Articles | Volume 27, issue 22
https://doi.org/10.5194/hess-27-4087-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-4087-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Nov 2023
Research article |
| 14 Nov 2023
| 14 Nov 2023
Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe
Samuel Scherrer
CORRESPONDING AUTHOR
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Gabriëlle De Lannoy
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Zdenko Heyvaert
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Michel Bechtold
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Clement Albergel
European Space Agency Climate Office, ECSAT, Didcot, UK
Tarek S. El-Madany
Department Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
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Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
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Hydrol. Earth Syst. Sci., 27, 1221–1242, https://doi.org/10.5194/hess-27-1221-2023, https://doi.org/10.5194/hess-27-1221-2023, 2023
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Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
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Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023, https://doi.org/10.5194/hess-27-39-2023, 2023
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Sinikka Jasmin Paulus, Tarek Sebastian El-Madany, René Orth, Anke Hildebrandt, Thomas Wutzler, Arnaud Carrara, Gerardo Moreno, Oscar Perez-Priego, Olaf Kolle, Markus Reichstein, and Mirco Migliavacca
Hydrol. Earth Syst. Sci., 26, 6263–6287, https://doi.org/10.5194/hess-26-6263-2022, https://doi.org/10.5194/hess-26-6263-2022, 2022
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Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
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Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo
Biogeosciences, 19, 5107–5123, https://doi.org/10.5194/bg-19-5107-2022, https://doi.org/10.5194/bg-19-5107-2022, 2022
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The standardized vegetation optical depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage, spans the past 3 decades and is derived from multiple spaceborne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data even if the data are not gap-free.
Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
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Louise Busschaert, Shannon de Roos, Wim Thiery, Dirk Raes, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 3731–3752, https://doi.org/10.5194/hess-26-3731-2022, https://doi.org/10.5194/hess-26-3731-2022, 2022
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Increasing amounts of water are used for agriculture. Therefore, we looked into how irrigation requirements will evolve under a changing climate over Europe. Our results show that, by the end of the century and under high emissions, irrigation water will increase by 30 % on average compared to the year 2000. Also, the irrigation requirement is likely to vary more from 1 year to another. However, if emissions are mitigated, these effects are reduced.
Robin van der Schalie, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu
Hydrol. Earth Syst. Sci., 26, 3611–3627, https://doi.org/10.5194/hess-26-3611-2022, https://doi.org/10.5194/hess-26-3611-2022, 2022
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Climate data records of surface soil moisture, vegetation optical depth, and land surface temperature can be derived from passive microwave observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here, we present a case study over the Okavango Delta, where we focus on inter-annual variability.
Sophia Walther, Simon Besnard, Jacob Allen Nelson, Tarek Sebastian El-Madany, Mirco Migliavacca, Ulrich Weber, Nuno Carvalhais, Sofia Lorena Ermida, Christian Brümmer, Frederik Schrader, Anatoly Stanislavovich Prokushkin, Alexey Vasilevich Panov, and Martin Jung
Biogeosciences, 19, 2805–2840, https://doi.org/10.5194/bg-19-2805-2022, https://doi.org/10.5194/bg-19-2805-2022, 2022
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Satellite observations help interpret station measurements of local carbon, water, and energy exchange between the land surface and the atmosphere and are indispensable for simulations of the same in land surface models and their evaluation. We propose generalisable and efficient approaches to systematically ensure high quality and to estimate values in data gaps. We apply them to satellite data of surface reflectance and temperature with different resolutions at the stations.
Anthony Mucia, Bertrand Bonan, Clément Albergel, Yongjun Zheng, and Jean-Christophe Calvet
Biogeosciences, 19, 2557–2581, https://doi.org/10.5194/bg-19-2557-2022, https://doi.org/10.5194/bg-19-2557-2022, 2022
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For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
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Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
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Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
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Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
Sara Modanesi, Christian Massari, Alexander Gruber, Hans Lievens, Angelica Tarpanelli, Renato Morbidelli, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 6283–6307, https://doi.org/10.5194/hess-25-6283-2021, https://doi.org/10.5194/hess-25-6283-2021, 2021
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Worldwide, the amount of water used for agricultural purposes is rising and the quantification of irrigation is becoming a crucial topic. Land surface models are not able to correctly simulate irrigation. Remote sensing observations offer an opportunity to fill this gap as they are directly affected by irrigation. We equipped a land surface model with an observation operator able to transform Sentinel-1 backscatter observations into realistic vegetation and soil states via data assimilation.
Shannon de Roos, Gabriëlle J. M. De Lannoy, and Dirk Raes
Geosci. Model Dev., 14, 7309–7328, https://doi.org/10.5194/gmd-14-7309-2021, https://doi.org/10.5194/gmd-14-7309-2021, 2021
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A spatially distributed version of the field-scale crop model AquaCrop v6.1 was developed for applications at various spatial scales. Multi-year 1 km simulations over central Europe were evaluated against biomass and surface soil moisture products derived from optical and microwave satellite missions, as well as in situ observations of soil moisture. The regional version of the AquaCrop model provides a suitable setup for subsequent satellite-based data assimilation.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
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The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
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The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
Michiel Maertens, Gabriëlle J. M. De Lannoy, Sebastian Apers, Sujay V. Kumar, and Sarith P. P. Mahanama
Hydrol. Earth Syst. Sci., 25, 4099–4125, https://doi.org/10.5194/hess-25-4099-2021, https://doi.org/10.5194/hess-25-4099-2021, 2021
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In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
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Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
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Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
Christopher Krich, Mirco Migliavacca, Diego G. Miralles, Guido Kraemer, Tarek S. El-Madany, Markus Reichstein, Jakob Runge, and Miguel D. Mahecha
Biogeosciences, 18, 2379–2404, https://doi.org/10.5194/bg-18-2379-2021, https://doi.org/10.5194/bg-18-2379-2021, 2021
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Ecosystems and the atmosphere interact with each other. These interactions determine e.g. the water and carbon fluxes and thus are crucial to understand climate change effects. We analysed the interactions for many ecosystems across the globe, showing that very different ecosystems can have similar interactions with the atmosphere. Meteorological conditions seem to be the strongest interaction-shaping factor. This means that common principles can be identified to describe ecosystem behaviour.
Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 1569–1586, https://doi.org/10.5194/hess-25-1569-2021, https://doi.org/10.5194/hess-25-1569-2021, 2021
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The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to Tb innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.
Judith Eeckman, Hélène Roux, Audrey Douinot, Bertrand Bonan, and Clément Albergel
Hydrol. Earth Syst. Sci., 25, 1425–1446, https://doi.org/10.5194/hess-25-1425-2021, https://doi.org/10.5194/hess-25-1425-2021, 2021
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The risk of flash flood is of growing importance for populations, particularly in the Mediterranean area in the context of a changing climate. The representation of soil processes in models is a key factor for flash flood simulation. The importance of the various methods for soil moisture estimation are highlighted in this work. Local measurements from the field as well as data derived from satellite imagery can be used to assess the performance of model outputs.
Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont
Geosci. Model Dev., 14, 1595–1614, https://doi.org/10.5194/gmd-14-1595-2021, https://doi.org/10.5194/gmd-14-1595-2021, 2021
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In the mountains, the combination of large model error and observation sparseness is a challenge for data assimilation. Here, we develop two variants of the particle filter (PF) in order to propagate the information content of observations into unobserved areas. By adjusting observation errors or exploiting background correlation patterns, we demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy with the PF in an idealised setting.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Miguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F. Trigo, Sofia L. Ermida, João P. A. Martins, and Emanuel Dutra
Geosci. Model Dev., 13, 3975–3993, https://doi.org/10.5194/gmd-13-3975-2020, https://doi.org/10.5194/gmd-13-3975-2020, 2020
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We used earth observations to evaluate and improve the representation of land surface temperature (LST) and vegetation coverage over Iberia in CHTESSEL and SURFEX land surface models. We demonstrate the added value of updating the vegetation types and fractions together with the representation of vegetation coverage seasonality. Results show a large reduction in daily maximum LST systematic error during warm months, with neutral impacts in other seasons.
Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, https://doi.org/10.5194/hess-24-4291-2020, 2020
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LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
Yongjun Zheng, Clément Albergel, Simon Munier, Bertrand Bonan, and Jean-Christophe Calvet
Geosci. Model Dev., 13, 3607–3625, https://doi.org/10.5194/gmd-13-3607-2020, https://doi.org/10.5194/gmd-13-3607-2020, 2020
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This study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framework for high-dimensional ensemble Kalman filters. The offline and online modes of ensemble Kalman filters are built to comprehensively assess their time to solution efficiencies. The offline mode is substantially faster than the online mode in terms of time to solution, especially for large-scale assimilation problems.
Thomas Wutzler, Oscar Perez-Priego, Kendalynn Morris, Tarek S. El-Madany, and Mirco Migliavacca
Geosci. Instrum. Method. Data Syst., 9, 239–254, https://doi.org/10.5194/gi-9-239-2020, https://doi.org/10.5194/gi-9-239-2020, 2020
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Continuous data of soil CO2 efflux can improve model prediction of climate warming, and automated data are becoming increasingly available. However, aggregating chamber-based data to plot scale pose challenges. Therefore, we showed, using 1 year of half-hourly data, how using the lognormal assumption tackles several challenges. We propose that plot-scale SO2 efflux observations should be reported together with lognormally based uncertainties and enter model constraining frameworks at log scale.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
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We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
Angelika Xaver, Luca Zappa, Gerhard Rab, Isabella Pfeil, Mariette Vreugdenhil, Drew Hemment, and Wouter Arnoud Dorigo
Geosci. Instrum. Method. Data Syst., 9, 117–139, https://doi.org/10.5194/gi-9-117-2020, https://doi.org/10.5194/gi-9-117-2020, 2020
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Soil moisture plays a key role in the hydrological cycle and the climate system. Although soil moisture can be observed by the means of satellites, ground observations are still crucial for evaluating and improving these satellite products. In this study, we investigate the performance of a consumer low-cost soil moisture sensor in the lab and in the field. We demonstrate that this sensor can be used for scientific applications, for example to create a dataset valuable for satellite validation.
Christopher Krich, Jakob Runge, Diego G. Miralles, Mirco Migliavacca, Oscar Perez-Priego, Tarek El-Madany, Arnaud Carrara, and Miguel D. Mahecha
Biogeosciences, 17, 1033–1061, https://doi.org/10.5194/bg-17-1033-2020, https://doi.org/10.5194/bg-17-1033-2020, 2020
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Causal inference promises new insight into biosphere–atmosphere interactions using time series only. To understand the behaviour of a specific method on such data, we used artificial and observation-based data. The observed structures are very interpretable and reveal certain ecosystem-specific behaviour, as only a few relevant links remain, in contrast to pure correlation techniques. Thus, causal inference allows to us gain well-constrained insights into processes and interactions.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
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The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Javier Pacheco-Labrador, Tarek S. El-Madany, M. Pilar Martin, Rosario Gonzalez-Cascon, Arnaud Carrara, Gerardo Moreno, Oscar Perez-Priego, Tiana Hammer, Heiko Moossen, Kathrin Henkel, Olaf Kolle, David Martini, Vicente Burchard, Christiaan van der Tol, Karl Segl, Markus Reichstein, and Mirco Migliavacca
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-501, https://doi.org/10.5194/bg-2019-501, 2020
Revised manuscript not accepted
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The new generation of sensors on-board satellites have the potential to provide richer information about the function of vegetation than before. This information, nowadays missing, is fundamental to improve our understanding and prediction of carbon and water cycles, and therefore to anticipate effects and responses to Climate Change. In this manuscript we propose a method to exploit the data provided by these satellites to successfully obtain this information key to face Climate Change.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
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Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
Bertrand Bonan, Clément Albergel, Yongjun Zheng, Alina Lavinia Barbu, David Fairbairn, Simon Munier, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 325–347, https://doi.org/10.5194/hess-24-325-2020, https://doi.org/10.5194/hess-24-325-2020, 2020
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This paper introduces an ensemble square root filter (EnSRF), a deterministic ensemble Kalman filter, for jointly assimilating observations of the surface soil moisture and leaf area index in the Land Data Assimilation System LDAS-Monde. LDAS-Monde constrains the Interaction between Soil, Biosphere and Atmosphere (ISBA) land surface model to improve the reanalysis of land surface variables. EnSRF is compared with the simplified extended Kalman filter over the European Mediterranean region.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
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Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Vicente Burchard-Levine, Héctor Nieto, David Riaño, Mirco Migliavacca, Tarek S. El-Madany, Oscar Perez-Priego, Arnaud Carrara, and M. Pilar Martín
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-354, https://doi.org/10.5194/hess-2019-354, 2019
Manuscript not accepted for further review
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Models are increasingly being used to understand surface water fluxes, which are of high use to manage crop irrigation, and to understand the earth system´s response to environmental change. However, often these models have higher uncertainty in complex ecosystems with multiple layers of vegetation. This manuscript adapts and analyzes a well known model to better simulate water fluxes for a savanna-like ecosystem and to understand the influence that vegetation has on their predictions.
Alexander Gruber, Tracy Scanlon, Robin van der Schalie, Wolfgang Wagner, and Wouter Dorigo
Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, https://doi.org/10.5194/essd-11-717-2019, 2019
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Soil moisture is a key variable in our Earth system. Knowledge of soil moisture and its dynamics across scales is vital for many applications such as the prediction of agricultural yields or irrigation demands, flood and drought monitoring, weather forecasting and climate modelling. To date, the ESA CCI SM products are the only consistent long-term multi-satellite soil moisture data sets available. This paper reviews the evolution of these products and their underlying merging methodology.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, https://doi.org/10.5194/hess-23-1973-2019, 2019
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This study investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modeling, in global water resource reanalysis. Analysis is based on ensemble hydrologic simulations for a period of 11 years based on six global hydrologic models and five precipitation datasets. Results show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure.
