Articles | Volume 25, issue 12
https://doi.org/10.5194/hess-25-6437-2021
© 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-25-6437-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Bending of the concentration discharge relationship can inform about in-stream nitrate removal
Department of Hydrogeology, UFZ – Helmholtz-Centre for Environmental Research, 04318 Leipzig, Germany
Unit Environmental Modeling, Flemish Institute for Technological Research NV – VITO, Boeretang 200, 2400, Mol, Belgium
Fanny Sarrazin
Department Computational Hydrosystems, UFZ – Helmholtz-Centre for Environmental Research, 04318 Leipzig, Germany
Rohini Kumar
Department Computational Hydrosystems, UFZ – Helmholtz-Centre for Environmental Research, 04318 Leipzig, Germany
Jan H. Fleckenstein
Department of Hydrogeology, UFZ – Helmholtz-Centre for Environmental Research, 04318 Leipzig, Germany
Bayreuth Center of Ecology and Environmental Research, University of Bayreuth, 95440 Bayreuth, Germany
Andreas Musolff
Department of Hydrogeology, UFZ – Helmholtz-Centre for Environmental Research, 04318 Leipzig, Germany
Related authors
No articles found.
Vishal Thakur, Yannis Markonis, Rohini Kumar, Johanna Ruth Thomson, Mijael Rodrigo Vargas Godoy, Martin Hanel, and Oldrich Rakovec
Hydrol. Earth Syst. Sci., 29, 4395–4416, https://doi.org/10.5194/hess-29-4395-2025, https://doi.org/10.5194/hess-29-4395-2025, 2025
Short summary
Short summary
Understanding the changes in water movement in earth is crucial for everyone. To quantify this water movement there are several techniques. We examined how different methods of estimating evaporation impact predictions of various types of water movement across Europe. We found that, while these methods generally agree on whether changes are increasing or decreasing, they differ in magnitude. This means selecting the right evaporation method is crucial for accurate predictions of water movement.
Álvaro Pardo-Álvarez, Jan H. Fleckenstein, Kalliopi Koutantou, and Philip Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3521, https://doi.org/10.5194/egusphere-2025-3521, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
An upgraded version of a numerical solver is introduced to better capture the three-dimensional interactions between surface water and groundwater. Built using open-source software, it adds new features to handle the complexity of real environments, including the representation of subsurface geology and the simulation of diverse dynamic processes, such as solute transport and heat transfer, in both domains. A test case and a full description of the novel features are provided in this paper.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, Yannis Markonis, and Miroslav Trnka
Hydrol. Earth Syst. Sci., 29, 3341–3358, https://doi.org/10.5194/hess-29-3341-2025, https://doi.org/10.5194/hess-29-3341-2025, 2025
Short summary
Short summary
We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, with clusters of 775 and 630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
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.
Hannes Müller Schmied, Simon Newland Gosling, Marlo Garnsworthy, Laura Müller, Camelia-Eliza Telteu, Atiq Kainan Ahmed, Lauren Seaby Andersen, Julien Boulange, Peter Burek, Jinfeng Chang, He Chen, Lukas Gudmundsson, Manolis Grillakis, Luca Guillaumot, Naota Hanasaki, Aristeidis Koutroulis, Rohini Kumar, Guoyong Leng, Junguo Liu, Xingcai Liu, Inga Menke, Vimal Mishra, Yadu Pokhrel, Oldrich Rakovec, Luis Samaniego, Yusuke Satoh, Harsh Lovekumar Shah, Mikhail Smilovic, Tobias Stacke, Edwin Sutanudjaja, Wim Thiery, Athanasios Tsilimigkras, Yoshihide Wada, Niko Wanders, and Tokuta Yokohata
Geosci. Model Dev., 18, 2409–2425, https://doi.org/10.5194/gmd-18-2409-2025, https://doi.org/10.5194/gmd-18-2409-2025, 2025
Short summary
Short summary
Global water models contribute to the evaluation of important natural and societal issues but are – as all models – simplified representation of reality. So, there are many ways to calculate the water fluxes and storages. This paper presents a visualization of 16 global water models using a standardized visualization and the pathway towards this common understanding. Next to academic education purposes, we envisage that these diagrams will help researchers, model developers, and data users.
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
Short summary
Short summary
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.
Masooma Batool, Fanny J. Sarrazin, and Rohini Kumar
Earth Syst. Sci. Data, 17, 881–916, https://doi.org/10.5194/essd-17-881-2025, https://doi.org/10.5194/essd-17-881-2025, 2025
Short summary
Short summary
Our paper presents a reconstruction and analysis of the gridded P surplus in European landscapes from 1850 to 2019 at a 5 arcmin resolution. By utilizing 48 different estimates, we account for uncertainties in major components of the P surplus. Our findings highlight substantial historical changes, with the total P surplus in the EU 27 tripling over 170 years. Our dataset enables flexible aggregation at various spatial scales, providing critical insights for land and water management strategies.
