Articles | Volume 26, issue 10
https://doi.org/10.5194/hess-26-2733-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-2733-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 May 2022
Research article |
| 24 May 2022
| 24 May 2022
On constraining a lumped hydrological model with both piezometry and streamflow: results of a large sample evaluation
Antoine Pelletier
CORRESPONDING AUTHOR
Direction de la recherche, École des Ponts, Marne-la-Vallée, France
UR HYCAR, Université Paris-Saclay, INRAE, Antony, France
Vazken Andréassian
UR HYCAR, Université Paris-Saclay, INRAE, Antony, France
Related authors
Antoine Pelletier and Vazken Andréassian
Hydrol. Earth Syst. Sci., 24, 1171–1187, https://doi.org/10.5194/hess-24-1171-2020, https://doi.org/10.5194/hess-24-1171-2020, 2020
Short summary
Short summary
There are many ways for water to join a river after a rainfall event, but they can be split into two categories: the quick ones that remain in the surface and the slow ones that use other trajectories. Thus, measured streamflow of a river can be split into two components: quickflow and baseflow. We present a new method to perform this separation, using only streamflow and rainfall data, which are generally broadly available. It is then used as an analysis tool of river dynamics over France.
Vazken Andréassian, Guilherme Mendoza Guimarães, Alban de Lavenne, and Julien Lerat
EGUsphere, https://doi.org/10.5194/egusphere-2025-414, https://doi.org/10.5194/egusphere-2025-414, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Using 4122 catchments from four continents, we investigate how annual streamflow depends on climate variables (rainfall and potential evaporation) and on the season when precipitation occurs, using and index representing the synchronicity between precipitation and potential evaporation. In all countries and under the main climates represented, synchronicity is, after precipitation, the second most important factor to explain annual streamflow variations.
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
Short summary
Short summary
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.
Olivier Delaigue, Guilherme Mendoza Guimarães, Pierre Brigode, Benoît Génot, Charles Perrin, Jean-Michel Soubeyroux, Bruno Janet, Nans Addor, and Vazken Andréassian
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-415, https://doi.org/10.5194/essd-2024-415, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This dataset covers 654 rivers all flowing in France. The provided time series and catchment attributes will be of interest to those modelers wishing to analyse hydrological behavior, perform model assessments.
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
Short summary
Short summary
The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024, https://doi.org/10.5194/essd-16-2073-2024, 2024
Short summary
Short summary
The aim of this work is to provide the first hydroclimatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named Simbi, provides hydroclimatic time series for around 150 stations and 24 catchment areas.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
Short summary
Short summary
Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Alban de Lavenne, Vazken Andréassian, Louise Crochemore, Göran Lindström, and Berit Arheimer
Hydrol. Earth Syst. Sci., 26, 2715–2732, https://doi.org/10.5194/hess-26-2715-2022, https://doi.org/10.5194/hess-26-2715-2022, 2022
Short summary
Short summary
A watershed remembers the past to some extent, and this memory influences its behavior. This memory is defined by the ability to store past rainfall for several years. By releasing this water into the river or the atmosphere, it tends to forget. We describe how this memory fades over time in France and Sweden. A few watersheds show a multi-year memory. It increases with the influence of groundwater or dry conditions. After 3 or 4 years, they behave independently of the past.
Paul Royer-Gaspard, Vazken Andréassian, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 25, 5703–5716, https://doi.org/10.5194/hess-25-5703-2021, https://doi.org/10.5194/hess-25-5703-2021, 2021
Short summary
Short summary
Most evaluation studies based on the differential split-sample test (DSST) endorse the consensus that rainfall–runoff models lack climatic robustness. In this technical note, we propose a new performance metric to evaluate model robustness without applying the DSST and which can be used with a single hydrological model calibration. Our work makes it possible to evaluate the temporal transferability of any hydrological model, including uncalibrated models, at a very low computational cost.
Pierre Nicolle, Vazken Andréassian, Paul Royer-Gaspard, Charles Perrin, Guillaume Thirel, Laurent Coron, and Léonard Santos
Hydrol. Earth Syst. Sci., 25, 5013–5027, https://doi.org/10.5194/hess-25-5013-2021, https://doi.org/10.5194/hess-25-5013-2021, 2021
Short summary
Short summary
In this note, a new method (RAT) is proposed to assess the robustness of hydrological models. The RAT method is particularly interesting because it does not require multiple calibrations (it is therefore applicable to uncalibrated models), and it can be used to determine whether a hydrological model may be safely used for climate change impact studies. Success at the robustness assessment test is a necessary (but not sufficient) condition of model robustness.
José Manuel Tunqui Neira, Vazken Andréassian, Gaëlle Tallec, and Jean-Marie Mouchel
Hydrol. Earth Syst. Sci., 24, 1823–1830, https://doi.org/10.5194/hess-24-1823-2020, https://doi.org/10.5194/hess-24-1823-2020, 2020
Short summary
Short summary
This paper deals with the mathematical representation of concentration–discharge relationships. We propose a two-sided affine power scaling relationship (2S-APS) as an alternative to the classic one-sided power scaling relationship (commonly known as
power law). We also discuss the identification of the parameters of the proposed relationship, using an appropriate numerical criterion, based on high-frequency chemical time series of the Orgeval-ORACLE observatory.