Felix Zaussinger, Wouter Dorigo, Alexander Gruber, Angelica Tarpanelli, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019, https://doi.org/10.5194/hess-23-897-2019, 2019
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About 70 % of global freshwater is consumed by irrigation. Yet, policy-relevant estimates of irrigation water use (IWU) are virtually lacking at regional to global scales. To bridge this gap, we develop a method for quantifying IWU from a combination of state-of-the-art remotely sensed and modeled soil moisture products and apply it over the United States for the period 2013–2016. Overall, our estimates agree well with reference data on irrigated area and irrigation water withdrawals.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
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Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Clement Albergel, Emanuel Dutra, Simon Munier, Jean-Christophe Calvet, Joaquin Munoz-Sabater, Patricia de Rosnay, and Gianpaolo Balsamo
Hydrol. Earth Syst. Sci., 22, 3515–3532, https://doi.org/10.5194/hess-22-3515-2018, https://doi.org/10.5194/hess-22-3515-2018, 2018
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ECMWF recently released the first 7-year segment of its latest atmospheric reanalysis: ERA-5 (2010–2016). ERA-5 has important changes relative to ERA-Interim including higher spatial and temporal resolutions as well as a more recent model and data assimilation system. ERA-5 is foreseen to replace ERA-Interim reanalysis. One of the main goals of this study is to assess whether ERA-5 can enhance the simulation performances with respect to ERA-Interim when it is used to force a land surface model.
Luca Ciabatta, Christian Massari, Luca Brocca, Alexander Gruber, Christoph Reimer, Sebastian Hahn, Christoph Paulik, Wouter Dorigo, Richard Kidd, and Wolfgang Wagner
Earth Syst. Sci. Data, 10, 267–280, https://doi.org/10.5194/essd-10-267-2018, https://doi.org/10.5194/essd-10-267-2018, 2018
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In this study, rainfall is estimated starting from satellite soil moisture observation on a global scale, using the ESA CCI soil moisture datasets. The new obtained rainfall product has proven to correctly identify rainfall events, showing performance sometimes higher than those obtained by using classical rainfall estimation approaches.
Matthias Forkel, Wouter Dorigo, Gitta Lasslop, Irene Teubner, Emilio Chuvieco, and Kirsten Thonicke
Geosci. Model Dev., 10, 4443–4476, https://doi.org/10.5194/gmd-10-4443-2017, https://doi.org/10.5194/gmd-10-4443-2017, 2017
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Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
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LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
Nemesio J. Rodríguez-Fernández, Joaquin Muñoz Sabater, Philippe Richaume, Patricia de Rosnay, Yann H. Kerr, Clement Albergel, Matthias Drusch, and Susanne Mecklenburg
Hydrol. Earth Syst. Sci., 21, 5201–5216, https://doi.org/10.5194/hess-21-5201-2017, https://doi.org/10.5194/hess-21-5201-2017, 2017
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The new SMOS satellite near-real-time (NRT) soil moisture (SM) product based on a neural network is presented. The NRT SM product has been evaluated with respect to the SMOS Level 2 product and against a large number of in situ measurements showing performances similar to those of the Level 2 product but it is available in less than 3.5 h after sensing. The new product is distributed by the European Space Agency and the European Organisation for the Exploitation of Meteorological Satellites.
Hélène Dewaele, Simon Munier, Clément Albergel, Carole Planque, Nabil Laanaia, Dominique Carrer, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4861–4878, https://doi.org/10.5194/hess-21-4861-2017, https://doi.org/10.5194/hess-21-4861-2017, 2017
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Soil maximum available water content (MaxAWC) is a key parameter in land surface models. Being difficult to measure, this parameter is usually unavailable. A 15-year time series of satellite-derived observations of leaf area index (LAI) is used to retrieve MaxAWC for rainfed straw cereals over France. Disaggregated LAI is sequentially assimilated into the ISBA LSM. MaxAWC is estimated minimising LAI analyses increments. Annual maximum LAI observations correlate with the MaxAWC estimates.
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
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This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
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The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
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Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman
Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, https://doi.org/10.5194/gmd-10-1945-2017, 2017
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Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.
Annelie Säurich, Bärbel Tiemeyer, Axel Don, Michel Bechtold, Wulf Amelung, and Annette Freibauer
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-127, https://doi.org/10.5194/bg-2017-127, 2017
Manuscript not accepted for further review
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Drained organic soils are hotspots of CO2 emissions. Due to mineralisation and mixing with mineral soil, the soil organic carbon (SOC) content of large areas of former peatlands decreased drastically. We evaluated potential CO2 emissions from such soils and true peat by aerobic incubation. Surprisingly, CO2 emissions increased in magnitude and variability with stronger disturbance and lower SOC content. This indicates that mixing peat with mineral soil is not a promising mitigation option.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, https://doi.org/10.5194/hess-21-2015-2017, 2017
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This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Gabriëlle J. M. De Lannoy and Rolf H. Reichle
Hydrol. Earth Syst. Sci., 20, 4895–4911, https://doi.org/10.5194/hess-20-4895-2016, https://doi.org/10.5194/hess-20-4895-2016, 2016
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The SMOS mission provides various various products to estimate soil moisture. This paper evaluates the performance of assimilating either Level-1-based multi-angle brightness temperature (Tb) observations, Level-1-based single-angle Tb observations, or Level 2 soil moisture retrievals, into the NASA Catchment land surface model.
Markus Enenkel, Christoph Reimer, Wouter Dorigo, Wolfgang Wagner, Isabella Pfeil, Robert Parinussa, and Richard De Jeu
Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, https://doi.org/10.5194/hess-20-4191-2016, 2016
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Soil moisture is a crucial variable for a variety of applications, ranging from weather forecasting and agricultural production to the monitoring of floods and droughts. Satellite observations are particularly important in regions where no in situ measurements are available. Our study presents a method to integrate global near-real-time satellite observations from different sensors into one harmonized, daily data set. A first validation shows good results on a global scale.
G. Balsamo, C. Albergel, A. Beljaars, S. Boussetta, E. Brun, H. Cloke, D. Dee, E. Dutra, J. Muñoz-Sabater, F. Pappenberger, P. de Rosnay, T. Stockdale, and F. Vitart
Hydrol. Earth Syst. Sci., 19, 389–407, https://doi.org/10.5194/hess-19-389-2015, https://doi.org/10.5194/hess-19-389-2015, 2015
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ERA-Interim/Land is a global land surface reanalysis covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim and a precipitation bias correction based on GPCP. A selection of verification results show the added value in representing the terrestrial water cycle and its main land surface storages and fluxes.
M. Bechtold, B. Tiemeyer, A. Laggner, T. Leppelt, E. Frahm, and S. Belting
Hydrol. Earth Syst. Sci., 18, 3319–3339, https://doi.org/10.5194/hess-18-3319-2014, https://doi.org/10.5194/hess-18-3319-2014, 2014
C. Szczypta, J.-C. Calvet, F. Maignan, W. Dorigo, F. Baret, and P. Ciais
Geosci. Model Dev., 7, 931–946, https://doi.org/10.5194/gmd-7-931-2014, https://doi.org/10.5194/gmd-7-931-2014, 2014
A. Loew, T. Stacke, W. Dorigo, R. de Jeu, and S. Hagemann
Hydrol. Earth Syst. Sci., 17, 3523–3542, https://doi.org/10.5194/hess-17-3523-2013, https://doi.org/10.5194/hess-17-3523-2013, 2013
Related subject area
Subject: Ecohydrology | Techniques and Approaches: Modelling approaches
Integration of the vegetation phenology module improves ecohydrological simulation by the SWAT-Carbon model
Green water availability and water-limited crop yields under a changing climate in Ethiopia
Ecohydrological responses to solar radiation changes
Technical assessment combined with an extended cost–benefit analysis for the restoration of groundwater and forest ecosystem services – an application for Grand Bahama
Are rivers becoming more intermittent in France? Learning from an extended set of climate projections based on the Coupled Model Intercomparison Project phase 5 (CMIP5)
Regional patterns and drivers of modelled water flows along environmental, functional, and stand structure gradients in Spanish forests
Machine learning and global vegetation: random forests for downscaling and gap filling
Unraveling phenological and stomatal responses to flash drought and implications for water and carbon budgets
Technical note: Seamless extraction and analysis of river networks in R
Advancing stream classification and hydrologic modeling of ungaged basins for environmental flow management in coastal southern California
Improving regional climate simulations based on a hybrid data assimilation and machine learning method
A comprehensive assessment of in situ and remote sensing soil moisture data assimilation in the APSIM model for improving agricultural forecasting across the US Midwest
Does non-stationarity induced by multiyear drought invalidate the paired-catchment method?
Is the reputation of Eucalyptus plantations for using more water than Pinus plantations justified?
Attributing trend in naturalized streamflow to temporally explicit vegetation change and climate variation in the Yellow River basin of China
Impacts of different types of El Niño events on water quality over the Corn Belt, United States
Leveraging sap flow data in a catchment-scale hybrid model to improve soil moisture and transpiration estimates
Coupled modelling of hydrological processes and grassland production in two contrasting climates
Does maximization of net carbon profit enable the prediction of vegetation behaviour in savanna sites along a precipitation gradient?
Modelling the artificial forest (Robinia pseudoacacia L.) root–soil water interactions in the Loess Plateau, China
A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration
Vegetation greening weakened the capacity of water supply to China's South-to-North Water Diversion Project
Structural changes to forests during regeneration affect water flux partitioning, water ages and hydrological connectivity: Insights from tracer-aided ecohydrological modelling
How does water yield respond to mountain pine beetle infestation in a semiarid forest?
Daily soil temperature modeling improved by integrating observed snow cover and estimated soil moisture in the USA Great Plains
Plant hydraulic transport controls transpiration sensitivity to soil water stress
Drought onset and propagation into soil moisture and grassland vegetation responses during the 2012–2019 major drought in Southern California
Quantifying the effects of urban green space on water partitioning and ages using an isotope-based ecohydrological model
Low and contrasting impacts of vegetation CO2 fertilization on global terrestrial runoff over 1982–2010: accounting for aboveground and belowground vegetation–CO2 effects
Global ecosystem-scale plant hydraulic traits retrieved using model–data fusion
Quantifying the effects of land use and model scale on water partitioning and water ages using tracer-aided ecohydrological models
Quantification of ecohydrological sensitivities and their influencing factors at the seasonal scale
Canopy temperature and heat stress are increased by compound high air temperature and water stress and reduced by irrigation – a modeling analysis
Evaluating a landscape-scale daily water balance model to support spatially continuous representation of flow intermittency throughout stream networks
Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites
Novel Keeling-plot-based methods to estimate the isotopic composition of ambient water vapor
Disentangling temporal and population variability in plant root water uptake from stable isotopic analysis: when rooting depth matters in labeling studies
Calibration of hydrological models for ecologically relevant streamflow predictions: a trade-off between fitting well to data and estimating consistent parameter sets?
Spatial variability of mean daily estimates of actual evaporation from remotely sensed imagery and surface reference data
Quantification of soil water balance components based on continuous soil moisture measurement and the Richards equation in an irrigated agricultural field of a desert oasis
Mapping the suitability of groundwater-dependent vegetation in a semi-arid Mediterranean area
Modeling boreal forest evapotranspiration and water balance at stand and catchment scales: a spatial approach
The 18O ecohydrology of a grassland ecosystem – predictions and observations
A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions
Dynamic responses of DOC and DIC transport to different flow regimes in a subtropical small mountainous river
Evaluation of ORCHIDEE-MICT-simulated soil moisture over China and impacts of different atmospheric forcing data
Testing an optimality-based model of rooting zone water storage capacity in temperate forests
A regional-scale ecological risk framework for environmental flow evaluations
Climate-driven disturbances in the San Juan River sub-basin of the Colorado River
Dominant effect of increasing forest biomass on evapotranspiration: interpretations of movement in Budyko space
Mingwei Li, Shouzhi Chen, Fanghua Hao, Nan Wang, Zhaofei Wu, Yue Xu, Jing Zhang, Yongqiang Zhang, and Yongshuo H. Fu
Hydrol. Earth Syst. Sci., 29, 2081–2095, https://doi.org/10.5194/hess-29-2081-2025, https://doi.org/10.5194/hess-29-2081-2025, 2025
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Climate-driven shifts in vegetation phenology have a significant impact on hydrological processes. In this study, we integrated a process-based phenology module into the SWAT-Carbon model, which led to a substantial improvement in the simulation of vegetation dynamics and hydrological processes in the Jinsha River watershed. Our findings highlight the critical need to incorporate vegetation phenology into hydrological models to achieve a more accurate representation of ecohydrological processes.
Mosisa Tujuba Wakjira, Nadav Peleg, Johan Six, and Peter Molnar
Hydrol. Earth Syst. Sci., 29, 863–886, https://doi.org/10.5194/hess-29-863-2025, https://doi.org/10.5194/hess-29-863-2025, 2025
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In this study, we implement a climate, water, and crop interaction model to evaluate current conditions and project future changes in rainwater availability and its yield potential, with the goal of informing adaptation policies and strategies in Ethiopia. Although climate change is likely to increase rainfall in Ethiopia, our findings suggest that water-scarce croplands in Ethiopia are expected to face reduced crop yields during the main growing season due to increases in temperature.
Yiran Wang, Naika Meili, and Simone Fatichi
Hydrol. Earth Syst. Sci., 29, 381–396, https://doi.org/10.5194/hess-29-381-2025, https://doi.org/10.5194/hess-29-381-2025, 2025
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In this study, we use climate model simulations and process-based ecohydrological modeling to assess the effects of solar radiation changes on hydrological variables. Results show that direct changes in solar radiation without the land–atmosphere feedback primarily affects sensible heat with limited effects on hydrology and vegetation. However, including land–atmosphere feedbacks exacerbates the effects of radiation changes on evapotranspiration and modifies vegetation productivity.
Anne Imig, Francesca Perosa, Carolina Iwane Hotta, Sophia Klausner, Kristen Welsh, Yan Zheng, and Arno Rein
Hydrol. Earth Syst. Sci., 28, 5459–5478, https://doi.org/10.5194/hess-28-5459-2024, https://doi.org/10.5194/hess-28-5459-2024, 2024
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In 2019, Hurricane Dorian led to salinization of groundwater resources on the island of Grand Bahama. We assessed the feasibility of managed aquifer recharge (MAR) for restoring fresh groundwater. Furthermore, we applied a financial and an extended cost–benefit analysis for assessing ecosystem services supported by MAR and reforestation. As a first estimate, MAR could only provide a small contribution to the water demand. Reforestation measures were assessed to be financially profitable.
