Articles | Volume 25, issue 6
https://doi.org/10.5194/hess-25-3319-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-3319-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
16 Jun 2021
Technical note |
| 16 Jun 2021
| 16 Jun 2021
Technical Note: Sequential ensemble data assimilation in convergent and divergent systems
Biosphere 2, University of Arizona, Tucson, AZ, USA
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Daniel Berg
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Heidelberg Graduate School, HGS MathComp, Heidelberg University, Heidelberg, Germany
Kurt Roth
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany
Related authors
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
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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.
Hannes H. Bauser, Daniel Berg, Ole Klein, and Kurt Roth
Hydrol. Earth Syst. Sci., 22, 4921–4934, https://doi.org/10.5194/hess-22-4921-2018, https://doi.org/10.5194/hess-22-4921-2018, 2018
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Data assimilation methods like the ensemble Kalman filter (EnKF) can combine models and measurements to estimate states and parameters, but require a proper representation of uncertainties. In soil hydrology, model errors typically vary rapidly in space and time, which is difficult to represent. Inflation methods can account for unrepresented model errors. To improve estimations in soil hydrology, we designed a method that can adjust the inflation of states and parameters to fast varying errors.
Hannes H. Bauser, Stefan Jaumann, Daniel Berg, and Kurt Roth
Hydrol. Earth Syst. Sci., 20, 4999–5014, https://doi.org/10.5194/hess-20-4999-2016, https://doi.org/10.5194/hess-20-4999-2016, 2016
Short summary
Short summary
The representation of soil water movement comes with uncertainties in all model components. We assess the key uncertainties for the case of a one-dimensional soil profile with measured water contents. We employ a data assimilation method to represent and reduce the key uncertainties. For intermittent phases where model assumptions are violated, we introduce a "closed-eye period" to bridge the gap. We also demonstrate the need to include heterogeneity.
Edoardo Martini, Matteo Bauckholt, Simon Kögler, Manuel Kreck, Kurt Roth, Ulrike Werban, Ute Wollschläger, and Steffen Zacharias
Earth Syst. Sci. Data, 13, 2529–2539, https://doi.org/10.5194/essd-13-2529-2021, https://doi.org/10.5194/essd-13-2529-2021, 2021
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We present the in situ data available from the soil monitoring network
STH-net, recently implemented at the Schäfertal Hillslope site (Germany). The STH-net provides data (soil water content, soil temperature, water level, and meteorological variables – measured at a 10 min interval since 1 January 2019) for developing and testing modelling approaches in the context of vadose zone hydrology at spatial scales ranging from the pedon to the hillslope.
Xicai Pan, Stefan Jaumann, Jiabao Zhang, and Kurt Roth
Hydrol. Earth Syst. Sci., 23, 3653–3663, https://doi.org/10.5194/hess-23-3653-2019, https://doi.org/10.5194/hess-23-3653-2019, 2019
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This study suggests an efficient approach to obtain plot-scale soil hydraulic properties for the shallow structural soils via non-invasive ground-penetrating radar measurements. Facilitated by spatial information of lateral water flow, this approach is more efficient than the widely used inversion approaches relying on intensive soil moisture monitoring. The acquisition of such quantitative information is of great interest to fields such as hydrology and precision agriculture.
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.
Hannes H. Bauser, Daniel Berg, Ole Klein, and Kurt Roth
Hydrol. Earth Syst. Sci., 22, 4921–4934, https://doi.org/10.5194/hess-22-4921-2018, https://doi.org/10.5194/hess-22-4921-2018, 2018
Short summary
Short summary
Data assimilation methods like the ensemble Kalman filter (EnKF) can combine models and measurements to estimate states and parameters, but require a proper representation of uncertainties. In soil hydrology, model errors typically vary rapidly in space and time, which is difficult to represent. Inflation methods can account for unrepresented model errors. To improve estimations in soil hydrology, we designed a method that can adjust the inflation of states and parameters to fast varying errors.
