence: application of autoencoder neural networks
Regionalization in global hydrological models and its impact on runoff simulations: a case study using WaterGAP3 (v 1.0.0)
PyGLDA: a fine-scale Python-based Global Land Data Assimilation system for integrating satellite gravity data into hydrological models
STORM v.2: A simple, stochastic rainfall model for exploring the impacts of climate and climate change at and near the land surface in gauged watersheds
Fluvial flood inundation and socio-economic impact model based on open data
RoGeR v3.0.5 – a process-based hydrological toolbox model in Python
Coupling a large-scale glacier and hydrological model (OGGM v1.5.3 and CWatM V1.08) – towards an improved representation of mountain water resources in global assessments
An open-source refactoring of the Canadian Small Lakes Model for estimates of evaporation from medium-sized reservoirs
EvalHyd v0.1.2: a polyglot tool for the evaluation of deterministic and probabilistic streamflow predictions
Modelling water quantity and quality for integrated water cycle management with the Water Systems Integrated Modelling framework (WSIMOD) software
HGS-PDAF (version 1.0): a modular data assimilation framework for an integrated surface and subsurface hydrological model
Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications
Reservoir Assessment Tool version 3.0: a scalable and user-friendly software platform to mobilize the global water management community
HydroFATE (v1): a high-resolution contaminant fate model for the global river system
Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2
GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications
GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers
mesas.py v1.0: a flexible Python package for modeling solute transport and transit times using StorAge Selection functions
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model
Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information
Representing the impact of Rhizophora mangroves on flow in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification
Enhancing the representation of water management in global hydrological models
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris E. Wendt
Geosci. Model Dev., 18, 4247–4271, https://doi.org/10.5194/gmd-18-4247-2025, https://doi.org/10.5194/gmd-18-4247-2025, 2025
Short summary
Short summary
Groundwater is vital for people and ecosystems, but most physical models lack the representation of surface–groundwater interactions, leading to inaccurate streamflow predictions in groundwater-rich areas. This study presents DECIPHeR-GW v1, which links surface and groundwater systems to improve predictions of streamflow and groundwater levels. Tested across England and Wales, DECIPHeR-GW shows high accuracy, especially in southeast England, making it a valuable tool for large-scale water management.
Dor Fridman, Mikhail Smilovic, Peter Burek, Sylvia Tramberend, and Taher Kahil
Geosci. Model Dev., 18, 3735–3754, https://doi.org/10.5194/gmd-18-3735-2025, https://doi.org/10.5194/gmd-18-3735-2025, 2025
Short summary
Short summary
Global hydrological models are applied at high spatial resolutions to quantify water availability and evaluate water scarcity mitigation options. Yet, they mainly oversee critical local processes. This paper presents and demonstrates the inclusion of wastewater treatment and reuse into a global hydrological model. As a result, model performance improves, and models consider treated wastewater as an alternative water source.
Robert Chlumsky, James R. Craig, and Bryan A. Tolson
Geosci. Model Dev., 18, 3387–3403, https://doi.org/10.5194/gmd-18-3387-2025, https://doi.org/10.5194/gmd-18-3387-2025, 2025
Short summary
Short summary
We aim to improve mapping of floods and present a new method for hydraulic modelling that uses a combination of novel geospatial analysis and existing hydraulic modelling approaches. This method is wrapped into a modelling software called Blackbird. We compared Blackbird with two other existing options for flood mapping and found that the Blackbird model outperformed both. The Blackbird model has the potential to support real-time and large-scale flood mapping applications in the future.
Hannes Müller Schmied, Simon Newland Gosling, Marlo Garnsworthy, Laura Müller, Camelia-Eliza Telteu, Atiq Kainan Ahmed, Lauren Seaby Andersen, Julien Boulange, Peter Burek, Jinfeng Chang, He Chen, Lukas Gudmundsson, Manolis Grillakis, Luca Guillaumot, Naota Hanasaki, Aristeidis Koutroulis, Rohini Kumar, Guoyong Leng, Junguo Liu, Xingcai Liu, Inga Menke, Vimal Mishra, Yadu Pokhrel, Oldrich Rakovec, Luis Samaniego, Yusuke Satoh, Harsh Lovekumar Shah, Mikhail Smilovic, Tobias Stacke, Edwin Sutanudjaja, Wim Thiery, Athanasios Tsilimigkras, Yoshihide Wada, Niko Wanders, and Tokuta Yokohata
Geosci. Model Dev., 18, 2409–2425, https://doi.org/10.5194/gmd-18-2409-2025, https://doi.org/10.5194/gmd-18-2409-2025, 2025
Short summary
Short summary
Global water models contribute to the evaluation of important natural and societal issues but are – as all models – simplified representation of reality. So, there are many ways to calculate the water fluxes and storages. This paper presents a visualization of 16 global water models using a standardized visualization and the pathway towards this common understanding. Next to academic education purposes, we envisage that these diagrams will help researchers, model developers, and data users.
Minki Hong, Nathaniel Chaney, Sergey Malyshev, Enrico Zorzetto, Anthony Preucil, and Elena Shevliakova
Geosci. Model Dev., 18, 2275–2301, https://doi.org/10.5194/gmd-18-2275-2025, https://doi.org/10.5194/gmd-18-2275-2025, 2025
Short summary
Short summary
This study shows the significance of groundwater in resolving the coupled terrestrial water–energy cycle. LM4-SHARC (soil–hillslope aquifer–river continuum) describes the hillslope groundwater using its emergent properties, yielding noticeable improvements in soil moisture/temperature and groundwater discharge predictions. The implications of groundwater-mediated hydrologic interactions between hillslopes and streams need further exploration in the Earth system modeling community.
