Articles | Volume 27, issue 6
https://doi.org/10.5194/hess-27-1325-2023
© Author(s) 2023. 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-27-1325-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Mar 2023
Research article |
| 28 Mar 2023
| 28 Mar 2023
Incorporating experimentally derived streamflow contributions into model parameterization to improve discharge prediction
Andreas Hartmann
CORRESPONDING AUTHOR
Chair of Hydrological Modeling and Water Resources, University of Freiburg, Freiburg, Germany
Institute of Groundwater Management, Technical University of Dresden, 01069 Dresden, Germany
Department of Civil Engineering, University of Bristol, Bristol, United Kingdom
Jean-Lionel Payeur-Poirier
Department of Hydrology, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, Bayreuth, Germany
Luisa Hopp
Department of Hydrology, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, Bayreuth, Germany
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Karst groundwater systems are vital but highly sensitive to climate change. Their complex underground flow makes them hard to manage without good data, so we gathered 118 high-quality records of spring discharge across Mediterranean mountain ranges. With an average of 19 years of data – including one nearly century-long record – this collection provides the detailed information needed to better predict water availability and protect these vulnerable groundwater sources.
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We developed the first global database of water from karst springs and cave drips that records different forms of oxygen and hydrogen, which naturally trace how rainwater moves through rocks. By gathering and checking thousands of measurements from around the globe and linking them with flow and rainfall data, the database provides a comprehensive view of water movement, allows scientists to compare regions, understand groundwater processes, and support sustainable water management worldwide.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Preprint withdrawn
Short summary
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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
Short summary
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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.
Pauline C. Treble, Yining Zang, Nikita Kaushal, István G. Hatvani, Péter Tanos, Zoltan Kern, Andy Baker, Andreas Hartmann, Franziska A. Lechleitner, Bryce Belanger, Bruna Daudt de Oliveira, Will Sinclair, Dana F. C. Riechelmann, András Hidas, Kei Yoshimura, Laia Comas-Bru, and the SISAL working group members
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-31, https://doi.org/10.5194/essd-2026-31, 2026
Preprint under review for ESSD
Short summary
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Water dripping from cave ceilings is studied to understand how water moves from the surface to the cave. This has applications for palaeoclimate, groundwater and cave conservation studies. We present a new database containing water isotope measurements for drip water and rainfall at 75 cave locations globally. The database is a SISAL working group initiative (Speleothem Isotopes Synthesis and AnaLysis) and complements cave speleothem databases previously constructed by SISAL.
Süleyman Selim Çallı, Kübra Özdemir Çallı, Brahim Akdim, Bruno Arfib, Aleksey Benderev, Sandra Beranger, Avi Burg, Onur Can, Jean-Baptiste Charlier, Mehmet Çelik, Arda Melih Çetin, Fehdi Chemseddine, Miroslava Deliyska, Lucio Di Matteo, Marco Dionigi, Romeo Eftimi, Jutta Eybl, Davide Fronzi, Nico Goldscheider, Ergin Gökkaya, Jorge Jodar, Herve Jourde, Eva Kaminsky, Konstantina Katsanou, Alireza Kavousi, Melike Kaya, David Labat, Tanja Liesch, Peter Malik, Christian Massari, Cyril Mayaud, Naomi Mazzilli, Pavel Pracny, Natasa Ravbar, Nathan Rispal, Simon Seelig, Vianney Sivelle, Marc Steinmann, Daniela Valigi, Gerfried Winkler, Ahmet Kemal Yahşi, and Andreas Hartmann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-281, https://doi.org/10.5194/essd-2026-281, 2026
Preprint under review for ESSD
Short summary
Short summary
Karst groundwater systems are vital but highly sensitive to climate change. Their complex underground flow makes them hard to manage without good data, so we gathered 118 high-quality records of spring discharge across Mediterranean mountain ranges. With an average of 19 years of data – including one nearly century-long record – this collection provides the detailed information needed to better predict water availability and protect these vulnerable groundwater sources.