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
Short summary
Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
Short summary
Short summary
Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz
Hydrol. Earth Syst. Sci., 27, 2989–3004, https://doi.org/10.5194/hess-27-2989-2023, https://doi.org/10.5194/hess-27-2989-2023, 2023
Short summary
Short summary
We analyzed the uncertainty of the water transit time distribution (TTD) arising from model input (interpolated tracer data) and structure (StorAge Selection, SAS, functions). We found that uncertainty was mainly associated with temporal interpolation, choice of SAS function, nonspatial interpolation, and low-flow conditions. It is important to characterize the specific uncertainty sources and their combined effects on TTD, as this has relevant implications for both water quantity and quality.
Trevor Page, Paul Smith, Keith Beven, Francesca Pianosi, Fanny Sarrazin, Susana Almeida, Liz Holcombe, Jim Freer, Nick Chappell, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 27, 2523–2534, https://doi.org/10.5194/hess-27-2523-2023, https://doi.org/10.5194/hess-27-2523-2023, 2023
Short summary
Short summary
This publication provides an introduction to the CREDIBLE Uncertainty Estimation (CURE) toolbox. CURE offers workflows for a variety of uncertainty estimation methods. One of its most important features is the requirement that all of the assumptions on which a workflow analysis depends be defined. This facilitates communication with potential users of an analysis. An audit trail log is produced automatically from a workflow for future reference.
Michael Rode, Jörg Tittel, Frido Reinstorf, Michael Schubert, Kay Knöller, Benjamin Gilfedder, Florian Merensky-Pöhlein, and Andreas Musolff
Hydrol. Earth Syst. Sci., 27, 1261–1277, https://doi.org/10.5194/hess-27-1261-2023, https://doi.org/10.5194/hess-27-1261-2023, 2023
Short summary
Short summary
Agricultural catchments show elevated phosphorus (P) concentrations during summer low flow. In an agricultural stream, we found that phosphorus in groundwater was a major source of stream water phosphorus during low flow, and stream sediments derived from farmland are unlikely to have increased stream phosphorus concentrations during low water. We found no evidence that riparian wetlands contributed to soluble reactive (SR) P loads. Agricultural phosphorus was largely buffered in the soil zone.
Carolin Winter, Tam V. Nguyen, Andreas Musolff, Stefanie R. Lutz, Michael Rode, Rohini Kumar, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 27, 303–318, https://doi.org/10.5194/hess-27-303-2023, https://doi.org/10.5194/hess-27-303-2023, 2023
Short summary
Short summary
The increasing frequency of severe and prolonged droughts threatens our freshwater resources. While we understand drought impacts on water quantity, its effects on water quality remain largely unknown. Here, we studied the impact of the unprecedented 2018–2019 drought in Central Europe on nitrate export in a heterogeneous mesoscale catchment in Germany. We show that severe drought can reduce a catchment's capacity to retain nitrogen, intensifying the internal pollution and export of nitrate.
Thomas Hermans, Pascal Goderniaux, Damien Jougnot, Jan H. Fleckenstein, Philip Brunner, Frédéric Nguyen, Niklas Linde, Johan Alexander Huisman, Olivier Bour, Jorge Lopez Alvis, Richard Hoffmann, Andrea Palacios, Anne-Karin Cooke, Álvaro Pardo-Álvarez, Lara Blazevic, Behzad Pouladi, Peleg Haruzi, Alejandro Fernandez Visentini, Guilherme E. H. Nogueira, Joel Tirado-Conde, Majken C. Looms, Meruyert Kenshilikova, Philippe Davy, and Tanguy Le Borgne
Hydrol. Earth Syst. Sci., 27, 255–287, https://doi.org/10.5194/hess-27-255-2023, https://doi.org/10.5194/hess-27-255-2023, 2023
Short summary
Short summary
Although invisible, groundwater plays an essential role for society as a source of drinking water or for ecosystems but is also facing important challenges in terms of contamination. Characterizing groundwater reservoirs with their spatial heterogeneity and their temporal evolution is therefore crucial for their sustainable management. In this paper, we review some important challenges and recent innovations in imaging and modeling the 4D nature of the hydrogeological systems.
