Articles | Volume 30, issue 15
https://doi.org/10.5194/hess-30-5023-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-5023-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Aug 2026
Research article |
| 11 Aug 2026
| 11 Aug 2026
Retrieving root-zone soil moisture from land surface modelling and GRACE/-FO and validating its dynamics with in-situ data over West Africa
Loudi Yap
CORRESPONDING AUTHOR
Research Laboratory in Geodesy, National Institute of Cartography, Yaoundé, Cameroon
Institute of Geodesy and Geoinformation (IGG), University of Bonn, 53115 Bonn, Germany
Jürgen Kusche
Institute of Geodesy and Geoinformation (IGG), University of Bonn, 53115 Bonn, Germany
Bamidele Oloruntoba
Institute of Bio- and Geosciences: Agrosphere (IBG-3), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, GeoverbundABC/J, 52425 Jülich, Germany
Helena Gerdener
Institute of Geodesy and Geoinformation (IGG), University of Bonn, 53115 Bonn, Germany
Harrie-Jan Hendricks Franssen
Institute of Bio- and Geosciences: Agrosphere (IBG-3), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, GeoverbundABC/J, 52425 Jülich, Germany
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EGUsphere, https://doi.org/10.5194/egusphere-2026-5883, https://doi.org/10.5194/egusphere-2026-5883, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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From 2018 to 2022, Germany had its most severe multi year drought in over seventy years. To see how forests coped, we measured the yearly growth rings of more than 460 beech, oak, pine and Douglas fir trees across Germany. Growth declined strongly, by 21 to 66 percent, but losses varied greatly, even between neighboring stands under the same weather. Translating drought severity into local growth losses therefore requires considering local growing conditions.
Bernd Uebbing, Kristin Vielberg, Roelof Rietbroek, Bene Aschenneller, Armin Köhl, and Jürgen Kusche
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About 90% of the excess heat in the Earth system is stored within the oceans leading to significant ocean warming and corresponding (volumetric) sea level change. We quantify global and regional ocean heat content change (OHC) by consistently combining space-geodetic altimetry, gravity and in situ temperature profile observations. Our results agree well with published estimates and highlight the benefit of consistently processing space-geodetic datasets for deriving high quality OHC estimates.
Julia Pfeffer, Benoît Meyssignac, Rory Bingham, Alejandro Blazquez, Marie Bouih, Carla Braitenberg, Luca Brocca, Henryk Dobslaw, Ramiro Ferrari, Ehsan Forootan, Helena Gerdener, Muhammad Tahir Javed, Laura Jensen, Volker Klemann, Anna Kremer, Jürgen Kusche, Gilles Larnicol, Muhammad Usman Liaqat, Francesco Leopardi, Elisavet-Maria Mamagiannou, Gerardo Maurizio, Roland Pail, Isabelle Panet, Thomas Papanikolaou, Peyman Saemian, Ingo Sasgen, Maike Schumacher, Marius Schlaak, Linus Shihora, Alireza Sobouti, Nico Sneeuw, Mohammad Javad Tourian, Dimitrios Tsoulis, Georgios Vergos, Bert Wouters, Fan Yang, and Ilias Daras
EGUsphere, https://doi.org/10.5194/egusphere-2026-4642, https://doi.org/10.5194/egusphere-2026-4642, 2026
This preprint is open for discussion and under review for Earth Observation (EO).
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The ESA SING project demonstrates how the future satellite gravity missions NGGM and MAGIC will improve observations of continental water storage, oceans, glaciers, sea level, earthquakes, and climate change. Their more accurate, higher-resolution gravity measurements will enhance Earth system monitoring, improve climate and hazard assessments, and strengthen operational services for water management, disaster preparedness, and environmental decision-making.
Haojin Zhao, Richard Hoffmann, Heye Bogena, Cosimo Brogi, Alexandre Belleflamme, Klaus Görgen, Johannes Keller, Lukas Strebel, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2026-4630, https://doi.org/10.5194/egusphere-2026-4630, 2026
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Farmers need timely information on how much water is available in the soil, especially as drought and weather variability increase. We developed an automated system that combines field measurements, computer simulations, and multiple weather forecasts to predict soil moisture up to ten days ahead. Applied at a German test site, the system improved agreement with observations by about 20 percent and turned forecasts into simple indicators that can support irrigation and field management.
Anna Klos, Jürgen Kusche, Anne Springer, Artur Lenczuk, Yorck Ewerdwalbesloh, Christian Mielke, Susanna Werth, Jan Mikocki, Kinga Klos, Jakub Rados, Malgorzata Sieczak, and Janusz Bogusz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-469, https://doi.org/10.5194/essd-2026-469, 2026
Revised manuscript under review for ESSD
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We provide long, daily displacement time series from thousands of stations across Europe, which have been carefully preselected to study hydrospheric changes in long-term, seasonal and short-term temporal scales. These changes correlate well with precipitation, dry and wet periods. This dataset provides a more detailed picture of regional changes in hydrosphere than previously available datasets.
