Articles | Volume 28, issue 17
https://doi.org/10.5194/hess-28-4011-2024
© Author(s) 2024. 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-28-4011-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Sep 2024
Research article |
| 03 Sep 2024
| 03 Sep 2024
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628CN Delft, the Netherlands
Markus Hrachowitz
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628CN Delft, the Netherlands
Gerrit Schoups
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628CN Delft, the Netherlands
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Laurène J. E. Bouaziz, Emma E. Aalbers, Albrecht H. Weerts, Mark Hegnauer, Hendrik Buiteveld, Rita Lammersen, Jasper Stam, Eric Sprokkereef, Hubert H. G. Savenije, and Markus Hrachowitz
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Punpim Puttaraksa Mapiam, Monton Methaprayun, Thom Bogaard, Gerrit Schoups, and Marie-Claire Ten Veldhuis
Hydrol. Earth Syst. Sci., 26, 775–794, https://doi.org/10.5194/hess-26-775-2022, https://doi.org/10.5194/hess-26-775-2022, 2022
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Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp
Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, https://doi.org/10.5194/hess-25-4887-2021, 2021
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Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, and Andrea Alessandri
Earth Syst. Dynam., 12, 725–743, https://doi.org/10.5194/esd-12-725-2021, https://doi.org/10.5194/esd-12-725-2021, 2021
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The roots of vegetation largely control the Earth's water cycle by transporting water from the subsurface to the atmosphere but are not adequately represented in land surface models, causing uncertainties in modeled water fluxes. We replaced the root parameters in an existing model with more realistic ones that account for a climate control on root development and found improved timing of modeled river discharge. Further extension of our approach could improve modeled water fluxes globally.
Sarah Hanus, Markus Hrachowitz, Harry Zekollari, Gerrit Schoups, Miren Vizcaino, and Roland Kaitna
Hydrol. Earth Syst. Sci., 25, 3429–3453, https://doi.org/10.5194/hess-25-3429-2021, https://doi.org/10.5194/hess-25-3429-2021, 2021
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This study investigates the effects of climate change on runoff patterns in six Alpine catchments in Austria at the end of the 21st century. Our results indicate a substantial shift to earlier occurrences in annual maximum and minimum flows in high-elevation catchments. Magnitudes of annual extremes are projected to increase under a moderate emission scenario in all catchments. Changes are generally more pronounced for high-elevation catchments.
Cody C. Routson, Darrell S. Kaufman, Nicholas P. McKay, Michael P. Erb, Stéphanie H. Arcusa, Kendrick J. Brown, Matthew E. Kirby, Jeremiah P. Marsicek, R. Scott Anderson, Gonzalo Jiménez-Moreno, Jessica R. Rodysill, Matthew S. Lachniet, Sherilyn C. Fritz, Joseph R. Bennett, Michelle F. Goman, Sarah E. Metcalfe, Jennifer M. Galloway, Gerrit Schoups, David B. Wahl, Jesse L. Morris, Francisca Staines-Urías, Andria Dawson, Bryan N. Shuman, Daniel G. Gavin, Jeffrey S. Munroe, and Brian F. Cumming
Earth Syst. Sci. Data, 13, 1613–1632, https://doi.org/10.5194/essd-13-1613-2021, https://doi.org/10.5194/essd-13-1613-2021, 2021
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We present a curated database of western North American Holocene paleoclimate records, which have been screened on length, resolution, and geochronology. The database gathers paleoclimate time series that reflect temperature, hydroclimate, or circulation features from terrestrial and marine sites, spanning a region from Mexico to Alaska. This publicly accessible collection will facilitate a broad range of paleoclimate inquiry.
Artemis Roodari, Markus Hrachowitz, Farzad Hassanpour, and Mostafa Yaghoobzadeh
Hydrol. Earth Syst. Sci., 25, 1943–1967, https://doi.org/10.5194/hess-25-1943-2021, https://doi.org/10.5194/hess-25-1943-2021, 2021
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Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, https://doi.org/10.5194/hess-25-1069-2021, 2021
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Petra Hulsman, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 957–982, https://doi.org/10.5194/hess-25-957-2021, https://doi.org/10.5194/hess-25-957-2021, 2021
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Satellite observations have increasingly been used for model calibration, while model structural developments largely rely on discharge data. For large river basins, this often results in poor representations of system internal processes. This study explores the combined use of satellite-based evaporation and total water storage data for model structural improvement and spatial–temporal model calibration for a large, semi-arid and data-scarce river system.
