Articles | Volume 21, issue 9
https://doi.org/10.5194/hess-21-4927-2017
© 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/hess-21-4927-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
29 Sep 2017
Research article |
| 29 Sep 2017
State and parameter estimation of two land surface models using the ensemble Kalman filter and the particle filter
Hongjuan Zhang
CORRESPONDING AUTHOR
Forschungszentrum Jülich, Agrosphere (IBG 3), Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems: HPSC TerrSys, Forschungszentrum Jülich, Jülich, Germany
Harrie-Jan Hendricks Franssen
Forschungszentrum Jülich, Agrosphere (IBG 3), Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems: HPSC TerrSys, Forschungszentrum Jülich, Jülich, Germany
Xujun Han
Forschungszentrum Jülich, Agrosphere (IBG 3), Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems: HPSC TerrSys, Forschungszentrum Jülich, Jülich, Germany
Jasper A. Vrugt
Department of Civil and Environmental Engineering, University of California Irvine, Irvine, USA
Department of Earth Systems Science, University of California Irvine, Irvine, USA
Harry Vereecken
Forschungszentrum Jülich, Agrosphere (IBG 3), Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems: HPSC TerrSys, Forschungszentrum Jülich, Jülich, Germany
Related authors
No articles found.
Teng Xu, Sinan Xiao, Sebastian Reuschen, Nils Wildt, Harrie-Jan Hendricks Franssen, and Wolfgang Nowak
Hydrol. Earth Syst. Sci., 28, 5375–5400, https://doi.org/10.5194/hess-28-5375-2024, https://doi.org/10.5194/hess-28-5375-2024, 2024
Short summary
Short summary
We provide a set of benchmarking scenarios for geostatistical inversion, and we encourage the scientific community to use these to compare their newly developed methods. To facilitate transparent, appropriate, and uncertainty-aware comparison of novel methods, we provide some accurate reference solutions, a high-end reference algorithm, and a diverse set of benchmarking metrics, all of which are publicly available. With this, we seek to foster more targeted and transparent progress in the field.
Manuela S. Kaufmann, Anja Klotzsche, Jan van der Kruk, Anke Langen, Harry Vereecken, and Lutz Weihermüller
EGUsphere, https://doi.org/10.5194/egusphere-2024-2889, https://doi.org/10.5194/egusphere-2024-2889, 2024
Short summary
Short summary
To use fertilizers more effectively, non-invasive geophysical methods can be used to understand nutrient distribution in the soil. We utilize in a long-term field study geophysical techniques to study soil properties and conditions under different fertilizer treatments. We compared the geophysical responds with soil samples and soil sensor data. Especially, electromagnetic induction and electrical resistivity tomography were effective in monitoring changes in nitrate levels over time.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
Short summary
Short summary
Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
Short summary
Short summary
Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Joschka Neumann, Nicolas Brüggemann, Patrick Chaumet, Normen Hermes, Jan Huwer, Peter Kirchner, Werner Lesmeister, Wilhelm August Mertens, Thomas Pütz, Jörg Wolters, Harry Vereecken, and Ghaleb Natour
EGUsphere, https://doi.org/10.5194/egusphere-2024-1598, https://doi.org/10.5194/egusphere-2024-1598, 2024
Short summary
Short summary
Climate change in combination with a steadily growing world population and a simultaneous decrease in agricultural land is one of the greatest global challenges facing mankind. In this context, Forschungszentrum Jülich established an "agricultural simulator" (AgraSim), which enables research into the effects of climate change on agricultural ecosystems and the optimization of agricultural cultivation and management strategies with the aid of combined experimental and numerical simulation.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
EGUsphere, https://doi.org/10.5194/egusphere-2024-1678, https://doi.org/10.5194/egusphere-2024-1678, 2024
Short summary
Short summary
The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two end members of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented super-sites.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie Fisher, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2024-978, https://doi.org/10.5194/egusphere-2024-978, 2024
Short summary
Short summary
Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land Surface Models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes and variability of carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research on these processes.
Lukas Strebel, Heye Bogena, Harry Vereecken, Mie Andreasen, Sergio Aranda-Barranco, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 28, 1001–1026, https://doi.org/10.5194/hess-28-1001-2024, https://doi.org/10.5194/hess-28-1001-2024, 2024
Short summary
Short summary
We present results from using soil water content measurements from 13 European forest sites in a state-of-the-art land surface model. We use data assimilation to perform a combination of observed and modeled soil water content and show the improvements in the representation of soil water content. However, we also look at the impact on evapotranspiration and see no corresponding improvements.
Bamidele Joseph Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2023-3132, https://doi.org/10.5194/egusphere-2023-3132, 2024
Short summary
Short summary
This study uses simulations to understand how the soil information across Africa affects the water balance, using 4 soil databases and 3 different rainfall datasets. Results show that the soil information impacts water balance estimates, especially with a higher rate of rainfall.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
Short summary
Short summary
In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
Short summary
Short summary
In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
Short summary
Short summary
Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
Short summary
Short summary
Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Jordan Bates, Francois Jonard, Rajina Bajracharya, Harry Vereecken, and Carsten Montzka
AGILE GIScience Ser., 3, 23, https://doi.org/10.5194/agile-giss-3-23-2022, https://doi.org/10.5194/agile-giss-3-23-2022, 2022
Wei Qu, Heye Bogena, Christoph Schüth, Harry Vereecken, Zongmei Li, and Stephan Schulz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-131, https://doi.org/10.5194/gmd-2022-131, 2022
Publication in GMD not foreseen
Short summary
Short summary
We applied the global sensitivity analysis LH-OAT to the integrated hydrology model ParFlow-CLM to investigate the sensitivity of the 12 parameters for different scenarios. And we found that the general patterns of the parameter sensitivities were consistent, however, for some parameters a significantly larger span of the sensitivities was observed, especially for the higher slope and in subarctic climatic scenarios.
Nicholas Jarvis, Jannis Groh, Elisabet Lewan, Katharina H. E. Meurer, Walter Durka, Cornelia Baessler, Thomas Pütz, Elvin Rufullayev, and Harry Vereecken
Hydrol. Earth Syst. Sci., 26, 2277–2299, https://doi.org/10.5194/hess-26-2277-2022, https://doi.org/10.5194/hess-26-2277-2022, 2022
Short summary
Short summary
We apply an eco-hydrological model to data on soil water balance and grassland growth obtained at two sites with contrasting climates. Our results show that the grassland in the drier climate had adapted by developing deeper roots, which maintained water supply to the plants in the face of severe drought. Our study emphasizes the importance of considering such plastic responses of plant traits to environmental stress in the modelling of soil water balance and plant growth under climate change.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
Short summary
Short summary
Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Lukas Strebel, Heye R. Bogena, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 15, 395–411, https://doi.org/10.5194/gmd-15-395-2022, https://doi.org/10.5194/gmd-15-395-2022, 2022
Short summary
Short summary
We present the technical coupling between a land surface model (CLM5) and the Parallel Data Assimilation Framework (PDAF). This coupling enables measurement data to update simulated model states and parameters in a statistically optimal way. We demonstrate the viability of the model framework using an application in a forested catchment where the inclusion of soil water measurements significantly improved the simulation quality.