Antoine Pelletier and Vazken Andréassian
Hydrol. Earth Syst. Sci., 24, 1171–1187, https://doi.org/10.5194/hess-24-1171-2020, https://doi.org/10.5194/hess-24-1171-2020, 2020
Short summary
Short summary
There are many ways for water to join a river after a rainfall event, but they can be split into two categories: the quick ones that remain in the surface and the slow ones that use other trajectories. Thus, measured streamflow of a river can be split into two components: quickflow and baseflow. We present a new method to perform this separation, using only streamflow and rainfall data, which are generally broadly available. It is then used as an analysis tool of river dynamics over France.
José Manuel Tunqui Neira, Vazken Andréassian, Gaëlle Tallec, and Jean-Marie Mouchel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-325, https://doi.org/10.5194/hess-2019-325, 2019
Manuscript not accepted for further review
Short summary
Short summary
This Technical Note deals with the mathematical representation of concentration-discharge relationships and with the identification of its parameters. We propose a two-sided power transformation alternative to the classical log-log transformation, and a multicriterion identification procedure allowing determining parameters that are efficient, both from the concentration and the load points of view.
Vazken Andréassian and Tewfik Sari
Hydrol. Earth Syst. Sci., 23, 2339–2350, https://doi.org/10.5194/hess-23-2339-2019, https://doi.org/10.5194/hess-23-2339-2019, 2019
Short summary
Short summary
In this Technical Note, we present two water balance formulas: the Turc–Mezentsev and Tixeront–Fu formulas. These formulas have a puzzling numerical similarity, which we discuss in detail and try to interpret mathematically and hydrologically.
Cédric Rebolho, Vazken Andréassian, and Nicolas Le Moine
Hydrol. Earth Syst. Sci., 22, 5967–5985, https://doi.org/10.5194/hess-22-5967-2018, https://doi.org/10.5194/hess-22-5967-2018, 2018
Short summary
Short summary
Inundation models are useful for hazard management and prevention. They are traditionally based on hydraulic partial differential equations (with satisfying results but large data and computational requirements). This study presents a simplified approach combining reach-scale geometric properties with steady uniform flow equations. The model shows promising results overall, although difficulties persist in the most complex urbanised reaches.
Vazken Andréassian, Laurent Coron, Julien Lerat, and Nicolas Le Moine
Hydrol. Earth Syst. Sci., 20, 4503–4524, https://doi.org/10.5194/hess-20-4503-2016, https://doi.org/10.5194/hess-20-4503-2016, 2016
Short summary
Short summary
We present a new method to derive the empirical (i.e., data-based) elasticity of streamflow to precipitation and potential evaporation. This method, which uses long-term hydrometeorological records, is tested on a set of 519 French catchments. We compare our method with the classical approach found in the literature and demonstrate its robustness and efficiency. Empirical elasticity is a powerful tool to test the extrapolation capacity of hydrological models.
Alban de Lavenne, Guillaume Thirel, Vazken Andréassian, Charles Perrin, and Maria-Helena Ramos
Proc. IAHS, 373, 87–94, https://doi.org/10.5194/piahs-373-87-2016, https://doi.org/10.5194/piahs-373-87-2016, 2016
Short summary
Short summary
Developing modelling tools that help to understand the spatial distribution of water resources is a key issue for better management. Ideally, hydrological models which discretise catchment space into sub-catchments should offer better streamflow simulations than lumped models, along with spatially-relevant water resources management solutions. However we demonstrate that those model raise other issues related to the calibration strategy and to the identifiability of the parameters.
F. Bourgin, V. Andréassian, C. Perrin, and L. Oudin
Hydrol. Earth Syst. Sci., 19, 2535–2546, https://doi.org/10.5194/hess-19-2535-2015, https://doi.org/10.5194/hess-19-2535-2015, 2015
D. Defrance, P. Javelle, D. Organde, S. Ecrepont, V. Andréassian, and P. Arnaud
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-4365-2014, https://doi.org/10.5194/hessd-11-4365-2014, 2014
Revised manuscript has not been submitted
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
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?
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
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
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
Seasonal variation in land cover estimates reveals sensitivities and opportunities for environmental models
Estimating response times, flow velocities, and roughness coefficients of Canadian Prairie basins
Learning landscape features from streamflow with autoencoders
On the use of streamflow transformations for hydrological model calibration
Simulation-based inference for parameter estimation of complex watershed simulators
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Catchment response to climatic variability: implications for root zone storage and streamflow predictions
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Projections of streamflow intermittence under climate change in European drying river networks
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
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Extended range forecasting of stream water temperature with deep learning models
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Analyzing the generalization capabilities of hybrid hydrological models for extrapolation to extreme events
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: An analysis based on 63 catchments in southeast China
Runoff component quantification and future streamflow projection in a large mountainous basin based on a multidata-constrained cryospheric-hydrological model
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
Scale-dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Evaluating the effects of topography and land use change on hydrological signatures: a comparative study of two adjacent watersheds
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2024-3355, https://doi.org/10.5194/egusphere-2024-3355, 2024
Short summary
Short summary
Long Short-Term Memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modeling. However, most studies focus on daily-scale predictions, 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 input of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
Short summary
Short summary
We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
Short summary
Short summary
This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
Short summary
Short summary
This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
Short summary
Short summary
A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
Short summary
Short summary
Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
Short summary
Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
Short summary
Short summary
Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
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. Discuss., https://doi.org/10.5194/hess-2024-272, https://doi.org/10.5194/hess-2024-272, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Our study projects how climate change will affect drying of river segments and stream networks in Europe, using advanced modeling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent, intense and start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists in evaluating the ecological health of river ecosystem.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
Short summary
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.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-221, https://doi.org/10.5194/hess-2024-221, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what it truly reflects 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 time scales for accurate drought characterization and monitoring.