Viola Steidl, Jürgen Kusche, Fupeng Li, and Xiao Xiang Zhu
EGUsphere, https://doi.org/10.5194/egusphere-2026-2312, https://doi.org/10.5194/egusphere-2026-2312, 2026
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Terrestrial water storage is an indicator of water availability, but forecasting its changes is difficult as it depends on processes acting at varying spatial and temporal scales. We introduce a hierarchical machine learning model that represents the Earth at two scales, the grid scale and the hydrological basin scale, to forecast global water storage changes up to six months ahead. We identify where model skill fades and which challenges to address to improve its forecasts.
Devavat Chiru Naik, Chandrika Thulaseedharan Dhanya, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2026-1296, https://doi.org/10.5194/egusphere-2026-1296, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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This study evaluates the CLM5 over India to support the development of a national drought monitoring framework. Soil moisture, evapotranspiration, and runoff simulations are assessed against multiple observational datasets using two atmospheric forcing datasets (IMDAA and ERA5). The results highlight the role of atmospheric forcing and irrigation representation in controlling hydrological partitioning and demonstrate CLM5’s ability to reproduce historical drought events across India.
Charlotte Hacker, Benjamin D. Gutknecht, Anno Löcher, and Jürgen Kusche
Earth Syst. Sci. Data, 18, 1747–1781, https://doi.org/10.5194/essd-18-1747-2026, https://doi.org/10.5194/essd-18-1747-2026, 2026
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Terrestrial water storage anomalies (TWSA) enable the study of changes in water storage. However, observational records of TWSA are limited to 2002 onwards. To overcome this limitation, we provide a long-term TWSA data set for the global land from 1984 to 2020 by combining a data-driven approach with time‑variable gravity observations from geodetic tracking data. The data set retains seasonal consistency and adds reliable long‑term signals due to the data combination.
Anne Springer, Gabriëlle De Lannoy, Matthew Rodell, Yorck Ewerdwalbesloh, Helena Gerdener, Mehdi Khaki, Bailing Li, Fupeng Li, Maike Schumacher, Natthachet Tangdamrongsub, Mohammad J. Tourian, Wanshu Nie, and Jürgen Kusche
Hydrol. Earth Syst. Sci., 30, 985–1022, https://doi.org/10.5194/hess-30-985-2026, https://doi.org/10.5194/hess-30-985-2026, 2026
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The GRACE (Gravity Recovery and Climate Experiment) and GRACE Follow-On satellites monitor changes in Earth's water storage by observing gravity variations. By integrating these observations into hydrological models through data assimilation, estimates of groundwater, soil moisture, and hydrological trends are improved, helping to monitor droughts, floods, and human water use. This review highlights recent advances in GRACE data assimilation, identifies key challenges, and discusses future directions with upcoming satellite missions.
Fang Li, Heye Reemt Bogena, Johannes Keller, Bagher Bayat, Rahul Raj, and Harrie-Jan Hendricks-Franssen
Hydrol. Earth Syst. Sci., 29, 6419–6443, https://doi.org/10.5194/hess-29-6419-2025, https://doi.org/10.5194/hess-29-6419-2025, 2025
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We developed a new method to improve hydrological modeling by jointly using soil moisture and groundwater level data from field sensors in a catchment in Germany. By updating the model separately for shallow and deep soil zones, we achieved more accurate predictions of soil water, groundwater depth, and evapotranspiration. Our results show that combining both data types gives more balanced and reliable outcomes than using either alone.
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This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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This paper presents TSMP2, a new version of an regional Earth system model that allows to simulate and analyze the complex interactions within terrestrial ecosystems from groundwater to atmosphere. TSMP2 links an atmospheric, a land surface model and an hydrological model through an external coupler and is fully open-source. We describe the TSMP2 model system, present the impact of coupling approaches, and outline our development strategy along with technical and performance aspects.