Stefan Jaumann and Kurt Roth
Hydrol. Earth Syst. Sci., 22, 2551–2573, https://doi.org/10.5194/hess-22-2551-2018, https://doi.org/10.5194/hess-22-2551-2018, 2018
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Ground-penetrating radar (GPR) is a noninvasive and nondestructive measurement method to monitor the hydraulic processes precisely and efficiently. We analyze synthetic as well as measured data from the ASSESS test site and show that the analysis yields accurate estimates for the soil hydraulic material properties as well as for the subsurface architecture by comparing the results to references derived from time domain reflectometry (TDR) and subsurface architecture ground truth data.
Julia Boike, Inge Juszak, Stephan Lange, Sarah Chadburn, Eleanor Burke, Pier Paul Overduin, Kurt Roth, Olaf Ippisch, Niko Bornemann, Lielle Stern, Isabelle Gouttevin, Ernst Hauber, and Sebastian Westermann
Earth Syst. Sci. Data, 10, 355–390, https://doi.org/10.5194/essd-10-355-2018, https://doi.org/10.5194/essd-10-355-2018, 2018
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A 20-year data record from the Bayelva site at Ny-Ålesund, Svalbard, is presented on meteorology, energy balance components, surface and subsurface observations. This paper presents the data set, instrumentation, calibration, processing and data quality control. The data show that mean annual, summer and winter soil temperature data from shallow to deeper depths have been warming over the period of record, indicating the degradation and loss of permafrost at this site.
Stefan Jaumann and Kurt Roth
Hydrol. Earth Syst. Sci., 21, 4301–4322, https://doi.org/10.5194/hess-21-4301-2017, https://doi.org/10.5194/hess-21-4301-2017, 2017
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We investigate the quantitative effect of neglected sensor position, small-scale heterogeneity, and lateral flow on soil hydraulic material properties. Thus, we analyze a fluctuating water table experiment in a 2-D architecture (ASSESS) with increasingly complex studies based on time domain reflectometry and hydraulic potential data. We found that 1-D studies may yield biased parameters and that estimating sensor positions as well as small-scale heterogeneity improves the model significantly.
Sina Muster, Kurt Roth, Moritz Langer, Stephan Lange, Fabio Cresto Aleina, Annett Bartsch, Anne Morgenstern, Guido Grosse, Benjamin Jones, A. Britta K. Sannel, Ylva Sjöberg, Frank Günther, Christian Andresen, Alexandra Veremeeva, Prajna R. Lindgren, Frédéric Bouchard, Mark J. Lara, Daniel Fortier, Simon Charbonneau, Tarmo A. Virtanen, Gustaf Hugelius, Juri Palmtag, Matthias B. Siewert, William J. Riley, Charles D. Koven, and Julia Boike
Earth Syst. Sci. Data, 9, 317–348, https://doi.org/10.5194/essd-9-317-2017, https://doi.org/10.5194/essd-9-317-2017, 2017
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Waterbodies are abundant in Arctic permafrost lowlands. Most waterbodies are ponds with a surface area smaller than 100 x 100 m. The Permafrost Region Pond and Lake Database (PeRL) for the first time maps ponds as small as 10 x 10 m. PeRL maps can be used to document changes both by comparing them to historical and future imagery. The distribution of waterbodies in the Arctic is important to know in order to manage resources in the Arctic and to improve climate predictions in the Arctic.
Xicai Pan, Stefan Jaumann, Jiabao Zhang, and Kurt Roth
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-77, https://doi.org/10.5194/tc-2017-77, 2017
Revised manuscript not accepted
Short summary
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This study proposes a new method for estimating hydraulic properties of active layers using ground-penetrating radar (GPR) and 2D inverse hydrological modeling. This method creatively turns over the adverse features of undulating frost table for 1D inverse estimation of hydraulic parameters to assets for 2D inverse estimation. Its advantages include non-destructive observations, a bigger scale of the soil hydraulic properties and efficiency for permafrost studies.