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2591, https://doi.org/10.5194/egusphere-2024-2591, 2024
Short summary
Short summary
We generate operational forecasts of daily maximum stream water temperature for the next month at 54 stations in Switzerland with our best performing data-driven model. The average forecast error is 0.38 °C for 1 day ahead and increases to 0.90 °C for 1 month 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.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
Short summary
Short summary
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
Short summary
The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Eduardo Acuna Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2024-2147, https://doi.org/10.5194/egusphere-2024-2147, 2024
Short summary
Short summary
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.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
Short summary
Short summary
The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
Short summary
Short summary
By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
Short summary
Short summary
Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
Short summary
Short summary
Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2024-1438, https://doi.org/10.5194/egusphere-2024-1438, 2024
Short summary
Short summary
Common intuition holds that higher input data resolution leads to better results. To assess the benefits of high-resolution data, we conducted simulation experiments using data with various temporal resolutions across multiple catchments, and found that higher resolution data does 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.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2024-1464, https://doi.org/10.5194/egusphere-2024-1464, 2024
Short summary
Short summary
Our study conducted a detailed analysis of runoff component and future trend in the Yarlung Tsangpo River basin owing to the existed differences in the published results, and find that the contributions of snowmelt and glacier melt runoff to streamflow were limited, both for ~5 % which were much lower than previous results. The streamflow there will continuously increase in the future, but the overestimated contribution from glacier melt would lead to an underestimation on such increasing trend.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
Short summary
Short summary
Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
Short summary
Short summary
Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
Short summary
Short summary
A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
Short summary
Short summary
Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
Short summary
Short summary
Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
Short summary
Short summary
Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart Lane, and Francesco Comiti
EGUsphere, https://doi.org/10.5194/egusphere-2024-1687, https://doi.org/10.5194/egusphere-2024-1687, 2024
Short summary
Short summary
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 an overparametrization limit is reached.
Haifan Liu, Haochen Yan, and Mingfu Guan
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-136, https://doi.org/10.5194/hess-2024-136, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
In mountainous areas, the relationship between slope and annual hydrological processes is pronounced. However, at lower elevations, this relationship is weak in steeper watersheds. In addition, urbanization leads to an increase in annual surface runoff in all watersheds, especially in steep-slope watersheds. Flatter watersheds exhibit a buffering capacity against urbanization. However, this buffering capacity is diminishing as annual rainfall intensity increases.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
Short summary
Short summary
We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
Short summary
Short summary
In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Cited articles
Ardia, D., Arango, J. O., and Gomez, N. G.: Jump-Diffusion Calibration using
Differential Evolution, Wilmott Magazine, 55, 76–79, https://doi.org/10.1002/wilm.10034, 2011a. a
Ardia, D., Boudt, K., Carl, P., Mullen, K. M., and Peterson, B. G.: Differential Evolution with DEoptim: An Application to Non-Convex
Portfolio Optimization, R J., 3, 27–34, 2011b. a
Ardia, D., Mullen, K. M., Peterson, B. G., and Ulrich, J.: DEoptim:
Differential Evolution in R, version 2.2-5, CRAN [code],
https://CRAN.R-project.org/package=DEoptim (last access: 17 May 2022), 2020. a
Aubert, D., Loumagne, C., and Oudin, L.: Sequential assimilation of soil
moisture and streamflow data in a conceptual rainfall–runoff model, J. Hydrol., 280, 145–161, https://doi.org/10.1016/s0022-1694(03)00229-4, 2003a. a
Aubert, D., Loumagne, C., Oudin, L., and Hégarat-Mascle, S. L.: Assimilation of soil moisture into hydrological models: the sequential method, Can. J. Remote Sens., 29, 711–717, https://doi.org/10.5589/m03-042, 2003b. a
Barthel, R.: HESS Opinions “Integration of groundwater and surface water
research: an interdisciplinary problem?”, Hydrol. Earth Syst. Sci., 18, 2615–2628, https://doi.org/10.5194/hess-18-2615-2014, 2014. a
Barthel, R. and Banzhaf, S.: Groundwater and Surface Water Interaction at the
Regional-scale – A Review with Focus on Regional Integrated Models, Water Resour. Manage., 30, 1–32, https://doi.org/10.1007/s11269-015-1163-z, 2015. a, b
Bartlett, M. S. and Porporato, A.: A Class of Exact Solutions of the Boussinesq Equation for Horizontal and Sloping Aquifers, Water Resour. Res., 54, 767–778, https://doi.org/10.1002/2017WR022056, 2018. a
Bauer, D. F.: Constructing Confidence Sets Using Rank Statistics, J. Am. Stat. Assoc., 67, 687–690, https://doi.org/10.1080/01621459.1972.10481279, 1972. a
Bel, F., Lacroix, A., Mollard, A., David, C., Beaudoin, N., Mary, B., Vachaud, G., Vauclin, M., and Garino, B.: Une approche interdisciplinaire,
pluri-échelle, multipartenaire des pollutions diffuses de l'eau: l'expérience de La Côte Saint-André (Isère), La Houille Blanche, 6, 72–79, https://doi.org/10.1051/lhb/1999074, 1999. a
Bergström, S. and Forsman, A.: Development of a conceptual deterministic rainfall-runoff model, Hydrol. Res., 4, 147–170, https://doi.org/10.2166/nh.1973.0012, 1973. a
Bergström, S. and Sandberg, G.: Simulation of Groundwater Response by
Conceptual Models, Hydrol. Res., 14, 71–84, https://doi.org/10.2166/nh.1983.0007, 1983. a
Beven, K.: Hydrograph separation?, in: Proc. BHS Third National Hydrology
Symposium, Institute of hydrology, 3.2–3.8, 1991. a
Beven, K.: Prophecy, reality and uncertainty in distributed hydrological
modelling, Adv. Water Resour., 16, 41–51, https://doi.org/10.1016/0309-1708(93)90028-e, 1993. a
Beven, K.: Rainfall-Runoff Modelling, John Wiley & Sons, Ltd,
https://doi.org/10.1002/9781119951001, 2012. a, b
Borzì, I., Bonaccorso, B., and Fiori, A.: A Modified IHACRES
Rainfall-Runoff Model for Predicting the Hydrologic Response of a River Basin
Connected with a Deep Groundwater Aquifer, Water, 11, 2031,
https://doi.org/10.3390/w11102031, 2019. a
Brigode, P., Génot, B., Lobligeois, F., and Delaigue, O.: Summary sheets of watershed-scale hydroclimatic observed data for France, INRAE,
https://doi.org/10.15454/UV01P1, 2021. a
Brunner, P. and Simmons, C. T.: HydroGeoSphere: A Fully Integrated, Physically Based Hydrological Model, Groundwater, 50, 170–176,
https://doi.org/10.1111/j.1745-6584.2011.00882.x, 2011. a
Carlier, C., Wirth, S. B., Cochand, F., Hunkeler, D., and Brunner, P.: Geology controls streamflow dynamics, J. Hydrol., 566, 756–769,
https://doi.org/10.1016/j.jhydrol.2018.08.069, 2018. a
Castany, G.: Traité pratique des eaux souterraines, Dunod, OCLC number 31063775, 1963. a
Coron, L., Thirel, G., Delaigue, O., Perrin, C., and Andréassian, V.: The
Suite of Lumped GR Hydrological Models in an R package, Environ. Model. Softw., 94, 166–171, https://doi.org/10.1016/j.envsoft.2017.05.002, 2017. a
Coron, L., Delaigue, O., Thirel, G., Dorchies, D., Perrin, C., and Michel, C.: airGR: Suite of GR Hydrological Models for Precipitation-Runoff
Modelling, r package version 1.6.10.4, INRAE [code], https://doi.org/10.15454/EX11NA, 2021. a, b, c, d
Creutzfeldt, B., Ferré, T., Troch, P., Merz, B., Wziontek, H., and Güntner, A.: Total water storage dynamics in response to climate variability and extremes: Inference from long-term terrestrial gravity measurement, J. Geophys. Res.-Atmos., 117, D08112, https://doi.org/10.1029/2011JD016472, 2012. a
Dassargues, A., Maréchal, J. C., Carabin, G., and Sels, O.: On the necessity to use three-dimensional groundwater models for describing impact of drought conditions on streamflow regimes, in: Hydrological Extremes: Understanding, Predicting, Mitigating, edited by: Gottschalk, L., Olivry, J.-C., Reed, D., and Rosbjerg, D., IAHS, 165–170, ISBN 978-1-901502-85-5, 1999. a