Veronika Forstner, Jannis Groh, Matevz Vremec, Markus Herndl, Harry Vereecken, Horst H. Gerke, Steffen Birk, and Thomas Pütz
Hydrol. Earth Syst. Sci., 25, 6087–6106, https://doi.org/10.5194/hess-25-6087-2021, https://doi.org/10.5194/hess-25-6087-2021, 2021
Short summary
Short summary
Lysimeter-based manipulative and observational experiments were used to identify responses of water fluxes and aboveground biomass (AGB) to climatic change in permanent grassland. Under energy-limited conditions, elevated temperature actual evapotranspiration (ETa) increased, while seepage, dew, and AGB decreased. Elevated CO2 mitigated the effect on ETa. Under water limitation, elevated temperature resulted in reduced ETa, and AGB was negatively correlated with an increasing aridity.
Yafei Huang, Jonas Weis, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-569, https://doi.org/10.5194/hess-2021-569, 2021
Manuscript not accepted for further review
Short summary
Short summary
Trends in agricultural droughts cannot be easily deduced from measurements. Here trends in agricultural droughts over 31 German and Dutch sites were calculated with model simulations and long-term observed meteorological data as input. We found that agricultural droughts are increasing although precipitation hardly decreases. The increase is driven by increase in evapotranspiration. The year 2018 was for half of the sites the year with the most extreme agricultural drought in the last 55 years.
Mengna Li, Yijian Zeng, Maciek W. Lubczynski, Jean Roy, Lianyu Yu, Hui Qian, Zhenyu Li, Jie Chen, Lei Han, Han Zheng, Tom Veldkamp, Jeroen M. Schoorl, Harrie-Jan Hendricks Franssen, Kai Hou, Qiying Zhang, Panpan Xu, Fan Li, Kai Lu, Yulin Li, and Zhongbo Su
Earth Syst. Sci. Data, 13, 4727–4757, https://doi.org/10.5194/essd-13-4727-2021, https://doi.org/10.5194/essd-13-4727-2021, 2021
Short summary
Short summary
The Tibetan Plateau is the source of most of Asia's major rivers and has been called the Asian Water Tower. Due to its remoteness and the harsh environment, there is a lack of field survey data to investigate its hydrogeology. Borehole core lithology analysis, an altitude survey, soil thickness measurement, hydrogeological surveys, and hydrogeophysical surveys were conducted in the Maqu catchment within the Yellow River source region to improve a full–picture understanding of the water cycle.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
Short summary
Short summary
In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
Jan Vanderborght, Valentin Couvreur, Felicien Meunier, Andrea Schnepf, Harry Vereecken, Martin Bouda, and Mathieu Javaux
Hydrol. Earth Syst. Sci., 25, 4835–4860, https://doi.org/10.5194/hess-25-4835-2021, https://doi.org/10.5194/hess-25-4835-2021, 2021
Short summary
Short summary
Root water uptake is an important process in the terrestrial water cycle. How this process depends on soil water content, root distributions, and root properties is a soil–root hydraulic problem. We compare different approaches to implementing root hydraulics in macroscopic soil water flow and land surface models.
Youri Rothfuss, Maria Quade, Nicolas Brüggemann, Alexander Graf, Harry Vereecken, and Maren Dubbert
Biogeosciences, 18, 3701–3732, https://doi.org/10.5194/bg-18-3701-2021, https://doi.org/10.5194/bg-18-3701-2021, 2021
Short summary
Short summary
The partitioning of evapotranspiration into evaporation from soil and transpiration from plants is crucial for a wide range of parties, from farmers to policymakers. In this work, we focus on a particular partitioning method, based on the stable isotopic analysis of water. In particular, we aim at highlighting the challenges that this method is currently facing and, in light of recent methodological developments, propose ways forward for the isotopic-partitioning community.
Cosimo Brogi, Johan A. Huisman, Lutz Weihermüller, Michael Herbst, and Harry Vereecken
SOIL, 7, 125–143, https://doi.org/10.5194/soil-7-125-2021, https://doi.org/10.5194/soil-7-125-2021, 2021
Short summary
Short summary
There is a need in agriculture for detailed soil maps that carry quantitative information. Geophysics-based soil maps have the potential to deliver such products, but their added value has not been fully investigated yet. In this study, we compare the use of a geophysics-based soil map with the use of two commonly available maps as input for crop growth simulations. The geophysics-based product results in better simulations, with improvements that depend on precipitation, soil, and crop type.
Theresa Boas, Heye Bogena, Thomas Grünwald, Bernard Heinesch, Dongryeol Ryu, Marius Schmidt, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, https://doi.org/10.5194/gmd-14-573-2021, 2021
Short summary
Short summary
In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Jannis Groh, Jan Vanderborght, Thomas Pütz, Hans-Jörg Vogel, Ralf Gründling, Holger Rupp, Mehdi Rahmati, Michael Sommer, Harry Vereecken, and Horst H. Gerke
Hydrol. Earth Syst. Sci., 24, 1211–1225, https://doi.org/10.5194/hess-24-1211-2020, https://doi.org/10.5194/hess-24-1211-2020, 2020
Michael Paul Stockinger, Heye Reemt Bogena, Andreas Lücke, Christine Stumpp, and Harry Vereecken
Hydrol. Earth Syst. Sci., 23, 4333–4347, https://doi.org/10.5194/hess-23-4333-2019, https://doi.org/10.5194/hess-23-4333-2019, 2019
Short summary
Short summary
Precipitation moves through the soil to become stream water. The fraction of precipitation that becomes stream water after 3 months (Fyw) can be calculated with the stable isotopes of water. Previously, this was done for all the isotope data available, e.g., for several years. We used 1 year of data to calculate Fyw and moved this calculation time window over the time series. Results highlight that Fyw varies in time. Comparison studies of different regions should take this into account.
Elias C. Massoud, Chonggang Xu, Rosie A. Fisher, Ryan G. Knox, Anthony P. Walker, Shawn P. Serbin, Bradley O. Christoffersen, Jennifer A. Holm, Lara M. Kueppers, Daniel M. Ricciuto, Liang Wei, Daniel J. Johnson, Jeffrey Q. Chambers, Charlie D. Koven, Nate G. McDowell, and Jasper A. Vrugt
Geosci. Model Dev., 12, 4133–4164, https://doi.org/10.5194/gmd-12-4133-2019, https://doi.org/10.5194/gmd-12-4133-2019, 2019
Short summary
Short summary
We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic vegetation model within a land surface model. By running the model 5000 times with changing input parameter values, we found that (1) the photosynthetic capacity controls carbon fluxes, (2) the allometry is important for tree growth, and (3) the targeted carbon storage is important for tree survival. These results can provide guidance on improved model parameterization for a better fit to observations.
