Articles | Volume 10, issue 5
https://doi.org/10.5194/gmd-10-1903-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-1903-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
17 May 2017
Model description paper |
| 17 May 2017
GLEAM v3: satellite-based land evaporation and root-zone soil moisture
Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, 9000 Ghent, Belgium
Diego G. Miralles
Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, 9000 Ghent, Belgium
Department of Earth Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1085–1087, 1081 HV Amsterdam, the Netherlands
Hans Lievens
Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, 9000 Ghent, Belgium
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, 20771 Maryland, USA
Robin van der Schalie
Transmissivity/VanderSat B.V., Space Technology Center, Huygensstraat 34, 2201 DK Noordwijk, Netherlands
Department of Earth Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1085–1087, 1081 HV Amsterdam, the Netherlands
Richard A. M. de Jeu
Transmissivity/VanderSat B.V., Space Technology Center, Huygensstraat 34, 2201 DK Noordwijk, Netherlands
Diego Fernández-Prieto
European Space Research Institute (ESRIN), European Space Agency (ESA), Via Galileo Galilei 64, 00044 Frascati, Italy
Hylke E. Beck
Joint Research Centre (JRC), European Comission, Via Enrico Fermi 2749, 21027 Ispra, Italy
Wouter A. Dorigo
Department of Geodesy and Geo-Information, Vienna University of Technology, Gußhausstraße 25–29, 1040 Vienna, Austria
Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, 9000 Ghent, Belgium
Niko E. C. Verhoest
Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, 9000 Ghent, Belgium
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Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
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Jiawei Hou, Albert I. J. M. van Dijk, Hylke E. Beck, Luigi J. Renzullo, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 26, 3785–3803, https://doi.org/10.5194/hess-26-3785-2022, https://doi.org/10.5194/hess-26-3785-2022, 2022
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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.
Verónica González-Gambau, Estrella Olmedo, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Justino Martínez, Pekka Alenius, Laura Tuomi, Rafael Catany, Manuel Arias, Carolina Gabarró, Nina Hoareau, Marta Umbert, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 2343–2368, https://doi.org/10.5194/essd-14-2343-2022, https://doi.org/10.5194/essd-14-2343-2022, 2022
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We present the first Soil Moisture and Ocean Salinity Sea Surface Salinity (SSS) dedicated products over the Baltic Sea (ESA Baltic+ Salinity Dynamics). The Baltic+ L3 product covers 9 days in a 0.25° grid. The Baltic+ L4 is derived by merging L3 SSS with sea surface temperature information, giving a daily product in a 0.05° grid. The accuracy of L3 is 0.7–0.8 and 0.4 psu for the L4. Baltic+ products have shown to be useful, covering spatiotemporal data gaps and for validating numerical models.
Jorn Van de Velde, Matthias Demuzere, Bernard De Baets, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 26, 2319–2344, https://doi.org/10.5194/hess-26-2319-2022, https://doi.org/10.5194/hess-26-2319-2022, 2022
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An important step in projecting future climate is the bias adjustment of the climatological and hydrological variables. In this paper, we illustrate how bias adjustment can be impaired by bias nonstationarity. Two univariate and four multivariate methods are compared, and for both types bias nonstationarity can be linked with less robust adjustment.
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.
Jessica Keune, Dominik L. Schumacher, and Diego G. Miralles
Geosci. Model Dev., 15, 1875–1898, https://doi.org/10.5194/gmd-15-1875-2022, https://doi.org/10.5194/gmd-15-1875-2022, 2022
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Air transports moisture and heat, shaping the weather we experience. When and where was this air moistened and warmed by the surface? To address this question, atmospheric models trace the history of air parcels in space and time. However, their uncertainties remain unexplored, which hinders their utility and application. Here, we present a framework that sheds light on these uncertainties. Our approach sets a new standard in the assessment of atmospheric moisture and heat trajectories.
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.
Justino Martínez, Carolina Gabarró, Antonio Turiel, Verónica González-Gambau, Marta Umbert, Nina Hoareau, Cristina González-Haro, Estrella Olmedo, Manuel Arias, Rafael Catany, Laurent Bertino, Roshin P. Raj, Jiping Xie, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 307–323, https://doi.org/10.5194/essd-14-307-2022, https://doi.org/10.5194/essd-14-307-2022, 2022
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Measuring salinity from space is challenging since the sensitivity of the brightness temperature to sea surface salinity is low, but the retrieval of SSS in cold waters is even more challenging. In 2019, the ESA launched a specific initiative called Arctic+Salinity to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Pablo A. Mendoza, Ian McNamara, Hylke E. Beck, Joschka Thurner, Alexandra Nauditt, Lars Ribbe, and Nguyen Xuan Thinh
Hydrol. Earth Syst. Sci., 25, 5805–5837, https://doi.org/10.5194/hess-25-5805-2021, https://doi.org/10.5194/hess-25-5805-2021, 2021
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Most rivers worldwide are ungauged, which hinders the sustainable management of water resources. Regionalisation methods use information from gauged rivers to estimate streamflow over ungauged ones. Through hydrological modelling, we assessed how the selection of precipitation products affects the performance of three regionalisation methods. We found that a precipitation product that provides the best results in hydrological modelling does not necessarily perform the best for regionalisation.
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.
Peter Uhe, Daniel Mitchell, Paul D. Bates, Nans Addor, Jeff Neal, and Hylke E. Beck
Geosci. Model Dev., 14, 4865–4890, https://doi.org/10.5194/gmd-14-4865-2021, https://doi.org/10.5194/gmd-14-4865-2021, 2021
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We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs, e.g., rainfall and temperature from observations or climate models, and takes them through a series of modeling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data sets, allowing it to be applied anywhere in the world.
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.
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.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
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Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
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.
Renaud Hostache, Dominik Rains, Kaniska Mallick, Marco Chini, Ramona Pelich, Hans Lievens, Fabrizio Fenicia, Giovanni Corato, Niko E. C. Verhoest, and Patrick Matgen
Hydrol. Earth Syst. Sci., 24, 4793–4812, https://doi.org/10.5194/hess-24-4793-2020, https://doi.org/10.5194/hess-24-4793-2020, 2020
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Our objective is to investigate how satellite microwave sensors, particularly Soil Moisture and Ocean Salinity (SMOS), may help to reduce errors and uncertainties in soil moisture simulations with a large-scale conceptual hydro-meteorological model. We assimilated a long time series of SMOS observations into a hydro-meteorological model and showed that this helps to improve model predictions. This work therefore contributes to the development of faster and more accurate drought prediction tools.
Brecht Martens, Dominik L. Schumacher, Hendrik Wouters, Joaquín Muñoz-Sabater, Niko E. C. Verhoest, and Diego G. Miralles
Geosci. Model Dev., 13, 4159–4181, https://doi.org/10.5194/gmd-13-4159-2020, https://doi.org/10.5194/gmd-13-4159-2020, 2020
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Climate reanalyses are widely used in different fields and an in-depth evaluation of the different variables provided by reanalyses is a necessary means to provide feedback on the quality to their users and the operational centres producing these data sets. In this study, we show the improvements of ECMWF's latest climate reanalysis (ERA5) upon its predecessor (ERA-Interim) in partitioning the available energy at the land surface.
Sujay V. Kumar, Thomas R. Holmes, Rajat Bindlish, Richard de Jeu, and Christa Peters-Lidard
Hydrol. Earth Syst. Sci., 24, 3431–3450, https://doi.org/10.5194/hess-24-3431-2020, https://doi.org/10.5194/hess-24-3431-2020, 2020
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Vegetation optical depth (VOD) is a byproduct of the soil moisture retrieval from passive microwave instruments. This study demonstrates that VOD information can be utilized for improving land surface water budget and carbon conditions through data assimilation.
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020, https://doi.org/10.5194/hess-24-2687-2020, 2020
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Rain gauges are unevenly spaced around the world with extremely low gauge density over places like Africa and South America. Here, water-related problems like floods, drought and famine are particularly severe and able to cause fatalities, migration and diseases. We have developed a rainfall dataset that exploits the synergies between rainfall and soil moisture to provide accurate rainfall observations which can be used to face these problems.
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.
Jorn Van de Velde, Bernard De Baets, Matthias Demuzere, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-83, https://doi.org/10.5194/hess-2020-83, 2020
Revised manuscript not accepted
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Though climate models have different types of biases in comparison to the observations, most research is focused on adjusting the intensity. Yet, variables like precipitation are also biased in the occurrence: there are too many days with rainfall. We compared four methods for adjusting the occurrence, with the goal of improving flood representation. From this comparison, we concluded that more advanced methods do not necessarily add value, especially in multivariate settings.