Felipe A. Saavedra, Andreas Musolff, Jana von Freyberg, Ralf Merz, Stefano Basso, and Larisa Tarasova
Hydrol. Earth Syst. Sci., 26, 6227–6245, https://doi.org/10.5194/hess-26-6227-2022, https://doi.org/10.5194/hess-26-6227-2022, 2022
Short summary
Short summary
Nitrate contamination of rivers from agricultural sources is a challenge for water quality management. During runoff events, different transport paths within the catchment might be activated, generating a variety of responses in nitrate concentration in stream water. Using nitrate samples from 184 German catchments and a runoff event classification, we show that hydrologic connectivity during runoff events is a key control of nitrate transport from catchments to streams in our study domain.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Jie Yang, Qiaoyu Wang, Ingo Heidbüchel, Chunhui Lu, Yueqing Xie, Andreas Musolff, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 26, 5051–5068, https://doi.org/10.5194/hess-26-5051-2022, https://doi.org/10.5194/hess-26-5051-2022, 2022
Short summary
Short summary
We assessed the effect of catchment topographic slopes on the nitrate export dynamics in terms of the nitrogen mass fluxes and concentration level using a coupled surface–subsurface model. We found that flatter landscapes tend to retain more nitrogen mass in the soil and export less nitrogen mass to the stream, explained by the reduced leaching and increased potential of degradation in flat landscapes. We emphasized that stream water quality is potentially less vulnerable in flatter landscapes.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
Short summary
Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel
Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, https://doi.org/10.5194/essd-14-4035-2022, 2022
Short summary
Short summary
This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff
Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, https://doi.org/10.5194/essd-14-3715-2022, 2022
Short summary
Short summary
Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
Guilherme E. H. Nogueira, Christian Schmidt, Daniel Partington, Philip Brunner, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 26, 1883–1905, https://doi.org/10.5194/hess-26-1883-2022, https://doi.org/10.5194/hess-26-1883-2022, 2022
Short summary
Short summary
In near-stream aquifers, mixing between stream water and ambient groundwater can lead to dilution and the removal of substances that can be harmful to the water ecosystem at high concentrations. We used a numerical model to track the spatiotemporal evolution of different water sources and their mixing around a stream, which are rather difficult in the field. Results show that mixing mainly develops as narrow spots, varying In time and space, and is affected by magnitudes of discharge events.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
Short summary
Short summary
The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
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
Short summary
Short summary
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.
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.
Cited articles
Abbott, B. W., Gruau, G., Zarnetske, J. P., Moatar, F., Barbe, L., Thomas, Z., Fovet, O., Kolbe, T., Gu, S., Pierson-Wickmann, A. C., Davy, P., and Pinay, G.: Unexpected spatial stability of water chemistry in headwater stream networks, Ecol. Lett., 21, 296–308, https://doi.org/10.1111/ele.12897, 2018.
Aguilera, R., Marcé, R., and Sabater, S.: Modeling nutrient retention at the watershed scale: Does small stream research apply to the whole river network?, J. Geophys. Res.-Biogeo., 118, 728–740, https://doi.org/10.1002/jgrg.20062, 2013.
Alexander, R. B., Smith, R. A., and Schwarz, G. E.: Effect of stream channel size on the delivery of nitrogen to the Gulf of Mexico, Nature, 403, 758–761, https://doi.org/10.1038/35001562, 2000.
Alexander, R. B., Böhlke, J. K., Boyer, E. W., David, M. B., Harvey, J. W., Mulholland, P. J., Seitzinger, S. P., Tobias, C. R., Tonitto, C., and Wollheim, W. M.: Dynamic modeling of nitrogen losses in river networks unravels the coupled effects of hydrological and biogeochemical processes, Biogeochemistry, 93, 91–116, https://doi.org/10.1007/s10533-008-9274-8, 2009.
Ameli, A. A., Beven, K., Erlandsson, M., Creed, I. F., McDonnell, J. J., and Bishop, K.: Primary weathering rates, water transit times, and concentration-discharge relations: A theoretical analysis for the critical zone, Water Resour. Res., 53, 942–960, https://doi.org/10.1002/2016wr019448, 2017.
Andreadis, K. M., Schumann, G. J. P., and Pavelsky, T.: A simple global river bankfull width and depth database, Water Resour. Res., 49, 7164–7168, https://doi.org/10.1002/wrcr.20440, 2013.
Basu, N. B., Rao, P. S. C., Thompson, S. E., Loukinova, N. V., Donner, S. D., Ye, S., and Sivapalan, M.: Spatiotemporal averaging of in-stream solute removal dynamics, Water Resour. Res., 47, W00J06, https://doi.org/10.1029/2010wr010196, 2011.
Bergstrom, A., McGlynn, B., Mallard, J., and Covino, T.: Watershed structural influences on the distributions of stream network water and solute travel times under baseflow conditions, Hydrol. Process., 30, 2671–2685, https://doi.org/10.1002/hyp.10792, 2016.
Bertuzzo, E., Helton, A. M., Hall, R. O., and Battin, T. J.: Scaling of dissolved organic carbon removal in river networks, Adv. Water Resour., 110, 136–146, https://doi.org/10.1016/j.advwatres.2017.10.009, 2017.
Beusen, A. H. W., Bouwman, A. F., Van Beek, L. P. H., Mogollón, J. M., and Middelburg, J. J.: Global riverine N and P transport to ocean increased during the 20th century despite increased retention along the aquatic continuum, Biogeosciences, 13, 2441–2451, https://doi.org/10.5194/bg-13-2441-2016, 2016.
Bieroza, M. Z., Heathwaite, A. L., Bechmann, M., Kyllmar, K., and Jordan, P.: The concentration-discharge slope as a tool for water quality management, Sci. Total Environ., 630, 738–749, https://doi.org/10.1016/j.scitotenv.2018.02.256, 2018.