Tristan Jaouen, Lionel Benoit, Louis Héraut, and Eric Sauquet
EGUsphere, https://doi.org/10.5194/egusphere-2024-2737, https://doi.org/10.5194/egusphere-2024-2737, 2024
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This study uses a multi-model approach to assess future changes in river flow intermittency across France under climate change. Combining projections from the Explore2 project with historical flow observations, logistic regressions estimate daily probabilities of flow intermittency (PFI) under RCP 2.6, 4.5, and 8.5 scenarios. Results suggest intensifying and prolonged dry spells throughout the 21st century, with southern France more affected, while uncertainty remains higher in northern regions.
Jesús Sánchez-Dávila, Miquel De Cáceres, Jordi Vayreda, and Javier Retana
Hydrol. Earth Syst. Sci., 28, 3037–3050, https://doi.org/10.5194/hess-28-3037-2024, https://doi.org/10.5194/hess-28-3037-2024, 2024
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Forest blue water is determined by the climate, functional traits, and stand structure variables. The leaf area index (LAI) is the main driver of the trade-off between the blue and green water. Blue water is concentrated in the autumn–winter season, and deciduous trees can increase the relative blue water. The leaf phenology and seasonal distribution are determinants for the relative blue water.
Barry van Jaarsveld, Sandra M. Hauswirth, and Niko Wanders
Hydrol. Earth Syst. Sci., 28, 2357–2374, https://doi.org/10.5194/hess-28-2357-2024, https://doi.org/10.5194/hess-28-2357-2024, 2024
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Drought often manifests itself in vegetation; however, obtaining high-resolution remote-sensing products that are spatially and temporally consistent is difficult. In this study, we show that machine learning (ML) can fill data gaps in existing products. We also demonstrate that ML can be used as a downscaling tool. By relying on ML for gap filling and downscaling, we can obtain a more holistic view of the impacts of drought on vegetation.
Nicholas K. Corak, Jason A. Otkin, Trent W. Ford, and Lauren E. L. Lowman
Hydrol. Earth Syst. Sci., 28, 1827–1851, https://doi.org/10.5194/hess-28-1827-2024, https://doi.org/10.5194/hess-28-1827-2024, 2024
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We simulate how dynamic vegetation interacts with the atmosphere during extreme drought events known as flash droughts. We find that plants nearly halt water and carbon exchanges and limit their growth during flash drought. This work has implications for how to account for changes in vegetation state during extreme drought events when making predictions under future climate scenarios.
Luca Carraro
Hydrol. Earth Syst. Sci., 27, 3733–3742, https://doi.org/10.5194/hess-27-3733-2023, https://doi.org/10.5194/hess-27-3733-2023, 2023
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Mathematical models are key to the study of environmental processes in rivers. Such models often require information on river morphology from geographic information system (GIS) software, which hinders the use of replicable workflows. Here I present rivnet, an R package for simple, robust, GIS-free extraction and analysis of river networks. The package is designed so as to require minimal user input and is oriented towards ecohydrological, ecological and biogeochemical modeling.
Stephen K. Adams, Brian P. Bledsoe, and Eric D. Stein
Hydrol. Earth Syst. Sci., 27, 3021–3039, https://doi.org/10.5194/hess-27-3021-2023, https://doi.org/10.5194/hess-27-3021-2023, 2023
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Managing streams for environmental flows involves prioritizing healthy stream ecosystems while distributing water resources. Classifying streams of similar types is a useful step in developing environmental flows. Environmental flows are often developed on data-poor streams that must be modeled. This paper has developed a new method of classification that prioritizes model accuracy. The new method advances environmental streamflow management and modeling of data-poor watersheds.
Xinlei He, Yanping Li, Shaomin Liu, Tongren Xu, Fei Chen, Zhenhua Li, Zhe Zhang, Rui Liu, Lisheng Song, Ziwei Xu, Zhixing Peng, and Chen Zheng
Hydrol. Earth Syst. Sci., 27, 1583–1606, https://doi.org/10.5194/hess-27-1583-2023, https://doi.org/10.5194/hess-27-1583-2023, 2023
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This study highlights the role of integrating vegetation and multi-source soil moisture observations in regional climate models via a hybrid data assimilation and machine learning method. In particular, we show that this approach can improve land surface fluxes, near-surface atmospheric conditions, and land–atmosphere interactions by implementing detailed land characterization information in basins with complex underlying surfaces.
Marissa Kivi, Noemi Vergopolan, and Hamze Dokoohaki
Hydrol. Earth Syst. Sci., 27, 1173–1199, https://doi.org/10.5194/hess-27-1173-2023, https://doi.org/10.5194/hess-27-1173-2023, 2023
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This study attempts to provide a framework for direct integration of soil moisture observations collected from soil sensors and satellite imagery into process-based crop models for improving the representation of agricultural systems. The performance of this framework was evaluated across 19 sites times years for crop yield, normalized difference vegetation index (NDVI), soil moisture, tile flow drainage, and nitrate leaching.
Yunfan Zhang, Lei Cheng, Lu Zhang, Shujing Qin, Liu Liu, Pan Liu, and Yanghe Liu
Hydrol. Earth Syst. Sci., 26, 6379–6397, https://doi.org/10.5194/hess-26-6379-2022, https://doi.org/10.5194/hess-26-6379-2022, 2022
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Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship. But whether changes can invalidate the most fundamental method (i.e., paired-catchment method (PCM)) for separating vegetation change impacts is still unknown. Using paired-catchment data with 10-year drought, PCM is shown to still be reliable even in catchments with non-stationarity. A new framework is further proposed to separate impacts of two non-stationary drivers, using paired-catchment data.
Don A. White, Shiqi Ren, Daniel S. Mendham, Francisco Balocchi-Contreras, Richard P. Silberstein, Dean Meason, Andrés Iroumé, and Pablo Ramirez de Arellano
Hydrol. Earth Syst. Sci., 26, 5357–5371, https://doi.org/10.5194/hess-26-5357-2022, https://doi.org/10.5194/hess-26-5357-2022, 2022
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Of all the planting options for wood production and carbon storage, Eucalyptus species provoke the greatest concern about their effect on water resources. We compared Eucalyptus and Pinus species (the two most widely planted genera) by fitting a simple model to the published estimates of their annual water use. There was no significant difference between the two genera. This has important implications for the global debate around Eucalyptus and is an option for carbon forests.
Zhihui Wang, Qiuhong Tang, Daoxi Wang, Peiqing Xiao, Runliang Xia, Pengcheng Sun, and Feng Feng
Hydrol. Earth Syst. Sci., 26, 5291–5314, https://doi.org/10.5194/hess-26-5291-2022, https://doi.org/10.5194/hess-26-5291-2022, 2022
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Variable infiltration capacity simulation considering dynamic vegetation types and structural parameters is able to better capture the effect of temporally explicit vegetation change and climate variation in hydrological regimes. Vegetation greening including interannual LAI and intra-annual LAI temporal pattern change induced by large-scale ecological restoration and non-vegetation underlying surface change played dominant roles in the natural streamflow reduction of the Yellow River basin.
Pan Chen, Wenhong Li, and Keqi He
Hydrol. Earth Syst. Sci., 26, 4875–4892, https://doi.org/10.5194/hess-26-4875-2022, https://doi.org/10.5194/hess-26-4875-2022, 2022
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The study assessed changes in total nitrogen (TN) and total phosphorus (TP) loads in response to eastern Pacific (EP) and central Pacific (CP) El Niño events over the Corn Belt, USA, using the SWAT model. Results showed that EP (CP) El Niño events improved (exacerbated) water quality in the region. Furthermore, EP El Niño had a much broader and longer impact on water quality at the outlets, but CP El Niño could lead to similar increases in TN/TP loads as EP El Niño at the specific watersheds.
Ralf Loritz, Maoya Bassiouni, Anke Hildebrandt, Sibylle K. Hassler, and Erwin Zehe
Hydrol. Earth Syst. Sci., 26, 4757–4771, https://doi.org/10.5194/hess-26-4757-2022, https://doi.org/10.5194/hess-26-4757-2022, 2022
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In this study, we combine a deep-learning approach that predicts sap flow with a hydrological model to improve soil moisture and transpiration estimates at the catchment scale. Our results highlight that hybrid-model approaches, combining machine learning with physically based models, are a promising way to improve our ability to make hydrological predictions.
Nicholas Jarvis, Jannis Groh, Elisabet Lewan, Katharina H. E. Meurer, Walter Durka, Cornelia Baessler, Thomas Pütz, Elvin Rufullayev, and Harry Vereecken
Hydrol. Earth Syst. Sci., 26, 2277–2299, https://doi.org/10.5194/hess-26-2277-2022, https://doi.org/10.5194/hess-26-2277-2022, 2022
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We apply an eco-hydrological model to data on soil water balance and grassland growth obtained at two sites with contrasting climates. Our results show that the grassland in the drier climate had adapted by developing deeper roots, which maintained water supply to the plants in the face of severe drought. Our study emphasizes the importance of considering such plastic responses of plant traits to environmental stress in the modelling of soil water balance and plant growth under climate change.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 525–550, https://doi.org/10.5194/hess-26-525-2022, https://doi.org/10.5194/hess-26-525-2022, 2022
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Most models that simulate water and carbon exchanges with the atmosphere rely on information about vegetation, but optimality models predict vegetation properties based on general principles. Here, we use the Vegetation Optimality Model (VOM) to predict vegetation behaviour at five savanna sites. The VOM overpredicted vegetation cover and carbon uptake during the wet seasons but also performed similarly to conventional models, showing that vegetation optimality is a promising approach.
Hongyu Li, Yi Luo, Lin Sun, Xiangdong Li, Changkun Ma, Xiaolei Wang, Ting Jiang, and Haoyang Zhu
Hydrol. Earth Syst. Sci., 26, 17–34, https://doi.org/10.5194/hess-26-17-2022, https://doi.org/10.5194/hess-26-17-2022, 2022
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Drying soil layers (DSLs) have been extensively reported in artificial forestland in the Loess Plateau, China, which has limited water resources and deep loess. To address this issue relating to plant root–soil water interactions, this study developed a root growth model that simulates both the dynamic rooting depth and fine-root distribution. Evaluation vs. field data proved a positive performance. Long-term simulation reproduced the evolution process of the DSLs and revealed their mechanisms.
Jiancong Chen, Baptiste Dafflon, Anh Phuong Tran, Nicola Falco, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 25, 6041–6066, https://doi.org/10.5194/hess-25-6041-2021, https://doi.org/10.5194/hess-25-6041-2021, 2021
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The novel hybrid predictive modeling (HPM) approach uses a long short-term memory recurrent neural network to estimate evapotranspiration (ET) and ecosystem respiration (Reco) with only meteorological and remote-sensing inputs. We developed four use cases to demonstrate the applicability of HPM. The results indicate HPM is capable of providing ET and Reco estimations in challenging mountainous systems and enhances our understanding of watershed dynamics at sparsely monitored watersheds.
Jiehao Zhang, Yulong Zhang, Ge Sun, Conghe Song, Matthew P. Dannenberg, Jiangfeng Li, Ning Liu, Kerong Zhang, Quanfa Zhang, and Lu Hao
Hydrol. Earth Syst. Sci., 25, 5623–5640, https://doi.org/10.5194/hess-25-5623-2021, https://doi.org/10.5194/hess-25-5623-2021, 2021
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To quantify how vegetation greening impacts the capacity of water supply, we built a hybrid model and conducted a case study using the upper Han River basin (UHRB) that serves as the water source area to the world’s largest water diversion project. Vegetation greening in the UHRB during 2001–2018 induced annual water yield (WY) greatly decreased. Vegetation greening also increased the possibility of drought and reduced a quarter of WY on average during drought periods.
Aaron J. Neill, Christian Birkel, Marco P. Maneta, Doerthe Tetzlaff, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 4861–4886, https://doi.org/10.5194/hess-25-4861-2021, https://doi.org/10.5194/hess-25-4861-2021, 2021
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Structural changes (cover and height of vegetation plus tree canopy characteristics) to forests during regeneration on degraded land affect how water is partitioned between streamflow, groundwater recharge and evapotranspiration. Partitioning most strongly deviates from baseline conditions during earlier stages of regeneration with dense forest, while recovery may be possible as the forest matures and opens out. This has consequences for informing sustainable landscape restoration strategies.
Jianning Ren, Jennifer C. Adam, Jeffrey A. Hicke, Erin J. Hanan, Christina L. Tague, Mingliang Liu, Crystal A. Kolden, and John T. Abatzoglou
Hydrol. Earth Syst. Sci., 25, 4681–4699, https://doi.org/10.5194/hess-25-4681-2021, https://doi.org/10.5194/hess-25-4681-2021, 2021
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Mountain pine beetle outbreaks have caused widespread tree mortality. While some research shows that water yield increases after trees are killed, many others document no change or a decrease. The climatic and environmental mechanisms driving hydrologic response to tree mortality are not well understood. We demonstrated that the direction of hydrologic response is a function of multiple factors, so previous studies do not necessarily conflict with each other; they represent different conditions.
Haidong Zhao, Gretchen F. Sassenrath, Mary Beth Kirkham, Nenghan Wan, and Xiaomao Lin
Hydrol. Earth Syst. Sci., 25, 4357–4372, https://doi.org/10.5194/hess-25-4357-2021, https://doi.org/10.5194/hess-25-4357-2021, 2021
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This study was done to develop an improved soil temperature model for the USA Great Plains by using common weather station variables as inputs. After incorporating knowledge of estimated soil moisture and observed daily snow depth, the improved model showed a near 50 % gain in performance compared to the original model. We conclude that our improved model can better estimate soil temperature at the surface soil layer where most hydrological and biological processes occur.
Brandon P. Sloan, Sally E. Thompson, and Xue Feng
Hydrol. Earth Syst. Sci., 25, 4259–4274, https://doi.org/10.5194/hess-25-4259-2021, https://doi.org/10.5194/hess-25-4259-2021, 2021
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Plants affect the global water and carbon cycles by modifying their water use and carbon intake in response to soil moisture. Global climate models represent this response with either simple empirical models or complex physical models. We reveal that the latter improves predictions in plants with large flow resistance; however, adding dependence on atmospheric moisture demand to the former matches performance of the latter, leading to a new tool for improving carbon and water cycle predictions.