Ralf Loritz, Markus Hrachowitz, Malte Neuper, and Erwin Zehe
Hydrol. Earth Syst. Sci., 25, 147–167, https://doi.org/10.5194/hess-25-147-2021, https://doi.org/10.5194/hess-25-147-2021, 2021
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This study investigates the role and value of distributed rainfall in the runoff generation of a mesoscale catchment. We compare the performance of different hydrological models at different periods and show that a distributed model driven by distributed rainfall yields improved performances only during certain periods. We then step beyond this finding and develop a spatially adaptive model that is capable of dynamically adjusting its spatial model structure in time.
Petra Hulsman, Hessel C. Winsemius, Claire I. Michailovsky, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 24, 3331–3359, https://doi.org/10.5194/hess-24-3331-2020, https://doi.org/10.5194/hess-24-3331-2020, 2020
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In the absence of discharge data in ungauged basins, remotely sensed river water level data, i.e. altimetry, may provide valuable information to calibrate hydrological models. This study illustrated that for large rivers in data-scarce regions, river altimetry data from multiple locations combined with GRACE data have the potential to fill this gap when combined with estimates of the river geometry, thereby allowing a step towards more reliable hydrological modelling in data-scarce regions.
Hongkai Gao, Christian Birkel, Markus Hrachowitz, Doerthe Tetzlaff, Chris Soulsby, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 23, 787–809, https://doi.org/10.5194/hess-23-787-2019, https://doi.org/10.5194/hess-23-787-2019, 2019
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Supported by large-sample ecological observations, a novel, simple and topography-driven runoff generation module (HSC-MCT) was created. The HSC-MCT is calibration-free, and therefore it can be used to predict in ungauged basins, and has great potential to be generalized at the global scale. Also, it allows us to reproduce the variation of saturation areas, which has great potential to be used for broader hydrological, ecological, climatological, and biogeochemical studies.
Laurène Bouaziz, Albrecht Weerts, Jaap Schellekens, Eric Sprokkereef, Jasper Stam, Hubert Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 22, 6415–6434, https://doi.org/10.5194/hess-22-6415-2018, https://doi.org/10.5194/hess-22-6415-2018, 2018
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We quantify net intercatchment groundwater flows in the Meuse basin in a complementary three-step approach through (1) water budget accounting, (2) testing a set of conceptual hydrological models and (3) evaluating against remote sensing actual evaporation data. We show that net intercatchment groundwater flows can make up as much as 25 % of mean annual precipitation in the headwaters and should therefore be accounted for in conceptual models to prevent overestimating actual evaporation rates.
Karin Mostbauer, Roland Kaitna, David Prenner, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 22, 3493–3513, https://doi.org/10.5194/hess-22-3493-2018, https://doi.org/10.5194/hess-22-3493-2018, 2018
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Debris flows represent a severe hazard in mountain regions and so far remain difficult to predict. We applied a hydrological model to link not only precipitation, but also snowmelt, antecedent soil moisture, etc. with debris flow initiation in an Alpine watershed in Austria. Our results highlight the value of this more holistic perspective for developing a better understanding of debris flow initiation.
Markus Hrachowitz and Martyn P. Clark
Hydrol. Earth Syst. Sci., 21, 3953–3973, https://doi.org/10.5194/hess-21-3953-2017, https://doi.org/10.5194/hess-21-3953-2017, 2017
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Physically based and conceptual models in hydrology are the two endpoints in the spectrum of modelling strategies, mostly differing in their degree of detail in resolving the model domain. Given the limitations both modelling strategies face, we believe that to achieve progress in hydrological modelling, a convergence of these methods is necessary. This would allow us to exploit the respective advantages of the bottom-up and top-down models while limiting their respective uncertainties.
Catchments as meta-organisms – a new blueprint for hydrological modelling
Hubert H. G. Savenije and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 21, 1107–1116, https://doi.org/10.5194/hess-21-1107-2017, https://doi.org/10.5194/hess-21-1107-2017, 2017
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The natural environment that we live in is the result of evolution. This does not only apply to ecosystems, but also to the physical environment through which the water flows. This has resulted in the formation of flow patterns that obey sometimes surprisingly simple mathematical laws. Hydrological models should represent the physics of these patterns and should account for the fact that the ecosystem adjusts itself continuously to changing circumstances. Physics-based models are alive!
Remko Nijzink, Christopher Hutton, Ilias Pechlivanidis, René Capell, Berit Arheimer, Jim Freer, Dawei Han, Thorsten Wagener, Kevin McGuire, Hubert Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 4775–4799, https://doi.org/10.5194/hess-20-4775-2016, https://doi.org/10.5194/hess-20-4775-2016, 2016
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The core component of many hydrological systems, the moisture storage capacity available to vegetation, is typically treated as a calibration parameter in hydrological models and often considered to remain constant in time. In this paper we test the potential of a recently introduced method to robustly estimate catchment-scale root-zone storage capacities exclusively based on climate data to reproduce the temporal evolution of root-zone storage under change (deforestation).