Delaigue, O., Génot, B., Lebecherel, L., Brigode, P., and Bourgin, P.-Y.: Base de données hydroclimatiques observées à l'échelle de la France, INRAE [data set], UR HYCAR, https://webgr.inrae.fr/base-de-donnees (last access: 17 May 2022), 2021. a
de Lavenne, A., Thirel, G., Andréassian, V., Perrin, C., and Ramos, M.-H.: Spatial variability of the parameters of a semi-distributed hydrological model, Proc. Int. Assoc. Hydrol. Sci., 373, 87–94, https://doi.org/10.5194/piahs-373-87-2016, 2016. a, b
Dembélé, M., Hrachowitz, M., Savenije, H. H. G., Mariéthoz, G., and Schaefli, B.: Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite
Data Sets, Water Resour. Res., 56, e2019WR026085, https://doi.org/10.1029/2019wr026085, 2020. a
Demirel, M. C., Özen, A., Orta, S., Toker, E., Demir, H. K., Ekmekcioǧlu, Ö., Tayşi, H., Eruçar, S., Saǧ, A. B., Sarı, Ö., Tuncer, E., Hancı, H., Özcan, T. İ., Erdem, H., Koşucu, M. M., Başakın, E. E., Ahmed, K., Anwar, A., Avcuoǧlu, M. B., Vanlı, Ö., Stisen, S., and Booij, M. J.: Additional Value of Using Satellite-Based Soil Moisture and Two Sources of Groundwater Data for Hydrological Model Calibration, Water, 11, 2083, https://doi.org/10.3390/w11102083, 2019. a
Eddelbuettel, D.: RcppDE: Global Optimization by Differential Evolution in C
Efstratiadis, A., Nalbantis, I., Koukouvinos, A., Rozos, E., and Koutsoyiannis, D.: HYDROGEIOS: a semi-distributed GIS-based hydrological model for modified river basins, Hydrol. Earth Syst. Sci., 12, 989–1006,
https://doi.org/10.5194/hess-12-989-2008, 2008. a
El-Nasr, A. A., Arnold, J. G., Feyen, J., and Berlamont, J.: Modelling the
hydrology of a catchment using a distributed and a semi-distributed model,
Hydrol. Process., 19, 573–587, https://doi.org/10.1002/hyp.5610, 2005. a
Feyen, L., Vázquez, R., Christiaens, K., Sels, O., and Feyen, J.:
Application of a distributed physically-based hydrological model to a medium
size catchment, Hydrol. Earth Syst. Sci., 4, 47–63,
https://doi.org/10.5194/hess-4-47-2000, 2000. a
Guérin, A., Devauchelle, O., Robert, V., Kitou, T., Dessert, C., Quiquerez, A., Allemand, P., and Lajeunesse, E.: Stream-Discharge Surges Generated by Groundwater Flow, Geophys. Res. Lett., 46, 7447–7455,
https://doi.org/10.1029/2019GL082291, 2019. a
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of
the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009. a
Habets, F., Gascoin, S., Korkmaz, S., Thiéry, D., Zribi, M., Amraoui, N.,
Carli, M., Ducharne, A., Leblois, E., Ledoux, E., Martin, E., Noilhan, J.,
Ottlé, C., and Viennot, P.: Multi-model comparison of a major flood in the groundwater-fed basin of the Somme River (France), Hydrol. Earth Syst. Sci., 14, 99–117, https://doi.org/10.5194/hess-14-99-2010, 2010. a, b, c
Hayashi, M.: Alpine Hydrogeology: The Critical Role of Groundwater in Sourcing the Headwaters of the World, Groundwater, 58, 498–510,
https://doi.org/10.1111/gwat.12965, 2020. a
Herron, N. and Croke, B.: Including the influence of groundwater exchanges in a lumped rainfall-runoff model, Math. Comput. Simul., 79, 2689–2700, https://doi.org/10.1016/j.matcom.2008.08.007, 2009. a
Hughes, D. A.: Incorporating groundwater recharge and discharge functions into an existing monthly rainfall–runoff model/Incorporation de fonctions de recharge et de vidange superficielle de nappes au sein d'un modèle pluie-débit mensuel existant, Hydrolog. Sci. J., 49, 297–311, https://doi.org/10.1623/hysj.49.2.297.34834, 2004. a
IGN: BD CARTO, Institut national de l'information géographique et forestière, https://geoservices.ign.fr/documentation/donnees/vecteur/bdcarto (last access: 17 May 2022), 2021. a
Immerzeel, W. and Droogers, P.: Calibration of a distributed hydrological model based on satellite evapotranspiration, J. Hydrol., 349, 411–424,
https://doi.org/10.1016/j.jhydrol.2007.11.017, 2008. a
Jakeman, A. J. and Hornberger, G. M.: How much complexity is warranted in a
rainfall-runoff model?, Water Resour. Res., 29, 2637–2649, https://doi.org/10.1029/93wr00877, 1993. a
Jian, J., Ryu, D., Costelloe, J. F., and Su, C.-H.: Towards hydrological model calibration using river level measurements, J. Hydrol.: Reg. Stud., 10, 95–109, https://doi.org/10.1016/j.ejrh.2016.12.085, 2017. a
Käser, D. and Hunkeler, D.: Contribution of alluvial groundwater to the
outflow of mountainous catchments, Water Resour. Res., 52, 680–697,
https://doi.org/10.1002/2014WR016730, 2016. a
