Articles | Volume 26, issue 21
https://doi.org/10.5194/hess-26-5431-2022
© Author(s) 2022. 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-26-5431-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Karst spring recession and classification: efficient, automated methods for both fast- and slow-flow components
Tunde Olarinoye
CORRESPONDING AUTHOR
Chair of Hydrological Modeling and Water Resource, University of
Freiburg, Freiburg, Germany
Tom Gleeson
Department of Civil Engineering, University of Victoria, Victoria, BC, Canada
Andreas Hartmann
Chair of Hydrological Modeling and Water Resource, University of
Freiburg, Freiburg, Germany
Chair of Groundwater Systems, Technical University Dresden, Dresden, Germany
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Thomas Fichtner, Yuly Juliana Aguilar Avila, Andreas Hartmann, Stefan Seeger, Martin Maier, and Stephan Raspe
EGUsphere, https://doi.org/10.5194/egusphere-2025-4025, https://doi.org/10.5194/egusphere-2025-4025, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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The study examines how spatial soil moisture variability influences SVAT model calibration and the estimation of groundwater recharge in forest ecosystems. We show that model-inherent uncertainties affect predictions more strongly than soil moisture variability itself. Our results demonstrate that reliable groundwater recharge can be achieved using data from just six to seven profiles, providing practical guidance for more efficient field monitoring and model calibration.
Theresa Blume, Peter Chifflard, Stefan Achleitner, Andreas Hartmann, Stefan Hergarten, Luisa Hopp, Bernhard Kohl, Florian Leese, Ilja van Meerveld, Christian Reinhardt-Imjela, and Markus Weiler
EGUsphere, https://doi.org/10.5194/egusphere-2025-4424, https://doi.org/10.5194/egusphere-2025-4424, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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Subsurface stormflow (SSF) is one of the least studied and therefore least understood runoff generation processes because detecting and quantifying SSF is extremely challenging. We present an ongoing concerted experimental effort to systematically investigate SSF across four catchments using a variety of methods covering different spatial scales. Centerpiece of this effort is the construction of 12 large trenches to capture and monitor SSF.
Markus Giese, Yvan Caballero, Andreas Hartmann, and Jean-Baptiste Charlier
Hydrol. Earth Syst. Sci., 29, 3037–3054, https://doi.org/10.5194/hess-29-3037-2025, https://doi.org/10.5194/hess-29-3037-2025, 2025
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Karst springs respond quickly to environmental changes, making them crucial to understanding climate impacts on groundwater. This study analyses long-term trends in precipitation, temperature, and discharge from more than 50 springs across Europe. Results show that while historical discharge trends align with those of rivers, recent changes are driven by rising temperatures rather than precipitation. These findings highlight climate-driven shifts in groundwater recharge and storage processes.
Pia Ebeling, Andreas Musolff, Rohini Kumar, Andreas Hartmann, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 29, 2925–2950, https://doi.org/10.5194/hess-29-2925-2025, https://doi.org/10.5194/hess-29-2925-2025, 2025
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Groundwater is a crucial resource at risk due to droughts. To understand drought effects on groundwater levels in Germany, we grouped 6626 wells into six regional and two national patterns. Weather explained half of the level variations with varied response times. Shallow groundwater responds fast and is more vulnerable to short droughts (a few months). Dampened deep heads buffer short droughts but suffer from long droughts and recoveries. Two nationwide trend patterns were linked to human water use.
Robert Reinecke, Annemarie Bäthge, Ricarda Dietrich, Sebastian Gnann, Simon N. Gosling, Danielle Grogan, Andreas Hartmann, Stefan Kollet, Rohini Kumar, Richard Lammers, Sida Liu, Yan Liu, Nils Moosdorf, Bibi Naz, Sara Nazari, Chibuike Orazulike, Yadu Pokhrel, Jacob Schewe, Mikhail Smilovic, Maryna Strokal, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
EGUsphere, https://doi.org/10.5194/egusphere-2025-1181, https://doi.org/10.5194/egusphere-2025-1181, 2025
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Here we describe a collaborative effort to improve predictions of how climate change will affect groundwater. The ISIMIP groundwater sector combines multiple global groundwater models to capture a range of possible outcomes and reduce uncertainty. Initial comparisons reveal significant differences between models in key metrics like water table depth and recharge rates, highlighting the need for structured model intercomparisons.
Mariana Gomez, Maximilian Nölscher, Andreas Hartmann, and Stefan Broda
Hydrol. Earth Syst. Sci., 28, 4407–4425, https://doi.org/10.5194/hess-28-4407-2024, https://doi.org/10.5194/hess-28-4407-2024, 2024
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To understand the impact of external factors on groundwater level modelling using a 1-D convolutional neural network (CNN) model, we train, validate, and tune individual CNN models for 505 wells distributed across Lower Saxony, Germany. We then evaluate the performance of these models against available geospatial and time series features. This study provides new insights into the relationship between these factors and the accuracy of groundwater modelling.