Hannes H. Bauser, Stefan Jaumann, Daniel Berg, and Kurt Roth
Hydrol. Earth Syst. Sci., 20, 4999–5014, https://doi.org/10.5194/hess-20-4999-2016, https://doi.org/10.5194/hess-20-4999-2016, 2016
Short summary
Short summary
The representation of soil water movement comes with uncertainties in all model components. We assess the key uncertainties for the case of a one-dimensional soil profile with measured water contents. We employ a data assimilation method to represent and reduce the key uncertainties. For intermittent phases where model assumptions are violated, we introduce a "closed-eye period" to bridge the gap. We also demonstrate the need to include heterogeneity.
Xicai Pan, Yanping Li, Qihao Yu, Xiaogang Shi, Daqing Yang, and Kurt Roth
The Cryosphere, 10, 1591–1603, https://doi.org/10.5194/tc-10-1591-2016, https://doi.org/10.5194/tc-10-1591-2016, 2016
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Using a 9-year dataset in conjunction with a process-based model, we verify that the common assumption of a considerably smaller thermal conductivity in the thawed season than the frozen season is not valid at a site with a stratified active layer on the Qinghai–Tibet Plateau (QTP). The unique hydraulic and thermal mechanism in the active layer challenges the concept of thermal offset used in conceptual permafrost models and hints at the reason for rapid permafrost warming on the QTP.
P. Klenk, S. Jaumann, and K. Roth
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-12215-2015, https://doi.org/10.5194/hessd-12-12215-2015, 2015
Revised manuscript has not been submitted
Short summary
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The main goal of our work is to quantify near-surface soil water dynamics by advancing non-invasive measurement methods such as surface-based Ground-Penetrating Radar (GPR). Here, we observe soil infiltration processes with a novel dual-frequency GPR system. The high precision of our approach allows (i) closely investigating the dynamic evolution of specific subsurface signals in different materials and (ii) monitoring the longterm effect of infiltration pulses over the course of several months.
P. Klenk, S. Jaumann, and K. Roth
Hydrol. Earth Syst. Sci., 19, 1125–1139, https://doi.org/10.5194/hess-19-1125-2015, https://doi.org/10.5194/hess-19-1125-2015, 2015
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In this study, we analyze a set of high-resolution, surface-based, 2-D ground-penetrating radar (GPR) observations of artificially induced subsurface water dynamics. In particular, we place close scrutiny on the evolution of the capillary fringe in a highly dynamic regime with surface-based time-lapse GPR. We thoroughly explain all observed phenomena based on theoretical soil physical considerations and numerical simulations of both subsurface water flow and the expected GPR response.
A. Dagenbach, J. S. Buchner, P. Klenk, and K. Roth
Hydrol. Earth Syst. Sci., 17, 611–618, https://doi.org/10.5194/hess-17-611-2013, https://doi.org/10.5194/hess-17-611-2013, 2013
Related subject area
Subject: Vadose Zone Hydrology | Techniques and Approaches: Uncertainty analysis
Evaluation of root zone soil moisture products over the Huai River basin
Data worth analysis within a model-free data assimilation framework for soil moisture flow
Impact of parameter updates on soil moisture assimilation in a 3D heterogeneous hillslope model
On the uncertainty of initial condition and initialization approaches in variably saturated flow modeling
Inflation method for ensemble Kalman filter in soil hydrology
Sensitivity and identifiability of hydraulic and geophysical parameters from streaming potential signals in unsaturated porous media
Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty
Deep drainage estimates using multiple linear regression with percent clay content and rainfall
En Liu, Yonghua Zhu, Jean-Christophe Calvet, Haishen Lü, Bertrand Bonan, Jingyao Zheng, Qiqi Gou, Xiaoyi Wang, Zhenzhou Ding, Haiting Xu, Ying Pan, and Tingxing Chen
Hydrol. Earth Syst. Sci., 28, 2375–2400, https://doi.org/10.5194/hess-28-2375-2024, https://doi.org/10.5194/hess-28-2375-2024, 2024
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Overestimated root zone soil moisture (RZSM) based on land surface models (LSMs) is attributed to overestimated precipitation and an underestimated ratio of transpiration to total evapotranspiration and performs better in the wet season. Underestimated SMOS L3 surface SM triggers the underestimated SMOS L4 RZSM, which performs better in the dry season due to the attenuated radiation in the wet season. LSMs should reduce and increase the frequency of wet and dry soil moisture, respectively.