Jian Peng, Simon Dadson, Feyera Hirpa, Ellen Dyer, Thomas Lees, Diego G. Miralles, Sergio M. Vicente-Serrano, and Chris Funk
Earth Syst. Sci. Data, 12, 753–769, https://doi.org/10.5194/essd-12-753-2020, https://doi.org/10.5194/essd-12-753-2020, 2020
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Africa has been severely influenced by intense drought events, which has led to crop failure, food shortages, famine, epidemics and even mass migration. The current study developed a high spatial resolution drought dataset entirely from satellite-based products. The dataset has been comprehensively inter-compared with other drought indicators and may contribute to an improved characterization of drought risk and vulnerability and minimize drought's impact on water and food security in Africa.
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.
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).
Jeroen Claessen, Annalisa Molini, Brecht Martens, Matteo Detto, Matthias Demuzere, and Diego G. Miralles
Biogeosciences, 16, 4851–4874, https://doi.org/10.5194/bg-16-4851-2019, https://doi.org/10.5194/bg-16-4851-2019, 2019
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Bidirectional interactions between vegetation and climate are unraveled over short (monthly) and long (inter-annual) temporal scales. Analyses use a novel causal inference method based on wavelet theory. The performance of climate models at representing these interactions is benchmarked against satellite data. Climate models can reproduce the overall climate controls on vegetation at all temporal scales, while their performance at representing biophysical feedbacks on climate is less adequate.
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.
Hendrik Wouters, Irina Y. Petrova, Chiel C. van Heerwaarden, Jordi Vilà-Guerau de Arellano, Adriaan J. Teuling, Vicky Meulenberg, Joseph A. Santanello, and Diego G. Miralles
Geosci. Model Dev., 12, 2139–2153, https://doi.org/10.5194/gmd-12-2139-2019, https://doi.org/10.5194/gmd-12-2139-2019, 2019
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The free software CLASS4GL (http://class4gl.eu) is designed to investigate the dynamic atmospheric boundary layer (ABL) with weather balloons. It mines observational data from global radio soundings, satellite and reanalysis data from the last 40 years to constrain and initialize an ABL model and automizes multiple experiments in parallel. CLASS4GL aims at fostering a better understanding of land–atmosphere feedbacks and the drivers of extreme weather.
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.
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.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 23, 925–948, https://doi.org/10.5194/hess-23-925-2019, https://doi.org/10.5194/hess-23-925-2019, 2019
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Potential evaporation (Ep) is the amount of water an ecosystem would consume if it were not limited by water availability or other stress factors. In this study, we compared several methods to estimate Ep using a global dataset of 107 FLUXNET sites. A simple radiation-driven method calibrated per biome consistently outperformed more complex approaches and makes a suitable tool to investigate the impact of water use and demand, drought severity and biome productivity.
Sanaa Hobeichi, Gab Abramowitz, Jason Evans, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 23, 851–870, https://doi.org/10.5194/hess-23-851-2019, https://doi.org/10.5194/hess-23-851-2019, 2019
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.
Hylke E. Beck, Ming Pan, Tirthankar Roy, Graham P. Weedon, Florian Pappenberger, Albert I. J. M. van Dijk, George J. Huffman, Robert F. Adler, and Eric F. Wood
Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, https://doi.org/10.5194/hess-23-207-2019, 2019
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We conducted a comprehensive evaluation of 26 precipitation datasets for the US using the Stage-IV gauge-radar dataset as a reference. The best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for reporting times. Our findings can be used as a guide to choose the most suitable precipitation dataset for a particular application.
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.
Christina Papagiannopoulou, Diego G. Miralles, Matthias Demuzere, Niko E. C. Verhoest, and Willem Waegeman
Geosci. Model Dev., 11, 4139–4153, https://doi.org/10.5194/gmd-11-4139-2018, https://doi.org/10.5194/gmd-11-4139-2018, 2018
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Common global land cover and climate classifications are based on vegetation–climatic characteristics derived from observational data, ignoring the interaction between the local climate and biome. Here, we model the interplay between vegetation and local climate by discovering spatial relationships among different locations. The resulting global
hydro-climatic biomescorrespond to regions of coherent climate–vegetation interactions that agree well with traditional global land cover maps.
Albert I. J. M. van Dijk, Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts
Hydrol. Earth Syst. Sci., 22, 4959–4980, https://doi.org/10.5194/hess-22-4959-2018, https://doi.org/10.5194/hess-22-4959-2018, 2018
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Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.
Anouk I. Gevaert, Luigi J. Renzullo, Albert I. J. M. van Dijk, Hans J. van der Woerd, Albrecht H. Weerts, and Richard A. M. de Jeu
Hydrol. Earth Syst. Sci., 22, 4605–4619, https://doi.org/10.5194/hess-22-4605-2018, https://doi.org/10.5194/hess-22-4605-2018, 2018
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We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
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Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Ronny Meier, Edouard L. Davin, Quentin Lejeune, Mathias Hauser, Yan Li, Brecht Martens, Natalie M. Schultz, Shannon Sterling, and Wim Thiery
Biogeosciences, 15, 4731–4757, https://doi.org/10.5194/bg-15-4731-2018, https://doi.org/10.5194/bg-15-4731-2018, 2018
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Deforestation not only releases carbon dioxide to the atmosphere but also affects local climatic conditions by altering energy fluxes at the land surface and thereby the local temperature. Here, we evaluate the local impact of deforestation in a widely used land surface model. We find that the model reproduces the daytime warming effect of deforestation well. On the other hand, the warmer temperatures observed during night in forests are not present in this model.
Minh Tu Pham, Hilde Vernieuwe, Bernard De Baets, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 22, 1263–1283, https://doi.org/10.5194/hess-22-1263-2018, https://doi.org/10.5194/hess-22-1263-2018, 2018
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In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Still, the developed model has great potential for hydrological impact analysis.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-682, https://doi.org/10.5194/hess-2017-682, 2018
Revised manuscript not accepted
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Potential evaporation is a key parameter in numerous models used for assessing water use and drought severity. Yet, multiple incompatible methods have been proposed, thus estimates of potential evaporation remain uncertain. Based on the largest available dataset of FLUXNET data, we identify the best method to calculate potential evaporation globally. A simple radiation-driven method calibrated per biome consistently performed best; more complex models did not perform as good.
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.
Yu Zhang, Ming Pan, Justin Sheffield, Amanda L. Siemann, Colby K. Fisher, Miaoling Liang, Hylke E. Beck, Niko Wanders, Rosalyn F. MacCracken, Paul R. Houser, Tian Zhou, Dennis P. Lettenmaier, Rachel T. Pinker, Janice Bytheway, Christian D. Kummerow, and Eric F. Wood
Hydrol. Earth Syst. Sci., 22, 241–263, https://doi.org/10.5194/hess-22-241-2018, https://doi.org/10.5194/hess-22-241-2018, 2018
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A global data record for all four terrestrial water budget variables (precipitation, evapotranspiration, runoff, and total water storage change) at 0.5° resolution and monthly scale for the period of 1984–2010 is developed by optimally merging a series of remote sensing products, in situ measurements, land surface model outputs, and atmospheric reanalysis estimates and enforcing the mass balance of water. Initial validations show the data record is reliable for climate related analysis.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
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This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
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.
Dominik Rains, Xujun Han, Hans Lievens, Carsten Montzka, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5929–5951, https://doi.org/10.5194/hess-21-5929-2017, https://doi.org/10.5194/hess-21-5929-2017, 2017
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We have assimilated 6 years of satellite-observed passive microwave data into a state-of-the-art land surface model to improve surface soil moisture as well as root-zone soil moisture simulations. Long-term assimilation effects/biases are identified, and they are especially dependent on model perturbations, applied to simulate model uncertainty. The implications are put into context of using such assimilation-improved data for classifying extremes within hydrological monitoring systems.
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.