Anne Klosterhalfen, Alexander Graf, Nicolas Brüggemann, Clemens Drüe, Odilia Esser, María P. González-Dugo, Günther Heinemann, Cor M. J. Jacobs, Matthias Mauder, Arnold F. Moene, Patrizia Ney, Thomas Pütz, Corinna Rebmann, Mario Ramos Rodríguez, Todd M. Scanlon, Marius Schmidt, Rainer Steinbrecher, Christoph K. Thomas, Veronika Valler, Matthias J. Zeeman, and Harry Vereecken
Biogeosciences, 16, 1111–1132, https://doi.org/10.5194/bg-16-1111-2019, https://doi.org/10.5194/bg-16-1111-2019, 2019
Short summary
Short summary
To obtain magnitudes of flux components of H2O and CO2 (e.g., transpiration, soil respiration), we applied source partitioning approaches after Scanlon and Kustas (2010) and after Thomas et al. (2008) to high-frequency eddy covariance measurements of 12 study sites covering various ecosystems (croplands, grasslands, and forests) in different climatic regions. We analyzed the interrelations among turbulence, site characteristics, and the performance of both partitioning methods.
Bibi S. Naz, Wolfgang Kurtz, Carsten Montzka, Wendy Sharples, Klaus Goergen, Jessica Keune, Huilin Gao, Anne Springer, Harrie-Jan Hendricks Franssen, and Stefan Kollet
Hydrol. Earth Syst. Sci., 23, 277–301, https://doi.org/10.5194/hess-23-277-2019, https://doi.org/10.5194/hess-23-277-2019, 2019
Short summary
Short summary
This study investigates the value of assimilating coarse-resolution remotely sensed soil moisture data into high-resolution land surface models for improving soil moisture and runoff modeling. The soil moisture estimates in this study, with complete spatio-temporal coverage and improved spatial resolution from the assimilation, offer a new reanalysis product for the monitoring of surface soil water content and other hydrological fluxes at 3 km resolution over Europe.
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Proc. IAHS, 380, 3–8, https://doi.org/10.5194/piahs-380-3-2018, https://doi.org/10.5194/piahs-380-3-2018, 2018
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Hydrol. Earth Syst. Sci., 22, 5735–5739, https://doi.org/10.5194/hess-22-5735-2018, https://doi.org/10.5194/hess-22-5735-2018, 2018
Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Béatrice Béchet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G. Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido-Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan-Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken
Earth Syst. Sci. Data, 10, 1237–1263, https://doi.org/10.5194/essd-10-1237-2018, https://doi.org/10.5194/essd-10-1237-2018, 2018
Short summary
Short summary
This paper presents and analyzes a global database of soil infiltration data, the SWIG database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists or they were digitized from published articles. We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models.
Roland Baatz, Pamela L. Sullivan, Li Li, Samantha R. Weintraub, Henry W. Loescher, Michael Mirtl, Peter M. Groffman, Diana H. Wall, Michael Young, Tim White, Hang Wen, Steffen Zacharias, Ingolf Kühn, Jianwu Tang, Jérôme Gaillardet, Isabelle Braud, Alejandro N. Flores, Praveen Kumar, Henry Lin, Teamrat Ghezzehei, Julia Jones, Henry L. Gholz, Harry Vereecken, and Kris Van Looy
Earth Syst. Dynam., 9, 593–609, https://doi.org/10.5194/esd-9-593-2018, https://doi.org/10.5194/esd-9-593-2018, 2018
Short summary
Short summary
Focusing on the usage of integrated models and in situ Earth observatory networks, three challenges are identified to advance understanding of ESD, in particular to strengthen links between biotic and abiotic, and above- and below-ground processes. We propose developing a model platform for interdisciplinary usage, to formalize current network infrastructure based on complementarities and operational synergies, and to extend the reanalysis concept to the ecosystem and critical zone.
Gaochao Cai, Jan Vanderborght, Matthias Langensiepen, Andrea Schnepf, Hubert Hüging, and Harry Vereecken
Hydrol. Earth Syst. Sci., 22, 2449–2470, https://doi.org/10.5194/hess-22-2449-2018, https://doi.org/10.5194/hess-22-2449-2018, 2018
Short summary
Short summary
Different crop growths had consequences for the parameterization of root water uptake models. The root hydraulic parameters of the Couvreur model but not the water stress parameters of the Feddes–Jarvis model could be constrained by the field data measured from rhizotron facilities. The simulated differences in transpiration from the two soils and the different water treatments could be confirmed by sap flow measurements. The Couvreur model predicted the ratios of transpiration fluxes better.
Hanna Post, Harrie-Jan Hendricks Franssen, Xujun Han, Roland Baatz, Carsten Montzka, Marius Schmidt, and Harry Vereecken
Biogeosciences, 15, 187–208, https://doi.org/10.5194/bg-15-187-2018, https://doi.org/10.5194/bg-15-187-2018, 2018
Short summary
Short summary
Estimated values of selected key CLM4.5-BGC parameters obtained with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) strongly altered catchment-scale NEE predictions in comparison to global default parameter values. The effect of perturbed meteorological input data on the uncertainty of the predicted carbon fluxes was notably higher for C3-grass and C3-crop than for coniferous and deciduous forest. A future distinction of different crop types including management is considered essential.
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
Short summary
Short summary
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.
Carsten Montzka, Michael Herbst, Lutz Weihermüller, Anne Verhoef, and Harry Vereecken
Earth Syst. Sci. Data, 9, 529–543, https://doi.org/10.5194/essd-9-529-2017, https://doi.org/10.5194/essd-9-529-2017, 2017
Short summary
Short summary
Global climate models require adequate parameterization of soil hydraulic properties, but typical resampling to the model grid introduces uncertainties. Here we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the problems. It preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters that enables modellers to perturb hydraulic parameters for model ensemble generation.
Roland Baatz, Harrie-Jan Hendricks Franssen, Xujun Han, Tim Hoar, Heye Reemt Bogena, and Harry Vereecken
Hydrol. Earth Syst. Sci., 21, 2509–2530, https://doi.org/10.5194/hess-21-2509-2017, https://doi.org/10.5194/hess-21-2509-2017, 2017
Short summary
Short summary
Soil moisture is a major variable that affects regional climate, weather and hydrologic processes on the Earth's surface. In this study, real-world data of a network of cosmic-ray sensors were assimilated into a regional land surface model to improve model states and soil hydraulic parameters. The results show the potential of these networks for improving model states and parameters. It is suggested to widen the number of observed variables and to increase the number of estimated parameters.
Xiaoqian Jiang, Roland Bol, Barbara J. Cade-Menun, Volker Nischwitz, Sabine Willbold, Sara L. Bauke, Harry Vereecken, Wulf Amelung, and Erwin Klumpp
Biogeosciences, 14, 1153–1164, https://doi.org/10.5194/bg-14-1153-2017, https://doi.org/10.5194/bg-14-1153-2017, 2017
Short summary
Short summary
It is the first study to distinguish the species of nano-sized (d=1−20 nm), small-sized (d=20−450 nm) colloidal P, and dissolved P (d<1 nm) of hydromorphic surface grassland soils from Cambisol, Stagnic Cambisol to Stagnosol using FFF and 31P-NMR. Evidence of nano-sized associations of OC–Fe(Al)–PO43/pyrophosphate in Stagnosol. Stagnic properties affect P speciation and availability by releasing dissolved inorganic and ester-bound P forms as well as nano-sized organic matter–Fe/Al–P colloids.