Billen, G., Lancelot, C., and Meybeck, M.: N, P and Si retention along the aquatic continuum from land to ocean, in: Ocean Margin Processes in Global Change, 1st Edn., John Wiley & Sons, 19–44, 1991.
Birgand, F., Skaggs, R. W., Chescheir, G. M., and Gilliam, J. W.: Nitrogen removal in streams of agricultural catchments – A literature review, Crit. Rev. Env. Sci. Tec., 37, 381–487, https://doi.org/10.1080/10643380600966426, 2007.
Botter, G., Basso, S., Rodriguez-Iturbe, I., and Rinaldo, A.: Resilience of river flow regimes, P. Natl. Acad. Sci. USA, 110, 12925–12930, https://doi.org/10.1073/pnas.1311920110, 2013.
Bouwman, A. F., Bierkens, M. F. P., Griffioen, J., Hefting, M. M., Middelburg, J. J., Middelkoop, H., and Slomp, C. P.: Nutrient dynamics, transfer and retention along the aquatic continuum from land to ocean: towards integration of ecological and biogeochemical models, Biogeosciences, 10, 1–22, https://doi.org/10.5194/bg-10-1-2013, 2013.
Boyer, E. W., Alexander, R. B., Parton, W. J., Li, C. S., Butterbach-Bahl, K., Donner, S. D., Skaggs, R. W., and Del Gross, S. J.: Modeling denitrification in terrestrial and aquatic ecosystems at regional scales, Ecol. Appl., 16, 2123–2142, https://doi.org/10.1890/1051-0761(2006)016[2123:Mditaa]2.0.Co;2, 2006.
Breiman, L., Friedman, J., Stone, C. J., and Olshen, R. A.: Classification and Regression Trees, Chapman & Hall, London, 1984.
Canfield, D. E., Glazer, A. N., and Falkowski, P. G.: The evolution and future of Earth's nitrogen cycle, Science, 330, 192–196, https://doi.org/10.1126/science.1186120, 2010.
Dehaspe, J.: R codes for a stream network model and a C–Q bending metric, HydroShare [code], https://doi.org/10.4211/hs.da70a09dc6074242ada756c29d12dcb3, 2021.
Diamond, J. S. and Cohen, M. J.: Complex patterns of catchment solute-discharge relationships for coastal plain rivers, Hydrol. Process., 32, 388–401, https://doi.org/10.1002/hyp.11424, 2018.
Dingman, S. L.: Analytical derivation of at-a-station hydraulic–geometry relations, J. Hydrol., 334, 17–27, https://doi.org/10.1016/j.jhydrol.2006.09.021, 2007.
Doyle, M. W.: Incorporating hydrologic variability into nutrient spiraling, J. Geophys. Res., 110, G01003, https://doi.org/10.1029/2005jg000015, 2005.
Dupas, R., Musolff, A., Jawitz, J. W., Rao, P. S. C., Jäger, C. G., Fleckenstein, J. H., Rode, M., and Borchardt, D.: Carbon and nutrient export regimes from headwater catchments to downstream reaches, Biogeosciences, 14, 4391–4407, https://doi.org/10.5194/bg-14-4391-2017, 2017.
Dupas, R., Minaudo, C., and Abbott, B. W.: Stability of spatial patterns in water chemistry across temperate ecoregions, Environ. Res. Lett., 14, 074015, https://doi.org/10.1088/1748-9326/ab24f4, 2019.
Durand, P., Breuer, L., Johnes, P. J., Billen, G., Butturini, A., Pinay, G., and Wright, R.: Nitrogen processes in aquatic ecosystems, in: The European Nitrogen Assessment: Sources, Effects and Policy Perspectives, edited by: Sutton, M., Howard, C., Erisman, J., Billen, G., Bleeker, A., Grennfelt, P., van Grinsven, H., and Grizzetti, B., Cambridge University Press, Cambridge, 2011.
Ebeling, P.: CCDB – catchment characteristics data base Germany, HydroShare [data set], https://doi.org/10.4211/hs.0fc1b5b1be4a475aacfd9545e72e6839, 2020a.
Ebeling, P.: WQQDB – water quality metrics for catchments across Germany, HydroShare [data set], https://doi.org/10.4211/hs.9b4deeca259b4f7398ce72121b4e2979, 2020b.
Ebeling, P., Kumar, R., Weber, M., Knoll, L., Fleckenstein, J. H., and Musolff, A.: Archetypes and Controls of Riverine Nutrient Export Across German Catchments, Water Resour. Res., 57, e2020WR028134, https://doi.org/10.1029/2020WR028134, 2021.
EEA – European Environmental Agency: DEM over Europe from the GMES RDA project (EU-DEM, resolution 25 m) – version 1, October 2013, European Environmental Agency, EEA geospatial data catalogue, EEA [data set], https://sdi.eea.europa.eu/data/66fa7dca-8772-4a5d-9d56-2caba4ecd36a (last access: 14 March 2021), 2013.