Ryan Bailey, Salam Abbas, Jeffrey Arnold, and Michael White
EGUsphere, https://doi.org/10.5194/egusphere-2025-300, https://doi.org/10.5194/egusphere-2025-300, 2025
Short summary
Short summary
Water managers often make use of computer models to assess a region’s water supply under future conditions and management scenarios. This article introduces a new computer model that combines a land surface model (SWAT+) and a groundwater model (MODFLOW) and shows how it can be applied to managed, irrigated watersheds. This new model can be used for regions that rely on both surface water and groundwater for drinking water, agriculture, and industry.
Emmanuel Nyenah, Petra Döll, Martina Flörke, Leon Mühlenbruch, Lasse Nissen, and Robert Reinecke
EGUsphere, https://doi.org/10.5194/egusphere-2025-1096, https://doi.org/10.5194/egusphere-2025-1096, 2025
Short summary
Short summary
We reprogrammed the latest WaterGAP model (2.2e) to create a sustainable global hydrological model. By utilizing best software practices like modular design, version control, and clear documentation, the new WaterGAP supports collaboration across teams. It can be easily understood, applied, and enhanced by both novice and experienced modellers. Additionally, we share the reprogramming process to assist in the reprogramming of other large geoscientific research software.
Damian N. Mingo, Remko Nijzink, Christophe Ley, and Jack S. Hale
Geosci. Model Dev., 18, 1709–1736, https://doi.org/10.5194/gmd-18-1709-2025, https://doi.org/10.5194/gmd-18-1709-2025, 2025
Short summary
Short summary
Hydrologists are often faced with selecting amongst a set of competing models with different numbers of parameters and ability to fit available data. Bayes’ factor is a tool that can be used to compare models; however, it is very difficult to compute Bayes' factor numerically. In our paper, we explore and develop highly efficient algorithms for computing Bayes’ factor of hydrological systems, which will introduce this useful tool for selecting models into everyday hydrological practice.
François Colleoni, Ngo Nghi Truyen Huynh, Pierre-André Garambois, Maxime Jay-Allemand, Didier Organde, Benjamin Renard, Thomas De Fournas, Apolline El Baz, Julie Demargne, and Pierre Javelle
EGUsphere, https://doi.org/10.5194/egusphere-2025-690, https://doi.org/10.5194/egusphere-2025-690, 2025
Short summary
Short summary
We present smash, an open-source framework for high-resolution hydrological modeling and data assimilation. It combines process-based models with neural networks for regionalization, enabling accurate simulations from catchment to country scale. With an efficient, differentiable solver, smash supports large-scale calibration and parallel computing. Tested on open datasets, it shows strong performance in river flow prediction, making it a valuable tool for research and operational use.
Kerry L. Callaghan, Andrew D. Wickert, Richard Barnes, and Jacqueline Austermann
Geosci. Model Dev., 18, 1463–1486, https://doi.org/10.5194/gmd-18-1463-2025, https://doi.org/10.5194/gmd-18-1463-2025, 2025
Short summary
Short summary
We present the Water Table Model (WTM), a new model for simulating groundwater and lake levels at continental scales over millennia. The WTM enables long-term evaluations of water-table changes. As a proof of concept, we simulate the North American water table for the present and the Last Glacial Maximum (LGM), showing that North America held more groundwater and lake water during the LGM than it does today – enough to lower sea levels by 14.98 cm. The open-source code is available on GitHub.
Chi-Ling Wei, Pei-Chun Chen, Chien-Yu Tseng, Ting-Yu Dai, Yun-Ting Ho, Ching-Chun Chou, Christian Onof, and Li-Pen Wang
Geosci. Model Dev., 18, 1357–1373, https://doi.org/10.5194/gmd-18-1357-2025, https://doi.org/10.5194/gmd-18-1357-2025, 2025
Short summary
Short summary
pyBL is an open-source package for generating realistic rainfall time series based on the Bartlett–Lewis (BL) model. It can preserve not only standard but also extreme rainfall statistics across various timescales. Notably, compared to traditional frequency analysis methods, the BL model requires only half the record length (or even shorter) to achieve similar consistency in estimating sub-hourly rainfall extremes. This makes it a valuable tool for modelling rainfall extremes with short records.
Till Francke, Cosimo Brogi, Alby Duarte Rocha, Michael Förster, Maik Heistermann, Markus Köhli, Daniel Rasche, Marvin Reich, Paul Schattan, Lena Scheiffele, and Martin Schrön
Geosci. Model Dev., 18, 819–842, https://doi.org/10.5194/gmd-18-819-2025, https://doi.org/10.5194/gmd-18-819-2025, 2025
Short summary
Short summary
Multiple methods for measuring soil moisture beyond the point scale exist. Their validation is generally hindered by not knowing the truth. We propose a virtual framework in which this truth is fully known and the sensor observations for cosmic ray neutron sensing, remote sensing, and hydrogravimetry are simulated. This allows for the rigorous testing of these virtual sensors to understand their effectiveness and limitations.
Zhi Li, Gregor Rickert, Na Zheng, Zhibo Zhang, Ilhan Özgen-Xian, and Daniel Caviedes-Voullième
Geosci. Model Dev., 18, 547–562, https://doi.org/10.5194/gmd-18-547-2025, https://doi.org/10.5194/gmd-18-547-2025, 2025
Short summary
Short summary
We introduce SERGHEI-RE, a 3D subsurface flow simulator with performance-portable parallel computing capabilities. SERGHEI-RE performs effectively on various computational devices: from personal computers to advanced clusters. It allows users to solve flow equations with multiple numerical schemes, making it adaptable to various hydrological scenarios. Testing results show its accuracy and performance, confirming that SERGHEI-RE is a powerful tool for hydrological research.