Bernd Schalge, Jehan Rihani, Gabriele Baroni, Daniel Erdal, Gernot Geppert, Vincent Haefliger, Barbara Haese, Pablo Saavedra, Insa Neuweiler, Harrie-Jan Hendricks Franssen, Felix Ament, Sabine Attinger, Olaf A. Cirpka, Stefan Kollet, Harald Kunstmann, Harry Vereecken, and Clemens Simmer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-557, https://doi.org/10.5194/hess-2016-557, 2016
Manuscript not accepted for further review
Short summary
Short summary
In this work we show how we used a coupled atmosphere-land surface-subsurface model at highest possible resolution to create a testbed for data assimilation. The model was able to capture all important processes and interactions between the compartments as well as showing realistic statistical behavior. This proves that using a model as a virtual truth is possible and it will enable us to develop data assimilation methods where states and parameters are updated across compartment.
Wei Qu, Heye R. Bogena, Johan A. Huisman, Marius Schmidt, Ralf Kunkel, Ansgar Weuthen, Henning Schiedung, Bernd Schilling, Jürgen Sorg, and Harry Vereecken
Earth Syst. Sci. Data, 8, 517–529, https://doi.org/10.5194/essd-8-517-2016, https://doi.org/10.5194/essd-8-517-2016, 2016
Short summary
Short summary
The Rollesbroich catchment is a hydrological observatory of the TERENO (Terrestrial Environmental Observatories) initiative. Hydrometeorological data and spatiotemporal variations in soil water content are measured at high temporal resolution and can be used for many purposes, e.g. validation of remote sensing retrievals, improving hydrological understanding, optimizing data assimilation and inverse modelling techniques. The data set is freely available online (http://www.tereno.net).
Wolfgang Kurtz, Guowei He, Stefan J. Kollet, Reed M. Maxwell, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 9, 1341–1360, https://doi.org/10.5194/gmd-9-1341-2016, https://doi.org/10.5194/gmd-9-1341-2016, 2016
Short summary
Short summary
This paper describes the development of a modular data assimilation (DA) system for the integrated Earth system model TerrSysMP with the help of the PDAF data assimilation library.
Currently, pressure and soil moisture data can be used to update model states and parameters in the subsurface compartment of TerrSysMP.
Results from an idealized twin experiment show that the developed DA system provides a good parallel performance and is also applicable for high-resolution modelling problems.
A. A. Ali, C. Xu, A. Rogers, R. A. Fisher, S. D. Wullschleger, E. C. Massoud, J. A. Vrugt, J. D. Muss, N. G. McDowell, J. B. Fisher, P. B. Reich, and C. J. Wilson
Geosci. Model Dev., 9, 587–606, https://doi.org/10.5194/gmd-9-587-2016, https://doi.org/10.5194/gmd-9-587-2016, 2016
Short summary
Short summary
We have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA V1.0) to predict the photosynthetic capacities at the global scale based on the optimization of key leaf-level metabolic processes. LUNA model predicts that future climatic changes would mostly affect plant photosynthetic capabilities in high-latitude regions and that Earth system models using fixed photosynthetic capabilities are likely to substantially overestimate future global photosynthesis.
X. Jiang, R. Bol, S. Willbold, H. Vereecken, and E. Klumpp
Biogeosciences, 12, 6443–6452, https://doi.org/10.5194/bg-12-6443-2015, https://doi.org/10.5194/bg-12-6443-2015, 2015
Short summary
Short summary
Overall P content increased with decreasing size of soil aggregate-sized fractions. The relative distribution and speciation of varying P forms were independent of particle size. The majority of alkaline extractable P was in the amorphous Fe/Al oxide fraction, most of which was orthophosphate. Significant amounts of monoester P were also bound to these oxides. Residual P contained similar amounts of P occluded in amorphous and crystalline Fe oxides. This P may be released by FeO dissolution.
Y. Rothfuss, S. Merz, J. Vanderborght, N. Hermes, A. Weuthen, A. Pohlmeier, H. Vereecken, and N. Brüggemann
Hydrol. Earth Syst. Sci., 19, 4067–4080, https://doi.org/10.5194/hess-19-4067-2015, https://doi.org/10.5194/hess-19-4067-2015, 2015
Short summary
Short summary
Profiles of soil water stable isotopes were followed non-destructively and with high precision for a period of 290 days in the laboratory
Rewatering at the end of the experiment led to instantaneous resetting of the isotope profiles, which could be closely followed with the new method
The evaporation depth dynamics was determined from isotope gradients calculation
Uncertainty associated with the determination of isotope kinetic fractionation where highlighted from inverse modeling.
X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-7395-2015, https://doi.org/10.5194/gmdd-8-7395-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
DasPy is a ready to use open source parallel multivariate land data assimilation framework with joint state and parameter estimation using Local Ensemble Transform Kalman Filter. The Community Land Model (4.5) was integrated as model operator. The Community Microwave Emission Modelling platform, COsmic-ray Soil Moisture Interaction Code and the Two-Source Formulation were integrated as observation operators for the multivariate assimilation of soil moisture and soil temperature, respectively.
S. Gebler, H.-J. Hendricks Franssen, T. Pütz, H. Post, M. Schmidt, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 2145–2161, https://doi.org/10.5194/hess-19-2145-2015, https://doi.org/10.5194/hess-19-2145-2015, 2015
H. Post, H. J. Hendricks Franssen, A. Graf, M. Schmidt, and H. Vereecken
Biogeosciences, 12, 1205–1221, https://doi.org/10.5194/bg-12-1205-2015, https://doi.org/10.5194/bg-12-1205-2015, 2015
Short summary
Short summary
This study introduces an extension of the classical two-tower approach for uncertainty estimation of measured net CO2 fluxes (NEE). Because land surface properties cannot be assumed identical at two eddy covariance towers, a correction for systematic flux differences is proposed to be added to the classical weather filter. With this extension, the overestimation of NEE uncertainty due to systematic flux differences (which are assumed to increase with tower distance) can considerably be reduced.
B. Scharnagl, S. C. Iden, W. Durner, H. Vereecken, and M. Herbst
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-2155-2015, https://doi.org/10.5194/hessd-12-2155-2015, 2015
Preprint withdrawn
X. Han, H.-J. H. Franssen, R. Rosolem, R. Jin, X. Li, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 615–629, https://doi.org/10.5194/hess-19-615-2015, https://doi.org/10.5194/hess-19-615-2015, 2015
Short summary
Short summary
This paper presents the joint assimilation of cosmic-ray neutron counts and land surface temperature with parameter estimation of leaf area index at an irrigated corn field. The results show that the data assimilation can reduce the systematic input errors due to the lack of irrigation data. The estimations of soil moisture, evapotranspiration and leaf area index can be improved in the joint assimilation framework.