Yining Zang, Pauline C. Treble, Kei Yoshimura, Jayson Gabriel Pinza, Fengbo Zhang, Kübra Özdemir Çallı, Xiaojun Mei, Admin Husic, Alena Gessert, Andrej Stroj, Bartolomé Andreo, Bernard Ladouche, Christine Stumpp, Diana Mance, Eleni Zagana, Fen Huang, Giuseppe Sappa, Harald Kunstmann, Heike Brielmann, Hong Zhou, Huaying Wu, Jakob Garvelmann, James Berglund, Jean-Baptiste Charlier, Jens Lange, Juan Antonio Barberá Fornell, Junbing Pu, Konstantina Katsanou, Kun Ren, Laura Toran, Laurence Gill, Maria Filippini, Martin Kralik, Matías Mudarra Martínez, Min Zhao, Mingming Luo, Nico Goldscheider, Nikolaos Lambrakis, Pantaleone De Vita, Qiong Xiao, Shi Yu, Silvia Iacurto, Silvio Coda, Ted McCormack, Vincenzo Allocca, W. George Darling, Walter D’Alessandro, Xulei Guo, Yundi Hu, Zhijun Wang, Eva Kaminsky, Jiří Faimon, Marek Lang, Pavel Pracný, and Andreas Hartmann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-812, https://doi.org/10.5194/essd-2025-812, 2026
Preprint under review for ESSD
Short summary
Short summary
We developed the first global database of water from karst springs and cave drips that records different forms of oxygen and hydrogen, which naturally trace how rainwater moves through rocks. By gathering and checking thousands of measurements from around the globe and linking them with flow and rainfall data, the database provides a comprehensive view of water movement, allows scientists to compare regions, understand groundwater processes, and support sustainable water management worldwide.
Robert Reinecke, Tanjila Akhter, 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, Wim Thiery, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
Geosci. Model Dev., 19, 523–542, https://doi.org/10.5194/gmd-19-523-2026, https://doi.org/10.5194/gmd-19-523-2026, 2026
Short summary
Short summary
Here we describe a collaborative effort to improve predictions of how climate change will affect groundwater. The ISIMIP (The Inter-Sectoral Impact Model Intercomparison Project) 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.
Emanuel Thoenes, Theresa Blume, Markus Weiler, Bernhard Kohl, Luisa Hopp, and Stefan Achleitner
EGUsphere, https://doi.org/10.5194/egusphere-2025-5110, https://doi.org/10.5194/egusphere-2025-5110, 2025
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Subsurface stormflow (SSF) is a key runoff mechanism in upland environments. The analysis of SSF at two trenched hillslopes showed that SSF volume was controlled by total rainfall and initial wetness, with threshold behaviour observed at one site. Peakflow depended on rainfall amount, with initial wetness and rainfall intensity being important for small and large events, respectively. The rate at which SSF increased was linked to rainfall intensity and amount.
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
Short summary
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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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Katharina Blaurock, Burkhard Beudert, and Luisa Hopp
Hydrol. Earth Syst. Sci., 29, 2377–2391, https://doi.org/10.5194/hess-29-2377-2025, https://doi.org/10.5194/hess-29-2377-2025, 2025
Short summary
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The release of carbon from landscapes into streams is one important component within the global carbon cycle. We measured the concentrations of dissolved organic carbon (DOC), one of the forms in which carbon can be present, in the streams of three nested forested subcatchments over 12 months. The export of DOC is closely linked to water flow processes within the subcatchments, but the interplay of soils, vegetation, topography, and microclimate results in distinct seasonal DOC release patterns.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Tunde Olarinoye, Tom Gleeson, and Andreas Hartmann
Hydrol. Earth Syst. Sci., 26, 5431–5447, https://doi.org/10.5194/hess-26-5431-2022, https://doi.org/10.5194/hess-26-5431-2022, 2022
Short summary
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.