Concetta D'Amato, Niccolò Tubini, and Riccardo Rigon
EGUsphere, https://doi.org/10.5194/egusphere-2024-4128, https://doi.org/10.5194/egusphere-2024-4128, 2025
Short summary
Short summary
This paper presents GEOSPACE and its 1D implementation: an open-source tool for simulating soil-plant-atmosphere continuum (SPAC) interactions. Using object-oriented programming, GEOSPACE modularizes SPAC processes, focusing on infiltration, evapotranspiration, and root water uptake. The 1D deployment integrates plant transpiration, soil evaporation, and root growth, providing a flexible and validated framework for ecohydrological modeling and applications.
Gerrit Huibert de Rooij
EGUsphere, https://doi.org/10.5194/egusphere-2024-3487, https://doi.org/10.5194/egusphere-2024-3487, 2025
Short summary
Short summary
Water flows ever more slowly in soil when the soil dries out. This can be described by the conductivity curve that accounts for water filling up small spaces, sticking to grains if films, and water vapour diffusion. This paper introduces a relatively simple model for this curve that needs one parameter less then most others. It works well for most soils, but some need the extra parameter. The paper also presents a computer program to determine the parameter values of this and other models.
Hannes Müller Schmied, Tim Trautmann, Sebastian Ackermann, Denise Cáceres, Martina Flörke, Helena Gerdener, Ellen Kynast, Thedini Asali Peiris, Leonie Schiebener, Maike Schumacher, and Petra Döll
Geosci. Model Dev., 17, 8817–8852, https://doi.org/10.5194/gmd-17-8817-2024, https://doi.org/10.5194/gmd-17-8817-2024, 2024
Short summary
Short summary
Assessing water availability and water use at the global scale is challenging but essential for a range of purposes. We describe the newest version of the global hydrological model WaterGAP, which has been used for numerous water resource assessments since 1996. We show the effects of new model features, as well as model evaluations, against water abstraction statistics and observed streamflow and water storage anomalies. The publicly available model output for several variants is described.
João António Martins Careto, Rita Margarida Cardoso, Ana Russo, Daniela Catarina André Lima, and Pedro Miguel Matos Soares
Geosci. Model Dev., 17, 8115–8139, https://doi.org/10.5194/gmd-17-8115-2024, https://doi.org/10.5194/gmd-17-8115-2024, 2024
Short summary
Short summary
This study proposes a new daily drought index, the generalised drought index (GDI). The GDI not only identifies the same events as established indices but is also capable of improving their results. The index is empirically based and easy to compute, not requiring fitting the data to a probability distribution. The GDI can detect flash droughts and longer-term events, making it a versatile tool for drought monitoring.
Laura L. Swatridge, Ryan P. Mulligan, Leon Boegman, and Shiliang Shan
Geosci. Model Dev., 17, 7751–7766, https://doi.org/10.5194/gmd-17-7751-2024, https://doi.org/10.5194/gmd-17-7751-2024, 2024
Short summary
Short summary
We develop an operational forecast system, Coastlines-LO, that can simulate water levels and surface waves in Lake Ontario driven by forecasts of wind speeds and pressure fields from an atmospheric model. The model has relatively low computational requirements, and results compare well with near-real-time observations, as well as with results from other existing forecast systems. Results show that with shorter forecast lengths, storm surge and wave predictions can improve in accuracy.
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 17, 7181–7198, https://doi.org/10.5194/gmd-17-7181-2024, https://doi.org/10.5194/gmd-17-7181-2024, 2024
Short summary
Short summary
Accurate hydrologic modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall–runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional modeling approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
Matevž Vremec, Raoul A. Collenteur, and Steffen Birk
Geosci. Model Dev., 17, 7083–7103, https://doi.org/10.5194/gmd-17-7083-2024, https://doi.org/10.5194/gmd-17-7083-2024, 2024
Short summary
Short summary
Geoscientists commonly use various potential evapotranpiration (PET) formulas for environmental studies, which can be prone to errors and sensitive to climate change. PyEt, a tested and open-source Python package, simplifies the application of 20 PET methods for both time series and gridded data, ensuring accurate and consistent PET estimations suitable for a wide range of environmental applications.
Nedal Aqel, Lea Reusser, Stephan Margreth, Andrea Carminati, and Peter Lehmann
Geosci. Model Dev., 17, 6949–6966, https://doi.org/10.5194/gmd-17-6949-2024, https://doi.org/10.5194/gmd-17-6949-2024, 2024
Short summary
Short summary
The soil water potential (SWP) determines various soil water processes. Since remote sensing techniques cannot measure it directly, it is often deduced from volumetric water content (VWC) information. However, under dynamic field conditions, the relationship between SWP and VWC is highly ambiguous due to different factors that cannot be modeled with the classical approach. Applying a deep neural network with an autoencoder enables the prediction of the dynamic SWP.
Jenny Kupzig, Nina Kupzig, and Martina Flörke
Geosci. Model Dev., 17, 6819–6846, https://doi.org/10.5194/gmd-17-6819-2024, https://doi.org/10.5194/gmd-17-6819-2024, 2024
Short summary
Short summary
Valid simulation results from global hydrological models (GHMs) are essential, e.g., to studying climate change impacts. Adapting GHMs to ungauged basins requires regionalization, enabling valid simulations. In this study, we highlight the impact of regionalization of GHMs on runoff simulations using an ensemble of regionalization methods for WaterGAP3. We have found that regionalization leads to temporally and spatially varying uncertainty, potentially reaching up to inter-model differences.