M. Sadegh and J. A. Vrugt
Hydrol. Earth Syst. Sci., 17, 4831–4850, https://doi.org/10.5194/hess-17-4831-2013, https://doi.org/10.5194/hess-17-4831-2013, 2013
W. Kurtz, H.-J. Hendricks Franssen, P. Brunner, and H. Vereecken
Hydrol. Earth Syst. Sci., 17, 3795–3813, https://doi.org/10.5194/hess-17-3795-2013, https://doi.org/10.5194/hess-17-3795-2013, 2013
V. R. N. Pauwels, G. J. M. De Lannoy, H.-J. Hendricks Franssen, and H. Vereecken
Hydrol. Earth Syst. Sci., 17, 3499–3521, https://doi.org/10.5194/hess-17-3499-2013, https://doi.org/10.5194/hess-17-3499-2013, 2013
Related subject area
Subject: Vadose Zone Hydrology | Techniques and Approaches: Stochastic approaches
Detecting hydrological connectivity using causal inference from time series: synthetic and real karstic case studies
Covariance resampling for particle filter – state and parameter estimation for soil hydrology
Inferring soil salinity in a drip irrigation system from multi-configuration EMI measurements using adaptive Markov chain Monte Carlo
Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction
Kalman filters for assimilating near-surface observations into the Richards equation – Part 1: Retrieving state profiles with linear and nonlinear numerical schemes
Kalman filters for assimilating near-surface observations into the Richards equation – Part 2: A dual filter approach for simultaneous retrieval of states and parameters
Kalman filters for assimilating near-surface observations into the Richards equation – Part 3: Retrieving states and parameters from laboratory evaporation experiments
State-space approach to evaluate spatial variability of field measured soil water status along a line transect in a volcanic-vesuvian soil
Damien Delforge, Olivier de Viron, Marnik Vanclooster, Michel Van Camp, and Arnaud Watlet
Hydrol. Earth Syst. Sci., 26, 2181–2199, https://doi.org/10.5194/hess-26-2181-2022, https://doi.org/10.5194/hess-26-2181-2022, 2022
Short summary
Short summary
Causal inference methods (CIMs) aim at identifying causal links from temporal dependencies found in time-series data. Using both synthetic data and real-time series from a karst system, we study and discuss the potential of four CIMs to reveal hydrological connections between variables in hydrological systems. Despite the ever-present risk of spurious hydrological connections, our results highlight that the nonlinear and multivariate CIM has a substantially lower false-positive rate.
Daniel Berg, Hannes H. Bauser, and Kurt Roth
Hydrol. Earth Syst. Sci., 23, 1163–1178, https://doi.org/10.5194/hess-23-1163-2019, https://doi.org/10.5194/hess-23-1163-2019, 2019
Short summary
Short summary
Particle filters are becoming popular for state and parameter estimations in hydrology. The renewal of the ensemble (resampling) is crucial in preventing filter degeneration. We introduce a resampling method that uses the weighted covariance of the ensemble, which contains information between observed and unobserved dimensions, to generate new ensemble members. This allows us to estimate the state and parameters for a rough initial guess in a synthetic hydrological case with just 100 particles.
Khan Zaib Jadoon, Muhammad Umer Altaf, Matthew Francis McCabe, Ibrahim Hoteit, Nisar Muhammad, Davood Moghadas, and Lutz Weihermüller
Hydrol. Earth Syst. Sci., 21, 5375–5383, https://doi.org/10.5194/hess-21-5375-2017, https://doi.org/10.5194/hess-21-5375-2017, 2017
Short summary
Short summary
In this study electromagnetic induction (EMI) measurements were used to estimate soil salinity in an agriculture field irrigated with a drip irrigation system. Electromagnetic model parameters and uncertainty were estimated using adaptive Bayesian Markov chain Monte Carlo (MCMC). Application of the MCMC-based inversion to the synthetic and field measurements demonstrates that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil.
Roland Baatz, Harrie-Jan Hendricks Franssen, Xujun Han, Tim Hoar, Heye Reemt Bogena, and Harry Vereecken
Hydrol. Earth Syst. Sci., 21, 2509–2530, https://doi.org/10.5194/hess-21-2509-2017, https://doi.org/10.5194/hess-21-2509-2017, 2017
Short summary
Short summary
Soil moisture is a major variable that affects regional climate, weather and hydrologic processes on the Earth's surface. In this study, real-world data of a network of cosmic-ray sensors were assimilated into a regional land surface model to improve model states and soil hydraulic parameters. The results show the potential of these networks for improving model states and parameters. It is suggested to widen the number of observed variables and to increase the number of estimated parameters.
G. B. Chirico, H. Medina, and N. Romano
Hydrol. Earth Syst. Sci., 18, 2503–2520, https://doi.org/10.5194/hess-18-2503-2014, https://doi.org/10.5194/hess-18-2503-2014, 2014
H. Medina, N. Romano, and G. B. Chirico
Hydrol. Earth Syst. Sci., 18, 2521–2541, https://doi.org/10.5194/hess-18-2521-2014, https://doi.org/10.5194/hess-18-2521-2014, 2014
H. Medina, N. Romano, and G. B. Chirico
Hydrol. Earth Syst. Sci., 18, 2543–2557, https://doi.org/10.5194/hess-18-2543-2014, https://doi.org/10.5194/hess-18-2543-2014, 2014
A. Comegna, A. Coppola, V. Comegna, G. Severino, A. Sommella, and C. D. Vitale
Hydrol. Earth Syst. Sci., 14, 2455–2463, https://doi.org/10.5194/hess-14-2455-2010, https://doi.org/10.5194/hess-14-2455-2010, 2010
Cited articles
Anderson, J. L.: An adaptive covariance inflation error correction algorithm for ensemble filters, Tellus A, 59, 210–224, https://doi.org/10.1111/j.1600-0870.2006.00216.x, 2007.
Bailey, R. T. and Baù, D.: Estimating geostatistical parameters and spatially-variable hydraulic conductivity within a catchment system using an ensemble smoother, Hydrol. Earth Syst. Sci., 16, 287–304, https://doi.org/10.5194/hess-16-287-2012, 2012.
Bateni, S. M. and Entekhabi, D.: Surface heat flux estimation with the ensemble Kalman smoother: Joint estimation of state and parameters, Water Resour. Res., 48, W08521, https://doi.org/10.1029/2011wr011542, 2012.
Bertoldi, G.: The water and energy balance at basin scale: a distributed modeling approach, University of Trento, Monograph of the School of Doctoral Studies in Environmental Engineering, 202 pp., ISBN 88-8443-069-0, 2004.
Blondin, C.: Parameterization of land-surface processes in numerical weather prediction, in Land Surface Evaporation: Measurements and Parameterization, Springer-Verlag, New York, 31–54, 1991.
Bogena, H. R., Herbst, M., Huisman, J. A., Rosenbaum, U., Weuthen, A., and Vereecken, H.: Potential of Wireless Sensor Networks for Measuring Soil Water Content Variability, Vadose Zone J., 9, 1002–1013, https://doi.org/10.2136/vzj2009.0173, 2010.
Bonan, G. B.: Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests, Science, 320, 1444–1449, https://doi.org/10.1126/science.1155121, 2008.
Brooks, R. H. and Corey, A. T.: Hydraulic Properties of Porous Media, Colorado State University, Clorado, 1964.
Burgers, G., van Leeuwen, P. J., and Evensen, G.: Analysis scheme in the ensemble Kalman filter, Mon. Weather Rev., 126, 1719–1724, https://doi.org/10.1175/1520-0493(1998)126<1719:asitek>2.0.co;2, 1998.