Katrien Van Eerdenbrugh, Stijn Van Hoey, Gemma Coxon, Jim Freer, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5315–5337, https://doi.org/10.5194/hess-21-5315-2017, https://doi.org/10.5194/hess-21-5315-2017, 2017
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Consistency in stage–discharge data is investigated using a methodology called Bidirectional Reach (BReach). Various measurement stations in the UK, New Zealand and Belgium are selected based on their historical ratings information and their characteristics related to data consistency. When applying a BReach analysis on them, the methodology provides results that appear consistent with the available knowledge and thus facilitates a reliable assessment of (in)consistency in stage–discharge data.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
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Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
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We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Christa D. Peters-Lidard, Martyn Clark, Luis Samaniego, Niko E. C. Verhoest, Tim van Emmerik, Remko Uijlenhoet, Kevin Achieng, Trenton E. Franz, and Ross Woods
Hydrol. Earth Syst. Sci., 21, 3701–3713, https://doi.org/10.5194/hess-21-3701-2017, https://doi.org/10.5194/hess-21-3701-2017, 2017
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In this synthesis of hydrologic scaling and similarity, we assert that it is time for hydrology to embrace a fourth paradigm of data-intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modeling, have laid the foundation for a data-driven framework for scrutinizing hydrological hypotheses. We call upon the community to develop a focused effort towards a fourth paradigm for hydrology.
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.
Hylke E. Beck, Albert I. J. M. van Dijk, Ad de Roo, Emanuel Dutra, Gabriel Fink, Rene Orth, and Jaap Schellekens
Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, https://doi.org/10.5194/hess-21-2881-2017, 2017
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Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.
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.
Hylke E. Beck, Albert I. J. M. van Dijk, Vincenzo Levizzani, Jaap Schellekens, Diego G. Miralles, Brecht Martens, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, https://doi.org/10.5194/hess-21-589-2017, 2017
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MSWEP (Multi-Source Weighted-Ensemble Precipitation) is a new global terrestrial precipitation dataset with a high 3-hourly temporal and 0.25° spatial resolution. The dataset is unique in that it takes advantage of a wide range of data sources, including gauge, satellite, and reanalysis data, to obtain the best possible precipitation estimates at global scale. The dataset outperforms existing gauge-adjusted precipitation datasets.
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.
Benedikt Gräler, Andrea Petroselli, Salvatore Grimaldi, Bernard De Baets, and Niko Verhoest
Proc. IAHS, 373, 175–178, https://doi.org/10.5194/piahs-373-175-2016, https://doi.org/10.5194/piahs-373-175-2016, 2016
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Many hydrological studies are devoted to the identification of events that are expected to occur on average within a certain time span. While this topic is well established in the univariate case, recent advances focus on a multivariate characterization of events based on copulas. Following a previous study, we show how the definition of the survival Kendall return period fits into the set of multivariate return periods.
Cristina M. Surdu, Claude R. Duguay, and Diego Fernández Prieto
The Cryosphere, 10, 941–960, https://doi.org/10.5194/tc-10-941-2016, https://doi.org/10.5194/tc-10-941-2016, 2016
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
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The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
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In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood
Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, https://doi.org/10.5194/gmd-9-283-2016, 2016
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In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
A. I. Stegehuis, R. Vautard, P. Ciais, A. J. Teuling, D. G. Miralles, and M. Wild
Geosci. Model Dev., 8, 2285–2298, https://doi.org/10.5194/gmd-8-2285-2015, https://doi.org/10.5194/gmd-8-2285-2015, 2015
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Many climate models have difficulties in properly reproducing climate extremes such as heat wave conditions. We use a regional climate model with different atmospheric physics schemes to simulate the heat wave events of 2003 in western Europe and 2010 in Russia. The five best-performing and diverse physics scheme combinations may be used in the future to perform heat wave analysis and to investigate the impact of climate change in summer in Europe.
H. Vernieuwe, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 19, 2685–2699, https://doi.org/10.5194/hess-19-2685-2015, https://doi.org/10.5194/hess-19-2685-2015, 2015
M. G. De Kauwe, J. Kala, Y.-S. Lin, A. J. Pitman, B. E. Medlyn, R. A. Duursma, G. Abramowitz, Y.-P. Wang, and D. G. Miralles
Geosci. Model Dev., 8, 431–452, https://doi.org/10.5194/gmd-8-431-2015, https://doi.org/10.5194/gmd-8-431-2015, 2015
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Stomatal conductance affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the CABLE land surface model (LSM). The new implementation resulted in a large reduction in the annual fluxes of transpiration across evergreen needleleaf, tundra and C4 grass regions. We conclude that optimisation theory can yield a tractable approach to predicting stomatal conductance in LSMs.
M. J. van den Berg, L. Delobbe, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 18, 5331–5344, https://doi.org/10.5194/hess-18-5331-2014, https://doi.org/10.5194/hess-18-5331-2014, 2014
M. Dessie, N. E. C. Verhoest, V. R. N. Pauwels, T. Admasu, J. Poesen, E. Adgo, J. Deckers, and J. Nyssen
Hydrol. Earth Syst. Sci., 18, 5149–5167, https://doi.org/10.5194/hess-18-5149-2014, https://doi.org/10.5194/hess-18-5149-2014, 2014
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In this study, topography is considered as a proxy for the variability of most of the catchment characteristics. The model study suggests that classifying the catchments into different runoff production areas based on topography and including the impermeable rocky areas separately in the modeling process mimics the rainfall–runoff process in the Upper Blue Nile basin well and yields a useful result for operational management of water resources in this data-scarce region.
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 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
C. M. Surdu, C. R. Duguay, L. C. Brown, and D. Fernández Prieto
The Cryosphere, 8, 167–180, https://doi.org/10.5194/tc-8-167-2014, https://doi.org/10.5194/tc-8-167-2014, 2014
M. T. Pham, W. J. Vanhaute, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 5167–5183, https://doi.org/10.5194/hess-17-5167-2013, https://doi.org/10.5194/hess-17-5167-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
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
J. Minet, N. E. C. Verhoest, S. Lambot, and M. Vanclooster
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-4063-2013, https://doi.org/10.5194/hessd-10-4063-2013, 2013
Revised manuscript has not been submitted
B. Gräler, M. J. van den Berg, S. Vandenberghe, A. Petroselli, S. Grimaldi, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 1281–1296, https://doi.org/10.5194/hess-17-1281-2013, https://doi.org/10.5194/hess-17-1281-2013, 2013
L. Loosvelt, H. Vernieuwe, V. R. N. Pauwels, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 461–478, https://doi.org/10.5194/hess-17-461-2013, https://doi.org/10.5194/hess-17-461-2013, 2013
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Representing the impact of Rhizophora mangroves on flow in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification
Enhancing the representation of water management in global hydrological models
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
Simulation of crop yield using the global hydrological model H08 (crp.v1)
How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
GEB v0.1: a large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe
Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python
Basin-scale gyres and mesoscale eddies in large lakes: a novel procedure for their detection and characterization, assessed in Lake Geneva
Laura L. Swatridge, Ryan P. Mulligan, Leon Boegman, and Shiliang Shan
Geosci. Model Dev., 17, 7751–7766, https://doi.org/10.5194/gmd-17-7751-2024, https://doi.org/10.5194/gmd-17-7751-2024, 2024
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We develop an operational forecast system, Coastlines-LO, that can simulate water levels and surface waves in Lake Ontario driven by forecasts of wind speeds and pressure fields from an atmospheric model. The model has relatively low computational requirements, and results compare well with near-real-time observations, as well as with results from other existing forecast systems. Results show that with shorter forecast lengths, storm surge and wave predictions can improve in accuracy.
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 17, 7181–7198, https://doi.org/10.5194/gmd-17-7181-2024, https://doi.org/10.5194/gmd-17-7181-2024, 2024
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Accurate hydrologic modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall–runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional modeling approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
Matevž Vremec, Raoul A. Collenteur, and Steffen Birk
Geosci. Model Dev., 17, 7083–7103, https://doi.org/10.5194/gmd-17-7083-2024, https://doi.org/10.5194/gmd-17-7083-2024, 2024
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Geoscientists commonly use various potential evapotranpiration (PET) formulas for environmental studies, which can be prone to errors and sensitive to climate change. PyEt, a tested and open-source Python package, simplifies the application of 20 PET methods for both time series and gridded data, ensuring accurate and consistent PET estimations suitable for a wide range of environmental applications.