Fan Yang, Maike Schumacher, Leire Retegui-Schiettekatte, Albert I. J. M. van Dijk, and Ehsan Forootan
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-125, https://doi.org/10.5194/gmd-2024-125, 2024
Short summary
Short summary
The satellite gravimetry can provide direct measurement of total water storage (TWS) that was never achieved before. In this study, we provide an open-source assimilation system to show how the satellite based TWS can be temporally, vertically and laterally disaggregated for constraining/validating/improving the global hydrological models. With this system, early warning and water management at a global scale would be more accurate, given the upcoming next-generation satellite gravity missions.
Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev., 17, 5387–5412, https://doi.org/10.5194/gmd-17-5387-2024, https://doi.org/10.5194/gmd-17-5387-2024, 2024
Short summary
Short summary
STORM v.2 (short for STOchastic Rainfall Model version 2.0) is an open-source and user-friendly modelling framework for simulating rainfall fields over a basin. It also allows simulating the impact of plausible climate change either on the total seasonal rainfall or the storm’s maximum intensity.
Lukas Riedel, Thomas Röösli, Thomas Vogt, and David N. Bresch
Geosci. Model Dev., 17, 5291–5308, https://doi.org/10.5194/gmd-17-5291-2024, https://doi.org/10.5194/gmd-17-5291-2024, 2024
Short summary
Short summary
River floods are among the most devastating natural hazards. We propose a flood model with a statistical approach based on openly available data. The model is integrated in a framework for estimating impacts of physical hazards. Although the model only agrees moderately with satellite-detected flood extents, we show that it can be used for forecasting the magnitude of flood events in terms of socio-economic impacts and for comparing these with past events.
Robin Schwemmle, Hannes Leistert, Andreas Steinbrich, and Markus Weiler
Geosci. Model Dev., 17, 5249–5262, https://doi.org/10.5194/gmd-17-5249-2024, https://doi.org/10.5194/gmd-17-5249-2024, 2024
Short summary
Short summary
The new process-based hydrological toolbox model, RoGeR (https://roger.readthedocs.io/), can be used to estimate the components of the hydrological cycle and the related travel times of pollutants through parts of the hydrological cycle. These estimations may contribute to effective water resources management. This paper presents the toolbox concept and provides a simple example of providing estimations to water resources management.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
Short summary
Short summary
This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
M. Graham Clark and Sean K. Carey
Geosci. Model Dev., 17, 4911–4922, https://doi.org/10.5194/gmd-17-4911-2024, https://doi.org/10.5194/gmd-17-4911-2024, 2024
Short summary
Short summary
This paper provides validation of the Canadian Small Lakes Model (CSLM) for estimating evaporation rates from reservoirs and a refactoring of the original FORTRAN code into MATLAB and Python, which are now stored in GitHub repositories. Here we provide direct observations of the surface energy exchange obtained with an eddy covariance system to validate the CSLM. There was good agreement between observations and estimations except under specific atmospheric conditions when evaporation is low.
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
Short summary
Short summary
The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Barnaby Dobson, Leyang Liu, and Ana Mijic
Geosci. Model Dev., 17, 4495–4513, https://doi.org/10.5194/gmd-17-4495-2024, https://doi.org/10.5194/gmd-17-4495-2024, 2024
Short summary
Short summary
Water management is challenging when models don't capture the entire water cycle. We propose that using integrated models facilitates management and improves understanding. We introduce a software tool designed for this task. We discuss its foundation, how it simulates water system components and their interactions, and its customisation. We provide a flexible way to represent water systems, and we hope it will inspire more research and practical applications for sustainable water management.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev., 17, 3559–3578, https://doi.org/10.5194/gmd-17-3559-2024, https://doi.org/10.5194/gmd-17-3559-2024, 2024
Short summary
Short summary
We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model; its large selection of different assimilation algorithms; and its modularity with respect to the combination of different types of observations, states and parameters.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
Short summary
Short summary
We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
Short summary
Short summary
The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
Geosci. Model Dev., 17, 2877–2899, https://doi.org/10.5194/gmd-17-2877-2024, https://doi.org/10.5194/gmd-17-2877-2024, 2024
Short summary
Short summary
Treated and untreated wastewaters are sources of contaminants of emerging concern. HydroFATE, a new global model, estimates their concentrations in surface waters, identifying streams that are most at risk and guiding monitoring/mitigation efforts to safeguard aquatic ecosystems and human health. Model predictions were validated against field measurements of the antibiotic sulfamethoxazole, with predicted concentrations exceeding ecological thresholds in more than 400 000 km of rivers worldwide.
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024, https://doi.org/10.5194/gmd-17-2141-2024, 2024
Short summary
Short summary
We show a new irrigation scheme included in the ORCHIDEE land surface model. The new irrigation scheme restrains irrigation due to water shortage, includes water adduction, and represents environmental limits and facilities to access water, due to representing infrastructure in a simple way. Our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, even if there are difficulties due to shortcomings and limited information.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
Short summary
Short summary
Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
Short summary
Short summary
We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024, https://doi.org/10.5194/gmd-17-477-2024, 2024
Short summary
Short summary
Over the last 10 years, scientists have developed StorAge Selection: a new way of modeling how material is transported through complex systems. Here, we present some new, easy-to-use, flexible, and very accurate code for implementing this method. We show that, in cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other codes to the right answer in an important way: it conserves mass.