Remko C. Nijzink, Luis Samaniego, Juliane Mai, Rohini Kumar, Stephan Thober, Matthias Zink, David Schäfer, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, https://doi.org/10.5194/hess-20-1151-2016, 2016
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The heterogeneity of landscapes in river basins strongly affects the hydrological response. In this study, the distributed mesoscale Hydrologic Model (mHM) was equipped with additional processes identified by landscapes within one modelling cell. Seven study catchments across Europe were selected to test the value of this additional sub-grid heterogeneity. In addition, the models were constrained based on expert knowledge. Generally, the modifications improved the representation of low flows.
S. Ceola, B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione, and T. Wagener
Hydrol. Earth Syst. Sci., 19, 2101–2117, https://doi.org/10.5194/hess-19-2101-2015, https://doi.org/10.5194/hess-19-2101-2015, 2015
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We present the outcomes of a collaborative hydrological experiment undertaken by five different international research groups in a virtual laboratory. Moving from the definition of accurate protocols, a rainfall-runoff model was independently applied by the research groups, which then engaged in a comparative discussion. The results revealed that sharing protocols and running the experiment within a controlled environment is fundamental for ensuring experiment repeatability and reproducibility.
O. Fovet, L. Ruiz, M. Hrachowitz, M. Faucheux, and C. Gascuel-Odoux
Hydrol. Earth Syst. Sci., 19, 105–123, https://doi.org/10.5194/hess-19-105-2015, https://doi.org/10.5194/hess-19-105-2015, 2015
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We studied the annual hysteretic patterns observed between stream flow and water storage in the saturated and unsaturated zones of a hillslope and a riparian zone. We described these signatures using a hysteresis index and then used this to assess conceptual hydrological models. This led us to identify four hydrological periods and a clearly distinct behaviour between riparian and hillslope groundwaters and to provide new information about the model performances.
S. Gharari, M. Hrachowitz, F. Fenicia, H. Gao, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4839–4859, https://doi.org/10.5194/hess-18-4839-2014, https://doi.org/10.5194/hess-18-4839-2014, 2014
S. Gharari, M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4861–4870, https://doi.org/10.5194/hess-18-4861-2014, https://doi.org/10.5194/hess-18-4861-2014, 2014
H. Gao, M. Hrachowitz, F. Fenicia, S. Gharari, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 1895–1915, https://doi.org/10.5194/hess-18-1895-2014, https://doi.org/10.5194/hess-18-1895-2014, 2014
T. Euser, H. C. Winsemius, M. Hrachowitz, F. Fenicia, S. Uhlenbrook, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 17, 1893–1912, https://doi.org/10.5194/hess-17-1893-2013, https://doi.org/10.5194/hess-17-1893-2013, 2013
M. Hrachowitz, H. Savenije, T. A. Bogaard, D. Tetzlaff, and C. Soulsby
Hydrol. Earth Syst. Sci., 17, 533–564, https://doi.org/10.5194/hess-17-533-2013, https://doi.org/10.5194/hess-17-533-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Adaptation of root zone storage capacity to climate change and its effects on future streamflow in Alpine catchments: towards non-stationary model parameters
Finding process-behavioural parameterisations of a hydrological model using a multi-step process-based calibration and evaluation scheme
Merits and limits of SWAT-GL: application in contrasting glaciated catchments
Hydrological regime index for non-perennial rivers
Assessing the adequacy of traditional hydrological models for climate change impact studies: a case for long short-term memory (LSTM) neural networks
Assessing the value of high-resolution data and parameter transferability across temporal scales in hydrological modeling: a case study in northern China
Technical note: How many models do we need to simulate hydrologic processes across large geographical domains?
CONCN: a high-resolution, integrated surface water–groundwater ParFlow modeling platform of continental China
Evaluating the effects of topography and land use change on hydrological signatures: a comparative study of two adjacent watersheds
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Long short-term memory networks for enhancing real-time flood forecasts: a case study for an underperforming hydrologic model
Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China
Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable
Scale dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Extended-range forecasting of stream water temperature with deep-learning models
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
Enhanced Baseflow Separation in Rural Catchments: Event-Specific Calibration of Recursive Digital Filters with Tracer-Derived Data
Projections of streamflow intermittence under climate change in European drying river networks
Economic valuation of subsurface water contributions to watershed ecosystem services using a fully integrated groundwater–surface-water model
Analyzing the generalization capabilities of a hybrid hydrological model for extrapolation to extreme events
CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland
Runoff component quantification and future streamflow projection in a large mountainous basin based on a multidata-constrained cryospheric–hydrological model
Exploring the potential processes controlling changes in precipitation–runoff relationships in non-stationary environments
Spatially Resolved Rainfall Streamflow Modeling in Central Europe
A diversity-centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Simulating the Tone River eastward diversion project in Japan carried out 4 centuries ago
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study
Heavy-tailed flood peak distributions: what is the effect of the spatial variability of rainfall and runoff generation?