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
Short summary
Short summary
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.
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
Preprint withdrawn
Short summary
Short summary
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
Short summary
Short summary
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).
Katharina Blaurock, Burkhard Beudert, Benjamin S. Gilfedder, Jan H. Fleckenstein, Stefan Peiffer, and Luisa Hopp
Hydrol. Earth Syst. Sci., 25, 5133–5151, https://doi.org/10.5194/hess-25-5133-2021, https://doi.org/10.5194/hess-25-5133-2021, 2021
Short summary
Short summary
Dissolved organic carbon (DOC) is an important part of the global carbon cycle with regards to carbon storage, greenhouse gas emissions and drinking water treatment. In this study, we compared DOC export of a small, forested catchment during precipitation events after dry and wet preconditions. We found that the DOC export from areas that are usually important for DOC export was inhibited after long drought periods.
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
Short summary
Short summary
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.
Cited articles
Appels, W. M., Graham, C. B., Freer, J. E., and McDonnell, J. J.:
Factors affecting the spatial pattern of bedrock groundwater recharge at the hillslope scale, Hydrol. Process., 29, 4594–4610, https://doi.org/10.1002/hyp.10481, 2015.
Bachmair, S. and Weiler, M.:
New Dimensions of Hillslope Hydrology, in: Forest Hydrology and Biogeochemistry, vol. 216, edited by: Levia, D. F., Carlyle-Moses, D., and Tanaka, T., Springer Netherlands, Dordrecht, 455–482, https://doi.org/10.1007/978-94-007-1363-5, 2011.
Barthold, F. K. and Woods, R. A.:
Stormflow generation: A meta-analysis of field evidence from small, forested catchments, Water Resour. Res., 51, 3730–3753, https://doi.org/10.1002/2014WR016221, 2015.
Beck, H., Van Dijk, A., Miralles, D., McVicar, T., Schellekens, J., and Adrian, Bruijnzeel.: Global-scale regionalization of hydrologic model parameters, Water Resour. Res., 3599–3622, https://doi.org/10.1002/2015WR018247, 2010.
Bergström, S., Lindström, G., and Pettersson, A.:
Multi-variable parameter estimation to increase confidence in hydrological modelling, Hydrol. Process., 16, 413–421, https://doi.org/10.1002/hyp.332, 2002.
Beven, K.:
A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Beven, K. J. and Binley, A.:
The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
Beven, K. J. and Kirkby, M. J.:
A physically based, variable contributing area model of basin hydrology, Hydrol. Sci. B., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.
Birkel, C. and Soulsby, C.:
Advancing tracer-aided rainfall-runoff modelling: A review of progress, problems and unrealised potential, Hydrol. Process., 29, 5227–5240, https://doi.org/10.1002/hyp.10594, 2015.
Birkel, C., Soulsby, C., and Tetzlaff, D.:
Modelling catchment-scale water storage dynamics: Reconciling dynamic storage with tracer-inferred passive storage, Hydrol. Process., 25, 3924–3936, https://doi.org/10.1002/hyp.8201, 2011.
Birkel, C., Soulsby, C., and Tetzlaff, D.:
Developing a consistent process-based conceptualization of catchment functioning using measurements of internal state variables, Water Resour. Res., 50, 3481–3501, https://doi.org/10.1002/2013WR014925, 2014.
Bishop, K., Seibert, J., Köhler, S., and Laudon, H.:
Resolving the Double Paradox of rapidly mobilized old water highly variable responses in runoff chemistry, Hydrol. Process., 18, 185–189, https://doi.org/10.1002/hyp.5209, 2004.
Bishop, K. H., Grip, H., and O'Neill, A.:
The origins of acid runoff in a hillslope during storm events, J. Hydrol., 116, 35–61, https://doi.org/10.1016/0022-1694(90)90114-D, 1990.