Khu, S.-T., Madsen, H., and di Pierro, F.: Incorporating multiple observations for distributed hydrologic model calibration: An approach using a multi-objective evolutionary algorithm and clustering, Adv. Water Resour., 31, 1387–1398, https://doi.org/10.1016/j.advwatres.2008.07.011, 2008. a
Klemeš, V.: Operational testing of hydrological simulation models,
Hydrolog. Sci. J., 31, 13–24, https://doi.org/10.1080/02626668609491024, 1986. a
Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube
basin under an ensemble of climate change scenarios, J. Hydrol., 424–425, 264–277, https://doi.org/10.1016/j.jhydrol.2012.01.011, 2012. a
Lalot, E., Curie, F., Wawrzyniak, V., Baratelli, F., Schomburgk, S., Flipo, N., Piegay, H., and Moatar, F.: Quantification of the contribution of the Beauce groundwater aquifer to the discharge of the Loire River using thermal
infrared satellite imaging, Hydrol. Earth Syst. Sci., 19, 4479–4492, https://doi.org/10.5194/hess-19-4479-2015, 2015. a
Leleu, I., Tonnelier, I., Puechberty, R., Gouin, P., Viquendi, I., Cobos, L.,
Foray, A., Baillon, M., and Ndima, P.-O.: La refonte du système d'information national pour la gestion et la mise à disposition des données hydrométriques, La Houille Blanche, 100, 25–32, https://doi.org/10.1051/lhb/2014004, 2014. a
Le Moine, N.: Le bassin versant de surface vu par le souterrain: une voie
d'amélioration des performances et du réalisme des modèles pluie-débit?, PhD thesis, Université Pierre et Marie Curie, Paris, France, cemagref Antony, http://www.theses.fr/2008PA066468 (last access: 17 May 2022), 2008. a, b, c, d
Le Moine, N., Andréassian, V., and Mathevet, T.: Confronting surface-
and groundwater balances on the La Rochefoucauld-Touvre karstic system
(Charente, France), Water Resour. Res., 44, W03403, https://doi.org/10.1029/2007wr005984, 2008. a, b
Lenhardt, F., Doucet, N., Boisson, M., and Billault, P.: The Cenomanian Sands
aquifer model: an effective groundwater management tool, Tech. rep., SOGREAH,
http://feflow.info/fileadmin/FEFLOW/content_tagung/TagungsCD/papers/5.pdf
(last access: 4 May 2022), 2009. a
Li, S., Gitau, M., Engel, B. A., Zhang, L., Du, Y., Wallace, C., and Flanagan, D. C.: Development of a distributed hydrological model to facilitate watershed management, Hydrolog. Sci. J., 62, 1755–1771,
https://doi.org/10.1080/02626667.2017.1351029, 2017. a
Lo, M.-H. and Famiglietti, J. S.: Effect of water table dynamics on land
surface hydrologic memory, J. Geophys. Res., 115, D22118, https://doi.org/10.1029/2010JD014191, 2010. a
Mackay, J., Jackson, C., and Wang, L.: A lumped conceptual model to simulate
groundwater level time-series, Environ. Model. Softw., 61, 229–245, https://doi.org/10.1016/j.envsoft.2014.06.003, 2014. a
Madsen, H.: Parameter estimation in distributed hydrological catchment
modelling using automatic calibration with multiple objectives, Adv. Water Resour., 26, 205–216, https://doi.org/10.1016/s0309-1708(02)00092-1, 2003. a
Maillet, E.: Essais d'hydraulique souterraine & fluviale, A. Hermann,
http://archive.org/details/essaisdhydrauli00mailgoog (last access: 17 May 2022), 1905. a
Mann, H. B. and Whitney, D. R.: On a Test of Whether one of Two Random
Variables is Stochastically Larger than the Other, Ann. Math. Stat., 18, 50–60, https://doi.org/10.1214/aoms/1177730491, 1947. a
McDonnell, J. J. and Beven, K.: Debates – The future of hydrological sciences: A (common) path forward? A call to action aimed at understanding velocities, celerities and residence time distributions of the headwater hydrograph, Water Resour. Res., 50, 5342–5350, https://doi.org/10.1002/2013WR015141, 2014. a
Michel, C.: Que peut-on faire en hydrologie avec modèle conceptuel
à un seul paramètre ?, La Houille Blanche, 69, 39–44, https://doi.org/10.1051/lhb/1983004, 1983. a
Michel, C.: Hydrologie appliquée aux petits bassins versants ruraux, Cemagref, https://side.developpement-durable.gouv.fr/Default/doc/SYRACUSE/162685/hydrologie-appliquee-aux-petits-bassins-ruraux (last access: 17 May 2022), 1991. a
Michel, C., Perrin, C., and Andréassian, V.: The exponential store: a correct formulation for rainfall–runoff modelling, Hydrolog. Sci. J., 48, 109–124, https://doi.org/10.1623/hysj.48.1.109.43484, 2003. a
Milzow, C., Krogh, P. E., and Bauer-Gottwein, P.: Combining satellite radar
altimetry, SAR surface soil moisture and GRACE total storage changes for
hydrological model calibration in a large poorly gauged catchment, Hydrol.