A Distributed Hybrid Physics-AI Framework for Learning Corrections of Internal Hydrological Fluxes and Enhancing High-Resolution Regionalized Flood Modeling
Combining uncertainty quantification and entropy-inspired concepts into a single objective function for rainfall-runoff model calibration
State updating of the Xin'anjiang model: joint assimilating streamflow and multi-source soil moisture data via the asynchronous ensemble Kalman filter with enhanced error models
Improving the hydrological consistency of a process-based solute-transport model by simultaneous calibration of streamflow and stream concentrations
Understanding the relationship between streamflow forecast skill and value across the western US
Leveraging soil diversity to mitigate hydrological extremes with nature-based solutions in productive catchments
Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments
The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa
Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model
Spatio-temporal patterns and trends of streamflow in water-scarce Mediterranean basins
A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments
Seasonal variation in land cover estimates reveals sensitivities and opportunities for environmental models
Soil moisture and precipitation intensity control the transit time distribution of quick flow in a flashy headwater catchment
Estimating response times, flow velocities, and roughness coefficients of Canadian Prairie basins
Learning landscape features from streamflow with autoencoders
The influence of lateral flow on land surface fluxes in southeast Australia varies with model resolution
Constraining pesticide degradation in conceptual distributed catchment models with compound-specific isotope analysis (CSIA)
On the use of streamflow transformations for hydrological model calibration
Unveiling the Impact of Potential Evapotranspiration Method Selection on Trends in Hydrological Cycle Components Across Europe
Simulation-based inference for parameter estimation of complex watershed simulators
Comparative Hydrological Modeling of Snow-Cover and Frozen Ground Impacts Under Topographically Complex Conditions
Magali Ponds, Sarah Hanus, Harry Zekollari, Marie-Claire ten Veldhuis, Gerrit Schoups, Roland Kaitna, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 3545–3568, https://doi.org/10.5194/hess-29-3545-2025, https://doi.org/10.5194/hess-29-3545-2025, 2025
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This research examines how future climate changes impact root zone storage, a key hydrological model parameter. Root zone storage – the soil water accessible to plants – adapts to climate but is often kept constant in models. We estimated climate-adapted storage in six Austrian Alps catchments. While storage increased, streamflow projections showed minimal change, which suggests that dynamic root zone representation is less critical in humid regions but warrants further study in arid areas.
Moritz M. Heuer, Hadysa Mohajerani, and Markus C. Casper
Hydrol. Earth Syst. Sci., 29, 3503–3525, https://doi.org/10.5194/hess-29-3503-2025, https://doi.org/10.5194/hess-29-3503-2025, 2025
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This study presents a process-behavioural calibration approach for water balance models. The different calibration steps aim at calibrating different hydrological processes: evapotranspiration, the runoff partitioning into surface runoff, interflow, and groundwater recharge, as well as the groundwater behaviour. This allows for selection of a model parameterisation that correctly predicts the discharge at the catchment outlet and simultaneously correctly depicts the underlying hydrological processes.
Timo Schaffhauser, Florentin Hofmeister, Gabriele Chiogna, Fabian Merk, Ye Tuo, Julian Machnitzke, Lucas Alcamo, Jingshui Huang, and Markus Disse
Hydrol. Earth Syst. Sci., 29, 3227–3256, https://doi.org/10.5194/hess-29-3227-2025, https://doi.org/10.5194/hess-29-3227-2025, 2025
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The glacier-expanded SWAT (Soil Water Assessment Tool) version, SWAT-GL, was tested in four different catchments, highlighting the capabilities of the glacier routine. It was evaluated based on the representation of glacier mass balance, snow cover and glacier hypsometry. The glacier changes over a long timescale could be adequately represented, leading to promising potential future applications in glaciated and high mountain environments and significantly outperforming standard SWAT models.
Pablo Fernando Dornes and Rocío Noelia Comas
Hydrol. Earth Syst. Sci., 29, 2901–2923, https://doi.org/10.5194/hess-29-2901-2025, https://doi.org/10.5194/hess-29-2901-2025, 2025
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The Desaguadero–Salado–Chadiluevú–Curacó (DSCC) River is a semiarid river which is heavily dammed at its tributaries which collect the snowmelt runoff. This runoff feeds mostly gravitational irrigation systems of very low efficiency. As a result, the DSCC River does not have natural runoff. The proposed hydrological regime index (HRI) is able to discriminate and quantify regime alterations under permanent and non-permanent flow conditions and with low- and high-impoundment conditions.