Nedal Aqel, Lea Reusser, Stephan Margreth, Andrea Carminati, and Peter Lehmann
Geosci. Model Dev., 17, 6949–6966, https://doi.org/10.5194/gmd-17-6949-2024, https://doi.org/10.5194/gmd-17-6949-2024, 2024
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The soil water potential (SWP) determines various soil water processes. Since remote sensing techniques cannot measure it directly, it is often deduced from volumetric water content (VWC) information. However, under dynamic field conditions, the relationship between SWP and VWC is highly ambiguous due to different factors that cannot be modeled with the classical approach. Applying a deep neural network with an autoencoder enables the prediction of the dynamic SWP.
Jenny Kupzig, Nina Kupzig, and Martina Flörke
Geosci. Model Dev., 17, 6819–6846, https://doi.org/10.5194/gmd-17-6819-2024, https://doi.org/10.5194/gmd-17-6819-2024, 2024
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Valid simulation results from global hydrological models (GHMs) are essential, e.g., to studying climate change impacts. Adapting GHMs to ungauged basins requires regionalization, enabling valid simulations. In this study, we highlight the impact of regionalization of GHMs on runoff simulations using an ensemble of regionalization methods for WaterGAP3. We have found that regionalization leads to temporally and spatially varying uncertainty, potentially reaching up to inter-model differences.
Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev., 17, 5387–5412, https://doi.org/10.5194/gmd-17-5387-2024, https://doi.org/10.5194/gmd-17-5387-2024, 2024
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STORM v.2 (short for STOchastic Rainfall Model version 2.0) is an open-source and user-friendly modelling framework for simulating rainfall fields over a basin. It also allows simulating the impact of plausible climate change either on the total seasonal rainfall or the storm’s maximum intensity.
Lukas Riedel, Thomas Röösli, Thomas Vogt, and David N. Bresch
Geosci. Model Dev., 17, 5291–5308, https://doi.org/10.5194/gmd-17-5291-2024, https://doi.org/10.5194/gmd-17-5291-2024, 2024
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River floods are among the most devastating natural hazards. We propose a flood model with a statistical approach based on openly available data. The model is integrated in a framework for estimating impacts of physical hazards. Although the model only agrees moderately with satellite-detected flood extents, we show that it can be used for forecasting the magnitude of flood events in terms of socio-economic impacts and for comparing these with past events.
Robin Schwemmle, Hannes Leistert, Andreas Steinbrich, and Markus Weiler
Geosci. Model Dev., 17, 5249–5262, https://doi.org/10.5194/gmd-17-5249-2024, https://doi.org/10.5194/gmd-17-5249-2024, 2024
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The new process-based hydrological toolbox model, RoGeR (https://roger.readthedocs.io/), can be used to estimate the components of the hydrological cycle and the related travel times of pollutants through parts of the hydrological cycle. These estimations may contribute to effective water resources management. This paper presents the toolbox concept and provides a simple example of providing estimations to water resources management.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
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This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
M. Graham Clark and Sean K. Carey
Geosci. Model Dev., 17, 4911–4922, https://doi.org/10.5194/gmd-17-4911-2024, https://doi.org/10.5194/gmd-17-4911-2024, 2024
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This paper provides validation of the Canadian Small Lakes Model (CSLM) for estimating evaporation rates from reservoirs and a refactoring of the original FORTRAN code into MATLAB and Python, which are now stored in GitHub repositories. Here we provide direct observations of the surface energy exchange obtained with an eddy covariance system to validate the CSLM. There was good agreement between observations and estimations except under specific atmospheric conditions when evaporation is low.
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
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The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Barnaby Dobson, Leyang Liu, and Ana Mijic
Geosci. Model Dev., 17, 4495–4513, https://doi.org/10.5194/gmd-17-4495-2024, https://doi.org/10.5194/gmd-17-4495-2024, 2024
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Water management is challenging when models don't capture the entire water cycle. We propose that using integrated models facilitates management and improves understanding. We introduce a software tool designed for this task. We discuss its foundation, how it simulates water system components and their interactions, and its customisation. We provide a flexible way to represent water systems, and we hope it will inspire more research and practical applications for sustainable water management.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev., 17, 3559–3578, https://doi.org/10.5194/gmd-17-3559-2024, https://doi.org/10.5194/gmd-17-3559-2024, 2024
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We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model; its large selection of different assimilation algorithms; and its modularity with respect to the combination of different types of observations, states and parameters.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
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We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
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The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
Geosci. Model Dev., 17, 2877–2899, https://doi.org/10.5194/gmd-17-2877-2024, https://doi.org/10.5194/gmd-17-2877-2024, 2024
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Treated and untreated wastewaters are sources of contaminants of emerging concern. HydroFATE, a new global model, estimates their concentrations in surface waters, identifying streams that are most at risk and guiding monitoring/mitigation efforts to safeguard aquatic ecosystems and human health. Model predictions were validated against field measurements of the antibiotic sulfamethoxazole, with predicted concentrations exceeding ecological thresholds in more than 400 000 km of rivers worldwide.
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024, https://doi.org/10.5194/gmd-17-2141-2024, 2024
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We show a new irrigation scheme included in the ORCHIDEE land surface model. The new irrigation scheme restrains irrigation due to water shortage, includes water adduction, and represents environmental limits and facilities to access water, due to representing infrastructure in a simple way. Our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, even if there are difficulties due to shortcomings and limited information.
João Careto, Rita Cardoso, Ana Russo, Daniela Lima, and Pedro Soares
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-9, https://doi.org/10.5194/gmd-2024-9, 2024
Revised manuscript accepted for GMD
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In this study, a new drought index is proposed, which not only is able to identify the same events but also can improve the results obtained from other established drought indices. The index is empirically based and is extremely straightforward to compute. It is as well, a daily drought index with the ability to not only assess flash droughts but also events at longer aggregation scales, such as the traditional monthly indices.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
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Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
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We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024, https://doi.org/10.5194/gmd-17-477-2024, 2024
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Over the last 10 years, scientists have developed StorAge Selection: a new way of modeling how material is transported through complex systems. Here, we present some new, easy-to-use, flexible, and very accurate code for implementing this method. We show that, in cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other codes to the right answer in an important way: it conserves mass.
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
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Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
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This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
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We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Hannes Müller Schmied, Tim Trautmann, Sebastian Ackermann, Denise Cáceres, Martina Flörke, Helena Gerdener, Ellen Kynast, Thedini Asali Peiris, Leonie Schiebener, Maike Schumacher, and Petra Döll
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-213, https://doi.org/10.5194/gmd-2023-213, 2023
Revised manuscript accepted for GMD
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Assessing water availability and water use at the global scale is challenging but essential for a range of purposes. We describe the newest version of the global hydrological model WaterGAP which has been used for numerous water resources assessments since 1996. We show the effects of new model features and model evaluations against observed streamflow and water storage anomalies as well as water abstractions statistics. The publically available model output for several variants is described.
Daniel Boateng and Sebastian G. Mutz
Geosci. Model Dev., 16, 6479–6514, https://doi.org/10.5194/gmd-16-6479-2023, https://doi.org/10.5194/gmd-16-6479-2023, 2023
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We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
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Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
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Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
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Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
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NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
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We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
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Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
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DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
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Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Zhipin Ai and Naota Hanasaki
Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, https://doi.org/10.5194/gmd-16-3275-2023, 2023
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Simultaneously simulating food production and the requirements and availability of water resources in a spatially explicit manner within a single framework remains challenging on a global scale. Here, we successfully enhanced the global hydrological model H08 that considers human water use and management to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. Our improved model will be beneficial for advancing global food–water nexus studies in the future.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev., 16, 3137–3163, https://doi.org/10.5194/gmd-16-3137-2023, https://doi.org/10.5194/gmd-16-3137-2023, 2023
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Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows us to select the most influential input parameters, but it has to be adapted to spatial modelling. This study will identify relevant methods that can be transposed to any hydrological and water quality model and improve the fate of pesticide knowledge.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
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In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
Jens A. de Bruijn, Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide Wada, and Jeroen C. J. H. Aerts
Geosci. Model Dev., 16, 2437–2454, https://doi.org/10.5194/gmd-16-2437-2023, https://doi.org/10.5194/gmd-16-2437-2023, 2023
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We present a computer simulation model of the hydrological system and human system, which can simulate the behaviour of individual farmers and their interactions with the water system at basin scale to assess how the systems have evolved and are projected to evolve in the future. For example, we can simulate the effect of subsidies provided on investment in adaptation measures and subsequent effects in the hydrological system, such as a lowering of the groundwater table or reservoir level.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
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During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
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It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
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Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
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This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
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Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
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Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
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Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
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A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
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Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
Shuqi Lin, Donald C. Pierson, and Jorrit P. Mesman
Geosci. Model Dev., 16, 35–46, https://doi.org/10.5194/gmd-16-35-2023, https://doi.org/10.5194/gmd-16-35-2023, 2023
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The risks brought by the proliferation of algal blooms motivate the improvement of bloom forecasting tools, but algal blooms are complexly controlled and difficult to predict. Given rapid growth of monitoring data and advances in computation, machine learning offers an alternative prediction methodology. This study tested various machine learning workflows in a dimictic mesotrophic lake and gave promising predictions of the seasonal variations and the timing of algal blooms.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
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A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Seyed Mahmood Hamze-Ziabari, Ulrich Lemmin, Frédéric Soulignac, Mehrshad Foroughan, and David Andrew Barry
Geosci. Model Dev., 15, 8785–8807, https://doi.org/10.5194/gmd-15-8785-2022, https://doi.org/10.5194/gmd-15-8785-2022, 2022
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A procedure combining numerical simulations, remote sensing, and statistical analyses is developed to detect large-scale current systems in large lakes. By applying this novel procedure in Lake Geneva, strategies for detailed transect field studies of the gyres and eddies were developed. Unambiguous field evidence of 3D gyre/eddy structures in full agreement with predictions confirmed the robustness of the proposed procedure.