Torsten Kanzow, Angelika Humbert, Thomas Mölg, Mirko Scheinert, Matthias Braun, Hans Burchard, Francesca Doglioni, Philipp Hochreuther, Martin Horwath, Oliver Huhn, Maria Kappelsberger, Jürgen Kusche, Erik Loebel, Katrina Lutz, Ben Marzeion, Rebecca McPherson, Mahdi Mohammadi-Aragh, Marco Möller, Carolyne Pickler, Markus Reinert, Monika Rhein, Martin Rückamp, Janin Schaffer, Muhammad Shafeeque, Sophie Stolzenberger, Ralph Timmermann, Jenny Turton, Claudia Wekerle, and Ole Zeising
The Cryosphere, 19, 1789–1824, https://doi.org/10.5194/tc-19-1789-2025, https://doi.org/10.5194/tc-19-1789-2025, 2025
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The Greenland Ice Sheet represents the second-largest contributor to global sea-level rise. We quantify atmosphere, ice and ocean processes related to the mass balance of glaciers in northeast Greenland, focusing on Greenland’s largest floating ice tongue, the 79° N Glacier. We find that together, the different in situ and remote sensing observations and model simulations reveal a consistent picture of a coupled atmosphere–ice sheet–ocean system that has entered a phase of major change.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
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We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
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Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Teng Xu, Sinan Xiao, Sebastian Reuschen, Nils Wildt, Harrie-Jan Hendricks Franssen, and Wolfgang Nowak
Hydrol. Earth Syst. Sci., 28, 5375–5400, https://doi.org/10.5194/hess-28-5375-2024, https://doi.org/10.5194/hess-28-5375-2024, 2024
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We provide a set of benchmarking scenarios for geostatistical inversion, and we encourage the scientific community to use these to compare their newly developed methods. To facilitate transparent, appropriate, and uncertainty-aware comparison of novel methods, we provide some accurate reference solutions, a high-end reference algorithm, and a diverse set of benchmarking metrics, all of which are publicly available. With this, we seek to foster more targeted and transparent progress in the field.
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
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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.
Petra Döll, Howlader Mohammad Mehedi Hasan, Kerstin Schulze, Helena Gerdener, Lara Börger, Somayeh Shadkam, Sebastian Ackermann, Seyed-Mohammad Hosseini-Moghari, Hannes Müller Schmied, Andreas Güntner, and Jürgen Kusche
Hydrol. Earth Syst. Sci., 28, 2259–2295, https://doi.org/10.5194/hess-28-2259-2024, https://doi.org/10.5194/hess-28-2259-2024, 2024
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Currently, global hydrological models do not benefit from observations of model output variables to reduce and quantify model output uncertainty. For the Mississippi River basin, we explored three approaches for using both streamflow and total water storage anomaly observations to adjust the parameter sets in a global hydrological model. We developed a method for considering the observation uncertainties to quantify the uncertainty of model output and provide recommendations.
Lukas Strebel, Heye Bogena, Harry Vereecken, Mie Andreasen, Sergio Aranda-Barranco, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 28, 1001–1026, https://doi.org/10.5194/hess-28-1001-2024, https://doi.org/10.5194/hess-28-1001-2024, 2024
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We present results from using soil water content measurements from 13 European forest sites in a state-of-the-art land surface model. We use data assimilation to perform a combination of observed and modeled soil water content and show the improvements in the representation of soil water content. However, we also look at the impact on evapotranspiration and see no corresponding improvements.
Matthias O. Willen, Martin Horwath, Eric Buchta, Mirko Scheinert, Veit Helm, Bernd Uebbing, and Jürgen Kusche
The Cryosphere, 18, 775–790, https://doi.org/10.5194/tc-18-775-2024, https://doi.org/10.5194/tc-18-775-2024, 2024
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Shrinkage of the Antarctic ice sheet (AIS) leads to sea level rise. Satellite gravimetry measures AIS mass changes. We apply a new method that overcomes two limitations: low spatial resolution and large uncertainties due to the Earth's interior mass changes. To do so, we additionally include data from satellite altimetry and climate and firn modelling, which are evaluated in a globally consistent way with thoroughly characterized errors. The results are in better agreement with independent data.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
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Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
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Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Lukas Strebel, Heye R. Bogena, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 15, 395–411, https://doi.org/10.5194/gmd-15-395-2022, https://doi.org/10.5194/gmd-15-395-2022, 2022
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We present the technical coupling between a land surface model (CLM5) and the Parallel Data Assimilation Framework (PDAF). This coupling enables measurement data to update simulated model states and parameters in a statistically optimal way. We demonstrate the viability of the model framework using an application in a forested catchment where the inclusion of soil water measurements significantly improved the simulation quality.
Yafei Huang, Jonas Weis, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-569, https://doi.org/10.5194/hess-2021-569, 2021
Manuscript not accepted for further review
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Trends in agricultural droughts cannot be easily deduced from measurements. Here trends in agricultural droughts over 31 German and Dutch sites were calculated with model simulations and long-term observed meteorological data as input. We found that agricultural droughts are increasing although precipitation hardly decreases. The increase is driven by increase in evapotranspiration. The year 2018 was for half of the sites the year with the most extreme agricultural drought in the last 55 years.
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Short summary
Rainfall shifts in West Africa affects agricultural productivity, highlighting how much water is stored in the soil. Soil moisture from 2003 to 2019 was assessed using satellite, model, and in-situ data. The European Space Agency Climate Change Initiative Soil Moisture dataset best tracked local conditions, while the Gravity Recovery and Climate Experiment Follow-On (GRACE-/FO)-based Global Land Water Storage version 2.0 captured regional variability, improving understanding of root-zone water.
Rainfall shifts in West Africa affects agricultural productivity, highlighting how much water is...
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