Blume, T., van Meerveld, I., and Weiler, M.:
The role of experimental work in hydrological sciences – insights from a community survey, Hydrolog. Sci. J., 62, 1–4, https://doi.org/10.1080/02626667.2016.1230675, 2016.
Bremicker, M.: Das Wasserhaushaltsmodell LARSIM, Modellgrundlagen und Anwendungsbeispiele, Freiburger Schriften zur Hydrologie, Insitut für Hydrologie, Universität Freiburg, Freiburg, 130 pp., ISSN 0945-1609, 2000.
Brown, V. A., McDonnell, J. J., Burns, D. A., and Kendall, C.:
The role of event water, a rapid shallow flow component, and catchment size in summer stormflow, J. Hydrol., 217, 171–190, https://doi.org/10.1016/S0022-1694(98)00247-9, 1999.
Burns, D. A., McDonnell, J. J., Hooper, R. P., Peters, N. E., Freer, J. E., Kendall, C., and Beven, K.:
Quantifying contributions to storm runoff through end-member mixing analysis and hydrologic measurements at the Panola Mountain research watershed (Georgia, USA), Hydrol. Process., 15, 1903–1924, https://doi.org/10.1002/hyp.246, 2001.
Capell, R., Tetzlaff, D., and Soulsby, C.: Can time domain and source area tracers reduce uncertainty in rainfall-runoff models in larger heterogeneous catchments?, Water Resour. Res., 48, W09544, https://doi.org/10.1029/2011WR011543, 2012.
Chang, Y., Hartmann, A., Liu, L., Jiang, G., and Wu, J.:
Identifying more realistic model structures by electrical conductivity observations of the karst spring, OSF Preprints, https://doi.org/10.31219/osf.io/gw876, 2020.
Chen, Z., Hartmann, A., Wagener, T., and Goldscheider, N.:
Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions, Hydrol. Earth Syst. Sci., 22, 3807–3823, https://doi.org/10.5194/hess-22-3807-2018, 2018.
Chifflard, P., Blume, T., Maerker, K., Hopp, L., van Meerveld, I., Graef, T., Gronz, O., Hartmann, A., Kohl, B., Martini, E., Reinhardt-Imjela, C., Reiss, M., Rinderer, M., and Achleitner, S.:
How can we model subsurface stormflow at the catchment scale if we cannot measure it?, Hydrol. Process., 33, 1378–1385, https://doi.org/10.1002/hyp.13407, 2019.
Christophersen, N. and Hooper, R. P.:
Multivariate Analysis of Stream Water Chemical Data: The Use of Principal Components Analysis for the End-Member Mixing Problem, Water Resour. Res., 28, 99–107, https://doi.org/10.1029/91wr02518, 1992.
Cirmo, C. P. and McDonnell, J. J.: Linking the hydrologic and biogeochemical controls of nitrogen transport in near-stream zones of temperate-forested catchments: a review, J. Hydrol., 199, 88–120, 1997.
Clark, M. P., Slater, A. G., Rupp, D. E., Woods, R. A., Vrugt, J. A., Gupta, H. V., Wagener, T., and Hay, L. E.:
Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models, Water Resour. Res., 44, 1–14, https://doi.org/10.1029/2007wr006735, 2008.
Du, E., Rhett Jackson, C., Klaus, J., McDonnell, J. J., Griffiths, N. A., Williamson, M. F., Greco, J. L., and Bitew, M.:
Interflow dynamics on a low relief forested hillslope: Lots of fill, little spill, J. Hydrol., 534, 648–658, https://doi.org/10.1016/j.jhydrol.2016.01.039, 2016.
DVWK: Ermittlung der Verdunstung, 238th Edn., DWA, 134 pp., ISBN 978-3-935067-84-3, 1996.
Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L., Brooks, P. D., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W., Mackay, D. S., McDonnell, J. J., Milly, P. C. D., Sullivan, P. L., Tague, C., Ajami, H., Chaney, N., Hartmann, A., Hazenberg, P., McNamara, J., Pelletier, J., Perket, J., Rouholahnejad-Freund, E., Wagener, T., Zeng, X., Beighley, E., Buzan, J., Huang, M., Livneh, B., Mohanty, B. P., Nijssen, B., Safeeq, M., Shen, C., van Verseveld, W., Volk, J., and Yamazaki, D.:
Hillslope Hydrology in Global Change Research and Earth System Modeling, Water Resour. Res., https://doi.org/10.1029/2018WR023903, 2019.
Freer, J., McDonnell, J. J., Beven, K. J., Peters, N. E., Burns, D. A., Hooper, R. P., Aulenbach, B., and Kendall, C.:
The role of bedrock topography on subsurface storm flow, Water Resour. Res., 38, 5–1-5–16, https://doi.org/10.1029/2001wr000872, 2002.
Genereux, D.:
Quantifying uncertainty in tracer-based hydrograph separations, Water Resour. Res., 34, 915–919, https://doi.org/10.1029/98WR00010, 1998.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.:
Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Hartmann, A., Wagener, T., Rimmer, A., Lange, J., Brielmann, H., and Weiler, M.: Testing the realism of model structures to identify karst system processes using water quality and quantity signatures, Water Resour. Res., 49, 3345–3358, https://doi.org/10.1002/wrcr.20229, 2013.
Hartmann, A., Barberá, J. A., and Andreo, B.:
On the value of water quality data and informative flow states in karst modelling, Hydrol. Earth Syst. Sci., 21, 5971–5985, https://doi.org/10.5194/hess-21-5971-2017, 2017.
Holmes, T. L., Stadnyk, T. A., Asadzadeh, M., and Gibson, J. J.: Variability in flow and tracer-based performance metric sensitivities reveal regional differences in dominant hydrological processes across the Athabasca River basin, J. Hydrol. Reg. Stud., 41, 101088, https://doi.org/10.1016/j.ejrh.2022.101088, 2022.
Hopp, L. and McDonnell, J. J.:
Connectivity at the hillslope scale: Identifying interactions between storm size, bedrock permeability, slope angle and soil depth, J. Hydrol., 376, 378–391, https://doi.org/10.1016/j.jhydrol.2009.07.047, 2009.
Hooper, R. P., Christophersen, N., and Peters, N. E.:
Modelling streamwater chemistry as a mixture of soilwater end-members - An application to the Panola Mountain catchment, Georgia, U. S. A., J. Hydrol., 116, 321–343, https://doi.org/10.1016/0022-1694(90)90131-G, 1990.
Inamdar, S., Dhillon, G., Singh, S., Dutta, S., Levia, D., Scott, D., Mitchell, M., Van Stan, J., and McHale, P.:
Temporal variation in end-member chemistry and its influence on runoff mixing patterns in a forested, Piedmont catchment, Water Resour. Res., 49, 1828–1844, https://doi.org/10.1002/wrcr.20158, 2013.
Institute of Groundwater Management: Modified HBV model, GitHub [code and data set], https://github.com/iGW-TU-Dresden/HBV_modified, last access: 25 March 2023.
Jakeman, A. J. and Hornberger, G. M.:
How much complexity is warranted in a rainfall-runoff model?, Water Resour. Res., 29, 2637–2649, https://doi.org/10.1029/93WR00877, 1993.
Kendall, C., McDonnell, J. J., and Gu, W.:
A look inside “black box” hydrograph separation models: A study at the hydrohill catchment, Hydrol. Process., 15, 1877–1902, https://doi.org/10.1002/hyp.245, 2001.
Klaus, J. and Jackson, C. R.:
Interflow Is Not Binary: A Continuous Shallow Perched Layer Does Not Imply Continuous Connectivity, Water Resour. Res., 54, 5921–5932, https://doi.org/10.1029/2018WR022920, 2018.