Carpenter, J., Clifford, P., and Fearnhead, P.: Improved particle filter for nonlinear problems, Radar, Sonar and Navigation, IEE P., 146, 2–7, https://doi.org/10.1049/ip-rsn:19990255, 1999.
Chen, Y. and Zhang, D.: Data assimilation for transient flow in geologic formations via ensemble Kalman filter, Adv. Water Resour., 29, 1107–1122, 2006.
Chen, W., Huang, C., Shen, H., and Li, X.: Comparison of ensemble-based state and parameter estimation methods for soil moisture data assimilation, Adv. Water Resour., 86, 425–438, 2015.
Cherkauer, K. A. and Lettenmaier, D. P.: Hydrologic effects of frozen soils in the upper Mississippi River basin, J. Geophys. Res.-Atmos., 104, 19599–19610, https://doi.org/10.1029/1999jd900337, 1999.
Clapp, R. B. and Hornberger, G. M.: Empirical equations for some soil hydraulic properties, Water Resour. Res., 14, 601–604, https://doi.org/10.1029/WR014i004p00601, 1978.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils, Water Resour. Res., 20, 682–690, https://doi.org/10.1029/WR020i006p00682, 1984.
DeChant, C. M. and Moradkhani, H.: Examining the effectiveness and robustness of sequential data assimilation methods for quantification of uncertainty in hydrologic forecasting, Water Resour. Res., 48, W04518, https://doi.org/10.1029/2011wr011011, 2012.
Demaria, E. M., Nijssen, B., and Wagener, T.: Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model, J. Geophys. Res.-Atmos., 112, D11113, https://doi.org/10.1029/2006jd007534, 2007.
Dickinson, R. E.: Modeling evapotranspiration for three-dimentional global climate models, in: Climate Processes and Climate Sensitivity, Monogr. Ser., edited by: Hansen, J. E. and Takahashi, T., Washington, D.C., 58–72, 1984.
Douc, R., Olivier, C., and Eric, M.: Comparison of resampling schemes for particle filtering, Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 64–69, https://doi.org/10.1109/ISPA.2005.195385, 2005.
Ducoudre, N. I., Laval, K., and Perrier, A.: SECHIBA, a new set of parameterizations of the hydrologic exchanges at the land-atmosphere interface within the LMD atmospheric general circulation model, J. Climate, 6, 248–273, 1993.
Dumedah, G. and Coulibaly, P.: Evaluating forecasting performance for data assimilation methods: The ensemble Kalman filter, the particle filter, and the evolutionary-based assimilation, Adv. Water Resour., 60, 47–63, https://doi.org/10.1016/j.advwatres.2013.07.007, 2013.
Erdal, D., Neuweiler, I., and Wollschläger, U.: Using a bias aware EnKF to account for unresolved structure in an unsaturated zone model, Water Resour. Res., 50, 132–147, https://doi.org/10.1002/2012WR013443, 2014.
Evensen, G.: Sequential data assimilation with a nonlinear quasi-geostrophic model usin Monte-Carlo methods to forecast error statistics, J. Geophys. Res.-Oceans, 99, 10143–10162, https://doi.org/10.1029/94jc00572, 1994.
Franchini, M. and Pacciani, M.: Comparative-analysis of several conceptual rainfall runoff models, J. Hydrol., 122, 161–219, https://doi.org/10.1016/0022-1694(91)90178-k, 1991.
Franssen, H. J. H. and Kinzelbach, W.: Real-time groundwater flow modeling with the Ensemble Kalman Filter: Joint estimation of states and parameters and the filter inbreeding problem, Water Resour. Res., 44, W09408, https://doi.org/10.1029/2007wr006505, 2008.
Gao, H., Tang, Q., Shi, X., Zhu, C., Bohn, T. J., Su, F., Sheffield, J., Pan, M., Lettenmaier, D. P., and Wood, E. F.: Water Budget Record from Variable Infiltration Capacity (VIC) Model, Algorithm Theoretical Basis Document for Terrestrial Water Cycle Data Records, 2010.
Gharamti, E. M., Hoteit, I., and Valstar, J.: Dual states estimation of a subsurface flow-transport coupled model using ensemble Kalman filtering, Adv. Water Resour., 60, 75–88, https://doi.org/10.1016/j.advwatres.2013.07.011, 2013.
Gordon, N. J., Salmond, D. J., and Smith, A. F. M.: Novel-approach to nonlinear non-Gaussian bayesian state estimation, IEE Proc.-F, 140, 107–113, 1993.
Han, X., Franssen, H. J. H., Montzka, C., and Vereecken, H.: soil moisture and soil properties estimation in the community Land Model with synthetic brightness temperature, Water Resour. Res., 50, 6081–6105, https://doi.org/10.1002/2013WR014586, 2014.
Hodgkinson, R. A., Pepper, T. J., and Wilson, D. W.: Evaluation of tipping bucket rain gauge performance and data quality, Sci. Rep. W6-048/SR, Environment Agency, Bristol, UK, 2004.
Hübner, C., Cardell-Oliver, R., Becker, R., Spohrer, K., Jotter, K., and Wagenknecht, T.: Wireless soil moisture sensor networks for environmental monitoring and vineyard irrigation, 8th International Conference on Electromagnetic Wave Interaction with Water and Moist Substances (ISEMA 2009), Helsinki, Finland, Vol. 408415, 2009.
Kalman, R. E.: A New Approach to Linear Filtering and Prediction Problems J. Basic Eng., 82, 35–45, 1960.
Kurtz, W., Hendricks Franssen, H.-J., and Vereecken, H.: Identification of time-variant river bed properties with the ensemble Kalman filter, Water Resour. Res., 48, W10534, https://doi.org/10.1029/2011WR011743, 2012.
Kurtz, W., Hendricks Franssen, H.-J., Kaiser, H. P., and Vereecken, H.: Joint assimilation of piezometric heads and groundwater temperatures for improved modelling of river-aquifer interactions, Water Resour. Res., 50, 1665–1688, https://doi.org/10.1002/2013wr014823, 2014.
Lawrence, D. M. and Slater, A. G.: Incorporating organic soil into a global climate model, Clim. Dynam., 30, 145–160, https://doi.org/10.1007/s00382-007-0278-1, 2008.
Lee, J. H.: Spatial-Scale prediction of the SVAT soil hydraulic variables characterizing stratified soils on the Tibetan Plateau from an EnKF analysis of SAR soil moisture, Vadose Zone J., 13, https://doi.org/10.2136/vzj2014.06.0060, 2014.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J. A.: simple hyhrologically based model of land-surface water and energy fluxes for general-circulation models, J. Geophys. Res.-Atmos., 99, 14415–14428, https://doi.org/10.1029/94jd00483, 1994.
Liang, X., Wood, E. F., and Lettenmaier, D. P.: Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification, Global Planet. Change, 13, 195–206, https://doi.org/10.1016/0921-8181(95)00046-1, 1996.