Jean-Luc Martel, François Brissette, Richard Arsenault, Richard Turcotte, Mariana Castañeda-Gonzalez, William Armstrong, Edouard Mailhot, Jasmine Pelletier-Dumont, Gabriel Rondeau-Genesse, and Louis-Philippe Caron
Hydrol. Earth Syst. Sci., 29, 2811–2836, https://doi.org/10.5194/hess-29-2811-2025, https://doi.org/10.5194/hess-29-2811-2025, 2025
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This study compares long short-term memory (LSTM) neural networks with traditional hydrological models to predict future streamflow under climate change. Using data from 148 catchments, it finds that LSTM models, which learn from extensive data sequences, perform differently and often better than traditional hydrological models. The continental LSTM model, which includes data from diverse climate zones, is particularly effective for understanding climate impacts on water resources.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 2633–2654, https://doi.org/10.5194/hess-29-2633-2025, https://doi.org/10.5194/hess-29-2633-2025, 2025
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We assessed the value of high-resolution data and parameter transferability across temporal scales based on seven catchments in northern China. We found that higher-resolution data do not always improve model performance, questioning the need for such data. Model parameters are transferable across different data resolutions but not across computational time steps. It is recommended to utilize a smaller computational time step when building hydrological models even without high-resolution data.
Wouter J. M. Knoben, Ashwin Raman, Gaby J. Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, Katie van Werkhoven, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 29, 2361–2375, https://doi.org/10.5194/hess-29-2361-2025, https://doi.org/10.5194/hess-29-2361-2025, 2025
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Hydrologic models are needed to provide simulations of water availability, floods, and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models and thus cannot easily be used to select an appropriate model for a specific place.
Chen Yang, Zitong Jia, Wenjie Xu, Zhongwang Wei, Xiaolang Zhang, Yiguang Zou, Jeffrey McDonnell, Laura Condon, Yongjiu Dai, and Reed Maxwell
Hydrol. Earth Syst. Sci., 29, 2201–2218, https://doi.org/10.5194/hess-29-2201-2025, https://doi.org/10.5194/hess-29-2201-2025, 2025
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We developed the first high-resolution, integrated surface water–groundwater hydrologic model of the entirety of continental China using ParFlow. The model shows good performance in terms of streamflow and water table depth when compared to global data products and observations. It is essential for water resources management and decision-making in China within a consistent framework in the changing world. It also has significant implications for similar modeling in other places in the world.
Haifan Liu, Haochen Yan, and Mingfu Guan
Hydrol. Earth Syst. Sci., 29, 2109–2132, https://doi.org/10.5194/hess-29-2109-2025, https://doi.org/10.5194/hess-29-2109-2025, 2025
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Land changes and landscape features critically impact water systems. Studying two watersheds in China’s Greater Bay Area, we found slope strongly influences water processes in mountainous areas. However, this relationship is weak in the lower regions of steeper watersheds. Urbanization leads to an increase in annual surface runoff, while flatter watersheds exhibit a buffering capacity against this effect. However, this buffering capacity diminishes with increasing annual rainfall intensity.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci., 29, 1981–2002, https://doi.org/10.5194/hess-29-1981-2025, https://doi.org/10.5194/hess-29-1981-2025, 2025
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Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite the fact that they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what they truly reflect in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and timescales for accurate drought characterization and monitoring.
Sebastian Gegenleithner, Manuel Pirker, Clemens Dorfmann, Roman Kern, and Josef Schneider
Hydrol. Earth Syst. Sci., 29, 1939–1962, https://doi.org/10.5194/hess-29-1939-2025, https://doi.org/10.5194/hess-29-1939-2025, 2025
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Accurate early-warning systems are crucial for reducing the damage caused by flooding events. In this study, we explored the potential of long short-term memory networks for enhancing the forecast accuracy of hydrologic models employed in operational flood forecasting. The presented approach elevated the investigated hydrologic model’s forecast accuracy for further ahead predictions and at flood event runoff.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025, https://doi.org/10.5194/hess-29-1919-2025, 2025
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Common intuition holds that higher input data resolution leads to better results. To assess the benefits of high-resolution data, we conduct simulation experiments using data with various temporal resolutions across multiple catchments and find that higher-resolution data do not always improve model performance, challenging the necessity of pursuing such data. In catchments with small areas or significant flow variability, high-resolution data is more valuable.
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025, https://doi.org/10.5194/hess-29-1703-2025, 2025
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The quantification of precipitation into evaporation and runoff is vital for water resources management. The Budyko framework, based on aridity and evaporative indices of a catchment, can be an ideal tool for that. However, recent research highlights deviations of catchments from the expected evaporative index, casting doubt on its reliability. This study quantifies deviations of 2387 catchments, finding them minor and predictable. Integrating these into predictions upholds the framework's efficacy.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025, https://doi.org/10.5194/hess-29-1725-2025, 2025
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In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until we observe overparameterization.