Knoben, W. J. M., Freer, J. E., and Woods, R. A.:
Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, 2019.
Kuczera, G. and Mroczkowski, M.:
Assessment of hydrologic parameter uncertainty and the worth of multiresponse data, Water Resour. Res., 34, 1481–1489, https://doi.org/10.1029/98WR00496, 1998.
Leavesley, G. H., Lichty, R. W., Troutman, B. M., and Saindon, L. G.:
Precipitation-runoff modeling system: User's manual, Water-resources investigations report 83, 4238 pp., https://doi.org/10.3133/wri834238, 1983.
Ledesma, J. L. J., Kothawala, D. N., Bastviken, P., Maehder, S., Grabs, T., and Futter, M. N.:
Stream Dissolved Organic Matter Composition Reflects the Riparian Zone, Not Upslope Soils in Boreal Forest Headwaters, Water Resour. Res., 54, 3896–3912, https://doi.org/10.1029/2017WR021793, 2018.
Lee, M.-H., Payeur-Poirier, J.-L., Park, J.-H., and Matzner, E.:
Variability in runoff fluxes of dissolved and particulate carbon and nitrogen from two watersheds of different tree species during intense storm events, Biogeosciences, 13, 5421–5432, https://doi.org/10.5194/bg-13-5421-2016, 2016.
Lindström, G., Johannson, B., Perrson, M., Gardelin, M., and Bergström, S.:
Development and test of the distributed HBV-96 hydrological model, J. Hydrol., 201, 272–288, 1997.
Markart, G., Römer, A., Bieber, G., Pirkl, H., Klebinder, K., Hörfarter, C., Ita, A., Jochum, B., Kohl, B., and Motschka, K.: Assessment of Shallow Interflow Velocities in Alpine Catchments for the Improvement of Hydrological Modelling BT, in: Engineering Geology for Society and Territory – Volume 3, Springer, 611–615, https://doi.org/10.1007/978-3-319-09054-2_122, 2015.
Markstrom, S. L., Regan, R. S., Hay, L. E., Viger, R. J., Webb, R. M. T., Payn, R. A., and LaFontaine, J. H.: PRMS-IV, the precipitation-runoff modeling system, version 4, US Geological Survey Techniques and Methods, US Geological Survey, https://doi.org/10.3133/tm6B7, 2015.
Mayer-Anhalt, L., Birkel, C., Sánchez-Murillo, R., and Schulz, S.:
Tracer-aided modelling reveals quick runoff generation and young streamflow ages in a tropical rainforest catchment, Hydrol. Process., 36, e14508, https://doi.org/10.1002/hyp.14508, 2022.
McDonnell, J. J., Stewart, M. K., and Owens, I. F.:
Effect of Catchment-Scale Subsurface Mixing on Stream Isotopic Response, Water Resour. Res., 27, 3065–3073, https://doi.org/10.1029/91WR02025, 1991.
McMillan, H., Tetzlaff, D., Clark, M., and Soulsby, C.: Do time-variable tracers aid the evaluation of hydrological model structure? A multimodel approach, Water Resour. Res., 48, W05501, https://doi.org/10.1029/2011WR011688, 2012.
Mudarra, M., Hartmann, A., and Andreo, B.: Combining Experimental Methods and Modeling to Quantify the Complex Recharge Behavior of Karst Aquifers, Water Resour. Res., 55, 1384–1404, https://doi.org/10.1029/2017WR021819, 2019.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., and Williams, J. R.:
Soil & Water Assessment Tool Theoretical Documentation Version 2009, Texas Water Resources Institute, 1–647, https://doi.org/10.1016/j.scitotenv.2015.11.063, 2011.