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
Short summary
Short summary
Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
Short summary
Short summary
This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
Short summary
Short summary
We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Daniel Boateng and Sebastian G. Mutz
Geosci. Model Dev., 16, 6479–6514, https://doi.org/10.5194/gmd-16-6479-2023, https://doi.org/10.5194/gmd-16-6479-2023, 2023
Short summary
Short summary
We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
Short summary
Short summary
Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
Short summary
Short summary
Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
Short summary
Short summary
Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
Short summary
Short summary
NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
Short summary
Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
Short summary
Short summary
Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
Short summary
Short summary
DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
Short summary
Short summary
Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Cited articles
Bates, P. D., Horritt, M. S., and Fewtrell, T. J.: A simple inertial
formulation of the shallow water equations for efficient two-dimensional
flood inundation modelling, J. Hydrol., 387, 33–45,
https://doi.org/10.1016/j.jhydrol.2010.03.027, 2010. a
Beighley, R. E., Eggert, K. G., Dunne, T., He, Y., Gummadi, V., and Verdin,
K. L.: Simulating hydrologic and hydraulic processes throughout the Amazon
River Basin, Hydrol. Process., 23, 1221–1235, https://doi.org/10.1002/hyp.7252,
2009. a, b
Beighley, R. E., Ray, R. L., He, Y., Lee, H., Schaller, L., Andreadis, K. M.,
Durand, M., Alsdorf, D. E., and Shum, C. K.: Comparing satellite derived
precipitation datasets using the Hillslope River Routing (HRR) model in the
Congo River Basin, Hydrol. Process., 25, 3216–3229,
https://doi.org/10.1002/hyp.8045, 2011. a
Boone, A., Habets, F., Noilhan, J., Clark, D., Dirmeyer, P., Fox, S., Gusev,
Y., Haddeland, I., Koster, R., Lohmann, D., Mahanama, S., Mitchell, K.,
Nasonova, O., Niu, G. Y., Pitman, A., Polcher, J., Shmakin, A. B., Tanaka,
K., Van den Hurk, B., Vérant, S., Verseghy, D., Viterbo, P., and Yang,
Z. L.: The Rhône-Aggregation land surface scheme intercomparison
project: An overview, J. Climate, 17, 187–208,
https://doi.org/10.1175/1520-0442(2004)017<0187:TRLSSI>2.0.CO;2, 2004. a
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E., Woods,
R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Brekke, L. D., Arnold,
J. R., Gochis, D. J., and Rasmussen, R. M.: A unified approach for
process-based hydrologic modeling: 1. Modeling concept, Water Resour.
Res., 51, 2498–2514, https://doi.org/10.1002/2015WR017198, 2015. a, b
Coe, M. T.: Modeling terrestrial hydrological systems at the continental
scale: Testing the accuracy of an atmospheric GCM, J. Climate, 13,
686–704, https://doi.org/10.1175/1520-0442(2000)013<0686:MTHSAT>2.0.CO;2, 2000. a
Collischonn, W., Fleischmann, A., Paiva, R. C. D., and Mejia, A.: Hydraulic
Causes for Basin Hydrograph Skewness, Water Resour. Res., 53,
10603–10618, https://doi.org/10.1002/2017WR021543, 2017. a
Courant, R., Friedrichs, K., and Lewy, H.: Über die partiellen
Differenzengleichungen der mathematischen Physik, Math. Ann.,
100, 32–74, https://doi.org/10.1007/BF01448839, 1928. a
Cunge, J. A.: On The Subject Of A Flood Propagation Computation Method
(Muskingum Method), J. Hydraul. Res., 7, 205–230,
https://doi.org/10.1080/00221686909500264, 1969. a, b, c
David, C. H., Maidment, D. R., Niu, G.-Y., Yang, Z.-L., Habets, F., and
Eijkhout, V.: River Network Routing on the NHDPlus Dataset, J.
Hydrometeorol., 12, 913–934, https://doi.org/10.1175/2011JHM1345.1, 2011. a, b, c
de Saint-Venant, A. J. C. B.: Théorie du mouvement non permanent des eaux,
avec application aux crues des rivières et a l'introduction de marées
dans leurs lits, Comptes Rendus des Séances de lAcadémie des
Sciences, Gauthier-Villars, Paris, France, 73, 1–11, 1871. a
Döll, P. and Lehner, B.: Validation of a new global 30-min drainage
direction map, J. Hydrol., 258, 214–231,
https://doi.org/10.1016/S0022-1694(01)00565-0, 2002. a, b
Duan, Q., Sorooshian, S., and Gupta, V.: Effective and efficient global
optimization for conceptual rainfall-runoff models, Water Resour.
Res., 28, 1015–1031, https://doi.org/10.1029/91WR02985, 1992. a
Fleischmann, A. S., Paiva, R. C. D., Collischonn, W., Sorribas, M. V., and
Pontes, P. R. M.: On river-floodplain interaction and hydrograph skewness,
Water Resour. Res., 52, 7615–7630, https://doi.org/10.1002/2016WR019233, 2016. a
Getirana, A. C. V., Boone, A., Yamazaki, D., Decharme, B., Papa, F., and
Mognard, N.: The Hydrological Modeling and Analysis Platform (HyMAP):
Evaluation in the Amazon Basin, J. Hydrometeorol., 13, 1641–1665,
https://doi.org/10.1175/JHM-D-12-021.1, 2012. a, b, c
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of
the mean squared error and NSE performance criteria: Implications for
improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009. a, b, c
Haddeland, I., Matheussen, B. V., and Lettenmaier, D. P.: Influence of spatial
resolution on simulated streamflow in a macroscale hydrologic model, Water
Resour. Res., 38, 29-1–29-10, https://doi.org/10.1029/2001WR000854, 2002. a
Hagemann, S. and Dümenil, L.: A parametrization of the lateral waterflow
for the global scale, Clim. Dynam., 14, 17–31,
https://doi.org/10.1007/s003820050205, 1997. a, b, c, d
Hagemann, S., Göttel, H., Jacob, D., Lorenz, P., and Roeckner, E.:
Improved regional scale processes reflected in projected hydrological
changes over large European catchments, Clim. Dynam., 32, 767–781,
https://doi.org/10.1007/s00382-008-0403-9, 2009. a, b, c, d
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D.,
and New, M.: A European daily high-resolution gridded data set of surface
temperature and precipitation for 1950–2006, J.