Cited articles
Amos, B., Arkebauer, T. J., and Doran, J. W.: Soil surface fluxes of greenhouse gases in an irrigated maize-based agroecosystem, Soil Sci. Soc. Am. J., 69, 387–395, https://doi.org/10.2136/sssaj2005.0387, 2005.
Arain, M. A. and Restrepo-Coupe, N.: Net ecosystem production in a temperate pine plantation in southeastern Canada, Agr. Forest Meteorol., 128, 223–241, 2005.
Ardö, J., Mölder, M., El-Tahir, B. A., and Elkhidir, H. A. M.: Seasonal variation of carbon fluxes in a sparse savanna in semi arid Sudan, Carbon Balance and Management, 3, 1–18, https://doi.org/10.1186/1750-0680-3-7, 2008.
Armstrong, R., Brodzik, M., Knowles, K., and Savoie, M.: Global Monthly EASE-Grid Snow Water Equivalent Climatology, Version 1, https://doi.org/10.5067/KJVERY3MIBPS, 2005.
Aubinet, M., Chermanne, B., Vandenhaute, M., Longdoz, B., Yernaux, M., and Laitat, E.: Long term carbon dioxide exchange above a mixed forest in the Belgian Ardennes, Agr. Forest Meteorol., 108, 293–315, 2001.
Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., and Susskind, J.: AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems, IEEE T. Geosci. Remote Sens., 41, 253–264, https://doi.org/10.1109/TGRS.2002.808356, 2003.
Baldocchi, D., Falge, E., Gu, L. H., Olson, R., Hollinger, D., Running, S., Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein, A., Katul, G., Law, B., Lee, X. H., Malhi, Y., Meyers, T., Munger, W., Oechel, W., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities, B. Am. Meteorol. Soc., 82, 2415–2434, https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2, 2001.
Bazot, S., Barthes, L., Blanot, D., and Fresneau, C.: Distribution of non-structural nitrogen and carbohydrate compounds in mature oak trees in a temperate forest at four key phenological stages, Trees, 27, 1023–1034, 2013.
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017.
Beringer, J.: Daly Pasture OzFlux site. OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14238, 2013a.
Beringer, J.: Dry River OzFluxsite. OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14229, 2013b.
Beringer, J.: Daly Uncleared OzFlux site. OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14239, 2013c.
Beringer, J.: Yanco JAXA OzFlux tower site. OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14235, 2013d.
Beringer, J.: Riggs Creek OzFluxsite. OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14246, 2014a.
Beringer, J.: Red Dirt Melon Farm OzFlux tower site. OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14245, 2014b.
Biederman, J. A., Scott, R. L., Goulden, M. L., Vargas, R., Litvak, M. E., Kolb, T. E., Yepez, E. A., Oechel, W. C., Blanken, P. D., and Bell, T. W.: Terrestrial carbon balance in a drier world: the effects of water availability in southwestern North America, Glob. Change Biol., 22, 1867–1879, https://doi.org/10.1111/gcb.13222, 2016.
Bond-Lamberty, B., Wang, C. K., and Gower, S. T.: Net primary production and net ecosystem production of a boreal black spruce wildfire chronosequence, Glob. Change Biol., 10, 473–487, https://doi.org/10.1111/j.1529-8817.2003.0742.x, 2004.
Borchard, N., Schirrmann, M., von Hebel, C., Schmidt, M., Baatz, R., Firbank, L., Vereecken, H., and Herbst, M.: Spatio-temporal drivers of soil and ecosystem carbon fluxes at field scale in an upland grassland in Germany, Agr. Ecosyst. Environ., 211, 84–93, 2015.
Brooks, R. H. and Corey, A. T.: Hydraulic properties of porous media and their relation to drainage design, T. ASAE, 7, 26–28, https://doi.org/10.13031/2013.40684, 1964.
Calperum Tech: Calperum Chowilla OzFlux tower site. OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14236, 2013.
Campbell, J. L. and Law, B. E.: Forest soil respiration across three climatically distinct chronosequences in Oregon, Biogeochemistry, 73, 109–125, 2005.
Chen, Q., Gong, P., Baldocchi, D., and Tian, Y. Q.: Estimating basal area and stem volume for individual trees from lidar data, Photogramm. Eng. Rem. S., 73, 1355–1365, https://doi.org/10.14358/PERS.73.12.1355, 2007.
Clapp, R. B. and Hornberger, G. M.: Empirical equations for some soil hydraulic properties, Water Resour. Res., 14, 601–604, 1978.
Cleverly, J.: Alice Springs Mulga OzFlux site. OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14217, 2011.
Colello, G. D., Grivet, C., Sellers, P. J., and Berry, J. A.: Modeling of energy, water, and CO2 flux in a temperate grassland ecosystem with SiB2: May–October 1987, J. Atmos. Sci., 55, 1141–1169, https://doi.org/10.1175/1520-0469(1998)055<1141:MOEWAC>2.0.CO;2, 1998.
Combe, M., de Arellano, J. V.-G., Ouwersloot, H. G., and Peters, W.: Plant water-stress parameterization determines the strength of land-atmosphere coupling, Agr. Forest Meteorol., 217, 61–73, https://doi.org/10.1016/j.agrformet.2015.11.006, 2016.
Cook, B. D., Davis, K. J., Wang, W. G., Desai, A., Berger, B. W., Teclaw, R. M., Martin, J. G., Bolstad, P. V., Bakwin, P. S., Yi, C. X., and Heilman, W.: Carbon exchange and venting anomalies in an upland deciduous forest in northern Wisconsin, USA, Agr. Forest Meteorol., 126, 271–295, https://doi.org/10.1016/j.agrformet.2004.06.008, 2004.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kallberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
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.
Diawara, A., Loustau, D., and Berbigier, P.: Comparison of 2 methods for estimating evaporation of a Pinus-Pinaster (AIT) forest – sap flow and energy-balance with sensible heat-flux measurements by an eddy-covariance method, Agr. Forest Meteorol., 54, 49–66, https://doi.org/10.1016/0168-1923(91)90040-W, 1991.
Dolman, A. J., Miralles, D. G., and de Jeu, R. A.: Fifty years since Monteith's 1965 seminal paper: the emergence of global ecohydrology, Ecohydrology, 7, 897–902, https://doi.org/10.1002/eco.1505, 2014.
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.
Dorigo, W. A., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiova, A., Sanchis-Dufau, A. D., 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, https://doi.org/10.2136/vzj2012.0097, 2013.
Dorigo, W. A., Gruber, A., de Jeu, R. A. M., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R. M., and Kidd, R.: Evaluation of the ESA CCI soil moisture product using ground-based observations, Remote Sens. Environ., 162, 380–395, https://doi.org/10.1016/j.rse.2014.07.023, 2015.
Eaton, A. K., Rouse, W. R., Lafleur, P. M., Marsh, P., and Blanken, P. D.: Surface energy balance of the western and central Canadian subarctic: Variations in the energy balance among five major terrain types, J. Climate, 14, 3692–3703, https://doi.org/10.1175/1520-0442(2001)014<3692:SEBOTW>2.0.CO;2, 2001.