Earth Syst. Sci., 15, 1729–1743, https://doi.org/10.5194/hess-15-1729-2011, 2011. a
Moore, R. J.: Real-Time Flood Forecasting Systems: Perspectives and Prospects, Springer, Berlin, Heidelberg, 147–189, https://doi.org/10.1007/978-3-642-58609-5_11, 1999. a
Moore, R. J. and Bell, V. A.: Incorporation of groundwater losses and well
level data in rainfall-runoff models illustrated using the PDM, Hydrol. Earth Syst. Sci., 6, 25–38, https://doi.org/10.5194/hess-6-25-2002, 2002. a, b, c
Moreda, F., Koren, V., Zhang, Z., Reed, S., and Smith, M.: Parameterization of distributed hydrological models: learning from the experiences of lumped
modeling, J. Hydrol., 320, 218–237, https://doi.org/10.1016/j.jhydrol.2005.07.014, 2006. a
Mostafaie, A., Forootan, E., Safari, A., and Schumacher, M.: Comparing
multi-objective optimization techniques to calibrate a conceptual hydrological model using in situ runoff and daily GRACE data, Comput. Geosci., 22, 789–814, https://doi.org/10.1007/s10596-018-9726-8, 2018. a
Mullen, K., Ardia, D., Gil, D., Windover, D., and Cline, J.: DEoptim: An R Package for Global Optimization by Differential Evolution, J. Stat. Softw., 40, 1–26, https://doi.org/10.18637/jss.v040.i06, 2011. a
Nash, J. and Sutcliffe, J.: River flow forecasting through conceptual models
part I – A discussion of principles, J. Hydrol., 10, 282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970. a, b, c
Nicolle, P., Pushpalatha, R., Perrin, C., François, D., Thiéry, D.,
Mathevet, T., Lay, M. L., Besson, F., Soubeyroux, J.-M., Viel, C., Regimbeau,
F., Andréassian, V., Maugis, P., Augeard, B., and Morice, E.: Benchmarking hydrological models for low-flow simulation and forecasting on
French catchments, Hydrol. Earth Syst. Sci., 18, 2829–2857,
https://doi.org/10.5194/hess-18-2829-2014, 2014. a
Nicolle, P., Besson, F., Delaigue, O., Etchevers, P., François, D., Lay,
M. L., Perrin, C., Rousset, F., Thiéry, D., Tilmant, F., Magand, C.,
Leurent, T., and Jacob, É.: PREMHYCE: An operational tool for low-flow forecasting, Proc. Int. Assoc. Hydrol. Sci., 383, 381–389, https://doi.org/10.5194/piahs-383-381-2020, 2020. a
Oudin, L., Weisse, A., Loumagne, C., and Hégarat-Mascle, S. L.: Assimilation of soil moisture into hydrological models for flood forecasting: a variational approach, Can. J. Remote Sens., 29, 679–686,
https://doi.org/10.5589/m03-038, 2003. a
Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil,
F., and Loumagne, C.: Which potential evapotranspiration input for a lumped
rainfall–runoff model?, J. Hydrol., 303, 290–306, https://doi.org/10.1016/j.jhydrol.2004.08.026, 2005. a
Pelletier, A. and Andréassian, V.: Hydrograph separation: an impartial
parametrisation for an imperfect method, Hydrol. Earth Syst. Sci., 24, 1171–1187, https://doi.org/10.5194/hess-24-1171-2020, 2020. a
Perrin, C., Michel, C., and Andréassian, V.: Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275–289, https://doi.org/10.1016/s0022-1694(03)00225-7, 2003. a, b, c
Pinault, J.-L., Amraoui, N., and Golaz, C.: Groundwater-induced flooding in
macropore-dominated hydrological system in the context of climate changes,
Water Resour. Res., 41, W05001, https://doi.org/10.1029/2004WR003169, 2005. a
Poncelet, C.: Du bassin au paramètre: jusqu'où peut-on régionaliser un modèle hydrologique conceptuel?, PhD thesis, Université Pierre et Marie Curie, Paris, http://www.theses.fr/2016PA066550 (last access: 17 May 2022), 2016. a
Price, K. V., Storn, R. M., and Lampinen, J. A.: Differential Evolution – A
Practical Approach to Global Optimization, Natural Computing, Springer-Verlag, ISBN 540209506, https://doi.org/10.1007/3-540-31306-0, 2006. a
Pushpalatha, R., Perrin, C., Le Moine, N., Mathevet, T., and Andrëassian, V.: A downward structural sensitivity analysis of hydrological models to improve low-flow simulation, J. Hydrol., 411, 66–76, https://doi.org/10.1016/j.jhydrol.2011.09.034, 2011. a, b, c
Pushpalatha, R., Perrin, C., Moine, N. L., and Andréassian, V.: A review
of efficiency criteria suitable for evaluating low-flow simulations, J. Hydrol., 420–421, 171–182, https://doi.org/10.1016/j.jhydrol.2011.11.055, 2012. a
Riboust, P., Thirel, G., Moine, N. L., and Ribstein, P.: Revisiting a Simple
Degree-Day Model for Integrating Satellite Data: Implementation of Swe-Sca
Hystereses, J. Hydrol. Hydromech., 67, 70–81, https://doi.org/10.2478/johh-2018-0004, 2018. a
Roche, P.-A., Miquel, J., and Gaume, E.: Hydrologie quantitative, Springer,
Paris, https://doi.org/10.1007/978-2-8178-0106-3, 2012. a, b, c, d
Slater, L. J., Thirel, G., Harrigan, S., Delaigue, O., Hurley, A., Khouakhi,
A., Prosdocimi, I., Vitolo, C., and Smith, K.: Using R in hydrology: a review
of recent developments and future directions, Hydrol. Earth Syst. Sci., 23, 2939–2963, https://doi.org/10.5194/hess-23-2939-2019, 2019. a, b