Maria Magdalena Warter, Michael Bliss Singer, Mark O. Cuthbert, Dar Roberts, Kelly K. Caylor, Romy Sabathier, and John Stella
Hydrol. Earth Syst. Sci., 25, 3713–3729, https://doi.org/10.5194/hess-25-3713-2021, https://doi.org/10.5194/hess-25-3713-2021, 2021
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Intensified drying of soil and grassland vegetation is raising the impact of fire severity and extent in Southern California. While browned grassland is a common sight during the dry season, this study has shown that there is a pronounced shift in the timing of senescence, due to changing climate conditions favoring milder winter temperatures and increased precipitation variability. Vegetation may be limited in its ability to adapt to these shifts, as drought periods become more frequent.
Mikael Gillefalk, Dörthe Tetzlaff, Reinhard Hinkelmann, Lena-Marie Kuhlemann, Aaron Smith, Fred Meier, Marco P. Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 3635–3652, https://doi.org/10.5194/hess-25-3635-2021, https://doi.org/10.5194/hess-25-3635-2021, 2021
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We used a tracer-aided ecohydrological model to quantify water flux–storage–age interactions for three urban vegetation types: trees, shrub and grass. The model results showed that evapotranspiration increased in the order shrub < grass < trees during one growing season. Additionally, we could show how
infiltration hotspotscreated by runoff from sealed onto vegetated surfaces can enhance both evapotranspiration and groundwater recharge.
Yuting Yang, Tim R. McVicar, Dawen Yang, Yongqiang Zhang, Shilong Piao, Shushi Peng, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 25, 3411–3427, https://doi.org/10.5194/hess-25-3411-2021, https://doi.org/10.5194/hess-25-3411-2021, 2021
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This study developed an analytical ecohydrological model that considers three aspects of vegetation response to eCO2 (i.e., stomatal response, LAI response, and rooting depth response) to detect the impact of eCO2 on continental runoff over the past 3 decades globally. Our findings suggest a minor role of eCO2 on the global runoff changes, yet highlight the negative runoff–eCO2 response in semiarid and arid regions which may further threaten the limited water resource there.
Yanlan Liu, Nataniel M. Holtzman, and Alexandra G. Konings
Hydrol. Earth Syst. Sci., 25, 2399–2417, https://doi.org/10.5194/hess-25-2399-2021, https://doi.org/10.5194/hess-25-2399-2021, 2021
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The flow of water through plants varies with species-specific traits. To determine how they vary across the world, we mapped the traits that best allowed a model to match microwave satellite data. We also defined average values across a few clusters of trait behavior. These form a tractable solution for use in large-scale models. Transpiration estimates using these clusters were more accurate than if using plant functional types. We expect our maps to improve transpiration forecasts.
Aaron Smith, Doerthe Tetzlaff, Lukas Kleine, Marco Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 2239–2259, https://doi.org/10.5194/hess-25-2239-2021, https://doi.org/10.5194/hess-25-2239-2021, 2021
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We used a tracer-aided ecohydrological model on a mixed land use catchment in northeastern Germany to quantify water flux–storage–age interactions at four model grid resolutions. The model's ability to reproduce spatio-temporal flux–storage–age interactions decreases with increasing model grid sizes. Similarly, larger model grids showed vegetation-influenced changes in blue and green water partitioning. Simulations reveal the value of measured soil and stream isotopes for model calibration.
Yiping Hou, Mingfang Zhang, Xiaohua Wei, Shirong Liu, Qiang Li, Tijiu Cai, Wenfei Liu, Runqi Zhao, and Xiangzhuo Liu
Hydrol. Earth Syst. Sci., 25, 1447–1466, https://doi.org/10.5194/hess-25-1447-2021, https://doi.org/10.5194/hess-25-1447-2021, 2021
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Ecohydrological sensitivity, defined as the response intensity of streamflow to vegetation change, indicates the hydrological sensitivity to vegetation change. The study revealed seasonal ecohydrological sensitivities were highly variable, depending on climate condition and watershed attributes. Dry season ecohydrological sensitivity was mostly determined by topography, soil and vegetation, while wet season ecohydrological sensitivity was mainly controlled by soil, landscape and vegetation.
Xiangyu Luan and Giulia Vico
Hydrol. Earth Syst. Sci., 25, 1411–1423, https://doi.org/10.5194/hess-25-1411-2021, https://doi.org/10.5194/hess-25-1411-2021, 2021
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Crop yield is reduced by heat and water stress, particularly when they co-occur. We quantify the joint effects of (unpredictable) air temperature and soil water availability on crop heat stress via a mechanistic model. Larger but more infrequent precipitation increased crop canopy temperatures. Keeping crops well watered via irrigation could reduce canopy temperature but not enough to always exclude heat damage. Thus, irrigation is only a partial solution to adapt to warmer and drier climates.
Songyan Yu, Hong Xuan Do, Albert I. J. M. van Dijk, Nick R. Bond, Peirong Lin, and Mark J. Kennard
Hydrol. Earth Syst. Sci., 24, 5279–5295, https://doi.org/10.5194/hess-24-5279-2020, https://doi.org/10.5194/hess-24-5279-2020, 2020
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There is a growing interest globally in the spatial distribution and temporal dynamics of intermittently flowing streams and rivers. We developed an approach to quantify catchment-wide flow intermittency over long time frames. Modelled patterns of flow intermittency in eastern Australia revealed highly dynamic behaviour in space and time. The developed approach is transferable to other parts of the world and can inform hydro-ecological understanding and management of intermittent streams.
Natasha MacBean, Russell L. Scott, Joel A. Biederman, Catherine Ottlé, Nicolas Vuichard, Agnès Ducharne, Thomas Kolb, Sabina Dore, Marcy Litvak, and David J. P. Moore
Hydrol. Earth Syst. Sci., 24, 5203–5230, https://doi.org/10.5194/hess-24-5203-2020, https://doi.org/10.5194/hess-24-5203-2020, 2020
Yusen Yuan, Taisheng Du, Honglang Wang, and Lixin Wang
Hydrol. Earth Syst. Sci., 24, 4491–4501, https://doi.org/10.5194/hess-24-4491-2020, https://doi.org/10.5194/hess-24-4491-2020, 2020
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The isotopic composition of ambient water vapor is an important source of atmospheric water vapor and has not been able to be estimated to date using the Keeling plot approach. Here we proposed two new methods to estimate the isotopic composition of ambient water vapor: one using the intersection point method and another relying on the intermediate value theorem.
Valentin Couvreur, Youri Rothfuss, Félicien Meunier, Thierry Bariac, Philippe Biron, Jean-Louis Durand, Patricia Richard, and Mathieu Javaux
Hydrol. Earth Syst. Sci., 24, 3057–3075, https://doi.org/10.5194/hess-24-3057-2020, https://doi.org/10.5194/hess-24-3057-2020, 2020
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Isotopic labeling of soil water is a broadly used tool for tracing the origin of water extracted by plants and computing root water uptake (RWU) profiles with multisource mixing models. In this study, we show how a method such as this may misconstrue time series of xylem water isotopic composition as the temporal dynamics of RWU by simulating data collected during a tall fescue rhizotron experiment with an isotope-enabled physical soil–root model accounting for variability in root traits.
Thibault Hallouin, Michael Bruen, and Fiachra E. O'Loughlin
Hydrol. Earth Syst. Sci., 24, 1031–1054, https://doi.org/10.5194/hess-24-1031-2020, https://doi.org/10.5194/hess-24-1031-2020, 2020
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A hydrological model was used to compare different parameterisation strategies in view of predicting ecologically relevant streamflow indices in 33 Irish catchments. Compared for 14 different periods, a strategy fitting simulated and observed streamflow indices yielded better performance than fitting simulated and observed streamflow, but it also yielded a less consistent ensemble of parameter sets, suggesting that these indices may not be hydrologically relevant for model parameterisation.
Robert N. Armstrong, John W. Pomeroy, and Lawrence W. Martz
Hydrol. Earth Syst. Sci., 23, 4891–4907, https://doi.org/10.5194/hess-23-4891-2019, https://doi.org/10.5194/hess-23-4891-2019, 2019
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Digital and thermal images taken near midday were used to scale daily point observations of key factors driving actual-evaporation estimates across a complex Canadian Prairie landscape. Point estimates of actual evaporation agreed well with observed values via eddy covariance. Impacts of spatial variations on areal estimates were minor, and no covariance was found between model parameters driving the energy term. The methods can be applied further to improve land surface parameterisations.
Zhongkai Li, Hu Liu, Wenzhi Zhao, Qiyue Yang, Rong Yang, and Jintao Liu
Hydrol. Earth Syst. Sci., 23, 4685–4706, https://doi.org/10.5194/hess-23-4685-2019, https://doi.org/10.5194/hess-23-4685-2019, 2019
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A database of soil moisture measurements from the middle Heihe River basin of China was used to test the potential of a soil moisture database in estimating the soil water balance components (SWBCs). We determined SWBCs using a method that combined the soil water balance method and the inverse Richards equation. This work confirmed that relatively reasonable estimations of the SWBCs in coarse-textured sandy soils can be derived using soil moisture measurements.
Inês Gomes Marques, João Nascimento, Rita M. Cardoso, Filipe Miguéns, Maria Teresa Condesso de Melo, Pedro M. M. Soares, Célia M. Gouveia, and Cathy Kurz Besson
Hydrol. Earth Syst. Sci., 23, 3525–3552, https://doi.org/10.5194/hess-23-3525-2019, https://doi.org/10.5194/hess-23-3525-2019, 2019
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Mediterranean cork woodlands are very particular agroforestry systems present in a confined area of the Mediterranean Basin. They are of great importance due to their high socioeconomic value; however, a decrease in water availability has put this system in danger. In this paper we build a model that explains this system's tree-species distribution in southern Portugal from environmental variables. This could help predict their future distribution under changing climatic conditions.
Samuli Launiainen, Mingfu Guan, Aura Salmivaara, and Antti-Jussi Kieloaho
Hydrol. Earth Syst. Sci., 23, 3457–3480, https://doi.org/10.5194/hess-23-3457-2019, https://doi.org/10.5194/hess-23-3457-2019, 2019
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Boreal forest evapotranspiration and water cycle is modeled at stand and catchment scale using physiological and physical principles, open GIS data and daily weather data. The approach can predict daily evapotranspiration well across Nordic coniferous-dominated stands and successfully reproduces daily streamflow and annual evapotranspiration across boreal headwater catchments in Finland. The model is modular and simple and designed for practical applications over large areas using open data.
Regina T. Hirl, Hans Schnyder, Ulrike Ostler, Rudi Schäufele, Inga Schleip, Sylvia H. Vetter, Karl Auerswald, Juan C. Baca Cabrera, Lisa Wingate, Margaret M. Barbour, and Jérôme Ogée
Hydrol. Earth Syst. Sci., 23, 2581–2600, https://doi.org/10.5194/hess-23-2581-2019, https://doi.org/10.5194/hess-23-2581-2019, 2019
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We evaluated the system-scale understanding of the propagation of the oxygen isotope signal (δ18O) of rain through soil and xylem to leaf water in a temperate drought-prone grassland. Biweekly δ18O observations of the water pools made during seven growing seasons were accurately reproduced by the 18O-enabled process-based model MuSICA. While water uptake occurred from shallow soil depths throughout dry and wet periods, leaf water 18O enrichment responded to both soil and atmospheric moisture.
Christoph Schürz, Brigitta Hollosi, Christoph Matulla, Alexander Pressl, Thomas Ertl, Karsten Schulz, and Bano Mehdi
Hydrol. Earth Syst. Sci., 23, 1211–1244, https://doi.org/10.5194/hess-23-1211-2019, https://doi.org/10.5194/hess-23-1211-2019, 2019
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For two Austrian catchments we simulated discharge and nitrate-nitrogen (NO3-N) considering future changes of climate, land use, and point source emissions together with the impact of different setups and parametrizations of the implemented eco-hydrological model. In a comprehensive analysis we identified the dominant sources of uncertainty for the simulation of discharge and NO3-N and further examined how specific properties of the model inputs control the future simulation results.
Yu-Ting Shih, Pei-Hao Chen, Li-Chin Lee, Chien-Sen Liao, Shih-Hao Jien, Fuh-Kwo Shiah, Tsung-Yu Lee, Thomas Hein, Franz Zehetner, Chung-Te Chang, and Jr-Chuan Huang
Hydrol. Earth Syst. Sci., 22, 6579–6590, https://doi.org/10.5194/hess-22-6579-2018, https://doi.org/10.5194/hess-22-6579-2018, 2018
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DOC and DIC export in Taiwan shows that the annual DOC and DIC fluxes were 2.7–4.8 and 48.4–54.3 ton C km2 yr1, respectively, which were approximately 2 and 20 times higher than the global means of 1.4 and 2.6 ton C km2 yr1, respectively.
Zun Yin, Catherine Ottlé, Philippe Ciais, Matthieu Guimberteau, Xuhui Wang, Dan Zhu, Fabienne Maignan, Shushi Peng, Shilong Piao, Jan Polcher, Feng Zhou, Hyungjun Kim, and other China-Trend-Stream project members
Hydrol. Earth Syst. Sci., 22, 5463–5484, https://doi.org/10.5194/hess-22-5463-2018, https://doi.org/10.5194/hess-22-5463-2018, 2018
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Simulations in China were performed in ORCHIDEE driven by different forcing datasets: GSWP3, PGF, CRU-NCEP, and WFDEI. Simulated soil moisture was compared to several datasets to evaluate the ability of ORCHIDEE in reproducing soil moisture dynamics. Results showed that ORCHIDEE soil moisture coincided well with other datasets in wet areas and in non-irrigated areas. It suggested that the ORCHIDEE-MICT was suitable for further hydrological studies in China.