Fischer, M. L., Billesbach, D. P., Berry, J. A., Riley, W. J., and Torn, M. S.: Spatiotemporal variations in growing season exchanges of CO2, H2O, and sensible heat in agricultural fields of the Southern Great Plains, Earth Interact., 11, 1–21, 2007.
Fisher, J. B., Tu, K. P., and Baldocchi, D. D.: Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites, Remote Sens. Environ., 112, 901–919, https://doi.org/10.1016/j.rse.2007.06.025, 2008.
Fisher, J. B., Melton, F., Middleton, E., Hain, C., Anderson, M., Allen, R., McCabe, M., Hook, S., Beldocchi, D., Townsend, P. A., Kilic, A., Tu, K., Miralles, D. G., Perret, J., Lagouarde, J.-P., Waliser, D., Purdy, A. J., French, A., Schimel, D., Famiglietti, J. S., Stephens, G., and Wood, E. F.: The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources, Water Resour. Res., 53, WR020175, https://doi.org/10.1002/2016WR020175, 2017. 2017.
Galvagno, M., Wohlfahrt, G., Cremonese, E., Rossini, M., Colombo, R., Filippa, G., Julitta, T., Manca, G., Siniscalco, C., and di Cella, U. M.: Phenology and carbon dioxide source/sink strength of a subalpine grassland in response to an exceptionally short snow season, Environ. Res. Lett., 8, 025008, https://doi.org/10.1088/1748-9326/8/2/025008, 2013.
Gash, J. H. C.: An analytical model of rainfall interception by forests, Q. J. Roy. Meteor. Soc., 105, 43–55, https://doi.org/10.1002/qj.49710544304, 1979.
Global Soil Data Task Group: Global Gridded Surfaces of Selected Soil Characteristics (IGBP-DIS), Oak Ridge, Tennessee, https://doi.org/10.3334/ORNLDAAC/569, available at: http://www.daac.ornl.gov, 2000.
Goldstein, A. H., Hultman, N. E., Fracheboud, J. M., Bauer, M. R., Panek, J. A., Xu, M., Qi, Y., Guenther, A. B., and Baugh, W.: Effects of climate variability on the carbon dioxide, water, and sensible heat fluxes above a ponderosa pine plantation in the Sierra Nevada (CA), Agr. Forest Meteorol., 101, 113–129, https://doi.org/10.1016/S0168-1923(99)00168-9, 2000.
Good, S. P., Noone, D., and Bowen, G.: Hydrologic connectivity constrains partitioning of global terrestrial water fluxes, Science, 349, 175–177, https://doi.org/10.1126/science.aaa5931, 2015.
Goulden, M. L., Munger, J. W., Fan, S. M., Daube, B. C., and Wofsy, S. C.: Measurements of carbon sequestration by long-term eddy covariance: Methods and a critical evaluation of accuracy, Glob. Change Biol., 2, 169–182, https://doi.org/10.1111/j.1365-2486.1996.tb00070.x, 1996.
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, https://doi.org/10.1038/ngeo2247, 2014.
Gruber, A., Su, C.-H., Zwieback, S., Crow, W. T., Dorigo, W., and Wagner, W.: Recent advances in (soil moisture) triple collocation analysis, International Journal of Applied Earth Observation and Geoinformation, 45, 200 – 211, https://doi.org/10.1016/j.jag.2015.09.002, 2016.
Guglielmetti, M., Schwank, M., Mätzler, C., Oberdörster, C., Vanderborght, J., and Flühler, H.: Measured microwave radiative transfer properties of a deciduous forest canopy, Remote Sens. Environ., 109, 523–532, https://doi.org/10.1016/j.rse.2007.02.003, 2007.
Guillod, B. P., Orlowsky, B., Miralles, D. G., Teuling, A. J., and Seneviratne, S. I.: Reconciling spatial and temporal soil moisture effects on afternoon rainfall, Nature Communications, 6, 6443, https://doi.org/10.1038/ncomms7443, 2015.
Hansen, M. C., Townshend, J. R. G., Defries, R. S., and Carroll, M.: Estimation of tree cover using MODIS data at global, continental and regional/local scales, Int. J. Remote Sens., 26, 4359–4380, 2005.
Henderson-Sellers, B.: A new formula for latent heat of vaporization of water as a function of temperature, Q. J. Roy. Meteor. Soc., 110, 1186–1190, https://doi.org/10.1002/qj.49711046626, 1984.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F., and Wolff, D. B.: The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales, J. Hydrometeorol., 8, 38–55, https://doi.org/10.1175/JHM560.1, 2007.
Huntington, T. G.: Evidence for intensification of the global water cycle: Review and synthesis, J. Hydrol., 319, 83–95, https://doi.org/10.1016/j.jhydrol.2005.07.003, 2006.
Irvine, J., Law, B. E., Kurpius, M. R., Anthoni, P. M., Moore, D., and Schwarz, P. A.: Age-related changes in ecosystem structure and function and effects on water and carbon exchange in ponderosa pine, Tree Physiol., 24, 753–763, 2004.
Jacquette, E., Al Bitar, A., Mialon, A., Kerr, Y. H., Quesney, A., Cabot, F., and Richaume, P.: SMOS CATDS level 3 global products over land, in: Remote Sensing for Agriculture, Ecosystems and Hydrology XII, edited by: Neale, C. and Maltese, A., vol. 7824 of Proceedings of SPIE-The International Society for Optical Engineering, 2010.
Jasechko, S., Sharp, Z. D., Gibson, J. J., Birks, S. J., Yi, Y., and Fawcett, P. J.: Terrestrial water fluxes dominated by transpiration, Nature, 496, 347–350, https://doi.org/10.1038/nature11983, 2013.
Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model, Biogeosciences, 6, 2001–2013, https://doi.org/10.5194/bg-6-2001-2009, 2009.
Kato, T., Tang, Y., Gu, S., Hirota, M., Du, M., Li, Y., and Zhao, X.: Temperature and biomass influences on interannual changes in CO2 exchange in an alpine meadow on the Qinghai-Tibetan Plateau, Glob. Change Biol., 12, 1285–1298, https://doi.org/10.1111/j.1365-2486.2006.01153.x, 2006.
Kelliher, F. M., Leuning, R., and Schulze, E. D.: Evaporation and canopy characteristics of coniferous forests and grasslands, Oecologia, 95, 153–163, https://doi.org/10.1007/BF00323485, 1993.
Knohl, A., Schulza, E. D., Kolle, O., and Buchmann, N.: Large carbon uptake by an unmanaged 250-year-old deciduous forest in Central Germany, Agr. Forest Meteorol., 118, 151–167, https://doi.org/10.1016/S0168-1923(03)00115-1, 2003.
Lievens, H., Kumar Tomer, S., Al Bitar, A., De Lannoy, G. J. M., Drusch, M., Dumedah, G., Hendricks Franssen, H.-J., Kerr, Y. H., Martens, B., Pan, M., Roundy, J. K., Vereecken, H., Walker, J. P., Wood, E. F., Verhoest, N. E. C., and Pauwels, V. R. N.: SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia, Remote Sens. Environ., 168, 146–162, https://doi.org/10.1016/j.rse.2015.06.025, 2015.
Lievens, H., Martens, B., Verhoest, N. E. C., Hahn, S., Reichle, R. H., and Miralles, D. G.: 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.
Liu, Y. Y., de Jeu, R. A. M., McCabe, M. F., Evans, J. P., and van Dijk, A. I. J. M.: Global long-term passive microwave satellite-based retrievals of vegetation optical depth, Geophys. Res. Lett., 38, L18402, https://doi.org/10.1029/2011GL048684, 2011.
Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., de Jeu, R. A. M., Wagner, W., McCabe, M. F., Evans, J. P., and van Dijk, A. I. J. M.: Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sens. Environ. 123, 280–297, https://doi.org/10.1016/j.rse.2012.03.014, 2012.
Liu, Y. Y., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P., and de Jeu, R. A. M.: Global vegetation biomass change (1988–2008) and attribution to environmental and human drivers, Global Ecol. Biogeogr., 22, 692–705, https://doi.org/10.1111/geb.12024, 2013.
Loew, A., Peng, J., and Borsche, M.: High-resolution land surface fluxes from satellite and reanalysis data (HOLAPS v1.0): evaluation and uncertainty assessment, Geosci. Model Dev., 9, 2499–2532, https://doi.org/10.5194/gmd-9-2499-2016, 2016.