Andreas Hartmann, Jean-Lionel Payeur-Poirier, and Luisa Hopp
Hydrol. Earth Syst. Sci., 27, 1325–1341, https://doi.org/10.5194/hess-27-1325-2023, https://doi.org/10.5194/hess-27-1325-2023, 2023
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We advance our understanding of including information derived from environmental tracers into hydrological modeling. We present a simple approach that integrates streamflow observations and tracer-derived streamflow contributions for model parameter estimation. We consider multiple observed streamflow components and their variation over time to quantify the impact of their inclusion for streamflow prediction at the catchment scale.
Romane Berthelin, Tunde Olarinoye, Michael Rinderer, Matías Mudarra, Dominic Demand, Mirjam Scheller, and Andreas Hartmann
Hydrol. Earth Syst. Sci., 27, 385–400, https://doi.org/10.5194/hess-27-385-2023, https://doi.org/10.5194/hess-27-385-2023, 2023
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Karstic recharge processes have mainly been explored using discharge analysis despite the high influence of the heterogeneous surface on hydrological processes. In this paper, we introduce an event-based method which allows for recharge estimation from soil moisture measurements. The method was tested at a karst catchment in Germany but can be applied to other karst areas with precipitation and soil moisture data available. It will allow for a better characterization of karst recharge processes.
Chinchu Mohan, Tom Gleeson, James S. Famiglietti, Vili Virkki, Matti Kummu, Miina Porkka, Lan Wang-Erlandsson, Xander Huggins, Dieter Gerten, and Sonja C. Jähnig
Hydrol. Earth Syst. Sci., 26, 6247–6262, https://doi.org/10.5194/hess-26-6247-2022, https://doi.org/10.5194/hess-26-6247-2022, 2022
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The relationship between environmental flow violations and freshwater biodiversity at a large scale is not well explored. This study intended to carry out an exploratory evaluation of this relationship at a large scale. While our results suggest that streamflow and EF may not be the only determinants of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods or with other biodiversity data or metrics.
Yan Liu, Jaime Fernández-Ortega, Matías Mudarra, and Andreas Hartmann
Hydrol. Earth Syst. Sci., 26, 5341–5355, https://doi.org/10.5194/hess-26-5341-2022, https://doi.org/10.5194/hess-26-5341-2022, 2022
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We adapt the informal Kling–Gupta efficiency (KGE) with a gamma distribution to apply it as an informal likelihood function in the DiffeRential Evolution Adaptive Metropolis DREAM(ZS) method. Our adapted approach performs as well as the formal likelihood function for exploring posterior distributions of model parameters. The adapted KGE is superior to the formal likelihood function for calibrations combining multiple observations with different lengths, frequencies and units.
Vili Virkki, Elina Alanärä, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu
Hydrol. Earth Syst. Sci., 26, 3315–3336, https://doi.org/10.5194/hess-26-3315-2022, https://doi.org/10.5194/hess-26-3315-2022, 2022
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Direct and indirect human actions have altered streamflow across the world since pre-industrial times. Here, we apply a method of environmental flow envelopes (EFEs) that develops the existing global environmental flow assessments by methodological advances and better consideration of uncertainty. By assessing the violations of the EFE, we comprehensively quantify the frequency, severity, and trends of flow alteration during the past decades, illustrating anthropogenic effects on streamflow.
Yong Chang, Benjamin Mewes, and Andreas Hartmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-77, https://doi.org/10.5194/hess-2022-77, 2022
Revised manuscript not accepted
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This study presents a work to investigate the feasibility of using EC to predict the discharge in a typical karst catchment. We found that the spring discharge can be well predicted by EC in storms using LSTM (Long Short Term Memory) model, while the prediction has relatively large uncertainties in small recharge events. To establish a roust LSTM model for long-term discharge prediction from EC in ungauged catchments, the random or fixed-interval discharge monitoring strategy is recommended.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
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Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Tesfalem Abraham, Yan Liu, Sirak Tekleab, and Andreas Hartmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-271, https://doi.org/10.5194/hess-2021-271, 2021
Preprint withdrawn
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In this study we demonstrate the use of global data products for the regionalization of model parameters. We combine three steps of uncertainty quantification from the parameter sampling, best parameter sets identification, and spatial cross-validation. Our results show the best validation parameters provide the most robust regionalization results, and the uncertainties from the regionalization in the ungauged catchments are higher than those obtained from simulations in the gauged catchments.
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Short summary
Analysis of karst spring recession is essential for management of groundwater. In karst, recession is dominated by slow and fast components; separating these components is by manual and subjective approaches. In our study, we tested the applicability of automated streamflow recession extraction procedures for a karst spring. Results showed that, by simple modification, streamflow extraction methods can identify slow and fast components: derived recession parameters are within reasonable ranges.
Analysis of karst spring recession is essential for management of groundwater. In karst,...