Nicolle, P., Pushpalatha, R., Perrin, C., François, D., Thiéry, D., Mathevet, T., Le Lay, M., Besson, F., Soubeyroux, J.-M., Viel, C., Regimbeau, F., Andréassian, V., Maugis, P., Augeard, B., and Morice, E.:
Benchmarking hydrological models for low-flow simulation and forecasting on French catchments, Hydrol. Earth Syst. Sci., 18, 2829–2857, https://doi.org/10.5194/hess-18-2829-2014, 2014.
Payeur-Poirier, J.-L.:
Hydrological Dynamics of Forested Catchments as Influenced by the East Asian Summer Monsoon, PhD thesis, University of Bayreuth, Bayreuth, 165 pp., 2018.
Perrin, C., Michel, C., and Andréassian, V.:
Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments, J. Hydrol., 242, 275–301, https://doi.org/10.1016/S0022-1694(00)00393-0, 2001.
Robson, A., Jenkins, A., and Neal, C.:
Towards predicting future episodic changes in stream chemistry, J. Hydrol., 125, 161–174, https://doi.org/10.1016/0022-1694(91)90027-F, 1991.
Robson, A., Beven, K., and Neal, C.:
Towards identifying sources of subsurface flow: A comparison of components identified by a physically based runoff model and those determined by chemical mixing techniques, Hydrol. Process., 6, 199–214, https://doi.org/10.1002/hyp.3360060208, 1992.
Rodell, B. Y. M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J. K., Walker, J. P., Lohmann, D., and Toll, D.: The Global Land Data Assimilation System, B. Am. Meteorol. Soc., 85, 381–394, https://doi.org/10.1175/BAMS-85-3-381, 2004.
Sarrazin, F., Hartmann, A., Pianosi, F., Rosolem, R., and Wagener, T.:
V2Karst V1.1: a parsimonious large-scale integrated vegetation–recharge model to simulate the impact of climate and land cover change in karst regions, Geosci. Model Dev., 11, 4933–4964, https://doi.org/10.5194/gmd-11-4933-2018, 2018.
Schulla, J. and Jasper, K.: Model description WaSiM-ETH (Water balance Simulation Model ETH), Institute for Atmospheric and Climate Science, Zurich, 181 pp., 2007.
Seibert, J. and McDonnell, J. J.:
On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration, Water Resour. Res., 38, 23–1-23–14, https://doi.org/10.1029/2001wr000978, 2002.
Seibert, J. and Vis, M. J. P.:
Teaching hydrological modeling with a user-friendly catchment-runoff-model software package, Hydrol. Earth Syst. Sci., 16, 3315–3325, https://doi.org/10.5194/hess-16-3315-2012, 2012.
Seibert, J., Rodhe, A., and Bishop, K.:
Simulating interactions between saturated and unsaturated storage in a conceptual runoff model, Hydrol. Process., 17, 379–390, https://doi.org/10.1002/hyp.1130, 2003.
Sklash, M. G., Farvolden, R. N., and Farvolden, R. N.:
The role of groundwater in storm runoff, Dev. Water Sci., 12, 45–65, https://doi.org/10.1016/S0167-5648(09)70009-7, 1979.
Son, K. and Sivapalan, M.:
Improving model structure and reducing parameter uncertainty in conceptual water balance models through the use of auxiliary data, Water Resour. Res., 43, 1–18, https://doi.org/10.1029/2006WR005032, 2007.
Sprenger, M., Volkmann, T. H. M., Blume, T., and Weiler, M.:
Estimating flow and transport parameters in the unsaturated zone with pore water stable isotopes, Hydrol. Earth Syst. Sci., 19, 2617–2635, https://doi.org/10.5194/hess-19-2617-2015, 2015.
Stadnyk, T. A., Delavau, C., Kouwen, N., and Edwards, T. W. D.:
Towards hydrological model calibration and validation: Simulation of stable water isotopes using the isoWATFLOOD model, Hydrol. Process., 27, 3791–3810, https://doi.org/10.1002/hyp.9695, 2013.