Geophys. Res.-Atmos., 113, D20119,
https://doi.org/10.1029/2008JD010201, 2008. a, b, c
Jacob, D., van den Hurk, B. J. J. M., Andrae, U., Elgered, G., Fortelius, C.,
Graham, L. P., Jackson, S. D., Karstens, U., Köpken, C., Lindau, R.,
Podzun, R., Rockel, B., Rubel, F., Sass, B. H., Smith, R. N. B., and Yang,
X.: A comprehensive model inter-comparison study investigating the water
budget during the BALTEX-PIDCAP period, Meteorol. Atmos. Phys.,
77, 19–43, https://doi.org/10.1007/s007030170015, 2001. a
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer,
L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G.,
Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A.,
Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S.,
Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M.,
Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R.,
Vautard, R., Weber, B., and Yiou, P.: EURO-CORDEX: new high-resolution
climate change projections for European impact research, Reg.
Environ. Change, 14, 563–578, https://doi.org/10.1007/s10113-013-0499-2, 2014. a, b, c, d, e
Kollat, J. B., Reed, P. M., and Wagener, T.: When are multiobjective
calibration trade-offs in hydrologic models meaningful?, Water Resour.
Res., 48, W03520, https://doi.org/10.1029/2011WR011534, 2012. a
Kumar, R., Livneh, B., and Samaniego, L.: Toward computationally efficient
large-scale hydrologic predictions with a multiscale regionalization scheme,
Water Resour. Res., 49, 5700–5714, https://doi.org/10.1002/wrcr.20431,
2013a. a, b, c, d
Lehner, B., Verdin, K., and Jarvis, A.: New global hydrography derived from
spaceborne elevation data , Eos, Transactions, 89, 93–94, 2008. a
Li, H., Wigmosta, M. S., Wu, H., Huang, M., Ke, Y., Coleman, A. M., and Leung,
L. R.: A Physically Based Runoff Routing Model for Land Surface and Earth
System Models, J. Hydrometeorol., 14, 808–828,
https://doi.org/10.1175/JHM-D-12-015.1, 2013. a, b, c
Li, H.-Y., Leung, L. R., Getirana, A., Huang, M., Wu, H., Xu, Y., Guo, J., and
Voisin, N.: Evaluating Global Streamflow Simulations by a Physically Based
Routing Model Coupled with the Community Land Model, J.
Hydrometeorol., 16, 948–971, https://doi.org/10.1175/JHM-D-14-0079.1, 2015. a, b
Lighthill, M. J. and Whitham, G. B.: On Kinematic Waves. I. Flood Movement in Long Rivers, P. Roy. Soc. Lond. A, 229, 281–316,
https://doi.org/10.1098/rspa.1955.0088, 1955. a, b
Livneh, B., Kumar, R., and Samaniego, L.: Influence of soil textural
properties on hydrologic fluxes in the Mississippi river basin, Hydrol.
Process., 29, 4638–4655, https://doi.org/10.1002/hyp.10601, 2015. a
Lohmann, D., Nolte Holube, R., and Raschke, E.: A large-scale horizontal
routing model to be coupled to land surface parametrization schemes, Tellus A, 48, 708–721, https://doi.org/10.1034/j.1600-0870.1996.t01-3-00009.x, 1996. a, b, c
Lohmann, D., Raschke, E., Nijssen, B., and Lettenmaier, D. P.: Regional scale
hydrology: I. Formulation of the VIC-2L model coupled to a routing model,
Hydrolog. Sci. J., 43, 131–141, 1998. a
Marx, A., Kumar, R., Thober, S., Rakovec, O., Wanders, N., Zink, M., Wood, E. F., Pan, M., Sheffield, J., and Samaniego, L.: Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 ∘C, Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, 2018. a, b, c, d
Maxwell, R. M. and Kollet, S. J.: Interdependence of groundwater dynamics and land-energy feedbacks under climate change, Nat. Geosci., 1, 665–669, https://doi.org/10.1038/ngeo315, 2008. a
Miguez Macho, G. and Fan, Y.: The role of groundwater in the Amazon water
cycle: 1. Influence on seasonal streamflow, flooding and wetlands, J. Geophys. Res.-Atmos., 117, D15113,
https://doi.org/10.1029/2012JD017539, 2012. a, b
Miller, J. R., Russell, G. L., and Caliri, G.: Continental-Scale River Flow in Climate Models, J. Climate, 7, 914–928,
https://doi.org/10.1175/1520-0442(1994)007<0914:CSRFIC>2.0.CO;2, 1994. a, b
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models part I – A discussion of principles, J.