Matthias J. R. Speich, Heike Lischke, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 22, 4097–4124, https://doi.org/10.5194/hess-22-4097-2018, https://doi.org/10.5194/hess-22-4097-2018, 2018
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To simulate the water balance of, e.g., a forest plot, it is important to estimate the maximum volume of water available to plants. This depends on soil properties and the average depth of roots. Rooting depth has proven challenging to estimate. Here, we applied a model assuming that plants dimension their roots to optimize their carbon budget. We compared its results with values obtained by calibrating a dynamic water balance model. In most cases, there is good agreement between both methods.
Gordon C. O'Brien, Chris Dickens, Eleanor Hines, Victor Wepener, Retha Stassen, Leo Quayle, Kelly Fouchy, James MacKenzie, P. Mark Graham, and Wayne G. Landis
Hydrol. Earth Syst. Sci., 22, 957–975, https://doi.org/10.5194/hess-22-957-2018, https://doi.org/10.5194/hess-22-957-2018, 2018
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In global water resource allocation, robust tools are required to establish environmental flows. In addition, tools should characterize past, present and future consequences of altered flows and non-flow variables to social and ecological management objectives. PROBFLO is a risk assessment method designed to meet best practice principles for regional-scale holistic E-flow assessments. The approach has been developed in Africa and applied across the continent.
Katrina E. Bennett, Theodore J. Bohn, Kurt Solander, Nathan G. McDowell, Chonggang Xu, Enrique Vivoni, and Richard S. Middleton
Hydrol. Earth Syst. Sci., 22, 709–725, https://doi.org/10.5194/hess-22-709-2018, https://doi.org/10.5194/hess-22-709-2018, 2018
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We applied the Variable Infiltration Capacity hydrologic model to examine scenarios of change under climate and landscape disturbances in the San Juan River basin, a major sub-watershed of the Colorado River basin. Climate change coupled with landscape disturbance leads to reduced streamflow in the San Juan River basin. Disturbances are expected to be widespread in this region. Therefore, accounting for these changes within the context of climate change is imperative for water resource planning.
Fernando Jaramillo, Neil Cory, Berit Arheimer, Hjalmar Laudon, Ype van der Velde, Thomas B. Hasper, Claudia Teutschbein, and Johan Uddling
Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, https://doi.org/10.5194/hess-22-567-2018, 2018
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Which is the dominant effect on evapotranspiration in northern forests, an increase by recent forests expansion or a decrease by the water use response due to increasing CO2 concentrations? We determined the dominant effect during the period 1961–2012 in 65 Swedish basins. We used the Budyko framework to study the hydroclimatic movements in Budyko space. Our findings suggest that forest expansion is the dominant driver of long-term and large-scale evapotranspiration changes.
Cited articles
Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008. a
Albergel, C., Munier, S., Leroux, D. J., Dewaele, H., Fairbairn, D., Barbu, A. L., Gelati, E., Dorigo, W., Faroux, S., Meurey, C., Le Moigne, P., Decharme, B., Mahfouf, J.-F., and Calvet, J.-C.: Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area, Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, 2017. a, b, c, d, e, f
Albergel, C., Dutra, E., Bonan, B., Zheng, Y., Munier, S., Balsamo, G., de Rosnay, P., Muñoz-Sabater, J., and Calvet, J.-C.: Monitoring and Forecasting the Impact of the 2018 Summer Heatwave on Vegetation, Remote Sens,, 11, 520, https://doi.org/10.3390/rs11050520, 2019. a
Albergel, C., Zheng, Y., Bonan, B., Dutra, E., Rodríguez-Fernández, N., Munier, S., Draper, C., de Rosnay, P., Muñoz Sabater, J., Balsamo, G., Fairbairn, D., Meurey, C., and Calvet, J.-C.: Data assimilation for continuous global assessment of severe conditions over terrestrial surfaces, Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, 2020. a, b, c, d, e, f
Alday, J. G., Camarero, J. J., Revilla, J., and Resco de Dios, V.: Similar diurnal, seasonal and annual rhythms in radial root expansion across two coexisting Mediterranean oak species, Tree Physiol., 40, 956–968, 2020. a
Al-Yaari, A., Dayau, S., Chipeaux, C., Aluome, C., Kruszewski, A., Loustau, D., and Wigneron, J.-P.: The AQUI soil moisture network for satellite microwave remote sensing validation in South-Western France, Remote Sens., 10, 1839, https://doi.org/10.3390/rs10111839, 2018. a
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009. a
Barbu, A. L., Calvet, J.-C., Mahfouf, J.-F., and Lafont, S.: Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France, Hydrol. Earth Syst. Sci., 18, 173–192, https://doi.org/10.5194/hess-18-173-2014, 2014. a, b, c
Bechtold, M., De Lannoy, G., Reichle, R., Roose, D., Balliston, N., Burdun, I., Devito, K., Kurbatova, J., Strack, M., and Zarov, E.: Improved groundwater table and L-band brightness temperature estimates for Northern Hemisphere peatlands using new model physics and SMOS observations in a global data assimilation framework, Remote Sens. Environ., 246, 111805, https://doi.org/10.1016/j.rse.2020.111805, 2020. a
Betts, A. K., Ball, J. H., Beljaars, A. C. M., Miller, M. J., and Viterbo, P. A.: The land surface-atmosphere interaction: A review based on observational and global modeling perspectives, J. Geophys. Res.-Atmos., 101, 7209–7225, https://doi.org/10.1029/95JD02135, 1996. a
Beyrich, F. and Adam, W.: Site and Data Report for the Lindenberg Reference Site in CEOP – Phase 1, Berichte des Deutschen Wetterdienstes, Offenbach am Main, 230 pp., 2007. a
Biddoccu, M., Ferraris, S., Opsi, F., and Cavallo, E.: Long-term monitoring of soil management effects on runoff and soil erosion in sloping vineyards in Alto Monferrato (North–West Italy), Soil Till. Res., 155, 176–189, 2016. a
Bircher, S., Skou, N., Jensen, K. H., Walker, J. P., and Rasmussen, L.: A soil moisture and temperature network for SMOS validation in Western Denmark, Hydrol. Earth Syst. Sci., 16, 1445–1463, https://doi.org/10.5194/hess-16-1445-2012, 2012. a
Blöschl, G., Blaschke, A. P., Broer, M., Bucher, C., Carr, G., Chen, X., Eder, A., Exner-Kittridge, M., Farnleitner, A., Flores-Orozco, A., Haas, P., Hogan, P., Kazemi Amiri, A., Oismüller, M., Parajka, J., Silasari, R., Stadler, P., Strauss, P., Vreugdenhil, M., Wagner, W., and Zessner, M.: The Hydrological Open Air Laboratory (HOAL) in Petzenkirchen: a hypothesis-driven observatory, Hydrol. Earth Syst. Sci., 20, 227–255, https://doi.org/10.5194/hess-20-227-2016, 2016. a
Bogdanovich, E., Perez-Priego, O., El-Madany, T. S., Guderle, M., Pacheco-Labrador, J., Levick, S. R., Moreno, G., Carrara, A., Pilar Martín, M., and Migliavacca, M.: Using terrestrial laser scanning for characterizing tree structural parameters and their changes under different management in a Mediterranean open woodland, Forest Ecol. Manage., 486, 118945, https://doi.org/10.1016/j.foreco.2021.118945, 2021. a
Bogena, H., Kunkel, R., Pütz, T., Vereecken, H., Kruger, E., Zacharias, S., Dietrich, P., Wollschläger, U., Kunstmann, H., Papen, H., Schmid, H., Munch, J., Priesack, E., Schwank, M., Bens, O., Brauer, A., Borg, E., and Hajnsek, I.: TERENO – Long-term monitoring network for terrestrial environmental research, Hydrol. Wasserbewirt., 56, 138–143, 2012. a
Bogena, H., Montzka, C., Huisman, J., Graf, A., Schmidt, M., Stockinger, M., von Hebel, C., Hendricks-Franssen, H., van der Kruk, J., Tappe, W., Lücke, A., Baatz, R., Bol, R., Groh, J., Pütz, T., Jakobi, J., Kunkel, R., Sorg, J., and Vereecken, H.: The TERENO-Rur Hydrological Observatory: A Multiscale Multi-Compartment Research Platform for the Advancement of Hydrological Science, Vadose Zone J., 17, 180055, https://doi.org/10.2136/vzj2018.03.0055, 2018. a
Bogena, H. R.: TERENO: German network of terrestrial environmental observatories, J. Large-Scale Res. Facil., 2, A52, https://doi.org/10.17815/jlsrf-2-98, 2016. a
Bonan, B., Albergel, C., Zheng, Y., Barbu, A. L., Fairbairn, D., Munier, S., and Calvet, J.-C.: An ensemble square root filter for the joint assimilation of surface soil moisture and leaf area index within the Land Data Assimilation System LDAS-Monde: application over the Euro-Mediterranean region, Hydrol. Earth Syst. Sci., 24, 325–347, https://doi.org/10.5194/hess-24-325-2020, 2020. a
Bonan, G.: Terrestrial Biosphere Models, Cambridge University Press, 1–24, https://doi.org/10.1017/9781107339217.002, 2019. a
Boussetta, S., Balsamo, G., Beljaars, A., Kral, T., and Jarlan, L.: Impact of a satellite-derived leaf area index monthly climatology in a global numerical weather prediction model, Int. J. Remote Sens., 34, 3520–3542, https://doi.org/10.1080/01431161.2012.716543, 2013. a
Brocca, L., Melone, F., and Moramarco, T.: On the estimation of antecedent wetness condition in rainfall-runoff modeling, Hydrol. Process., 22, 629–642, https://doi.org/10.1002/hyp.6629, 2008. a
Brocca, L., Melone, F., Moramarco, T., and Morbidelli, R.: Antecedent wetness conditions based on ERS scatterometer data, J. Hydrol., 364, 73–87, 2009. a
Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., A, D., Matgen, P., Martínez-Fernádez, J., Llorens, P., Latron, J., Martin, C., and Bittelli, M.: Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe, Remote Sens. Environ., 115, 3390–3408, https://doi.org/10.1016/j.rse.2011.08.003, 2011a. a
Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martínez-Fernández, J., Llorens, P., Latron, J., Martin, C., and Bittelli, M.: Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe, Remote Sens. Environ., 115, 3390–3408, 2011b. a, b
Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., and Piguet, B.: In situ soil moisture observations for the CAL/VAL of SMOS: the SMOSMANIA network, in: 2007 IEEE International Geoscience and Remote Sensing Symposium, 1196–1199, https://doi.org/10.1109/IGARSS.2007.4423019, 2007. a
Calvet, J.-C., Fritz, N., Berne, C., Piguet, B., Maurel, W., and Meurey, C.: Deriving pedotransfer functions for soil quartz fraction in southern France from reverse modeling, SOIL, 2, 615–629, https://doi.org/10.5194/soil-2-615-2016, 2016. a
Capello, G., Biddoccu, M., Ferraris, S., and Cavallo, E.: Effects of tractor passes on hydrological and soil erosion processes in tilled and grassed vineyards, Water, 11, 2118, https://doi.org/10.3390/w11102118, 2019. a
Casals, P., Gimeno, C., Carrara, A., Lopez-Sangil, L., and Sanz, M.: Soil CO2 efflux and extractable organic carbon fractions under simulated precipitation events in a Mediterranean Dehesa, Soil Biol. Biochem., 41, 1915–1922, https://doi.org/10.1016/j.soilbio.2009.06.015, 2009. a
Chen, X., Su, Z., Ma, Y., Trigo, I., and Gentine, P.: Remote sensing of global daily evapotranspiration based on a surface energy balance method and reanalysis data, J. Geophys. Res.-Atmos., 126, e2020JD032873, https://doi.org/10.1029/2020JD032873, 2021. a
Crow, W. T., Gomez, C. A., Sabater, J. M., Holmes, T., Hain, C. R., Lei, F., Dong, J., Alfieri, J. G., and Anderson, M. C.: Soil Moisture–Evapotranspiration Overcoupling and L-Band Brightness Temperature Assimilation: Sources and Forecast Implications, J. Hydrometeorol., 21, 2359–2374, https://doi.org/10.1175/JHM-D-20-0088.1, 2020. a
Dahlin, K. M., Fisher, R. A., and Lawrence, P. J.: Environmental drivers of drought deciduous phenology in the Community Land Model, Biogeosciences, 12, 5061–5074, https://doi.org/10.5194/bg-12-5061-2015, 2015. a, b
Dahlin, K. M., Ponte, D. D., Setlock, E., and Nagelkirk, R.: Global patterns of drought deciduous phenology in semi-arid and savanna-type ecosystems, Ecography, 40, 314–323, https://doi.org/10.1111/ecog.02443, 2017. a
Darouich, H., Ramos, T. B., Pereira, L. S., Rabino, D., Bagagiolo, G., Capello, G., Simionesei, L., Cavallo, E., and Biddoccu, M.: Water Use and Soil Water Balance of Mediterranean Vineyards under Rainfed and Drip Irrigation Management: Evapotranspiration Partition and Soil Management Modelling for Resource Conservation, Water, 14, 554, https://doi.org/10.3390/w14040554, 2022. a