Tromp-Van Meerveld, H. J. and McDonnell, J. J.:
Threshold relations in subsurface stormflow: 2. The fill and spill hypothesis, Water Resour. Res., 42, 1–11, https://doi.org/10.1029/2004WR003800, 2006.
Uhlenbrook, S. and Leibundgut, C.: Integration of tracer information into the development of a rainfall-runoff model, IAHS Publ., 258, 93–100, 1999.
Uhlenbrook, S., Holocher, J., Leibundgut, C., and Seibert, J.:
Using a conceptual rainfall-runoff model on different scales by comparing a headwater with larger basins, IAHS Publications – Series of Proceedings and Reports – Intern Assoc Hydrological Sciences, 248, 297–306, 1998.
Uhlenbrook, S., Seibert, J., Leibundgut, C., and Rodhe, A.:
Incertitude de prévision d'un modèle conceptuel pluie-débit due à l'identification des paramètres et de la structure du modèle, Hydrolog. Sci. J., 44, 779–797, https://doi.org/10.1080/02626669909492273, 1999.
Vrugt, J. A., Stauffer, P. H., Wöhling, Th., Robinson, B. A., and Vesselinov, V. V.:
Inverse Modeling of Subsurface Flow and Transport Properties: A Review with New Developments, Vadose Zone J., 7, 843–864, https://doi.org/10.2136/vzj2007.0078, 2008.
Wagener, T. and Gupta, H. V.:
Model identification for hydrological forecasting under uncertainty, Stoch. Env. Res. Risk A., 19, 378–387, https://doi.org/10.1007/s00477-005-0006-5, 2005.
Wendling, U., Schellin, H.-G., and Thomae, M.: Bereitstellung von täglichen Informationen zum Wasserhaushalt des Bodens für die Zwecke der agrarmeteorologischen Beratung, Z. Meteorol., 41, 468–474, 1991.
Wheater, H. S., Bishop, K. H., and Beck, M. B.:
The identification of conceptual hydrological models for surface water acidification, Hydrol. Process., 1, 89–109, https://doi.org/10.1002/hyp.3360010109, 1986.
WMO: Manual on Stream Gauging, Vol. II – Computation of discharge, WMO Library, 198 pp., WMO – World Meteorological Organization, ISBN 978-92-63-11044-2, 2010.
Woods, R. and Rowe, L.:
The changing spatial variability of subsurface flow across a hillside, Journal of Hydrology New Zealand, 35, 51–86, 1996.
Yang, X., Tetzlaff, D., Soulsby, C., Smith, A., and Borchardt, D.:
Catchment Functioning Under Prolonged Drought Stress: Tracer-Aided Ecohydrological Modeling in an Intensively Managed Agricultural Catchment, Water Resour. Res., 57, e2020WR029094, https://doi.org/10.1029/2020WR029094, 2021.
Ye, W., Bates, B. C., Viney, N. R., Sivapalan, M., and Jakeman, A. J.:
Performance of conceptual rainfall-runoff models in low-yielding ephemeral catchments, Water Resour. Res., 33, 153–166, https://doi.org/10.1029/96wr02840, 1997.
Zhao, P., Tang, X., Zhao, P., Wang, C., and Tang, J.:
Identifying the water source for subsurface flow with deuterium and oxygen-18 isotopes of soil water collected from tension lysimeters and cores, J. Hydrol., 503, 1–10, https://doi.org/10.1016/j.jhydrol.2013.08.033, 2013.
Zillgens, B., Merz, B., Kirnbauer, R., and Tilch, N.:
Analysis of the runoff response of an alpine catchment at different scales, Hydrol. Earth Syst. Sci., 11, 1441–1454, https://doi.org/10.5194/hess-11-1441-2007, 2007.
Short summary
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.
We advance our understanding of including information derived from environmental tracers into...