Liang, X., Xie, Z. H., and Huang, M. Y.: A new parameterization for surface and groundwater interactions and its impact on water budgets with the variable infiltration capacity (VIC) land surface model, J. Geophys. Res.-Atmos., 108, 8613, https://doi.org/10.1029/2002jd003090, 2003.
Liu, J. S. and Chen, R.: Sequential Monte Carlo methods for dynamic systems, J. Am. Stat. Assoc., 93, 1032–1044, https://doi.org/10.2307/2669847, 1998.
Liu, Y. and Gupta, H. V.: Uncertainty in hydrologic modeling: Toward an integrated data assimilation framework, Water Resour. Res., 43, W07401, https://doi.org/10.1029/2006wr005756, 2007.
Lue, H., Yu, Z., Zhu, Y., Drake, S., Hao, Z., and Sudicky, E. A.: Dual state-parameter estimation of root zone soil moisture by optimal parameter estimation and extended Kalman filter data assimilation, Adv. Water Resour., 34, 395–406, https://doi.org/10.1016/j.advwatres.2010.12.005, 2011.
Milly, P. C. D. and Shmakin A. B.: Global modeling of land water and energy balances. Part II: Land-characteristic contributions to spatial variability, J. Hydrometeorol., 3, 296–307, 2002.
Monteith, J. L.: Gas exchange in plant communities, in: Environmental Control of Plant Growth, edited by: Evans, L. T., Academic Press, New York, 95–112, 1963.
Montzka, C., Moradkhani, H., Weihermueller, L., Franssen, H. J. H., Canty, M., and Vereecken, H.: Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter, J. Hydrol., 399, 410–421, https://doi.org/10.1016/j.jhydrol.2011.01.020, 2011.
Montzka, C., Grant, J. P., Moradkhani, H., Franssen, H. J. H., Weihermüller, L., Drusch, M., and Vereecken, H.: Estimation of radiative transfer parameters from L-band passive microwave brightness temperatures using advanced data assimilation, Vadose Zone J., 12, https://doi.org/10.2136/vzj2012.0040, 2013.
Moradkhani, H., DeChant, C. M., and Sorooshian, S.: Evolution of ensemble data assimilation for uncertainty quantification using the particle filter-Markov chain Monte Carlo method, Water Resour. Res., 48, W12520, https://doi.org/10.1029/2012wr012144, 2012.
Moradkhani, H., Hsu, K. L., Gupta, H., and Sorooshian, S.: Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter, Water Resour. Res., 41, W05012, https://doi.org/10.1029/2004wr003604, 2005a.
Moradkhani, H., Sorooshian, S., Gupta, H. V., and Houser, P. R.: Dual state-parameter estimation of hydrological models using ensemble Kalman filter, Adv. Water Resour., 28, 135–147, https://doi.org/10.1016/j.advwatres.2004.09.002, 2005b.
Niu, G. Y., Yang, Z. L., Dickinson, R. E., and Gulden, L. E.: A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models, J. Geophys. Res.-Atmos., 110, D21106, https://doi.org/10.1029/2005JD006111, 2005.
Niu, G. Y., Yang, Z. L., Dickinson, R. E., Gulden, L. E., and Su, H.: Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data, J. Geophys. Res.-Atmos., 112, D07103, https://doi.org/10.1029/2006jd007522, 2007.
Oleson, K. W., Lawrence, D. M., and Bonan, G. B.: Technical description of version 4.5 of the Community Land Model (CLM), NCAR Technical Note NCAR/TN-503+STR, 422, https://doi.org/10.5065/D6RR1W7M, 2013.
Pasetto, D., Camporese, M., and Putti, M.: Ensemble Kalman filter versus particle filter for a physically-based coupled surface-subsurface model, Adv. Water Resour., 47, 1–13, https://doi.org/10.1016/j.advwatres.2012.06.009, 2012.
Pasetto, D., Niu, G. Y., Pangle, L., Paniconi, C., Putti, M., and Troch, P. A.: Impact of sensor failure on the observability of flow dynamics at the Biosphere 2 LEO hillslopes, Adv. Water Resour., 86, 327–339, https://doi.org/10.1016/j.advwatres.2015.04.014, 2015.
Pauwels, V. R. N., Balenzano, A., Satalino, G., Skriver, H., Verhoest, N. E. C., and Mattia, F.: Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach, IEEE T. Geosci. Remote, 47, 455–467, https://doi.org/10.1109/TGRS.2008.2007849, 2009.
Plaza, D. A., De Keyser, R., De Lannoy, G. J. M., Giustarini, L., Matgen, P., and Pauwels, V. R. N.: The importance of parameter resampling for soil moisture data assimilation into hydrologic models using the particle filter, Hydrol. Earth Syst. Sci., 16, 375–390, https://doi.org/10.5194/hess-16-375-2012, 2012.
Qin, J., Liang, S., Yang, K., Kaihotsu, I., Liu, R., and Koike, T.: Simultaneous estimation of both soil moisture and model parameters using particle filtering method through the assimilation of microwave signal, J. Geophys. Res.-Atmos., 114, D15103, https://doi.org/10.1029/2008jd011358, 2009.
Qu, W., Bogena, H. R., Huisman, J. A., Martinez, G., Pachepsky, Y. A., and Vereecken, H.: Effects of soil hydraulic properties on the spatial variability of soil water content: evidence from sensor network data and inverse modeling, Vadose Zone J., 13, https://doi.org/10.2136/vzj2014.07.0099, 2014.
Rasmussen, J., Madsen, H., Jensen, K. H., and Refsgaard, J. C.: Data assimilation in integrated hydrological modeling using ensemble Kalman filtering: evaluating the effect of ensemble size and localization on filter performance, Hydrol. Earth Syst. Sci., 19, 2999–3013, https://doi.org/10.5194/hess-19-2999-2015, 2015.
Romano, N., Palladino, M., and Chirico, G. B.: Parameterization of a bucket model for soil-vegetation-atmosphere modeling under seasonal climatic regimes, Hydrol. Earth Syst. Sci., 15, 3877–3893, https://doi.org/10.5194/hess-15-3877-2011, 2011.
Schaake, J. C., Koren, V. I., Duan, Q. Y., Mitchell, K., and Chen, F.: Simple water balance model for estimating runoff at different spatial and temporal scales, J. Geophys. Res., 101, 7461–7475, https://doi.org/10.1029/95JD02892, 1996.
Schwinger, J., Kollet, S., Hoppe, C., and Elbern, H.: Sensitivity of latent heat fluxes to initial values and parameters of a Land-Surface Model, Vadose Zone J., 9, 984–1001, 2010.
Shi, L., Zhang, Q., Song, X., and Fang, X.: Application of groundwater level data to data assimilation for unsaturated flow, Adv. Water Resour., 26, 404–412, 2015.
Shi, Y., Davis, K. J., Zhang, F., Duffy, C. J., and Yu, X.: Parameter estimation of a physically based land surface hydrologic model using the ensemble Kalman filter: A synthetic experiment, Water Resour. Res., 50, 706–724, https://doi.org/10.1002/2013WR014070, 2014.