De Lannoy, G. J., Bechtold, M., Albergel, C., Brocca, L., Calvet, J.-C., Carrassi, A., Crow, W. T., De Rosnay, P., Durand, M., Forman, B., Geppert, G., Girotto, M., Hendricks-Franssen, H.-J., Jonas, T., Kumar, S. V., Lievens, H., Lu, Y., Massari, C., Pauwels, V., Reichle, R., and Steele-Dunne, S.: Perspective on Satellite-Based Land Data Assimilation to Estimate Water Cycle Components in an Era of Advanced Data Availability and Model Sophistication, Front. Water, 4, 156, https://doi.org/10.3389/frwa.2022.981745, 2022. a
De Lannoy, G. J. M. and Reichle, R. H.: Global Assimilation of Multiangle and Multipolarization SMOS Brightness Temperature Observations into the GEOS-5 Catchment Land Surface Model for Soil Moisture Estimation, J. Hydrometeorol., 17, 669–691, https://doi.org/10.1175/JHM-D-15-0037.1, 2016. a
De Lannoy, G. J. M., Houser, P. R., Pauwels, V. R. N., and Verhoest, N. E. C.: State and bias estimation for soil moisture profiles by an ensemble Kalman filter: Effect of assimilation depth and frequency, Water Resour. Res., 43, W06401, https://doi.org/10.1029/2006WR005100, 2007a. a, b
De Lannoy, G. J. M., Reichle, R. H., Houser, P. R., Pauwels, V. R. N., and Verhoest, N. E. C.: Correcting for forecast bias in soil moisture assimilation with the ensemble Kalman filter, Water Resour. Res., 43, W09410, https://doi.org/10.1029/2006WR005449, 2007b. a, b, c
Derber, J. C. and Wu, W.-S.: The Use of TOVS Cloud-Cleared Radiances in the NCEP SSI Analysis System, Mon. Weather Rev., 126, 2287–2299, https://doi.org/10.1175/1520-0493(1998)126<2287:TUOTCC>2.0.CO;2, 1998. a
Desroziers, G., Berre, L., Chapnik, B., and Poli, P.: Diagnosis of observation, background and analysis-error statistics in observation space, Q. J. Roy. Meteorol. Soc., 131, 3385–3396, https://doi.org/10.1256/qj.05.108, 2005. a, b, c
Dickinson, R. E., Shaikh, M., Bryant, R., and Graumlich, L.: Interactive Canopies for a Climate Model, J. Climate, 11, 2823–2836, https://doi.org/10.1175/1520-0442(1998)011<2823:ICFACM>2.0.CO;2, 1998. a
Dong, J. and Ochsner, T. E.: Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns, Water Resour. Res., 54, 2199–2211, https://doi.org/10.1002/2017WR021692, 2018. a
Dorigo, W., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiová, A., Sanchis-Dufau, A., Zamojski, D., Cordes, C., Wagner, W., and Drusch, M.: Global Automated Quality Control of In Situ Soil Moisture Data from the International Soil Moisture Network, Vadose Zone J., 12, vzj2012.0097, https://doi.org/10.2136/vzj2012.0097, 2013. a
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi, M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y., Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C., van der Schalie, R., Seneviratne, S. I., Smolander, T., and Lecomte, P.: ESA CCI Soil Moisture for improved Earth system understanding: State-of-the-art and future directions, Remote Sens. Environ., 203, 185–215, https://doi.org/10.1016/j.rse.2017.07.001, 2017. a
Dorigo, W., Himmelbauer, I., Aberer, D., Schremmer, L., Petrakovic, I., Zappa, L., Preimesberger, W., Xaver, A., Annor, F., Ardö, J., Baldocchi, D., Bitelli, M., Blöschl, G., Bogena, H., Brocca, L., Calvet, J.-C., Camarero, J. J., Capello, G., Choi, M., Cosh, M. C., van de Giesen, N., Hajdu, I., Ikonen, J., Jensen, K. H., Kanniah, K. D., de Kat, I., Kirchengast, G., Kumar Rai, P., Kyrouac, J., Larson, K., Liu, S., Loew, A., Moghaddam, M., Martínez Fernández, J., Mattar Bader, C., Morbidelli, R., Musial, J. P., Osenga, E., Palecki, M. A., Pellarin, T., Petropoulos, G. P., Pfeil, I., Powers, J., Robock, A., Rüdiger, C., Rummel, U., Strobel, M., Su, Z., Sullivan, R., Tagesson, T., Varlagin, A., Vreugdenhil, M., Walker, J., Wen, J., Wenger, F., Wigneron, J. P., Woods, M., Yang, K., Zeng, Y., Zhang, X., Zreda, M., Dietrich, S., Gruber, A., van Oevelen, P., Wagner, W., Scipal, K., Drusch, M., and Sabia, R.: The International Soil Moisture Network: serving Earth system science for over a decade, Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, 2021. a, b
Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and Jackson, T.: The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675–1698, https://doi.org/10.5194/hess-15-1675-2011, 2011. a
Draper, C. S., Reichle, R. H., De Lannoy, G. J. M., and Liu, Q.: Assimilation of passive and active microwave soil moisture retrievals, Geophys. Res. Lett., 39, L04401, https://doi.org/10.1029/2011GL050655, 2012. a
Drusch, M., Wood, E. F., and Gao, H.: Observation operators for the direct assimilation of TRMM microwave imager retrieved soil moisture, Geophys. Res. Lett., 32, L15403, https://doi.org/10.1029/2005GL023623, 2005. a
El-Madany, T. S., Reichstein, M., Perez-Priego, O., Carrara, A., Moreno, G., Pilar Martín, M., Pacheco-Labrador, J., Wohlfahrt, G., Nieto, H., Weber, U., Kolle, O., Luo, Y.-P., Carvalhais, N., and Migliavacca, M.: Drivers of spatio-temporal variability of carbon dioxide and energy fluxes in a Mediterranean savanna ecosystem, Agr. Forest Meteorol., 262, 258–278, ISSN https://doi.org/10.1016/j.agrformet.2018.07.010, 2018. a, b
El-Madany, T. S., Reichstein, M., Carrara, A., Martín, M. P., Moreno, G., Gonzalez-Cascon, R., Peñuelas, J., Ellsworth, D. S., Burchard-Levine, V., Hammer, T. W., Knauer, J., Kolle, O., Luo, Y., Pacheco-Labrador, J., Nelson, J. A., Perez-Priego, O., Rolo, V., Wutzler, T., and Migliavacca, M.: How Nitrogen and Phosphorus Availability Change Water Use Efficiency in a Mediterranean Savanna Ecosystem, J. Geophys. Res.-Biogeo., 126, e2020JG006005, https://doi.org/10.1029/2020JG006005, 2021. a, b
Erlingis, J. M., Rodell, M., Peters-Lidard, C. D., Li, B., Kumar, S. V., Famiglietti, J. S., Granger, S. L., Hurley, J. V., Liu, P.-W., and Mocko, D. M.: A High-Resolution Land Data Assimilation System Optimized for the Western United States, J. Am. Water Resour. Assoc., 57, 692–710, https://doi.org/10.1111/1752-1688.12910, 2021. a, b
Evensen, G.: The ensemble Kalman filter: Theoretical formulation and practical implementation, Ocean Dynam., 53, 343–367, 2003. a
Evensen, G.: The ensemble Kalman filter for combined state and parameter estimation, IEEE Control Syst. Mag., 29, 83–104, https://doi.org/10.1109/MCS.2009.932223, 2009. a
Fairbairn, D., Barbu, A. L., Napoly, A., Albergel, C., Mahfouf, J.-F., and Calvet, J.-C.: The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France, Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, 2017. a, b
Fang, H., Baret, F., Plummer, S., and Schaepman-Strub, G.: An Overview of Global Leaf Area Index (LAI): Methods, Products, Validation, and Applications, Rev. Geophys., 57, 739–799, https://doi.org/10.1029/2018RG000608, 2019. a
Forkel, M., Drüke, M., Thurner, M., Dorigo, W., Schaphoff, S., Thonicke, K., von Bloh, W., and Carvalhais, N.: Constraining modelled global vegetation dynamics and carbon turnover using multiple satellite observations, Sci. Rep., 9, 1–12, https://doi.org/10.1038/s41598-019-55187-7, 2019. a
Fox, A. M., Hoar, T. J., Anderson, J. L., Arellano, A. F., Smith, W. K., Litvak, M. E., MacBean, N., Schimel, D. S., and Moore, D. J. P.: Evaluation of a Data Assimilation System for Land Surface Models Using CLM4.5, J. Adv. Model. Earth Syst., 10, 2471–2494, https://doi.org/10.1029/2018MS001362, 2018. a, b, c, d, e, f
Frankenberg, C., Fisher, J. B., Worden, J., Badgley, G., Saatchi, S. S., Lee, J.-E., Toon, G. C., Butz, A., Jung, M., Kuze, A., and Yokota, T.: New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity, Geophys. Res. Lett., 38, L17706, https://doi.org/10.1029/2011GL048738, 2011. a
Fratini, G. and Mauder, M.: Towards a consistent eddy-covariance processing: an intercomparison of EddyPro and TK3, Atmos. Meas. Tech., 7, 2273–2281, https://doi.org/10.5194/amt-7-2273-2014, 2014. a
Frei, M. and Künsch, H. R.: Bridging the ensemble Kalman and particle filters, Biometrika, 100, 781–800, https://doi.org/10.1093/biomet/ast020, 2013. a, b
Friedl, M., McIver, D., Hodges, J., Zhang, X., Muchoney, D., Strahler, A., Woodcock, C., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., and Schaaf, C.: Global land cover mapping from MODIS: algorithms and early results, Remote Sens. Environ., 83, 287–302, https://doi.org/10.1016/S0034-4257(02)00078-0, 2002. a
Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Bakker, D. C. E., Hauck, J., Le Quéré, C., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Bates, N. R., Becker, M., Bellouin, N., Bopp, L., Chau, T. T. T., Chevallier, F., Chini, L. P., Cronin, M., Currie, K. I., Decharme, B., Djeutchouang, L. M., Dou, X., Evans, W., Feely, R. A., Feng, L., Gasser, T., Gilfillan, D., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, O., Harris, I., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Luijkx, I. T., Jain, A., Jones, S. D., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lienert, S., Liu, J., Marland, G., McGuire, P. C., Melton, J. R., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Niwa, Y., Ono, T., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Schwingshackl, C., Séférian, R., Sutton, A. J., Sweeney, C., Tanhua, T., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F., van der Werf, G. R., Vuichard, N., Wada, C., Wanninkhof, R., Watson, A. J., Willis, D., Wiltshire, A. J., Yuan, W., Yue, C., Yue, X., Zaehle, S., and Zeng, J.: Global Carbon Budget 2021, Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, 2022. a
Fuchsberger, J., Kirchengast, G., and Kabas, T.: WegenerNet high-resolution weather and climate data from 2007 to 2020, Earth Syst. Sci. Data, 13, 1307–1334, https://doi.org/10.5194/essd-13-1307-2021, 2021. a
Gim, H.-J., Park, S. K., Kang, M., Thakuri, B. M., Kim, J., and Ho, C.-H.: An improved parameterization of the allocation of assimilated carbon to plant parts in vegetation dynamics for Noah-MP, J. Adv. Mode. Earth Syst., 9, 1776–1794, https://doi.org/10.1002/2016MS000890, 2017. a
Girotto, M., Reichle, R. H., Rodell, M., Liu, Q., Mahanama, S., and De Lannoy, G. J.: Multi-sensor assimilation of SMOS brightness temperature and GRACE terrestrial water storage observations for soil moisture and shallow groundwater estimation, Remote Sens. Environ., 227, 12–27, https://doi.org/10.1016/j.rse.2019.04.001, 2019. a
González-Zamora, Á., Sánchez, N., Pablos, M., and Martínez-Fernández, J.: CCI soil moisture assessment with SMOS soil moisture and in situ data under different environmental conditions and spatial scales in Spain, Remote Sens. Environ., 225, 469–482, https://doi.org/10.1016/j.rse.2018.02.010, 2019. a
GRDC: Watershed Boundaries of GRDC Stations, Global Runoff Data Centre, BfG – Federal Institute of Hydrology, Koblenz, Germany, https://portal.grdc.bafg.de/ (last access: 3 November 2023), 2011. a
Greve, P., Orlowsky, B., Mueller, B., Sheffield, J., Reichstein, M., and Seneviratne, S. I.: Global assessment of trends in wetting and drying over land, Nat. Geosci., 7, 716–721, 2014. a
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W.: Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, 2019. a, b
Gruber, A., De Lannoy, G., Albergel, C., Al-Yaari, A., Brocca, L., Calvet, J.-C., Colliander, A., Cosh, M., Crow, W., Dorigo, W., Draper, C., Hirschi, M., Kerr, Y., Konings, A., Lahoz, W., McColl, K., Montzka, C., Muñoz-Sabater, J., Peng, J., Reichle, R., Richaume, P., Rüdiger, C., Scanlon, T., van der Schalie, R., Wigneron, J.-P., and Wagner, W.: Validation practices for satellite soil moisture retrievals: What are (the) errors?, Remote Sens. Environ., 244, 111806, https://doi.org/10.1016/j.rse.2020.111806, 2020. a
Hansen, M. C., DeFries, R. S., Townshend, J. R., and Sohlberg, R.: Global land cover classification at 1 km spatial resolution using a classification tree approach, Int. J. Remote Sens., 21, 1331–1364, 2000. a
Hashimoto, H., Nemani, R. R., Bala, G., Cao, L., Michaelis, A. R., Ganguly, S., Wang, W., Milesi, C., Eastman, R., Lee, T., and Myneni, R.: Constraints to vegetation growth reduced by region-specific changes in seasonal climate, Climate, 7, 27, https://doi.org/10.3390/cli7020027, 2019. a
He, X., Liu, S., Xu, T., Yu, K., Gentine, P., Zhang, Z., Xu, Z., Jiao, D., and Wu, D.: Improving predictions of evapotranspiration by integrating multi-source observations and land surface model, Agr. Water Manage., 272, 107827, https://doi.org/10.1016/j.agwat.2022.107827, 2022. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Heyvaert, Z., Scherrer, S., Bechtold, M., Gruber, A., Dorigo, W., Kumar, S., and De Lannoy, G.: Impact of design factors for ESA CCI satellite soil moisture data assimilation over Europe, J. Hydrometeorol., 24, 1193–1208, https://doi.org/10.1175/JHM-D-22-0141.1, 2023. a