Hydrol., 10, 282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970. a, b, c
Neal, J., Schumann, G., and Bates, P.: A subgrid channel model for simulating
river hydraulics and floodplain inundation over large and data sparse areas,
Water Resour. Res., 48, W11506, https://doi.org/10.1029/2012WR012514, 2012. a, b, c
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M.,
Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The
community Noah land surface model with multiparameterization options
(Noah-MP): 1. Model description and evaluation with local-scale
measurements, J. Geophys. Res., 116, D12109,
https://doi.org/10.1029/2010JD015139, 2011. a, b, c
O'Calaghan, J. F. and Mark, D. M.: The Extraction of Drainage Networks From
Digital Elevation Data, Comput. Vision Graph., 28,
323–344, https://doi.org/10.1016/S0734-189X(84)80011-0, 1984. a, b, c
Oki, T., Nishimura, T., and Dirmeyer, P.: Assessment of annual runoff from
land surface models using Total Runoff Integrating Pathways (TRIP), J. Meteorol. Soc. Jpn., 77, 235–255,
https://doi.org/10.2151/jmsj1965.77.1B_235, 1999. a, b, c
Paiva, R. C. D., Collischonn, W., and Tucci, C. E. M.: Large scale hydrologic
and hydrodynamic modeling using limited data and a GIS based approach,
J. Hydrol., 406, 170–181, https://doi.org/10.1016/j.jhydrol.2011.06.007,
2011. a
Pontes, P. R. M., Fan, F. M., Fleischmann, A. S., Paiva, R. C. D., Buarque,
D. C., Siqueira, V. A., Jardim, P. F., Sorribas, M. V., and Collischonn, W.:
MGB-IPH model for hydrological and hydraulic simulation of large floodplain
river systems coupled with open source GIS, Environ. Modell.
Softw., 94, 1–20, https://doi.org/10.1016/j.envsoft.2017.03.029, 2017. a, b
Rakovec, O., Kumar, R., Mai, J., Cuntz, M., Thober, S., Zink, M., Attinger, S.,
Schäfer, D., Schrön, M., and Samaniego, L.: Multiscale and
multivariate evaluation of water fluxes and states over european river
Basins, J. Hydrometeorol., 17, 287–307,
https://doi.org/10.1175/JHM-D-15-0054.1, 2016. a, b, c, d
Reichstein, M., Bahn, M., Ciais, P., Frank, D., Mahecha, M. D., Seneviratne,
S. I., Zscheischler, J., Beer, C., Buchmann, N., Frank, D. C., Papale, D.,
Rammig, A., Smith, P., Thonicke, K., van der Velde, M., Vicca, S., Walz, A.,
and Wattenbach, M.: Climate extremes and the carbon cycle, Nature, 500,
287–295, https://doi.org/10.1038/nature12350, 2013. a
Sachs, L.: Angewandte Statistik: Anwendung statistischer Methoden, 9 edn.,
Springer-Verlag Berlin Heidelberg GmbH, Germany, 1999. a
Samaniego, L., Kumar, R., and Zink, M.: Implications of Parameter Uncertainty
on Soil Moisture Drought Analysis in Germany, J. Hydrometeorol.,
14, 47–68, https://doi.org/10.1175/JHM-D-12-075.1, 2013. a
Samaniego, L., Kumar, R., Breuer, L., Chamorro, A., Flörke, M.,
Pechlivanidis, I. G., Schäfer, D., Shah, H., Vetter, T., Wortmann, M.,
and Zeng, X.: Propagation of forcing and model uncertainties on to
hydrological drought characteristics in a multi-model century-long experiment
in large river basins, Climatic Change, 141, 435–449,
https://doi.org/10.1007/s10584-016-1778-y, 2017a. a
Samaniego, L., Kumar, R., Thober, S., Rakovec, O., Zink, M., Wanders, N., Eisner, S., Müller Schmied, H., Sutanudjaja, E. H., Warrach-Sagi, K., and Attinger, S.: Toward seamless hydrologic predictions across spatial scales, Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, 2017b. a
Samaniego, L., Thober, S., Kumar, R., Wanders, N., Rakovec, O., Pan, M., Zink,
M., Sheffield, J., Wood, E. F., and Marx, A.: Anthropogenic warming
exacerbates European soil moisture droughts, Nat. Clim. Change, 8,
421–426, https://doi.org/10.1038/s41558-018-0138-5, 2018. a, b, c
Sein, D. V., Mikolajewicz, U., Gröger, M., Fast, I., Cabos, W., Pinto,
J. G., Hagemann, S., Semmler, T., Izquierdo, A., and Jacob, D.: Regionally
coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation, J. Adv. Model. Earth Syst.,
7, 268–304, https://doi.org/10.1002/2014MS000357, 2015. a
Shafii, M. and Tolson, B. A.: Optimizing hydrological consistency by
incorporating hydrological signatures into model calibration objectives,
Water Resour. Res., 51, 1–19, https://doi.org/10.1002/2014WR016520, 2015. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the
Experiment Design, B. Am. Meteorol. Soc., 93,
485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a, b
Thober, S. and Samaniego, L.: Robust ensemble selection by multivariate
evaluation of extreme precipitation and temperature characteristics, J. Geophys. Res.-Atmos., 119, 594–613,
https://doi.org/10.1002/2013JD020505, 2014. a
Thober, S., Kumar, R., Sheffield, J., Mai, J., Schäfer, D., and Samaniego,
L.: Seasonal Soil Moisture Drought Prediction over Europe Using the North
American Multi-Model Ensemble (NMME), J. Hydrometeorol., 16,
2329–2344, https://doi.org/10.1175/JHM-D-15-0053.1, 2015. a
Thober, S., Kumar, R., Wanders, N., Marx, A., Pan, M., Rakovec, O., Samaniego,
L., Sheffield, J., Wood, E. F., and Zink, M.: Multi-model ensemble
projections of European river floods and high flows at 1.5, 2, and 3 degrees
global warming, Environ. Res. Lett., 13, 014003,
https://doi.org/10.1088/1748-9326/aa9e35, 2018. a, b, c, d
Thober, S., Cuntz, M., Kelbling, M., Kumar, R., Mai, J., and Samaniego, L.: The multiscale Routing Model mRM, Zenodo, https://doi.org/10.5281/zenodo.3229679, 2019. a
Todini, E.: A mass conservative and water storage consistent variable parameter Muskingum-Cunge approach, Hydrol. Earth Syst. Sci., 11, 1645–1659, https://doi.org/10.5194/hess-11-1645-2007, 2007. a, b, c
Van der Linden, P. and Mitchell, J.: ENSEMBLES: Climate Change and its
Impacts: Summary of research and results from the ENSEMBLES project, Tech.