Luojus, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Kangwa, M., Smolander, T., and Derksen, C.: Global snow monitoring for climate research: Algorithm Theoretical Basis Document(ATBD) – SWE-algorithm, Tech. Rep. Version/Revision 1.0/02, 2013.
Ma, S., Baldocchi, D. D., Xu, L., and Hehn, T.: Inter-annual variability in carbon dioxide exchange of an oak/grass savanna and open grassland in California, Agr. Forest Meteorol., 147, 157–171, https://doi.org/10.1016/j.agrformet.2007.07.008, 2007.
Macfarlane, C.: Great Western Woodlands OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14226, 2013.
Mach, D. M., Christian, H. J., Blakeslee, R. J., Boccippio, D. J., Goodman, S. J., and Boeck, W. L.: Performance assessment of the Optical Transient Detector and Lightning Imaging Sensor, J. Geophys. Res.-Atmos., 112, D09210, https://doi.org/10.1029/2006JD007787, 2007.
Maidment, D. R.: Handbook of Hydrology, McGraw-Hill, 1993.
Martens, B., Miralles, D. G., Lievens, H., Fernández-Prieto, D., and Verhoest, N. E. C.: Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture, Int. J. Appl. Earth Obs., 48, 146–162, https://doi.org/10.1016/j.jag.2015.09.012, 2016.
McCabe, M. F., Ershadi, A., Jimenez, C., Miralles, D. G., Michel, D., and Wood, E. F.: The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data, Geosci. Model Dev., 9, 283– 305, https://doi.org/10.5194/gmd-9-283-2016, 2016.
McCaughey, J. H., Pejam, M. R., Arain, M. A., and Cameron, D. A.: Carbon dioxide and energy fluxes from a boreal mixedwood forest ecosystem in Ontario, Canada, Agr. Forest Meteorol., 140, 79–96, https://doi.org/10.1016/j.agrformet.2006.08.010, 2006.
McEwing, K. R., Fisher, J. P., and Zona, D.: Environmental and vegetation controls on the spatial variability of CH4 emission from wet-sedge and tussock tundra ecosystems in the Arctic, Plant Soil, 388, 37–52, 2015.
McNaughton, K. G. and Black, T. A.: Study of evapotranspiration from a Douglas-fir forest using energy-balance approach, Water Resour. Res., 9, 1579–1590, https://doi.org/10.1029/WR009i006p01579, 1973.
Michel, D., Jiménez, C., Miralles, D. G., Jung, M., Hirschi, M., Ershadi, A., Martens, B., McCabe, M. F., Fisher, J. B., Mu, Q., Seneviratne, S. I., Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms, Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, 2016.
Milyukova, I. M., Kolle, O., Varlagin, A. V., Vygodskaya, N. N., Schulze, E. D., and Lloyd, J.: Carbon balance of a southern taiga spruce stand in European Russia, Tellus B, 54, 429–442, https://doi.org/10.1034/j.1600-0889.2002.01387.x, 2002.
Miralles, D. G., Crow, W. T., and Cosh, M. H.: Estimating spatial sampling errors in coarse-scale soil moisture estimates derived from point-scale observations, J. Hydrometeorol., 11, 1423–1429, https://doi.org/10.1175/2010JHM1285.1, 2010a.
Miralles, D. G., Gash, J. H., Holmes, T. R. H., de Jeu, R. A. M., and Dolman, A. J.: Global canopy interception from satellite observations, J. Geophys. Res.-Atmos., 115, https://doi.org/10.1029/2009JD013530, 2010b.
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.
Miralles, D. G., van den Berg, M. J., Teuling, A. J., and de Jeu, R. A. M.: Soil moisture-temperature coupling: A multiscale observational analysis, Geophys. Res. Lett., 39, L21707, https://doi.org/10.1029/2012GL053703, 2012.
Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C., and de Arellano, J. V.-G.: Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation, Nat. Geosci., 7, 345–349, https://doi.org/10.1038/NGEO2141, 2014a.
Miralles, D. G., van den Berg, M. J., Gash, J. H., Parinussa, R. M., de Jeu, R. A. M., Beck, H. E., Holmes, T. R. H., Jiménez, C., Verhoest, N. E. C., Dorigo, W. A., Teuling, A. J., and Dolman, A. J.: El Niño-La Niña cycle and recent trends in continental evaporation, Nature Climate Change, 4, 122–126, https://doi.org/10.1038/NCLIMATE2068, 2014b.
Miralles, D. G., Jiménez, C., Jung, M., Michel, D., Ershadi, A., McCabe, M. F., Hirschi, M., Martens, B., Dolman, A. J., Fisher, J. B., Mu, Q., Seneviratne, S. I., Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets, Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, 2016a.
Miralles, D. G., Martens, B., Dolman, A. J., Jiménez, C., McCabe, M. F., and Wood, E. F.: Global Land Evaporation [in: State of the Climate in 2015], B. Amer. Meteor. Soc., 97, S34–S35, 2016b.
Moureaux, C., Debacq, A., Bodson, B., Heinesch, B., and Aubinet, M.: Annual net ecosystem carbon exchange by a sugar beet crop, Agr. Forest Meteorol., 139, 25–39, 2006.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.: Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sens. Environ., 111, 519–536, https://doi.org/10.1016/j.rse.2007.04.015, 2007.
Noormets, A., McNulty, S. G., DeForest, J. L., Sun, G., Li, Q., and Chen, J.: Drought during canopy development has lasting effect on annual carbon balance in a deciduous temperate forest, New Phytol., 179, 818–828, https://doi.org/10.1111/j.1469-8137.2008.02501.x, 2008.
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.
Priestley, J. H. C. and Taylor, J.: On the assessment of surface heat flux and evaporation using large-scale parameters, Mon. Weather Rev., 100, 81–92, 1972.
Richards, L. A.: Capillary conduction of liquids through porous mediums, Physics, 1, 318–333, 1931.
Richardson, A. D., Hollinger, D. Y., Burba, G. G., Davis, K. J., Flanagan, L. B., Katul, G. G., Munger, J. W., Ricciuto, D. M., Stoy, P. C., and Suyker, A. E.: A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes, Agr. Forest Meteorol., 136, 1–18, 2006.
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. Soc., 85, 381–394, https://doi.org/10.1175/BAMS-85-3-381, 2004.
Ronda, R. J., Van den Hurk, B. J. J. M., and Holtslag, A. A. M.: Spatial heterogeneity of the soil moisture content and its impact on surface flux densities and near-surface meteorology, J. Hydrometeorol., 3, 556–570, https://doi.org/10.1175/1525-7541(2002)003<0556:SHOTSM>2.0.CO;2, 2002.
Ruehr, N. K., Martin, J. G., and Law, B. E.: Effects of water availability on carbon and water exchange in a young ponderosa pine forest: Above- and belowground responses, Agr. Forest Meteorol., 164, 136–148, https://doi.org/10.1016/j.agrformet.2012.05.015, 2012.
Schlesinger, W. H. and Jasechko, S.: Transpiration in the global water cycle, Agr. Forest Meteorol., 189, 115–117, https://doi.org/10.1016/j.agrformet.2014.01.011, 2014.
Schmid, H. P., Grimmond, C. S. B., Cropley, F., Offerle, B., and Su, H. B.: Measurements of CO2 and energy fluxes over a mixed hardwood forest in the mid-western United States, Agr. Forest Meteorol., 103, 357–374, https://doi.org/10.1016/S0168-1923(00)00140-4, 2000.
Schroder, I.: Arcturus Emerald OzFlux tower site OzFlux: Australian and New Zealand flux research and monitoring, http://hdl.handle.net/102.100.100/14249, 2014.
Scipal, K., Holmes, T., de Jeu, R., Naeimi, V., and Wagner, W.: A possible solution for the problem of estimating the error structure of global soil moisture data sets, Geophys. Res. Lett., 35, https://doi.org/10.1029/2008GL035599, 2008.
Scott, R. L.: Using watershed water balance to evaluate the accuracy of eddy covariance evaporation measurements for three semiarid ecosystems, Agr. Forest Meteorol., 150, 219–225, https://doi.org/10.1016/j.agrformet.2009.11.002, 2010.
Scott, R. L., Jenerette, G. D., Potts, D. L., and Huxman, T. E.: Effects of seasonal drought on net carbon dioxide exchange from a woody-plant-encroached semiarid grassland, J. Geophys. Res.-Biogeo., 114, https://doi.org/10.1029/2008JG000900, 2009.