Shi, Y., Davis, K. J., Zhang, F. and Duffy, C. J., and Yu, X.: Parameter estimation of a physically-based land surface hydrologic model using an ensemble Kalman filter: A multivariate real-data experiment, Adv. Water Resour., 83, 421–427, https://doi.org/10.1016/j.advwatres.2015.06.009, 2015.
Shuttleworth, W. J.: Putting the “vap” into evaporation, Hydrol. Earth Syst. Sci., 11, 210–244, https://doi.org/10.5194/hess-11-210-2007, 2007.
Song, X., Shi, L., Ye, M., Yang, J., and Michael, N. I.: Numerical Comparison of Iterative Ensemble Kalman Filters for Unsaturated Flow Inverse Modeling, Vadose Zone J., 13, https://doi.org/10.2136/vzj2013.05.0083, 2014.
Tang, Q., Kurtz, W., Brunner, P., Vereecken, H., and Franssen, H. J. H.: Characterisation of river–aquifer exchange fluxes: The role of spatial patterns of riverbed hydraulic conductivities, J. Hydrol., 531, 111–123, https://doi.org/10.1016/j.jhydrol.2015.08.019, 2015.
Troy, T. J., Wood, E. F., and Sheffield, J.: An efficient calibration method for continental-scale land surface modeling, Water Resour. Res., 44, W09411, https://doi.org/10.1029/2007wr006513, 2008.
Vereecken, H., Huisman, J. A., Bogena, H., Vanderborght, J., Vrugt, J. A., and Hopmans, J. W.: On the value of soil moisture measurements in vadose zone hydrology: A review, Water Resour. Res., 44, W00D06, https://doi.org/10.1029/2008wr006829, 2008.
Vereecken, H., Schnepf, A., Hopmans, J. W., Javaux, M., Or, D., Roose, T., Vanderborght, J., Young, M. H., Amelung, W., Aitkenhead, M., Allison, S. D., Assouline, S., Baveye, P., Berli, M., Brüggemann, N., Finke, P., Flury, M., Gaiser, T., Govers, G., Ghezzehei, T., Hallett, P., Hendricks Franssen, H. J., Heppell, J., Horn, R., Huisman, J. A., Jacques, D., Jonard, F., Kollet, S., Lafolie, F., Lamorski, K., Leitner, D., McBratney, A., Minasny, B., Montzka, C., Nowak, W., Pachepsky, Y., Padarian, J., Romano, N., Roth, K., Rothfuss, Y., Rowe, E. C., Schwen, A., Šimúnek, J., Tiktak, A., Van Dam, J., van der Zee, S. E. A. T. M., Vogel, H. J., Vrugt, J. A., Wöhling, T., and Young, I. M.: Modeling Soil Processes: Review, Key Challenges, and New Perspectives, Vadose Zone J., 15, https://doi.org/10.2136/vzj2015.09.0131, 2016.
Vrugt J. A.: Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB Implementation, Environ. Modell. Softw., 75, 273–316, https://doi.org/10.1016/j.envsoft.2015.08.013, 2016.
Vrugt, J. A., Diks, C. G. H., Gupta, H. V., Bouten, W., and Verstraten, J. M.: Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation, Water Resour. Res., 41, W01017, https://doi.org/10.1029/2004WR003059, 2005a.
Vrugt, J. A., Robinson B. A., and Vesselinov V. V.: Improved inverse modeling for flow and transport in subsurface media: Combined parameter and state estimation, Geophys. Res. Lett., 32, L18408, https://doi.org/10.1029/2005GL023940, 2005b.
Vrugt, J. A., Ter Braak, C. J., Clark, M. P., Hyman, J. M., and Robinson, B. A.: Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation, Water Resour. Res., 44, W00B09, https://doi.org/10.1029/2007WR006720, 2008.
Vrugt, J. A., Ter Braak, C. J. F., Diks, C. G. H., Robinson, B. A., Hyman, J. M., and Higdon, D.: Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling, Int. J. Nonl. Sci. Num., 10, 273–290, 2009.
Vrugt, J. A., Ter Braak, C. J. F., Diks, C. G. H., and Schoups, G.: Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications, Adv. Water Resour., 51, 457–478, https://doi.org/10.1016/j.advwatres.2012.04.002, 2013.
Weerts, A. H. and El Serafy, G. Y. H.: Particle filtering and ensemble Kalman filtering for state updating with hydrological conceptual rainfall-runoff models, Water Resour. Res., 42, W09403, https://doi.org/10.1029/2005wr004093, 2006.
Whitaker, J. S. and Hamill T. M.: Evaluating Methods to Account for System Errors in Ensemble Data Assimilation, Mon. Weather Rev., 140, 3078–3089, https://doi.org/10.1175/mwr-d-11-00276.1, 2012.
Wigmosta, M. S., Vail, L. W., and Lettenmaier, D. P.: A distributed hydrology-vegetation model for complex terrain, Water Resour. Res., 30, 1665–1679, 1994.
Williams, M., Richardson, A. D., Reichstein, M., Stoy, P. C., Peylin, P., Verbeeck, H., Carvalhais, N., Jung, M., Hollinger, D. Y., Kattge, J., Leuning, R., Luo, Y., Tomelleri, E., Trudinger, C. M., and Wang, Y.-P.: Improving land surface models with FLUXNET data, Biogeosciences, 6, 1341–1359, https://doi.org/10.5194/bg-6-1341-2009, 2009.
Wu, C. C. and Margulis, S. A.: Feasibility of real-time soil state and flux characterization for wastewater reuse using an embedded sensor network data assimilation approach, J. Hydrol., 399, 313–325, https://doi.org/10.1016/j.jhydrol.2011.01.011, 2011.
Wu, C. C. and Margulis, S. A.: Real-Time Soil Moisture and Salinity Profile Estimation Using Assimilation of Embedded Sensor Datastreams, Vadose Zone J., 12, https://doi.org/10.2136/vzj2011.0176, 2013.
Xie, Z., Yuan, F., Duan, Q., Zheng, J., Liang, M., and Chen, F.: Regional parameter estimation of the VIC land surface model: methodology and application to river basins in China, J. Hydrometeorol., 8, 447–468, https://doi.org/10.1175/jhm568.1, 2007.
Yan, H., DeChant, C. M., and Moradkhani, H.: Improving Soil Moisture Profile Prediction With the Particle Filter-Markov Chain Monte Carlo Method, IEEE T. Geosci. Remote, 53, 6134–6147, https://doi.org/10.1109/tgrs.2015.2432067, 2015.
Zhao, R. J.: The Xinanjiang model applied in China, J. Hydrol., 135, 371–381, 1992.
Zeng, X. and Decker, M.: Improving the numerical solution of soil moisture-based Richards equation for land models with a deep or shallow water table, J. Hydrometeorol., 10, 308–319, https://doi.org/10.1175/2008JHM1011.1, 2009.
Short summary
Applications of data assimilation (DA) arise in many fields of geosciences, perhaps most importantly in weather forecasting and hydrology. We want to investigate the roles of data assimilation methods and land surface models (LSMs) in joint estimation of states and parameters in the assimilation experiments. We find that all DA methods can improve prediction of states, and that differences between DA methods were limited but that the differences between LSMs were much larger.
Applications of data assimilation (DA) arise in many fields of geosciences, perhaps most...