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025, https://doi.org/10.5194/hess-29-1685-2025, 2025
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We generate operational forecasts of daily maximum stream water temperature for 32 consecutive days at 54 stations in Switzerland with our best-performing data-driven model. The average forecast error is 0.38 °C for 1 d ahead and increases to 0.90 °C for 32 d ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1749–1758, https://doi.org/10.5194/hess-29-1749-2025, https://doi.org/10.5194/hess-29-1749-2025, 2025
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Long short-term memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modelling. However, most studies focus on predictions at a daily scale, limiting the benefits of sub-daily (e.g. hourly) predictions in applications like flood forecasting. In this study, we introduce a new architecture, multi-frequency LSTM (MF-LSTM), designed to use inputs of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
Fernanda Helfer, Felipe Bernardi, Claudia Alessandra Peixoto de Barros, Daniel Gustavo Allasia, Jean Paolo Gomes Minella, Rutinéia Tassi, and Néverton Scariot
EGUsphere, https://doi.org/10.5194/egusphere-2025-244, https://doi.org/10.5194/egusphere-2025-244, 2025
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We explored how water flows in small rural streams to improve tools for better managing water resources. Using a new method, we adjusted existing models to consider the size of rainfall events, showing that water movement patterns change depending on the rain’s intensity. This approach makes predictions more accurate and helps scientists and managers understand water availability and protect ecosystems.
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci., 29, 1615–1636, https://doi.org/10.5194/hess-29-1615-2025, https://doi.org/10.5194/hess-29-1615-2025, 2025
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Our study projects how climate change will affect the drying of river segments and stream networks in Europe, using advanced modelling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent and intense and will start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists for evaluating the ecological health of river ecosystem.
Tariq Aziz, Steven K. Frey, David R. Lapen, Susan Preston, Hazen A. J. Russell, Omar Khader, Andre R. Erler, and Edward A. Sudicky
Hydrol. Earth Syst. Sci., 29, 1549–1568, https://doi.org/10.5194/hess-29-1549-2025, https://doi.org/10.5194/hess-29-1549-2025, 2025
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This study determines the value of subsurface water for ecosystem services' supply in an agricultural watershed in Ontario, Canada. Using a fully integrated water model and an economic valuation approach, the research highlights subsurface water's critical role in maintaining watershed ecosystem services. The study informs on the sustainable use of subsurface water and introduces a new method for managing watershed ecosystem services.
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1277–1294, https://doi.org/10.5194/hess-29-1277-2025, https://doi.org/10.5194/hess-29-1277-2025, 2025
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Data-driven techniques have shown the potential to outperform process-based models in rainfall–runoff simulations. Hybrid models, combining both approaches, aim to enhance accuracy and maintain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions, we test their generalization capabilities for extreme hydrological events.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
Hydrol. Earth Syst. Sci., 29, 1061–1082, https://doi.org/10.5194/hess-29-1061-2025, https://doi.org/10.5194/hess-29-1061-2025, 2025
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This study reconstructs daily runoff in Switzerland (1962–2023) using a deep-learning model, providing a spatially contiguous dataset on a medium-sized catchment grid. The model outperforms traditional hydrological methods, revealing shifts in Swiss water resources, including more frequent dry years and declining summer runoff. The reconstruction is publicly available.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1033–1060, https://doi.org/10.5194/hess-29-1033-2025, https://doi.org/10.5194/hess-29-1033-2025, 2025
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Owing to differences in the existing published results, we conducted a detailed analysis of the runoff components and future trends in the Yarlung Tsangpo River basin and found that the contributions of snowmelt and glacier melt runoff to streamflow (both ~5 %) are limited and much lower than previous results. The streamflow in this area will continuously increase in the future, but the overestimated contribution of glacier melt could lead to an underestimation of this increasing trend.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025, https://doi.org/10.5194/hess-29-903-2025, 2025
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This study develops an integrated framework based on the novel Driving index for changes in Precipitation–Runoff Relationships (DPRR) to explore the controlling changes in precipitation–runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation–runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Marc Aurel Vischer, Noelia Otero, and Jackie Ma
EGUsphere, https://doi.org/10.5194/egusphere-2024-3649, https://doi.org/10.5194/egusphere-2024-3649, 2025
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We use a neural network to predict the amount of water flowing into rivers. Our focus is on large river catchment areas in central Europe with pronounced human activity. Our model scales efficiently to large amounts of data and is thus able to processes the input without prior aggregation, capturing fine spatial detail and improving prediction in large catchments. Our model’s internal states can be adapted to allow capturing human activity more explicitly in the future.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025, https://doi.org/10.5194/hess-29-785-2025, 2025
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Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine learning (ML) models are increasingly being applied for flood forecasting. Such models are typically trained on large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets that maximise the spatio-temporal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025, https://doi.org/10.5194/hess-29-753-2025, 2025
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This study presents the first distributed hydrological simulation which confirms claims raised by historians that the eastward diversion project of the Tone River in Japan was conducted 4 centuries ago to increase low flows and subsequent travelling possibilities surrounding the capital, Edo (Tokyo), using inland navigation. We showed that great steps forward can be made for improving quality of life with small human engineering waterworks and small interventions in the regime of natural flows.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025, https://doi.org/10.5194/hess-29-683-2025, 2025
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This work investigates how hydrological models are transferred to a period in which climate conditions are different to the ones of the period in which they were set up. The robustness assessment test built to detect dependencies between model error and climatic drivers was applied to three hydrological models in 352 catchments in Denmark, France and Sweden. Potential issues are seen in a significant number of catchments for the models, even though the catchments differ for each model.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025, https://doi.org/10.5194/hess-29-627-2025, 2025
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Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 29, 447–463, https://doi.org/10.5194/hess-29-447-2025, https://doi.org/10.5194/hess-29-447-2025, 2025
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Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small catchments compared to large catchments, and spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show effects. The results can improve estimations of probabilities of extreme floods.
