Articles | Volume 22, issue 2
https://doi.org/10.5194/hess-22-1193-2018
© Author(s) 2018. 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-22-1193-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Feb 2018
Research article |
| 12 Feb 2018
Parametric soil water retention models: a critical evaluation of expressions for the full moisture range
Raneem Madi
Dept. Soil System Science, Helmholtz Centre for Environmental Research – UFZ, Halle, Germany
Gerrit Huibert de Rooij
CORRESPONDING AUTHOR
Dept. Soil System Science, Helmholtz Centre for Environmental Research – UFZ, Halle, Germany
Henrike Mielenz
Institute for Crop and Soil Science, Julius Kühn-Institut – JKI, Braunschweig, Germany
Juliane Mai
Dept. Computational Hydrosystems, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
currently at: Dept. Civil & Environmental Engineering, Univ. of Waterloo, Waterloo, Canada
Related authors
No articles found.
Maria Staudinger, Anna Herzog, Ralf Loritz, Tobias Houska, Sandra Pool, Diana Spieler, Paul D. Wagner, Juliane Mai, Jens Kiesel, Stephan Thober, Björn Guse, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2025-1076, https://doi.org/10.5194/egusphere-2025-1076, 2025
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Four process-based and four data-driven hydrological models are compared using different training data. We found process-based models to perform better with small data sets but stop learning soon, while data-driven models learn longer. The study highlights the importance of memory in data and the impact of different data sampling methods on model performance. The direct comparison of these models is novel and provides a clear understanding of their performance under various data conditions.
Asha Nambiar and Gerrit Huibert de Rooij
EGUsphere, https://doi.org/10.5194/egusphere-2025-412, https://doi.org/10.5194/egusphere-2025-412, 2025
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The way infiltrating water moves in soil affects vegetation as well as groundwater recharge. This flow of soil water is captured by a mathematical function that covers all water contents from very dry to water-saturated. We tested several such functions for different soils and climates to see how model-calculated water fluxes are affected. Luckily, the effects of weather and the soil are much more important than the choice of the mathematical function.
Gerrit Huibert de Rooij
EGUsphere, https://doi.org/10.5194/egusphere-2024-3487, https://doi.org/10.5194/egusphere-2024-3487, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Water flows ever more slowly in soil when the soil dries out. This can be described by the conductivity curve that accounts for water filling up small spaces, sticking to grains if films, and water vapour diffusion. This paper introduces a relatively simple model for this curve that needs one parameter less then most others. It works well for most soils, but some need the extra parameter. The paper also presents a computer program to determine the parameter values of this and other models.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Samah Larabi, Juliane Mai, Markus Schnorbus, Bryan A. Tolson, and Francis Zwiers
Hydrol. Earth Syst. Sci., 27, 3241–3263, https://doi.org/10.5194/hess-27-3241-2023, https://doi.org/10.5194/hess-27-3241-2023, 2023
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The computational cost of sensitivity analysis (SA) becomes prohibitive for large hydrologic modeling domains. Here, using a large-scale Variable Infiltration Capacity (VIC) deployment, we show that watershed classification helps identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. Findings reveal the opportunity to leverage climate and land cover attributes to reduce the cost of SA and facilitate more rapid deployment of large-scale land surface models.
Robert Chlumsky, Juliane Mai, James R. Craig, and Bryan A. Tolson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-69, https://doi.org/10.5194/hess-2023-69, 2023
Revised manuscript not accepted
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A blended model allows multiple hydrologic processes to be represented in a single model, which allows for a model to achieve high performance without the need to modify its structure for different catchments. Here, we improve upon the initial blended version by testing more than 30 blended models in twelve catchments to improve the overall model performance. We validate our proposed, updated blended model version with independent catchments, and make this version available for open use.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Gerrit Huibert de Rooij
Hydrol. Earth Syst. Sci., 26, 5849–5858, https://doi.org/10.5194/hess-26-5849-2022, https://doi.org/10.5194/hess-26-5849-2022, 2022
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The way soils capture infiltrating water affects crops and natural vegetation as well as groundwater recharge. This retention of soil water is captured by a mathematical function that covers all water contents from very dry to water-saturated. Unfortunately, data in the dry range are often absent or unreliable. I modified an earlier function to be more robust in the absence of dry-range data, and present a computer program to estimate the parameters of the new function.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
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Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Michelle Viswanathan, Tobias K. D. Weber, Sebastian Gayler, Juliane Mai, and Thilo Streck
Biogeosciences, 19, 2187–2209, https://doi.org/10.5194/bg-19-2187-2022, https://doi.org/10.5194/bg-19-2187-2022, 2022
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We analysed the evolution of model parameter uncertainty and prediction error as we updated parameters of a maize phenology model based on yearly observations, by sequentially applying Bayesian calibration. Although parameter uncertainty was reduced, prediction quality deteriorated when calibration and prediction data were from different maize ripening groups or temperature conditions. The study highlights that Bayesian methods should account for model limitations and inherent data structures.