Ehrhardt, S., Kumar, R., Fleckenstein, J. H., Attinger, S., and Musolff, A.: Trajectories of nitrate input and output in three nested catchments along a land use gradient, Hydrol. Earth Syst. Sci., 23, 3503–3524, https://doi.org/10.5194/hess-23-3503-2019, 2019.
Ensign, S. H. and Doyle, M. W.: Nutrient spiraling in streams and river networks, J. Geophys. Res.-Biogeo., 111, G04009, https://doi.org/10.1029/2005jg000114, 2006.
Ensign, S. H., McMillan, S. K., Thompson, S. P., and Piehler, M. F.: Nitrogen and phosphorus attenuation within the stream network of a coastal, agricultural watershed, J. Environ. Qual., 35, 1237–1247, https://doi.org/10.2134/jeq2005.0341, 2006.
ESRI: ArcGIS Desktop: Release 10, Environmental Systems Research Institute, Redlands, CA, 2011.
Fisher, S. G., Sponseller, R. A., and Heffernan, J. B.: Horizons in stream biogeochemistry: Flowpaths to progress, Ecology, 85, 2369–2379, https://doi.org/10.1890/03-0244, 2004.
Galloway, J. N., Schlesinger, W. H., Levy, H., Michaels, A., and Schnoor, J. L.: Nitrogen fixation: Anthropogenic enhancement-environmental response, Global. Biogeochem. Cy., 9, 235–252, https://doi.org/10.1029/95gb00158, 1995.
Godsey, S. E., Kirchner, J. W., and Clow, D. W.: Concentration-discharge relationships reflect chemostatic characteristics of US catchments, Hydrol. Process., 23, 1844–1864, https://doi.org/10.1002/hyp.7315, 2009.
Gomez-Velez, J. D., Harvey, J., Cardenas, M. B., and Kiel, B.: Denitrification in the Mississippi River network controlled by flow through river bedforms, Nat. Geosci., 8, 941–945, https://doi.org/10.1038/Ngeo2567, 2015.
Hall, R. O., Tank, J. L., Sobota, D. J., and Mulholland, P. J.: Nitrate removal in stream ecosystems measured by 15N addition experiments: Total uptake, Limnol. Oceanogr., 54, 653–665, https://doi.org/10.4319/lo.2009.54.3.0653, 2009.
Helton, A. M., Poole, G. C., Meyer, J. L., Wollheim, W. M., Peterson, B. J., Mulholland, P. J., Bernhardt, E. S., Stanford, J. A., Arango, C., Ashkenas, L. R., Cooper, L. W., Dodds, W. K., Gregory, S. V., Hall, R. O., Hamilton, S. K., Johnson, S. L., McDowell, W. H., Potter, J. D., Tank, J. L., Thomas, S. M., Valett, H. M., Webster, J. R., and Zeglin, L.: Thinking outside the channel: modeling nitrogen cycling in networked river ecosystems, Front. Ecol. Environ., 9, 229–238, https://doi.org/10.1890/080211, 2010.
Helton, A. M., Hall, R. O., and Bertuzzo, E.: How network structure can affect nitrogen removal by streams, Freshwater Biol., 63, 128–140, https://doi.org/10.1111/fwb.12990, 2018.
Hensley, R. T., Cohen, M. J., and Korhnak, L. V.: Inferring nitrogen removal in large rivers from high-resolution longitudinal profiling, Limnol. Oceanogr., 59, 1152–1170, https://doi.org/10.4319/lo.2014.59.4.1152, 2014.
Horton, R. E.: Erosional Development of Streams and Their Drainage Basins – Hydrophysical Approach to Quantitative Morphology, Geol. Soc. Am. Bull., 56, 275–370, https://doi.org/10.1130/0016-7606(1945)56[275:edosat]2.0.co;2, 1945.
Jarvie, H. P., Sharpley, A. N., Kresse, T., Hays, P. D., Williams, R. J., King, S. M., and Berry, L. G.: Coupling High-Frequency Stream Metabolism and Nutrient Monitoring to Explore Biogeochemical Controls on Downstream Nitrate Delivery, Environ. Sci. Technol., 52, 13708–13717, https://doi.org/10.1021/acs.est.8b03074, 2018.
Jawitz, J. W. and Mitchell, J.: Temporal inequality in catchment discharge and solute export, Water Resour. Res., 47, W00J14, https://doi.org/10.1029/2010wr010197, 2011.
Kadlec, R. H. and Reddy, K. R.: Temperature effects in treatment wetlands, Water. Environ. Res., 73, 543–557, https://doi.org/10.2175/106143001x139614, 2001.
Kiel, B. A. and Cardenas, M. B.: Lateral hyporheic exchange throughout the Mississippi River network, Nat. Geosci., 7, 413–417, https://doi.org/10.1038/Ngeo2157, 2014.
Kirchner, J. W., Feng, X., and Neal, C.: Fractal stream chemistry and its implications for contaminant transport in catchments, Nature, 403, 524–527, https://doi.org/10.1038/35000537, 2000.