Huang, A., Shen, R., Shi, C., and Sun, S.: Effects of satellite LAI data on modelling land surface temperature and related energy budget in the Noah-MP land surface model, J. Hydrol., 613, 128351, https://doi.org/10.1016/j.jhydrol.2022.128351, 2022. a, b
Ikonen, J., Vehviläinen, J., Rautiainen, K., Smolander, T., Lemmetyinen, J., Bircher, S., and Pulliainen, J.: The Sodankylä in situ soil moisture observation network: an example application of ESA CCI soil moisture product evaluation, Geoscientific Instrumentation, Meth. Data Syst., 5, 95–108, https://doi.org/10.5194/gi-5-95-2016, 2016. a
Ikonen, J., Smolander, T., Rautiainen, K., Cohen, J., Lemmetyinen, J., Salminen, M., and Pulliainen, J.: Spatially distributed evaluation of ESA CCI Soil Moisture products in a northern boreal forest environment, Geosciences, 8, 51, https://doi.org/10.3390/geosciences8020051, 2018. a
Jarlan, L., Balsamo, G., Lafont, S., Beljaars, A., Calvet, J. C., and Mougin, E.: Analysis of leaf area index in the ECMWF land surface model and impact on latent heat and carbon fluxes: Application to West Africa, J. Geophys. Res.-Atmos., 113, D24117, https://doi.org/10.1029/2007JD009370, 2008. a, b, c
Jensen, K. H. and Refsgaard, J. C.: HOBE: The Danish hydrological observatory, Vadose Zone J., 17, 1–24, 2018. a
Joiner, J. and Yoshida, Y.: Satellite-based reflectances capture large fraction of variability in global gross primary production (GPP) at weekly time scales, Agr. Forest Meteorol., 291, 108092, https://doi.org/10.1016/j.agrformet.2020.108092, 2020. a
Joiner, J. and Yoshida, Y.: Global MODIS and FLUXNET-derived Daily Gross Primary Production, V2, ORNL DAAC, Oak Ridge, Tennessee, https://doi.org/10.3334/ORNLDAAC/1835, 2021. a
Joiner, J., Yoshida, Y., Zhang, Y., Duveiller, G., Jung, M., Lyapustin, A., Wang, Y., and Tucker, C. J.: Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data, Remote Sensing, 10, 1346, https://doi.org/10.3390/rs10091346, 2018. a
Kirchengast, G., Kabas, T., Leuprecht, A., Bichler, C., and Truhetz, H.: WegenerNet: A Pioneering High-Resolution Network for Monitoring Weather and Climate, B. Am. Meteorol. Soc., 95, 227–242, https://doi.org/10.1175/BAMS-D-11-00161.1, 2014. a
Kolassa, J., Reichle, R. H., Koster, R. D., Liu, Q., Mahanama, S., and Zeng, F.-W.: An Observation-Driven Approach to Improve Vegetation Phenology in a Global Land Surface Model, J. Adv. Model. Earth Syst., 12, e2020MS002083, https://doi.org/10.1029/2020MS002083, 2020. a
Koster, R. D., Walker, G. K., Mahanama, S. P. P., and Reichle, R. H.: Soil Moisture Initialization Error and Subgrid Variability of Precipitation in Seasonal Streamflow Forecasting, J. Hydrometeorol., 15, 69–88, https://doi.org/10.1175/JHM-D-13-050.1, 2014. a
Koster, R. D., Liu, Q., Mahanama, S. P. P., and Reichle, R. H.: Improved Hydrological Simulation Using SMAP Data: Relative Impacts of Model Calibration and Data Assimilation, J. Hydrometeorol., 19, 727–741, https://doi.org/10.1175/JHM-D-17-0228.1, 2018. a, b, c
Kumar, S., Peters-Lidard, C., Tian, Y., Houser, P., Geiger, J., Olden, S., Lighty, L., Eastman, J., Doty, B., Dirmeyer, P., Adams, J., Mitchell, K., Wood, E., and Sheffield, J.: Land information system: An interoperable framework for high resolution land surface modeling, Environ. Model. Softw., 21, 1402–1415, https://doi.org/10.1016/j.envsoft.2005.07.004, 2006. a
Kumar, S. V., Reichle, R. H., Koster, R. D., Crow, W. T., and Peters-Lidard, C. D.: Role of subsurface physics in the assimilation of surface soil moisture observations, J. Hydrometeorol., 10, 1534–1547, 2009. a
Kumar, S. V., Peters-Lidard, C. D., Mocko, D., Reichle, R., Liu, Y., Arsenault, K. R., Xia, Y., Ek, M., Riggs, G., Livneh, B., and Cosh, M.: Assimilation of Remotely Sensed Soil Moisture and Snow Depth Retrievals for Drought Estimation, J. Hydrometeorol., 15, 2446–2469, https://doi.org/10.1175/JHM-D-13-0132.1, 2014. a, b, c, d
Kumar, S. V., Jasinski, M., Mocko, D. M., Rodell, M., Borak, J., Li, B., Beaudoing, H. K., and Peters-Lidard, C. D.: NCA-LDAS Land Analysis: Development and Performance of a Multisensor, Multivariate Land Data Assimilation System for the National Climate Assessment, J. Hydrometeorol., 20, 1571–1593, https://doi.org/10.1175/JHM-D-17-0125.1, 2019a. a
Kumar, S. V., M. Mocko, D., Wang, S., Peters-Lidard, C. D., and Borak, J.: Assimilation of remotely sensed leaf area index into the Noah-MP land surface model: impacts on water and carbon fluxes and states over the continental United States, J. Hydrometeorol., 20, 1359–1377, 2019b. a, b, c, d, e, f, g, h, i, j, k, l
Kumar, S. V., Holmes, T. R., Bindlish, R., de Jeu, R., and Peters-Lidard, C.: Assimilation of vegetation optical depth retrievals from passive microwave radiometry, Hydrol. Earth Syst. Sci., 24, 3431–3450, https://doi.org/10.5194/hess-24-3431-2020, 2020. a, b, c
Kumar, S. V., Holmes, T., Andela, N., Dharssi, I., Vinodkumar, Hain, C., Peters-Lidard, C., Mahanama, S. P., Arsenault, K. R., Nie, W., and Getirana, A.: The 2019–2020 Australian Drought and Bushfires Altered the Partitioning of Hydrological Fluxes, Geophys. Res. Lett., 48, e2020GL091411, https://doi.org/10.1029/2020GL091411, 2021. a, b, c
Laanaia, N., Carrer, D., Calvet, J.-C., and Pagé, C.: How will climate change affect the vegetation cycle over France? A generic modeling approach, Clim. Risk Manage., 13, 31–42, https://doi.org/10.1016/j.crm.2016.06.001, 2016. a
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton, P. E., Swenson, S. C., Lawrence, P. J., Zeng, X., Yang, Z.-L., Levis, S., Sakaguchi, K., Bonan, G. B., and Slater, A. G.: Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model, J. Adv. Model. Earth Syst., 3, M03001, https://doi.org/10.1029/2011MS00045, 2011. a, b
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C., Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., Kennedy, D., Kluzek, E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., Riley, W. J., Sacks, W. J., Shi, M., Vertenstein, M., Wieder, W. R., Xu, C., Ali, A. A., Badger, A. M., Bisht, G., van den Broeke, M., Brunke, M. A., Burns, S. P., Buzan, J., Clark, M., Craig, A., Dahlin, K., Drewniak, B., Fisher, J. B., Flanner, M., Fox, A. M., Gentine, P., Hoffman, F., Keppel-Aleks, G., Knox, R., Kumar, S., Lenaerts, J., Leung, L. R., Lipscomb, W. H., Lu, Y., Pandey, A., Pelletier, J. D., Perket, J., Randerson, J. T., Ricciuto, D. M., Sanderson, B. M., Slater, A., Subin, Z. M., Tang, J., Thomas, R. Q., Val Martin, M., and Zeng, X.: The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty, J. Adv. Model. Earth Syst., 11, 4245–4287, https://doi.org/10.1029/2018MS001583, 2019. a
Leroux, D. J., Calvet, J.-C., Munier, S., and Albergel, C.: Using satellite-derived vegetation products to evaluate LDAS-Monde over the Euro-Mediterranean area, Remote Sensi., 10, 1199, https://doi.org/10.3390/rs10081199, 2018. a
Li, J., Miao, C., Zhang, G., Fang, Y.-H., Shangguan, W., and Niu, G.-Y.: Global Evaluation of the Noah-MP Land Surface Model and Suggestions for Selecting Parameterization Schemes, J. Geophys. Res.-Atmos., 127, e2021JD035753, https://doi.org/10.1029/2021JD035753, 2022. a
Lievens, H., Martens, B., Verhoest, N., Hahn, S., Reichle, R., and Miralles, D.: Assimilation of global radar backscatter and radiometer brightness temperature observations to improve soil moisture and land evaporation estimates, Remote Sens. Environ., 189, 194–210, https://doi.org/10.1016/j.rse.2016.11.022, 2017. a
Ling, X. L., Fu, C. B., Guo, W. D., and Yang, Z.-L.: Assimilation of Remotely Sensed LAI Into CLM4CN Using DART, J. Adv. Model. Earth Syst., 11, 2768–2786, https://doi.org/10.1029/2019MS001634, 2019. a
Loew, A., Dall'Amico, J. T., Schlenz, F., and Mauser, W.: The Upper Danube Soil Moisture Validation Site: Measurements and Activities, in: Earth Observation and Water Cycle Science, vol. 674 of ESA Special Publication, edited by: Lacoste, H., p. 56, 2009. a
Ma, N., Niu, G.-Y., Xia, Y., Cai, X., Zhang, Y., Ma, Y., and Fang, Y.: A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States, J. Geophys. Res.-Atmos., 122, 12245–12268, https://doi.org/10.1002/2017JD027597, 2017. a
MacBean, N., Maignan, F., Peylin, P., Bacour, C., Bréon, F.-M., and Ciais, P.: Using satellite data to improve the leaf phenology of a global terrestrial biosphere model, Biogeosciences, 12, 7185–7208, https://doi.org/10.5194/bg-12-7185-2015, 2015. a, b
MacBean, N., Peylin, P., Chevallier, F., Scholze, M., and Schürmann, G.: Consistent assimilation of multiple data streams in a carbon cycle data assimilation system, Geosci. Model Dev., 9, 3569–3588, https://doi.org/10.5194/gmd-9-3569-2016, 2016. a, b
Maertens, M., De Lannoy, G. J. M., Apers, S., Kumar, S. V., and Mahanama, S. P. P.: Land surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parameters, Hydrol. Earth Syst. Sci., 25, 4099–4125, https://doi.org/10.5194/hess-25-4099-2021, 2021. a, b, c
Maes, W. H., Pagán, B. R., Martens, B., Gentine, P., Guanter, L., Steppe, K., Verhoest, N. E., Dorigo, W., Li, X., Xiao, J., and Miralles, D. G.: Sun-induced fluorescence closely linked to ecosystem transpiration as evidenced by satellite data and radiative transfer models, Remote Sens. Environ., 249, 112030, https://doi.org/10.1016/j.rse.2020.112030, 2020. a
Mahmud, K., Scott, R. L., Biederman, J. A., Litvak, M. E., Kolb, T., Meyers, T. P., Krishnan, P., Bastrikov, V., and MacBean, N.: Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO2 Flux and its Inter-Annual Variability, J. Geophys. Res.-Biogeo., 126, e2021JG006400, https://doi.org/10.1029/2021JG006400, 2021. a, b, c
Marczewski, W., Slominski, J., Slominska, E., Usowicz, B., Usowicz, J., Romanov, S., Maryskevych, O., Nastula, J., and Zawadzki, J.: Strategies for validating and directions for employing SMOS data, in the Cal-Val project SWEX (3275) for wetlands, Hydrol. Earth Syst. Sci. Discuss., 7, 7007–7057, https://doi.org/10.5194/hessd-7-7007-2010, 2010. a
Martens, B., Miralles, D., Lievens, H., Fernández-Prieto, D., and Verhoest, N.: Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture, Int. J. Appl. Earth Obs. Geoinform., 48, 146–162, https://doi.org/10.1016/j.jag.2015.09.012, 2016. a
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017. a, b
Martens, B., De Jeu, R. A. M., Verhoest, N. E. C., Schuurmans, H., Kleijer, J., and Miralles, D. G.: Towards Estimating Land Evaporation at Field Scales Using GLEAM, Remote Sens., 10, 1720, https://doi.org/10.3390/rs10111720, 2018. a
Martini, D., Sakowska, K., Wohlfahrt, G., Pacheco-Labrador, J., van der Tol, C., Porcar-Castell, A., Magney, T. S., Carrara, A., Colombo, R., El-Madany, T. S., Gonzalez-Cascon, R., Martín, M. P., Julitta, T., Moreno, G., Rascher, U., Reichstein, M., Rossini, M., and Migliavacca, M.: Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production, New Phytol., 233, 2415–2428, https://doi.org/10.1111/nph.17920, 2022. a
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011. a
Miralles, D. G., Nieto, R., McDowell, N. G., Dorigo, W. A., Verhoest, N. E., Liu, Y. Y., Teuling, A. J., Dolman, A. J., Good, S. P., and Gimeno, L.: Contribution of water-limited ecoregions to their own supply of rainfall, Environ. Res. Lett., 11, 124007, https://doi.org/10.1088/1748-9326/11/12/124007, 2016. a
Mitchell, H. L., Houtekamer, P. L., and Pellerin, G.: Ensemble Size, Balance, and Model-Error Representation in an Ensemble Kalman Filter, Mon. Weather Rev., 130, 2791–2808, https://doi.org/10.1175/1520-0493(2002)130<2791:ESBAME>2.0.CO;2, 2002. a
Mocko, D. M., Kumar, S. V., Peters-Lidard, C. D., and Wang, S.: Assimilation of Vegetation Conditions Improves the Representation of Drought over Agricultural Areas, J. Hydrometeorol., 22, 1085–1098, https://doi.org/10.1175/JHM-D-20-0065.1, 2021. a, b, c, d
Morbidelli, R., Saltalippi, C., Flammini, A., Cifrodelli, M., Picciafuoco, T., Corradini, C., and Govindaraju, R. S.: In situ measurements of soil saturated hydraulic conductivity: Assessment of reliability through rainfall–runoff experiments, Hydrol. Process., 31, 3084–3094, 2017. a