Soulsby, C., Tetzlaff, D., Rodgers, P., Dunn, S., and Waldron, S.: Runoff
processes, stream water residence times and controlling landscape
characteristics in a mesoscale catchment: An initial evaluation, J. Hydrol., 325, 197–221, https://doi.org/10.1016/j.jhydrol.2005.10.024, 2006. a
Spearman, C.: Demonstration of Formulae for True Measurement of Correlation,
Am. J. Psychol., 18, 161–169, https://doi.org/10.2307/1412408, 1907. a
Stadnyk, T. A. and Holmes, T. L.: On the value of isotope-enabled hydrological model calibration, Hydrolog. Sci. J., 65, 1525–1538,
https://doi.org/10.1080/02626667.2020.1751847, 2020. a
Stadnyk, T. A., Delavau, C., Kouwen, N., and Edwards, T. W. D.: Towards
hydrological model calibration and validation: simulation of stable water
isotopes using the isoWATFLOOD model, Hydrol. Process., 27, 3791–3810, https://doi.org/10.1002/hyp.9695, 2013. a
Swenson, S., Yeh, P. J.-F., Wahr, J., and Famiglietti, J.: A comparison of
terrestrial water storage variations from GRACE with in situ measurements
from Illinois, Geophys. Res. Lett., 33, L16401, https://doi.org/10.1029/2006GL026962, 2006. a
Syed, T. H., Famiglietti, J. S., Rodell, M., Chen, J., and Wilson, C. R.:
Analysis of terrestrial water storage changes from GRACE and GLDAS, Water
Resour. Res., 44, W02433, https://doi.org/10.1029/2006WR005779, 2008. a
Széles, B., Parajka, J., Hogan, P., Silasari, R., Pavlin, L., Strauss,
P., and Blöschl, G.: The Added Value of Different Data Types for
Calibrating and Testing a Hydrologic Model in a Small Catchment, Water
Resour. Res., 56, e2019WR026153, https://doi.org/10.1029/2019wr026153, 2020. a, b, c
Tague, C. and Grant, G. E.: Groundwater dynamics mediate low-flow response to
global warming in snow-dominated alpine regions, Water Resour. Res., 45, W07421, https://doi.org/10.1029/2008WR007179, 2009. a
Thiéry, D.: Forecast of changes in piezometric levels by a lumped hydrological model, J. Hydrol., 97, 129–148, https://doi.org/10.1016/0022-1694(88)90070-4, 1988. a, b, c
Thiéry, D.: Logiciel GARDÉNIA, version v8.2, Guide d'utilisation, bRGM report RP-62797-FR, BRGM, Orléans, France,
https://www.brgm.fr/sites/default/files/documents/2020-11/logiciel-gardenia-v8-2-rp-62797-fr-notice.pdf
(last access: 17 May 2022), 2014. a
Thirel, G., Salamon, P., Burek, P., and Kalas, M.: Assimilation of MODIS Snow
Cover Area Data in a Distributed Hydrological Model Using the Particle Filter, Remote Sens., 5, 5825–5850, https://doi.org/10.3390/rs5115825, 2013. a
Tiel, M., Stahl, K., Freudiger, D., and Seibert, J.: Glacio-hydrological model calibration and evaluation, WIREs Water, 7, W07421, https://doi.org/10.1002/wat2.1483, 2020. a
Tilmant, F., Nicolle, P., Bourgin, F., Besson, F., Delaigue, O., Etchevers, P., François, D., Lay, M. L., Perrin, C., Rousset, F., Thiéry, D.,
Magand, C., Leurent, T., and Jacob, É.: PREMHYCE: un outil opérationnel pour la prévision des étiages, La Houille Blanche, 106, 37–44, https://doi.org/10.1051/lhb/2020043, 2020.
a
Tobin, B. W. and Schwartz, B. F.: Quantifying the role of karstic groundwater
in a snowmelt-dominated hydrologic system, Hydrol. Process., 34, 3439–3447, https://doi.org/10.1002/hyp.13833, 2020. a, b
Tomasella, J., Hodnett, M. G., Cuartas, L. A., Nobre, A. D., Waterloo, M. J.,
and Oliveira, S. M.: The water balance of an Amazonian micro-catchment: the
effect of interannual variability of rainfall on hydrological behaviour,
Hydrol. Process., 22, 2133–2147, https://doi.org/10.1002/hyp.6813, 2008. a
Vidal, J.-P., Martin, E., Franchistéguy, L., Baillon, M., and Soubeyroux,
J.-M.: A 50-year high-resolution atmospheric reanalysis over France with the
Safran system, Int. J. Climatol., 30, 1627–1644, https://doi.org/10.1002/joc.2003, 2009. a
Wilcoxon, F.: Individual Comparisons by Ranking Methods, Biometr. Bull., 1, 80–83, https://doi.org/10.2307/3001968, 1945. a
Wirth, S. B., Carlier, C., Cochand, F., Hunkeler, D., and Brunner, P.:
Lithological and Tectonic Control on Groundwater Contribution to Stream
Discharge During Low-Flow Conditions, Water, 12, 821, https://doi.org/10.3390/w12030821, 2020. a
Short summary
A large part of the water cycle takes place underground. In many places, the soil stores water during the wet periods and can release it all year long, which is particularly visible when the river level is low. Modelling tools that are used to simulate and forecast the behaviour of the river struggle to represent this. We improved an existing model to take underground water into account using measurements of the soil water content. Results allow us make recommendations for model users.
A large part of the water cycle takes place underground. In many places, the soil stores water...