Klemes, V.: Dilettantism in Hydrology – Transition or Destiny, Water Resour. Res., 22, S177–S188, https://doi.org/10.1029/WR022i09Sp0177S, 1986.
Kuhn, M.: caret: Classification and Regression Training, R package version 6.0-86, available at: https://CRAN.R-project.org/package=caret (last access: 16 December 2021), 2020.
Kumar, R., Hesse, F., Rao, P. S. C., Musolff, A., Jawitz, J. W., Sarrazin, F., Samaniego, L., Fleckenstein, J. H., Rakovec, O., Thober, S., and Attinger, S.: Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe, Nat. Commun., 11, 6302, https://doi.org/10.1038/s41467-020-19955-8, 2020.
Kunz, J. V., Hensley, R., Brase, L., Borchardt, D., and Rode, M.: High frequency measurements of reach scale nitrogen uptake in a fourth order river with contrasting hydromorphology and variable water chemistry (Weisse Elster, Germany), Water Resour. Res., 53, 328–343, https://doi.org/10.1002/2016wr019355, 2017.
Langbein, W. B. and Leopold, L. B.: Quasi-Equilibrium States in Channel Morphology, Am. J. Sci., 262, 782–794, https://doi.org/10.2475/ajs.262.6.782, 1964.
Leopold, L. B. and Maddock, T.: The hydraulic geometry of stream channels and some physiographic implications, US Government Printing Office, Washington, DC, 1953.
Li, L., Sullivan, P. L., Benettin, P., Cirpka, O. A., Bishop, K., Brantley, S. L., Knapp, J. L. A., Meerveld, I., Rinaldo, A., Seibert, J., Wen, H., and Kirchner, J. W.: Toward catchment hydro-biogeochemical theories, WIREs Water, 8, e1495, https://doi.org/10.1002/wat2.1495, 2020.
Lindgren, G. A. and Destouni, G.: Nitrogen loss rates in streams: Scale-dependence and up-scaling methodology, Geophys. Res. Lett., 31, 1–4, https://doi.org/10.1029/2004gl019996, 2004.
Marcé, R. and Armengol, J.: Modeling nutrient in-stream processes at the watershed scale using Nutrient Spiralling metrics, Hydrol. Earth Syst. Sci., 13, 953–967, https://doi.org/10.5194/hess-13-953-2009, 2009.
Marcé, R., von Schiller, D., Aguilera, R., Martí, E., and Bernal, S.: Contribution of Hydrologic Opportunity and Biogeochemical Reactivity to the Variability of Nutrient Retention in River Networks, Global. Biogeochem. Cy., 32, 376–388, https://doi.org/10.1002/2017gb005677, 2018.
Marinos, R. E., Van Meter, K. J., and Basu, N. B.: Is the River a Chemostat: Scale Versus Land Use Controls on Nitrate Concentration-Discharge Dynamics in the Upper Mississippi River Basin, Geophys. Res. Lett., 47, e2020GL087051, https://doi.org/10.1029/2020gl087051, 2020.
McDonnell, J. J., Sivapalan, M., Vaché, K., Dunn, S., Grant, G., Haggerty, R., Hinz, C., Hooper, R., Kirchner, J., Roderick, M. L., Selker, J., and Weiler, M.: Moving beyond heterogeneity and process complexity: A new vision for watershed hydrology, Water Resour. Res., 43, W07301, https://doi.org/10.1029/2006wr005467, 2007.
Meybeck, M. and Moatar, F.: Daily variability of river concentrations and fluxes: indicators based on the segmentation of the rating curve, Hydrol. Process., 26, 1188–1207, https://doi.org/10.1002/hyp.8211, 2012.
Minaudo, C., Dupas, R., Gascuel-Odoux, C., Roubeix, V., Danis, P.-A., and Moatar, F.: Seasonal and event-based concentration-discharge relationships to identify catchment controls on nutrient export regimes, Adv. Water Resour., 131, 103379, https://doi.org/10.1016/j.advwatres.2019.103379, 2019.
Mineau, M. M., Wollheim, W. M., and Stewart, R. J.: An index to characterize the spatial distribution of land use within watersheds and implications for river network nutrient removal and export, Geophys. Res. Lett., 42, 6688–6695, https://doi.org/10.1002/2015gl064965, 2015.
Moatar, F., Abbott, B. W., Minaudo, C., Curie, F., and Pinay, G.: Elemental properties, hydrology, and biology interact to shape concentration-discharge curves for carbon, nutrients, sediment, and major ions, Water Resour. Res., 53, 1270–1287, https://doi.org/10.1002/2016wr019635, 2017.
Mueller, C., Musolff, A., Strachauer, U., Brauns, M., Tarasova, L., Merz, R., and Knöller, K.: Tomography of anthropogenic nitrate contribution along a mesoscale river, Sci. Total Environ., 615, 773–783, https://doi.org/10.1016/j.scitotenv.2017.09.297, 2018.
Mulholland, P. J. and Tank, J. L.: Can uptake length in streams be determined by nutrient addition experiments? Results from an interbiome comparison study, J. N. Am. Benthol. Soc., 21, 544–560, https://doi.org/10.2307/1468429, 2002.