Scott, R. L., Hamerlynck, E. P., Jenerette, G. D., Moran, M. S., and Barron-Gafford, G. A.: Carbon dioxide exchange in a semidesert grassland through drought-induced vegetation change, J. Geophys. Res.-Biogeo., 115, https://doi.org/10.1029/2010JG001348, 2010.
Sellers, P. J., Fennessy, M. J., and Dickinson, R. E.: A numerical approach to calculating soil wetness and evapotranspiration over large grid areas, J. Geophys. Res.-Atmos., 112, d18106, https://doi.org/10.1029/2007JD008781, 2007.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture-climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010.
Serraj, R., Allen, L. H., and Sinclair, T. R.: Soybean leaf growth and gas exchange response to drought under carbon dioxide enrichment, Glob. Change Biol., 5, 283–291, https://doi.org/10.1046/j.1365-2486.1999.00222.x, 1999.
Shuttleworth, W. J. and Calder, I. R.: Has the Priestley-Taylor equation any relevance to forest evaporation?, J. Appl. Meteorol., 18, 639–646, https://doi.org/10.1175/1520-0450(1979)018<0639:HTPTEA>2.0.CO;2, 1979.
Shuttleworth, W. J., Gash, J. H., Lloyd, C. R., Moore, C. J., Roberts, J., Marques, A. D., Fisch, G., Silva, V. D., Molton, L. C. B., Sa, L. D. D., Nobre, J. C., Cabral, O. M. R., Patel, S. R., and Demoraes, J. C.: Observations of radiation exchange above and below Amazonian forest, Q. J. Roy. Meteor. Soc., 110, 1163–1169, https://doi.org/10.1002/qj.49711046623, 1984.
Simbahan, G. C., Dobermann, A., Goovaerts, P., Ping, J. L., and Haddix, M. L.: Fine-resolution mapping of soil organic carbon based on multivariate secondary data, Geoderma, 132, 471–489, https://doi.org/10.1016/j.geoderma.2005.07.001, 2006.
Steininger, M. K.: Net carbon fluxes from forest clearance and regrowth in the Amazon, Ecol. Appl., 14, 313–322, https://doi.org/10.1890/02-6007, 2004.
Taylor, C. M., de Jeu, R. A. M., Guichard, F., Harris, P. P., and Dorigo, W. A.: Afternoon rain more likely over drier soils, Nature, 489, 423–426, https://doi.org/10.1038/nature11377, 2012.
Teuling, A. J., Seneviratne, S. I., Stoeckli, R., Reichstein, M., Moors, E., Ciais, P., Luyssaert, S., van den Hurk, B., Ammann, C., Bernhofer, C., Dellwik, E., Gianelle, D., Gielen, B., Gruenwald, T., Klumpp, K., Montagnani, L., Moureaux, C., Sottocornola, M., and Wohlfahrt, G.: Contrasting response of European forest and grassland energy exchange to heatwaves, Nat. Geosci., 3, 722–727, https://doi.org/10.1038/NGEO950, 2010.
Tuanmu, M.-N. and Jetz, W.: A global 1-km consensus land-cover product for biodiversity and ecosystem modelling, Global Ecol. Biogeogr., 23, 1031–1045, 2014.
Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R., Meyers, T. P., Prueger, J. H., Starks, P. J., and Wesely, M. L.: Correcting eddy-covariance flux underestimates over a grassland, Agri. Forest Meteorol., 103, 279–300, 2000.
Valente, F., David, J. S., and Gash, J. H. C.: Modelling interception loss for two sparse eucalypt and pine forests in central Portugal using reformulated Rutter and Gash analytical models, J. Hydrol., 190, 141–162, https://doi.org/10.1016/S0022-1694(96)03066-1, 1997.
van der Schalie, R., Parinussa, R., Renzullo, L. J., van Dijk, A. I. J. M., Su, C.-H., and de Jeu, R. A. M.: SMOS soil moisture retrievals using the Land Parameter Retrieval Model: Evaluation over the Murrumbidgee catchment, southeast Australia, Remote Sens. Environ., 163, 70–79, https://doi.org/10.1016/j.rse.2015.03.006, 2015.
van der Schalie, R., Kerr, Y. H., Wigneron, J.-P., Rodríguez-Fernández, N. J., Al-Yaari, A., and de Jeu, R. A. M.: Global SMOS soil moisture retrievals from The Land Parameter Retrieval Model, Int. J. Appl. Earth Obs., 45, 125–134, https://doi.org/10.1016/j.jag.2015.08.005, 2016.
Verma, S. B., Dobermann, A., Cassman, K. G., Walters, D. T., Knops, J. M., Arkebauer, T. J., Suyker, A. E., Burba, G. G., Amos, B., Yang, H. S., Ginting, D., Hubbard, K. G., Gitelson, A. A., and Walter-Shea, E. A.: Annual carbon dioxide exchange in irrigated and rainfed maize-based agroecosystems, Agr. Forest Meteorol., 131, 77–96, https://doi.org/10.1016/j.agrformet.2005.05.003, 2005.
Viswanadham, Y., Filho, V. P. S., and Andre, R. G. B.: The Priestley-Taylor parameter-alpha for the amazon forest, Forest Ecol. Manage., 38, 211–225, https://doi.org/10.1016/0378-1127(91)90143-J, 1991.
Wagner, W., Dorigo, W. A., de Jeu, R. A. M., Fernández-Prieto, D., Benveniste, J., Haas, E., and Ertl, M.: Fusion of active and passive microwave observations to create an essential climate variable data record on soil moisture, in: Proceedings of the XXII International Society for Photogrammetry and Remote Sensing (ISPRS) Congress, Melbourne, Australia, vol. 25, 2012.
Wang, K. and Dickinson, R. E.: A review of global terrestrial evapotranspiration: observation, modelling, climatology and climatic variability, Rev. Geophys., 50, RG2005, https://doi.org/10.1029/2011RG000373, 2012.
Wang, L., Good, S. P., and Caylor, K. K.: Global synthesis of vegetation control on evapotranspiration partitioning, Geophys. Res. Lett., 41, 6753–6757, 2014.
Wielicki, B. A.: Clouds and the Earth's Radiant Energy System (CERES): An earth observing system experiment, B. Am. Meteorol. Soc., 77, 853–868, https://doi.org/10.1175/1520-0477(1996)077<0853:CATERE>2.0.CO;2, 1996.
Wild, M., Grieser, J., and Schaer, C.: Combined surface solar brightening and increasing greenhouse effect support recent intensification of the global land-based hydrological cycle, Geophys. Res. Lett., 35, L17706, https://doi.org/10.1029/2008GL034842, 2008.
Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., Berbigier, P., Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A., Ibrom, A., Law, B., Kowalski, A., Meyers, T., Moncrieff, J., Monson, R., Oechel, W., Tenhunen, J., Valentini, R., and Verma, S.: Energy balance closure at FLUXNET sites, Agr. Forest Meteorol., 113, 223–243, https://doi.org/10.1016/S0168-1923(02)00109-0, 2002.
Yilmaz, M. T. and Crow, W. T.: Evaluation of Assumptions in Soil Moisture Triple Collocation Analysis, J. Hydrometeorol., 15, 1293–1302, https://doi.org/10.1175/JHM-D-13-0158.1, 2014.
Yilmaz, T. M. 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.
Zeeman, M. J., Hiller, R., Gilgen, A. K., Michna, P., Plüss, P., Buchmann, N., and Eugster, W.: Management, not climate, controls net CO2 fluxes and carbon budgets of three grasslands along an elevational gradient in Switzerland, Agr. Forest Meteorol., 50, 519–530, 2010.
Zhang, K., Kimball, J. S., Nemani, R. R., and Running, S. W.: A continuous satellite-derived global record of land surface evapotranspiration from 1983 to 2006, Water Resour. Res., 46, W09522, https://doi.org/10.1029/2009WR008800, 2010.
Zhang, Y., Peña-Arancibia, J. L., McVicar, T. R., Chiew, F. H. S., Vaze, J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y. Y., Miralles, D. G., and Pan, M.: Multi-decadal trends in global terrestrial evapotranspiration and its components, Scientific reports, 6, 19124, https://doi.org/10.1038/srep19124, 2016.
Short summary
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.
Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of...