Ngo Nghi Truyen Huynh, Pierre-André Garambois, Benjamin Renard, François Colleoni, Jérôme Monnier, and Hélène Roux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3665, https://doi.org/10.5194/egusphere-2024-3665, 2025
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Understanding and modeling flash flood-prone areas remains challenging due to limited data and scale-relevant hydrological theory. While machine learning shows promise, its integration with process-based models is difficult. We present an approach incorporating machine learning into a high-resolution hydrological model to correct internal fluxes and transfer parameters between watersheds. Results show improved accuracy, advancing development of learnable and interpretable process-based models.
Alonso Pizarro, Demetris Koutsoyiannis, and Alberto Montanari
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-389, https://doi.org/10.5194/hess-2024-389, 2025
Revised manuscript accepted for HESS
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We introduce RUMI, a new metric to improve rainfall-runoff simulations. RUMI better captures the link between observed and simulated stream flows by considering uncertainty at a core computation step. Tested on 99 catchments and with the GR4J model, it outperforms traditional metrics by providing more reliable and consistent results. RUMI paves the way for more accurate hydrological predictions.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht H. Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci., 29, 335–360, https://doi.org/10.5194/hess-29-335-2025, https://doi.org/10.5194/hess-29-335-2025, 2025
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Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping to better prepare for and respond to floods.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
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To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their physical realism, which is measured by the ability of the model to reproduce observed system dynamics. Using a model to represent the dynamics of water and nitrate and dissolved organic carbon concentrations in an agricultural catchment, we showed that using solute-concentration data for calibration is useful to improve the hydrological consistency of the model.
Parthkumar A. Modi, Jared C. Carbone, Keith S. Jennings, Hannah Kamen, Joseph R. Kasprzyk, Bill Szafranski, Cameron W. Wobus, and Ben Livneh
EGUsphere, https://doi.org/10.5194/egusphere-2024-4046, https://doi.org/10.5194/egusphere-2024-4046, 2025
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This study shows that in unmanaged snow-dominated basins, high forecast accuracy doesn’t always lead to high economic value, especially during extreme conditions like droughts. It highlights how irregular errors in modern forecasting systems weaken the connection between accuracy and value. These findings call for forecast evaluations to focus not only on accuracy but also on economic impacts, providing valuable guidance for better water resource management under uncertainty.
Benjamin Guillaume, Adrien Michez, and Aurore Degré
EGUsphere, https://doi.org/10.5194/egusphere-2024-3978, https://doi.org/10.5194/egusphere-2024-3978, 2025
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Nature-based solutions (NbS) can mitigate floods and agricultural droughts by enhancing soil health and restoring hydrological cycles. This study highlights that leveraging soil diversity is key to optimizing NbS performance.
Haley A. Canham, Belize Lane, Colin B. Phillips, and Brendan P. Murphy
Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025, https://doi.org/10.5194/hess-29-27-2025, 2025
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The influence of watershed disturbances has proved challenging to disentangle from natural streamflow variability. This study evaluates the influence of time-varying hydrologic controls on rainfall–runoff in undisturbed and wildfire-disturbed watersheds using a novel time-series event separation method. Across watersheds, water year type and season influenced rainfall–runoff patterns. Accounting for these controls enabled clearer isolation of wildfire effects.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci., 28, 5511–5539, https://doi.org/10.5194/hess-28-5511-2024, https://doi.org/10.5194/hess-28-5511-2024, 2024
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Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .
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
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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.
Laia Estrada, Xavier Garcia, Joan Saló-Grau, Rafael Marcé, Antoni Munné, and Vicenç Acuña
Hydrol. Earth Syst. Sci., 28, 5353–5373, https://doi.org/10.5194/hess-28-5353-2024, https://doi.org/10.5194/hess-28-5353-2024, 2024
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Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological model, integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, https://doi.org/10.5194/hess-28-5331-2024, 2024
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Daniel T. Myers, David Jones, Diana Oviedo-Vargas, John Paul Schmit, Darren L. Ficklin, and Xuesong Zhang
Hydrol. Earth Syst. Sci., 28, 5295–5310, https://doi.org/10.5194/hess-28-5295-2024, https://doi.org/10.5194/hess-28-5295-2024, 2024
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We studied how streamflow and water quality models respond to land cover data collected by satellites during the growing season versus the non-growing season. The land cover data showed more trees during the growing season and more built areas during the non-growing season. We next found that the use of non-growing season data resulted in a higher modeled nutrient export to streams. Knowledge of these sensitivities would be particularly important when models inform water resource management.
Hatice Türk, Christine Stumpp, Markus Hrachowitz, Karsten Schulz, Peter Strauss, Günter Blöschl, and Michael Stockinger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-359, https://doi.org/10.5194/hess-2024-359, 2024
Revised manuscript accepted for HESS
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Using advances in transit time estimation and tracer data, we tested if fast-flow transit times are controlled solely by soil moisture or are also controlled by precipitation intensity. We used soil moisture-dependent and precipitation intensity-conditional transfer functions. We showed that significant portion of event water bypasses the soil matrix through fast flow paths (overland flow, tile drains, preferential flow paths) in dry soil conditions for both low and high-intensity precipitation.
Kevin R. Shook, Paul H. Whitfield, Christopher Spence, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 28, 5173–5192, https://doi.org/10.5194/hess-28-5173-2024, https://doi.org/10.5194/hess-28-5173-2024, 2024
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Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Anjana Devanand, Jason Evans, Andy Pitman, Sujan Pal, David Gochis, and Kevin Sampson
EGUsphere, https://doi.org/10.5194/egusphere-2024-3148, https://doi.org/10.5194/egusphere-2024-3148, 2024
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Including lateral flow increases evapotranspiration near major river channels in high-resolution land surface simulations in southeast Australia, consistent with observations. The 1-km resolution model shows a widespread pattern of dry ridges that does not exist at coarser resolutions. Our results have implications for improved simulations of droughts and future water availability.
Sylvain Payraudeau, Pablo Alvarez-Zaldivar, Paul van Dijk, and Gwenaël Imfeld
EGUsphere, https://doi.org/10.5194/egusphere-2024-2840, https://doi.org/10.5194/egusphere-2024-2840, 2024
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Our study focuses on the rising concern of pesticides damaging aquatic ecosystems, which puts drinking water, the environment, and human health at risk. We provided more accurate estimates of how pesticides break down and spread in small water systems, helping to improve pesticide management practices. By using unique chemical markers in our analysis, we enhanced the accuracy of our predictions, offering important insights for better protection of water sources and natural ecosystems.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
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We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Vishal Thakur, Yannis Markonis, Rohini Kumar, Johanna Ruth Thomson, Mijael Rodrigo Vargas Godoy, Martin Hanel, and Oldrich Rakovec
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-341, https://doi.org/10.5194/hess-2024-341, 2024
Revised manuscript accepted for HESS
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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.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Nan Wu, Ke Zhang, Amir Naghibi, Hossein Hashemi, Zhongrui Ning, Qinuo Zhang, Xuejun Yi, Haijun Wang, Wei Liu, Wei Gao, and Jerker Jarsjö
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-324, https://doi.org/10.5194/hess-2024-324, 2024
Revised manuscript accepted for HESS
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The hydrology of cold regions in the human population is poorly understood due to complex motion and limited data, hindering streamflow analysis. Using existing models, we compared runoff from an extended model with snowmelt and frozen ground, validating its reliability and integration. This study focuses on the effects of snowmelt and frozen ground on runoff, affecting precipitation type, surface-groundwater partitioning, and evapotranspiration.
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Donohue, R. J., Roderick, M. L., and McVicar, T. R.: On the importance of including vegetation dynamics in Budyko's hydrological model, Hydrol. Earth Syst. Sci., 11, 983–995, https://doi.org/10.5194/hess-11-983-2007, 2007.
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Hrachowitz, M., Stockinger, M., Coenders-Gerrits, M., van der Ent, R., Bogena, H., Lücke, A., and Stumpp, C.: Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment, Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, 2021.
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Short summary
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting...