rep., Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK,
https://doi.org/10.1029/2008JD010201, 2009. a, b
Vereecken, H., Weihermüller, L., Assouline, S., Simunek, J., Verhoef, A.,
Herbst, M., Archer, N. A. L., Mohanty, B., Montzka, C., Vanderborght, J.,
Balsamo, G., Bechtold, M., Boone, A., Chadburn, S., Cunz, M., Decharme, B.,
Ducharne, A., Ek, M., Garrigues, S., Görgen, K., Ingwersen, J., Kollet, S.,
Lawrence, D., Li, Q., Or, D., Swenson, S., De Vrese, P., Walko, R., Wu, Y.,
and Xue, Y.: Infiltration from the pedon to global grid scales: an overview
and outlook for land surface modelling, Vadose Zone J.,
https://doi.org/10.2136/vzj2018.10.0191, online first, available at: https://dl.sciencesocieties.org/publications/vzj/first-look, last access: 3 May 2019. a
Wanders, N., Thober, S., Kumar, R., Pan, M., Sheffield, J., Samaniego, L., and
Wood, E. F.: Development and Evaluation of a Pan-European Multimodel
Seasonal Hydrological Forecasting System, J. Hydrometeorol., 20,
99–115, https://doi.org/10.1175/JHM-D-18-0040.1, 2019. a, b, c
Wood, E. F., Lettenmaier, D. P., Liang, X., Lohmann, D., Boone, A., Chang, S., Chen, F., Dai, Y., Dickinson, R. E., Duan, Q., Ek, M., Gusev, Y. M., Habets, F., Irannejad, P., Koster, R., Mitchel, K. E., Nasonova, O. N., Noilhan, J., Schaake, J., Schlosser, A., Shao, Y., Shmakin, A. B., Verseghy, D., Warrach, K., Wetzel, P., Xue, Y., Yang, Z.-L., and Zeng, Q.-c.: The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) Phase 2(c) Red–Arkansas River basin experiment:, Global Planet.
Change, 19, 115–135, https://doi.org/10.1016/S0921-8181(98)00044-7, 1998. a
Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, L. P. H., Bierkens, M.
F. P., Blyth, E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis, D., van de Giesen, N., Houser, P., Jaffé, P. R., Kollet, S., Lehner, B.,
Lettenmaier, D. P., Peters Lidard, C., Sivapalan, M., Sheffield, J., Wade,
A., and Whitehead, P.: Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earths terrestrial water, Water Resour.
Res., 47, W05301, https://doi.org/10.1029/2010WR010090, 2011. a, b
Yamazaki, D., Oki, T., and Kanae, S.: Deriving a global river network map and its sub-grid topographic characteristics from a fine-resolution flow direction map, Hydrol. Earth Syst. Sci., 13, 2241–2251, https://doi.org/10.5194/hess-13-2241-2009, 2009. a, b, c, d
Yamazaki, D., Kanae, S., Kim, H., and Oki, T.: A physically based description
of floodplain inundation dynamics in a global river routing model, Water
Resour. Res., 47, W04501, https://doi.org/10.1029/2010WR009726, 2011.
a
Yamazaki, D., de Almeida, G. A. M., and Bates, P. D.: Improving computational
efficiency in global river models by implementing the local inertial flow
equation and a vector-based river network map, Water Resour. Res., 49,
7221–7235, https://doi.org/10.1002/wrcr.20552, 2013. a, b
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M:
Description of the non-hydrostatic dynamical core, Q. J.
Roy. Meteor. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2014. a
Zhang, Y., Zheng, H., Chiew, F. H. S., Peña-Arancibia, J., Zhou, X., Zhang,
Y., Zheng, H., Chiew, F. H. S., Peña-Arancibia, J., and Zhou, X.:
Evaluating Regional and Global Hydrological Models against Streamflow and
Evapotranspiration Measurements, J. Hydrometeorol., 17, 995–1010,
https://doi.org/10.1175/JHM-D-15-0107.1, 2016. a, b, c
Zhou, X., Zhang, Y., Wang, Y., Zhang, H., Vaze, J., Zhang, L., Yang, Y., and
Zhou, Y.: Benchmarking global land surface models against the observed mean
annual runoff from 150 large basins, J. Hydrol., 470-471,
269–279, https://doi.org/10.1016/j.jhydrol.2012.09.002, 2012. a
Zink, M., Samaniego, L., Kumar, R., Thober, S., Mai, J., Schäfer, D., and
Marx, A.: The German drought monitor, Environ. Res. Lett., 11,
074002, https://doi.org/10.1088/1748-9326/11/7/074002, 2016. a
Short summary
We present a model that aggregates simulated runoff along a river
(i.e. a routing model). The unique feature of the model is that it
can be run at multiple resolutions without any modifications to the
input data. The model internally (dis-)aggregates all input data to
the resolution given by the user. The model performance does not
depend on the chosen resolution. This allows efficient model
calibration at coarse resolution and subsequent model application at
fine resolution.
We present a model that aggregates simulated runoff along a river
(i.e. a routing model). The...