Mulholland, P. J., Helton, A. M., Poole, G. C., Hall, R. O., Hamilton, S. K., Peterson, B. J., Tank, J. L., Ashkenas, L. R., Cooper, L. W., Dahm, C. N., Dodds, W. K., Findlay, S. E., Gregory, S. V., Grimm, N. B., Johnson, S. L., McDowell, W. H., Meyer, J. L., Valett, H. M., Webster, J. R., Arango, C. P., Beaulieu, J. J., Bernot, M. J., Burgin, A. J., Crenshaw, C. L., Johnson, L. T., Niederlehner, B. R., O'Brien, J. M., Potter, J. D., Sheibley, R. W., Sobota, D. J., and Thomas, S. M.: Stream denitrification across biomes and its response to anthropogenic nitrate loading, Nature, 452, 202–205, https://doi.org/10.1038/nature06686, 2008.
Musolff, A.: WQQDB – water quality and quantity data base Germany: metadata, Hydroshare, https://doi.org/10.4211/hs.a42addcbd59a466a9aa56472dfef8721, 2020.
Musolff, A., Fleckenstein, J. H., Rao, P. S. C., and Jawitz, J. W.: Emergent archetype patterns of coupled hydrologic and biogeochemical responses in catchments, Geophys. Res. Lett., 44, 4143–4151, https://doi.org/10.1002/2017gl072630, 2017.
Newbold, J. D., Elwood, J. W., Oneill, R. V., and Vanwinkle, W.: Measuring Nutrient Spiralling in Streams, Can. J. Fish. Aquat. Sci., 38, 860–863, https://doi.org/10.1139/f81-114, 1981.
O'Brien, J. M., Dodds, W. K., Wilson, K. C., Murdock, J. N., and Eichmiller, J.: The saturation of N cycling in Central Plains streams: 15N experiments across a broad gradient of nitrate concentrations, Biogeochemistry, 84, 31–49, https://doi.org/10.1007/s10533-007-9073-7, 2007.
Ocampo, C. J., Oldham, C. E., and Sivapalan, M.: Nitrate attenuation in agricultural catchments: Shifting balances between transport and reaction, Water Resour. Res., 42, W01408, https://doi.org/10.1029/2004wr003773, 2006.
Oldham, C. E., Farrow, D. E., and Peiffer, S.: A generalized Damköhler number for classifying material processing in hydrological systems, Hydrol. Earth Syst. Sci., 17, 1133–1148, https://doi.org/10.5194/hess-17-1133-2013, 2013.
Pennino, M. J., Kaushal, S. S., Beaulieu, J. J., Mayer, P. M., and Arango, C. P.: Effects of urban stream burial on nitrogen uptake and ecosystem metabolism: implications for watershed nitrogen and carbon fluxes, Biogeochemistry, 121, 247–269, https://doi.org/10.1007/s10533-014-9958-1, 2014.
Peterson, B. J., Wollheim, W. M., Mulholland, P. J., Webster, J. R., Meyer, J. L., Tank, J. L., Marti, E., Bowden, W. B., Valett, H. M., Hershey, A. E., McDowell, W. H., Dodds, W. K., Hamilton, S. K., Gregory, S., and Morrall, D. D.: Control of nitrogen export from watersheds by headwater streams, Science, 292, 86–90, https://doi.org/10.1126/science.1056874, 2001.
Pianosi, F. and Wagener, T.: A simple and efficient method for global sensitivity analysis based on cumulative distribution functions, Environ. Modell. Softw., 67, 1–11, https://doi.org/10.1016/j.envsoft.2015.01.004, 2015.
Pianosi, F. and Wagener, T.: Distribution-based sensitivity analysis from a generic input-output sample, Environ. Modell. Softw., 108, 197–207, https://doi.org/10.1016/j.envsoft.2018.07.019, 2018.
Pianosi, F., Sarrazin, F., and Wagener, T.: A Matlab toolbox for Global Sensitivity Analysis, Environ. Modell. Softw., 70, 80–85, https://doi.org/10.1016/j.envsoft.2015.04.009, 2015.
Pressley, A. N.: Elementary Differential Geometry, 1st Edn., Springer, London, https://doi.org/10.1007/978-1-84882-891-9, 2001.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, 2013.
Risse-Buhl, U., Anlanger, C., Kalla, K., Neu, T. R., Noss, C., Lorke, A., and Weitere, M.: The role of hydrodynamics in shaping the composition and architecture of epilithic biofilms in fluvial ecosystems, Water Res., 127, 211–222, https://doi.org/10.1016/j.watres.2017.09.054, 2017.
Rode, M., Halbedel Nee Angelstein, S., Anis, M. R., Borchardt, D., and Weitere, M.: Continuous In-Stream Assimilatory Nitrate Uptake from High-Frequency Sensor Measurements, Environ. Sci. Technol., 50, 5685–5694, https://doi.org/10.1021/acs.est.6b00943, 2016.