Benedikt J. Werner, Oliver J. Lechtenfeld, Andreas Musolff, Gerrit H. de Rooij, Jie Yang, Ralf Gründling, Ulrike Werban, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 25, 6067–6086, https://doi.org/10.5194/hess-25-6067-2021, https://doi.org/10.5194/hess-25-6067-2021, 2021
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Export of dissolved organic carbon (DOC) from riparian zones (RZs) is an important yet poorly understood component of the catchment carbon budget. This study chemically and spatially classifies DOC source zones within a RZ of a small catchment to assess DOC export patterns. Results highlight that DOC export from only a small fraction of the RZ with distinct DOC composition dominates overall DOC export. The application of a spatial, topographic proxy can be used to improve DOC export models.
Nicolas Gasset, Vincent Fortin, Milena Dimitrijevic, Marco Carrera, Bernard Bilodeau, Ryan Muncaster, Étienne Gaborit, Guy Roy, Nedka Pentcheva, Maxim Bulat, Xihong Wang, Radenko Pavlovic, Franck Lespinas, Dikra Khedhaouiria, and Juliane Mai
Hydrol. Earth Syst. Sci., 25, 4917–4945, https://doi.org/10.5194/hess-25-4917-2021, https://doi.org/10.5194/hess-25-4917-2021, 2021
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In this paper, we highlight the importance of including land-data assimilation as well as offline precipitation analysis components in a regional reanalysis system. We also document the performance of the first multidecadal 10 km reanalysis performed with the GEM atmospheric model that can be used for seamless land-surface and hydrological modelling in North America. It is of particular interest for transboundary basins, as existing datasets often show discontinuities at the border.
Gerrit Huibert de Rooij, Juliane Mai, and Raneem Madi
Hydrol. Earth Syst. Sci., 25, 983–1007, https://doi.org/10.5194/hess-25-983-2021, https://doi.org/10.5194/hess-25-983-2021, 2021
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The way soils capture infiltrating water affects crops and natural vegetation and groundwater recharge. This retention of soil water is described by a mathematical function that covers all water contents from very dry to water saturated. We combined two existing lines of research to improve the behaviour of a popular function for very dry and very wet conditions. Our new function could handle a wider range of conditions than earlier curves. We provide fits to a wide range of soils.
Juliane Mai, James R. Craig, and Bryan A. Tolson
Hydrol. Earth Syst. Sci., 24, 5835–5858, https://doi.org/10.5194/hess-24-5835-2020, https://doi.org/10.5194/hess-24-5835-2020, 2020
Conrad Jackisch, Kai Germer, Thomas Graeff, Ines Andrä, Katrin Schulz, Marcus Schiedung, Jaqueline Haller-Jans, Jonas Schneider, Julia Jaquemotte, Philipp Helmer, Leander Lotz, Andreas Bauer, Irene Hahn, Martin Šanda, Monika Kumpan, Johann Dorner, Gerrit de Rooij, Stefan Wessel-Bothe, Lorenz Kottmann, Siegfried Schittenhelm, and Wolfgang Durner
Earth Syst. Sci. Data, 12, 683–697, https://doi.org/10.5194/essd-12-683-2020, https://doi.org/10.5194/essd-12-683-2020, 2020
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Soil water content and matric potential are central hydrological state variables. A large variety of automated probes and sensor systems for field monitoring exist. In a field experiment under idealised conditions we compared 15 systems for soil moisture and 14 systems for matric potential. The individual records of one system agree well with the others. Most records are also plausible. However, the absolute values of the different measuring systems span a very large range of possible truths.
Benedikt J. Werner, Andreas Musolff, Oliver J. Lechtenfeld, Gerrit H. de Rooij, Marieke R. Oosterwoud, and Jan H. Fleckenstein
Biogeosciences, 16, 4497–4516, https://doi.org/10.5194/bg-16-4497-2019, https://doi.org/10.5194/bg-16-4497-2019, 2019
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Increased dissolved organic carbon (DOC) concentration in streams can pose a threat to downstream water resources. Analyzing data from an in-stream probe we found that hydroclimatic and hydrological drivers can describe up to 72 % of the observed DOC concentration and composition variability. Variability was found to be highest during discharge events with warm and dry preconditions. The findings suggest an impact of climate change on DOC exports and thus also on downstream water quality.