Yakun Wang, Xiaolong Hu, Lijun Wang, Jinmin Li, Lin Lin, Kai Huang, and Liangsheng Shi
Hydrol. Earth Syst. Sci., 27, 2661–2680, https://doi.org/10.5194/hess-27-2661-2023, https://doi.org/10.5194/hess-27-2661-2023, 2023
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To avoid overloaded monitoring cost from redundant measurements, this study proposed a non-parametric data worth analysis framework to assess the worth of future soil moisture data regarding the model-free unsaturated flow models before data gathering. Results indicated that (1) the method can quantify the data worth of alternative monitoring schemes to obtain the optimal one, and (2) high-quality and representative small data could be a better choice than unfiltered big data.
Natascha Brandhorst and Insa Neuweiler
Hydrol. Earth Syst. Sci., 27, 1301–1323, https://doi.org/10.5194/hess-27-1301-2023, https://doi.org/10.5194/hess-27-1301-2023, 2023
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Data assimilation aims at quantifying and minimizing model uncertainty. In hydrological models, this uncertainty is mainly caused by the uncertain soil hydraulic parameters and their spatial variability. In this study, the impact of updating these parameters along with the model states on the estimated soil moisture is investigated. It is shown that parameter updates are beneficial and that it is advisable to resolve heterogeneous structures instead of applying a simplified soil structure.
Danyang Yu, Jinzhong Yang, Liangsheng Shi, Qiuru Zhang, Kai Huang, Yuanhao Fang, and Yuanyuan Zha
Hydrol. Earth Syst. Sci., 23, 2897–2914, https://doi.org/10.5194/hess-23-2897-2019, https://doi.org/10.5194/hess-23-2897-2019, 2019
Hannes H. Bauser, Daniel Berg, Ole Klein, and Kurt Roth
Hydrol. Earth Syst. Sci., 22, 4921–4934, https://doi.org/10.5194/hess-22-4921-2018, https://doi.org/10.5194/hess-22-4921-2018, 2018
Short summary
Short summary
Data assimilation methods like the ensemble Kalman filter (EnKF) can combine models and measurements to estimate states and parameters, but require a proper representation of uncertainties. In soil hydrology, model errors typically vary rapidly in space and time, which is difficult to represent. Inflation methods can account for unrepresented model errors. To improve estimations in soil hydrology, we designed a method that can adjust the inflation of states and parameters to fast varying errors.
Anis Younes, Jabran Zaouali, François Lehmann, and Marwan Fahs
Hydrol. Earth Syst. Sci., 22, 3561–3574, https://doi.org/10.5194/hess-22-3561-2018, https://doi.org/10.5194/hess-22-3561-2018, 2018
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Water movement through unsaturated soils generates streaming potential (SP). Reliability of SP for the determination of soil properties is investigated. First, influence of hydraulic and geophysical soil parameters on the SP signals is assessed using global sensitivity analysis. Then, a Bayesian approach is used to assess the identifiability of the parameters from SP data. The results of a synthetic drainage column experiment show that all parameters can be reasonably estimated from SP signals.
K. Steffens, M. Larsbo, J. Moeys, E. Kjellström, N. Jarvis, and E. Lewan
Hydrol. Earth Syst. Sci., 18, 479–491, https://doi.org/10.5194/hess-18-479-2014, https://doi.org/10.5194/hess-18-479-2014, 2014
D. L. Wohling, F. W. Leaney, and R. S. Crosbie
Hydrol. Earth Syst. Sci., 16, 563–572, https://doi.org/10.5194/hess-16-563-2012, https://doi.org/10.5194/hess-16-563-2012, 2012
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Short summary
Data assimilation methods are used throughout the geosciences to combine information from uncertain models and uncertain measurement data. In this study, we distinguish between the characteristics of geophysical systems, i.e., divergent systems (initially nearby states will drift apart) and convergent systems (initially nearby states will coalesce), and demonstrate the implications for sequential ensemble data assimilation methods, which require a sufficient divergent component.
Data assimilation methods are used throughout the geosciences to combine information from...