Runkel, R. L. and Bencala, K. E.: Transport of reacting solutes in rivers and streams, in: Environmental Hydrology, Kluwer Academic Publishers, Dordrecht, the Netherlands, 1995.
Schlesinger, W. H., Reckhow, K. H., and Bernhardt, E. S.: Global change: The nitrogen cycle and rivers, Water Resour. Res., 42, https://doi.org/10.1029/2005wr004300, 2006.
Seitzinger, S. P., Styles, R. V., Boyer, E. W., Alexander, R. B., Billen, G., Howarth, R. W., Mayer, B., and Van Breemen, N.: Nitrogen retention in rivers: model development and application to watersheds in the northeastern U. S. A., Biogeochemistry, 57–58, 199–237, https://doi.org/10.1023/A:1015745629794, 2002.
Seybold, E. and McGlynn, B.: Hydrologic and biogeochemical drivers of dissolved organic carbon and nitrate uptake in a headwater stream network, Biogeochemistry, 138, 23–48, https://doi.org/10.1007/s10533-018-0426-1, 2018.
Stream Solute Workshop: Concepts and Methods for Assessing Solute Dynamics in Stream Ecosystems, J. N. Am. Benthol. Soc., 9, 95–119, https://doi.org/10.2307/1467445, 1990.
Tunqui Neira, J. M., Andréassian, V., Tallec, G., and Mouchel, J.-M.: Technical note: A two-sided affine power scaling relationship to represent the concentration–discharge relationship, Hydrol. Earth Syst. Sci., 24, 1823–1830, https://doi.org/10.5194/hess-24-1823-2020, 2020.
Vanni, M. J.: Nutrient Cycling by Animals in Freshwater Ecosystems, Annu. Rev. Ecol. Syst., 33, 341–370, https://doi.org/10.1146/annurev.ecolsys.33.010802.150519, 2002.
Vanni, M. J. and McIntyre, P. B.: Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis, Ecology, 97, 3460–3471, https://doi.org/10.1002/ecy.1582, 2016.
Wei, T. and Simko, V.: R package “corrplot”: Visualization of a Correlation Matrix, version 0.84, GitHub, https://github.com/taiyun/corrplot (last access: 16 December 2021), 2017.
Winter, C., Lutz, S. R., Musolff, A., Kumar, R., Weber, M., and Fleckenstein, J. H.: Disentangling the impact of catchment heterogeneity on nitrate export dynamics from event to long-term time scales, Water. Resour. Res., 57, e2020WR027992, https://doi.org/10.1002/essoar.10503228.1, 2021.
Wollheim, W. M., Vörösmarty, C. J., Peterson, B. J., Seitzinger, S. P., and Hopkinson, C. S.: Relationship between river size and nutrient removal, Geophys. Res. Lett., 33, L06410, https://doi.org/10.1029/2006gl025845, 2006.
Wollheim, W. M., Peterson, B. J., Thomas, S. M., Hopkinson, C. H., and Vörösmarty, C. J.: Dynamics of N removal over annual time periods in a suburban river network, J. Geophys. Res., 113, G03038, https://doi.org/10.1029/2007jg000660, 2008.
Wollheim, W. M., Mulukutla, G. K., Cook, C., and Carey, R. O.: Aquatic Nitrate Retention at River Network Scales Across Flow Conditions Determined Using Nested In Situ Sensors, Water Resour. Res., 53, 9740–9756, https://doi.org/10.1002/2017wr020644, 2017.
Wollheim, W. M., Bernal, S., Burns, D. A., Czuba, J. A., Driscoll, C. T., Hansen, A. T., Hensley, R. T., Hosen, J. D., Inamdar, S., Kaushal, S. S., Koenig, L. E., Lu, Y. H., Marzadri, A., Raymond, P. A., Scott, D., Stewart, R. J., Vidon, P. G., and Wohl, E.: River network saturation concept: factors influencing the balance of biogeochemical supply and demand of river networks, Biogeochemistry, 141, 503–521, https://doi.org/10.1007/s10533-018-0488-0, 2018.
Yang, X., Jomaa, S., Buttner, O., and Rode, M.: Autotrophic nitrate uptake in river networks: A modeling approach using continuous high-frequency data, Water. Res., 157, 258–268, https://doi.org/10.1016/j.watres.2019.02.059, 2019.
Yang, X. Q., Jomaa, S., Zink, M., Fleckenstein, J. H., Borchardt, D., and Rode, M.: A New Fully Distributed Model of Nitrate Transport and Removal at Catchment Scale, Water Resour. Res., 54, 5856–5877, https://doi.org/10.1029/2017wr022380, 2018.
Zarnetske, J. P., Haggerty, R., Wondzell, S. M., and Baker, M. A.: Dynamics of nitrate production and removal as a function of residence time in the hyporheic zone, J. Geophys. Res., 116, G01025, https://doi.org/10.1029/2010jg001356, 2011.
Short summary
Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low-frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
Increased nitrate concentrations in surface waters can compromise river ecosystem health. As...