Stephan Thober, Matthias Cuntz, Matthias Kelbling, Rohini Kumar, Juliane Mai, and Luis Samaniego
Geosci. Model Dev., 12, 2501–2521, https://doi.org/10.5194/gmd-12-2501-2019, https://doi.org/10.5194/gmd-12-2501-2019, 2019
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We present a model that aggregates simulated runoff along a river
(i.e. a routing model). The unique feature of the model is that it
can be run at multiple resolutions without any modifications to the
input data. The model internally (dis-)aggregates all input data to
the resolution given by the user. The model performance does not
depend on the chosen resolution. This allows efficient model
calibration at coarse resolution and subsequent model application at
fine resolution.
Gerrit Huibert de Rooij
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-97, https://doi.org/10.5194/gmd-2018-97, 2018
Publication in GMD not foreseen
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Areas that have few or no weather stations or are subject to climate change still need weather data in order to model the demand for water, the risk of floods and droughts, etc. TEmpotRain generates rainfall, daily temperature extremes, and daily potential evaporation (from the soil) / transpiration (by plants). The physical meaning of the model parameters is clear. This allows realistic values for them to be estimated, even for hypothetical (future) climates for which data are not available.
Mehmet C. Demirel, Juliane Mai, Gorka Mendiguren, Julian Koch, Luis Samaniego, and Simon Stisen
Hydrol. Earth Syst. Sci., 22, 1299–1315, https://doi.org/10.5194/hess-22-1299-2018, https://doi.org/10.5194/hess-22-1299-2018, 2018
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Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, https://doi.org/10.5194/hess-21-5009-2017, 2017
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A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.
Remko C. Nijzink, Luis Samaniego, Juliane Mai, Rohini Kumar, Stephan Thober, Matthias Zink, David Schäfer, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, https://doi.org/10.5194/hess-20-1151-2016, 2016
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The heterogeneity of landscapes in river basins strongly affects the hydrological response. In this study, the distributed mesoscale Hydrologic Model (mHM) was equipped with additional processes identified by landscapes within one modelling cell. Seven study catchments across Europe were selected to test the value of this additional sub-grid heterogeneity. In addition, the models were constrained based on expert knowledge. Generally, the modifications improved the representation of low flows.
Rohini Kumar, Jude L. Musuuza, Anne F. Van Loon, Adriaan J. Teuling, Roland Barthel, Jurriaan Ten Broek, Juliane Mai, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 20, 1117–1131, https://doi.org/10.5194/hess-20-1117-2016, https://doi.org/10.5194/hess-20-1117-2016, 2016
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In a maiden attempt, we performed a multiscale evaluation of the widely used SPI to characterize local- and regional-scale groundwater (GW) droughts using observations at 2040 groundwater wells in Germany and the Netherlands. From this data-based exploratory analysis, we provide sufficient evidence regarding the inability of the SPI to characterize GW drought events, and stress the need for more GW observations and accounting for regional hydrogeological characteristics in GW drought monitoring.
E. Bloem, M. de Gee, and G. H. de Rooij
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-6993-2014, https://doi.org/10.5194/hessd-11-6993-2014, 2014
Manuscript not accepted for further review
G. H. de Rooij
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-83-2014, https://doi.org/10.5194/hessd-11-83-2014, 2014
Revised manuscript has not been submitted
B. te Brake, M. J. van der Ploeg, and G. H. de Rooij
Hydrol. Earth Syst. Sci., 17, 1933–1949, https://doi.org/10.5194/hess-17-1933-2013, https://doi.org/10.5194/hess-17-1933-2013, 2013
Related subject area
Subject: Vadose Zone Hydrology | Techniques and Approaches: Mathematical applications
Differentiating between crop and soil effects on soil moisture dynamics
Forward and inverse modeling of water flow in unsaturated soils with discontinuous hydraulic conductivities using physics-informed neural networks with domain decomposition
Hydraulic and transport parameter assessment using column infiltration experiments
On the consistency of scale among experiments, theory, and simulation
Solar-forced diurnal regulation of cave drip rates via phreatophyte evapotranspiration
Multi-scale analysis of bias correction of soil moisture
Generalized analytical solution for advection-dispersion equation in finite spatial domain with arbitrary time-dependent inlet boundary condition
Helen Scholz, Gunnar Lischeid, Lars Ribbe, Ixchel Hernandez Ochoa, and Kathrin Grahmann
Hydrol. Earth Syst. Sci., 28, 2401–2419, https://doi.org/10.5194/hess-28-2401-2024, https://doi.org/10.5194/hess-28-2401-2024, 2024
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Sustainable management schemes in agriculture require knowledge of site-specific soil hydrological processes, especially the interplay between soil heterogeneities and crops. We disentangled such effects on soil moisture in a diversified arable field with different crops and management schemes by applying a principal component analysis. The main effects on soil moisture variability were quantified. Meteorological drivers, followed by different seasonal behaviour of crops, had the largest impact.