Mucia, A., Bonan, B., Zheng, Y., Albergel, C., and Calvet, J.-C.: From Monitoring to Forecasting Land Surface Conditions Using a Land Data Assimilation System: Application over the Contiguous United States, Remote Sens., 12, 2020, https://doi.org/10.3390/rs12122020, 2020. a, b
Mucia, A., Bonan, B., Albergel, C., Zheng, Y., and Calvet, J.-C.: Assimilation of passive microwave vegetation optical depth in LDAS-Monde: a case study over the continental USA, Biogeosciences, 19, 2557–2581, https://doi.org/10.5194/bg-19-2557-2022, 2022. a, b
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., and Wagner, W.: An improved soil moisture retrieval algorithm for ERS and METOP scatterometer observations, IEEE T. Geosci. Remote, 47, 1999–2013, 2009. a
Nair, R. K. F., Morris, K. A., Hertel, M., Luo, Y., Moreno, G., Reichstein, M., Schrumpf, M., and Migliavacca, M.: N : P stoichiometry and habitat effects on Mediterranean savanna seasonal root dynamics, Biogeosciences, 16, 1883–1901, https://doi.org/10.5194/bg-16-1883-2019, 2019. a
Nie, W., Kumar, S. V., Arsenault, K. R., Peters-Lidard, C. D., Mladenova, I. E., Bergaoui, K., Hazra, A., Zaitchik, B. F., Mahanama, S. P., McDonnell, R., Mocko, D. M., and Navari, M.: Towards effective drought monitoring in the Middle East and North Africa (MENA) region: implications from assimilating leaf area index and soil moisture into the Noah-MP land surface model for Morocco, Hydrol. Earth Syst. Sci., 26, 2365–2386, https://doi.org/10.5194/hess-26-2365-2022, 2022. a
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.-Atmos., 116, D12109, https://doi.org/10.1029/2010JD015139, 2011. a, b, c
Niu, G.-Y., Fang, Y.-H., Chang, L.-L., Jin, J., Yuan, H., and Zeng, X.: Enhancing the Noah-MP Ecosystem Response to Droughts With an Explicit Representation of Plant Water Storage Supplied by Dynamic Root Water Uptake, J. Adv. Model. Earth Syst., 12, e2020MS002062, https://doi.org/10.1029/2020MS002062, 2020. a
Owe, M., de Jeu, R., and Holmes, T.: Multisensor historical climatology of satellite-derived global land surface moisture, J. Geophys. Res.-Earth, 113, F01002, https://doi.org/10.1029/2007JF000769, 2008. a
Parrens, M., Mahfouf, J.-F., Barbu, A. L., and Calvet, J.-C.: Assimilation of surface soil moisture into a multilayer soil model: design and evaluation at local scale, Hydrol. Earth Syst. Sci., 18, 673–689, https://doi.org/10.5194/hess-18-673-2014, 2014. a
Paulik, C., Preimesberger, W., Scherrer, S., Stradiotti, P., Hahn, S., Baum, D., Plocon, A., Mistelbauer, T., Scanlon, T., Schmitzer, M., Gruber, A., Teubner, I., and van der Horst, T.: pytesmo – a Python Toolbox for the Evaluation of Soil Moisture observations, Zenodo [code], https://doi.org/10.5281/zenodo.596422, 2022. a
Peters-Lidard, C. D., Houser, P. R., Tian, Y., Kumar, S. V., Geiger, J., Olden, S., Lighty, L., Doty, B., Dirmeyer, P., Adams, J., Mitchell, K., Wood, E. F., and Sheffield, J.: High-performance Earth system modeling with NASA/GSFC's Land Information System, Innov. Syst. Softw. Eng., 3, 157–165, 2007. a
Petropoulos, G. P. and McCalmont, J. P.: An operational in situ soil moisture & soil temperature monitoring network for West Wales, UK: The WSMN network, Sensors, 17, 1481, https://doi.org/10.3390/s17071481, 2017. a
Preimesberger, W., Scanlon, T., Su, C., Gruber, A., and Dorigo, W.: Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record, IEEE T. Geosci. Remote, 59, 2845–2862, https://doi.org/10.1109/TGRS.2020.3012896, 2020. a
Raffelli, G., Previati, M., Canone, D., Gisolo, D., Bevilacqua, I., Capello, G., Biddoccu, M., Cavallo, E., Deiana, R., Cassiani, G., and Ferraris, S.: Local-and plot-scale measurements of soil moisture: Time and spatially resolved field techniques in plain, hill and mountain sites, Water, 9, 706, https://doi.org/10.3390/w9090706, 2017. a
Rahman, A., Maggioni, V., Zhang, X., Houser, P., Sauer, T., and Mocko, D. M.: The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model, Remote Sens., 14, 437, https://doi.org/10.3390/rs14030437, 2022a. a, b
Reichle, R. H. and Koster, R. D.: Bias reduction in short records of satellite soil moisture, Geophys. Res. Lett., 31, L19501, https://doi.org/10.1029/2004GL020938, 2004. a, b
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J. K., Walker, J. P., Lohmann, D., and Toll, D.: The Global Land Data Assimilation System, B. Am. Meteorol. Soci., 85, 381–394, https://doi.org/10.1175/BAMS-85-3-381, 2004. a, b
Ryu, D., Crow, W. T., Zhan, X., and Jackson, T. J.: Correcting Unintended Perturbation Biases in Hydrologic Data Assimilation, J. Hydrometeorol., 10, 734–750, https://doi.org/10.1175/2008JHM1038.1, 2009. a
Sabater, J. M., Rüdiger, C., Calvet, J.-C., Fritz, N., Jarlan, L., and Kerr, Y.: Joint assimilation of surface soil moisture and LAI observations into a land surface model, Agr. Forest Meteorol., 148, 1362–1373, https://doi.org/10.1016/j.agrformet.2008.04.003, 2008. a
Sawada, Y. and Koike, T.: Simultaneous estimation of both hydrological and ecological parameters in an ecohydrological model by assimilating microwave signal, J. Geophys. Res.-Atmos., 119, 8839–8857, https://doi.org/10.1002/2014JD021536, 2014. a
Sawada, Y., Koike, T., and Walker, J. P.: A land data assimilation system for simultaneous simulation of soil moisture and vegetation dynamics, J. Geophys. Res.-Atmos., 120, 5910–5930, https://doi.org/10.1002/2014JD022895, 2015. a
Schlenz, F., dall'Amico, J. T., Loew, A., and Mauser, W.: Uncertainty Assessment of the SMOS Validation in the Upper Danube Catchment, IEEE T. Geosci. Remote, 50, 1517–1529, 2012. a
Scholze, M., Kaminski, T., Knorr, W., Voßbeck, M., Wu, M., Ferrazzoli, P., Kerr, Y., Mialon, A., Richaume, P., Rodríguez-Fernández, N., Vittucci, C., Wigneron, J.-P., Mecklenburg, S., and Drusch, M.: Mean European Carbon Sink Over 2010–2015 Estimated by Simultaneous Assimilation of Atmospheric CO2, Soil Moisture, and Vegetation Optical Depth, Geophys. Res. Lett., 46, 13796–13803, https://doi.org/10.1029/2019GL085725, 2019. a
Shah, H. L., Zhou, T., Sun, N., Huang, M., and Mishra, V.: Roles of irrigation and reservoir operations in modulating terrestrial water and energy budgets in the Indian Subcontinental River basins, J. Geophys. Res.-Atmos., 124, 12915–12936, 2019. a
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D, and Huang, X.-Y.: A Description of the Advanced Research WRF Model Version 4.3, National Center for Atmospheric Research, Boulder, CO, USA, https://doi.org/10.5065/1dfh-6p97, 2021. a
Smets, B., Verger, A., Camacho, F., der Goten, R. V., and Jacobs, T.: Copernicus Global Land Operations “Vegetation and Energy” – Product User Manual – LAI/FAPAR/FCover, Collection 1 km, Version 2, Tech. rep., Copernicus, https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_PUM_LAI1km-V2_I1.33.pdf (last access: 3 November 2023), 2019. a, b
Tharammal, T., Bala, G., Devaraju, N., and Nemani, R.: A review of the major drivers of the terrestrial carbon uptake: model-based assessments, consensus, and uncertainties, Environ. Res. Lett., 14, 093005, https://doi.org/10.1088/1748-9326/ab3012, 2019a. a
Tharammal, T., Bala, G., Narayanappa, D., and Nemani, R.: Potential roles of CO2 fertilization, nitrogen deposition, climate change, and land use and land cover change on the global terrestrial carbon uptake in the twenty-first century, Clim. Dynam., 52, 4393–4406, 2019b. a
Thiery, W., Davin, E. L., Lawrence, D. M., Hirsch, A. L., Hauser, M., and Seneviratne, S. I.: Present-day irrigation mitigates heat extremes, J. Geophys. Res.-Atmos., 122, 1403–1422, 2017. a
Tian, Y., Peters-Lidard, C. D., Kumar, S. V., Geiger, J., Houser, P. R., Eastman, J. L., Dirmeyer, P., Doty, B., and Adams, J.: High-performance land surface modeling with a Linux cluster, Comput. Geosci., 34, 1492–1504, 2008. a
van Leeuwen, P. J., Künsch, H. R., Nerger, L., Potthast, R., and Reich, S.: Particle filters for high-dimensional geoscience applications: A review, Q. J. Roy. Meteorol. Soc., 145, 2335–2365, https://doi.org/10.1002/qj.3551, 2019. a, b
Verger, A., Baret, F., and Weiss, M.: Near Real-Time Vegetation Monitoring at Global Scale, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 7, 3473–3481, https://doi.org/10.1109/JSTARS.2014.2328632, 2014. a
Vreugdenhil, M., Dorigo, W., Broer, M., Haas, P., Eder, A., Hogan, P., Blöschl, G., and Wagner, W.: Towards a high-density soil moisture network for the validation of SMAP in Petzenkirchen, Austria, in: 2013 IEEE International Geoscience and Remote Sensing Symposium-IGARSS, 1865–1868, 2013. a
Wagner, W., Lemoine, G., and Rott, H.: A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data, Remote Sens. Environ., 70, 191–207, https://doi.org/10.1016/S0034-4257(99)00036-X, 1999. a
Walker, A. P., De Kauwe, M. G., Bastos, A., Belmecheri, S., Georgiou, K., Keeling, R. F., McMahon, S. M., Medlyn, B. E., Moore, D. J. P., Norby, R. J., Zaehle, S., Anderson-Teixeira, K. J., Battipaglia, G., Brienen, R. J. W., Cabugao, K. G., Cailleret, M., Campbell, E., Canadell, J. G., Ciais, P., Craig, M. E., Ellsworth, D. S., Farquhar, G. D., Fatichi, S., Fisher, J. B., Frank, D. C., Graven, H., Gu, L., Haverd, V., Heilman, K., Heimann, M., Hungate, B. A., Iversen, C. M., Joos, F., Jiang, M., Keenan, T. F., Knauer, J., Körner, C., Leshyk, V. O., Leuzinger, S., Liu, Y., MacBean, N., Malhi, Y., McVicar, T. R., Penuelas, J., Pongratz, J., Powell, A. S., Riutta, T., Sabot, M. E. B., Schleucher, J., Sitch, S., Smith, W. K., Sulman, B., Taylor, B., Terrer, C., Torn, M. S., Treseder, K. K., Trugman, A. T., Trumbore, S. E., van Mantgem, P. J., Voelker, S. L., Whelan, M. E., and Zuidema, P. A.: Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2, New Phytol., 229, 2413–2445, https://doi.org/10.1111/nph.16866, 2021. a
Wen, J., Koehler, P., Duveiller, G., Parazoo, N., Magney, T., Hooker, G., Yu, L., Chang, C., and Sun, Y.: Global High-Resolution Estimates of SIF from Fused SCIAMACHY and GOME-2, 2002–2018, ORNL DAAC, Oak Ridge, Tennessee, https://doi.org/10.3334/ORNLDAAC/1864, 2021. a
Wigneron, J.-P., Dayan, S., Kruszewski, A., Aluome, C., AI-Yaari, M. G.-E. A., Fan, L., Guven, S., Chipeaux, C., Moisy, C., Guyon, D., and Loustau, D.: The aqui network: soil moisture sites in the “Les landes” forest and graves vineyards (Bordeaux aquitaine region, France), in: IGARSS 2018 – 2018 IEEE International Geoscience and Remote Sensing Symposium, 3739–3742, 2018. a
Wutzler, T., Lucas-Moffat, A., Migliavacca, M., Knauer, J., Sickel, K., Šigut, L., Menzer, O., and Reichstein, M.: Basic and extensible post-processing of eddy covariance flux data with REddyProc, Biogeosciences, 15, 5015–5030, https://doi.org/10.5194/bg-15-5015-2018, 2018. a
Xu, T., Chen, F., He, X., Barlage, M., Zhang, Z., Liu, S., and He, X.: Improve the Performance of the Noah-MP-Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data, J. Adv. Model. Earth Syst., 13, e2020MS002394, https://doi.org/10.1029/2020MS002394, 2021. a, b
Yang, Z.-L., Niu, G.-Y., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Longuevergne, L., Manning, K., Niyogi, D., Tewari, M., and Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins, J. Geophys. Res.-Atmos., 116, D12110, https://doi.org/10.1029/2010JD015140, 2011. a
Yilmaz, M. T. and Crow, W. T.: The Optimality of Potential Rescaling Approaches in Land Data Assimilation, J. Hydrometeorol., 14, 650–660, https://doi.org/10.1175/JHM-D-12-052.1, 2013. a
Zacharias, S., Bogena, H., Samaniego, L., Mauder, M., Fuß, R., Pütz, T., Frenzel, M., Schwank, M., Baessler, C., Butterbach-Bahl, K., Bens, O., Borg, E., Brauer, A., Dietrich, P., Hajnsek, I., Helle, G., Kiese, R., Kunstmann, H., Klotz, S., and Vereecken, H.: A Network of Terrestrial Environmental Observatories in Germany, Vadose Zone J., 10, 955–973, https://doi.org/10.2136/vzj2010.0139, 2011. a
Zreda, M., Desilets, D., Ferré, T., and Scott, R.: Measuring soil moisture content non-invasively at intermediate spatial scale using cosmic-ray neutrons, Geophys. Res. Lett., 35, L21402, https://doi.org/10.1029/2008GL035655, 2008. a
Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T., and Rosolem, R.: COSMOS: the COsmic-ray Soil Moisture Observing System, Hydrol. Earth Syst. Sci., 16, 4079–4099, https://doi.org/10.5194/hess-16-4079-2012, 2012. a
Short summary
We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
We explored different options for data assimilation (DA) of the remotely sensed leaf area index...