Toshiyuki Bandai and Teamrat A. Ghezzehei
Hydrol. Earth Syst. Sci., 26, 4469–4495, https://doi.org/10.5194/hess-26-4469-2022, https://doi.org/10.5194/hess-26-4469-2022, 2022
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Scientists use a physics-based equation to simulate water dynamics that influence hydrological and ecological phenomena. We present hybrid physics-informed neural networks (PINNs) to leverage the growing availability of soil moisture data and advances in machine learning. We showed that PINNs perform comparably to traditional methods and enable the estimation of rainfall rates from soil moisture. However, PINNs are challenging to train and significantly slower than traditional methods.
Anis Younes, Thierry Mara, Marwan Fahs, Olivier Grunberger, and Philippe Ackerer
Hydrol. Earth Syst. Sci., 21, 2263–2275, https://doi.org/10.5194/hess-21-2263-2017, https://doi.org/10.5194/hess-21-2263-2017, 2017
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The estimation of flow and solute transport in unsaturated soil is essential for quantifying groundwater resources or pollution. Usual column laboratory experiments and a new method are analyzed using a global sensitivity analysis. The data sets are composed of water pressure and water content measured inside the column and water flow rate and solute BTC measured at the outflow. Non-invasive methods (using flow rate and BTC only) provide comparable results than usual invasive methods.
James E. McClure, Amanda L. Dye, Cass T. Miller, and William G. Gray
Hydrol. Earth Syst. Sci., 21, 1063–1076, https://doi.org/10.5194/hess-21-1063-2017, https://doi.org/10.5194/hess-21-1063-2017, 2017
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A complicating factor in describing the flow of two immiscible fluids in a porous medium is ensuring that experiments, theory, and simulation are all formulated at the same length scale. We have quantitatively analyzed the internal structure of a two-fluid system including the distribution of phases and the location of interfaces between phases. The data we have obtained allow for a clearer definition of capillary pressure at the averaged scale as a state function that describes the system.
Katie Coleborn, Gabriel C. Rau, Mark O. Cuthbert, Andy Baker, and Owen Navarre
Hydrol. Earth Syst. Sci., 20, 4439–4455, https://doi.org/10.5194/hess-20-4439-2016, https://doi.org/10.5194/hess-20-4439-2016, 2016
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This is the first observation of tree water use in cave drip water. Our novel time series analysis using the synchrosqueeze transform identified daily and sub-daily oscillations in drip rate. The only hypothesis consistent with hydrologic theory and the data was that the oscillations were caused by solar driven pumping by trees above the cave. We propose a new protocol for inferring karst architecture and our findings support research on the impact trees on speleothem paleoclimate proxies.
C.-H. Su and D. Ryu
Hydrol. Earth Syst. Sci., 19, 17–31, https://doi.org/10.5194/hess-19-17-2015, https://doi.org/10.5194/hess-19-17-2015, 2015
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Global environmental monitoring requires geophysical measurements from a variety of sources and sensors to close the information gap. This paper proposes a novel approach for analysing temporal scale-by-scale differences (biases and errors) between geophysical estimates from disparate sources. This allows assessment of different bias correction schemes, and forms the basis for a multi-scale bias correction scheme and data-adaptive, non-linear de-noising.
J.-S. Chen and C.-W. Liu
Hydrol. Earth Syst. Sci., 15, 2471–2479, https://doi.org/10.5194/hess-15-2471-2011, https://doi.org/10.5194/hess-15-2471-2011, 2011
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Short summary
Water flows through soils with more difficulty when the soil is dried out. Scant rainfall in deserts may therefore result in a seemingly wet soil, but the water will often not penetrate deeply enough to replenish the groundwater. We compared the mathematical functions that describe how well different soils hold their water and found that only a few of them are realistic. The function one chooses to model the soil can have a large impact on the estimate of groundwater recharge.
Water flows through soils with more difficulty when the soil is dried out. Scant rainfall in...
