Research article
24 May 2022
Research article
| 24 May 2022
Quantifying multi-year hydrological memory with Catchment Forgetting Curves
Alban de Lavenne et al.
Related authors
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.
Samuel Morin, Hugues François, Marion Réveillet, Eric Sauquet, Louise Crochemore, Flora Branger, Etiene Leblois, and Marie Dumont
EGUsphere, https://doi.org/10.5194/egusphere-2022-1186, https://doi.org/10.5194/egusphere-2022-1186, 2022
Short summary
Short summary
Ski resorts are a key socio-economic asset of several mountain areass. Grooming and snowmaking are routinely used to manage the snow cover on ski pistes, but despite vivid debate, little is known about their impact on water resources downstreams. This study quantifies, for the pilot ski resort La Plagne in the French Alps, the impact of grooming and snowmaking on downstream river flow. Hydrological impacts are mostly apparent at the seasonal scale but rather neutral on the annual scale.
Antoine Pelletier and Vazken Andréassian
Hydrol. Earth Syst. Sci., 26, 2733–2758, https://doi.org/10.5194/hess-26-2733-2022, https://doi.org/10.5194/hess-26-2733-2022, 2022
Short summary
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.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
Short summary
Short summary
Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Saúl Arciniega-Esparza, Christian Birkel, Andrés Chavarría-Palma, Berit Arheimer, and José Agustín Breña-Naranjo
Hydrol. Earth Syst. Sci., 26, 975–999, https://doi.org/10.5194/hess-26-975-2022, https://doi.org/10.5194/hess-26-975-2022, 2022
Short summary
Short summary
In the humid tropics, a notoriously data-scarce region, we need to find alternatives in order to reasonably apply hydrological models. Here, we tested remotely sensed rainfall data in order to drive a model for Costa Rica, and we evaluated the simulations against evapotranspiration satellite products. We found that our model was able to reasonably simulate the water balance and streamflow dynamics of over 600 catchments where the satellite data helped to reduce the model uncertainties.
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.
Marc Girons Lopez, Louise Crochemore, and Ilias G. Pechlivanidis
Hydrol. Earth Syst. Sci., 25, 1189–1209, https://doi.org/10.5194/hess-25-1189-2021, https://doi.org/10.5194/hess-25-1189-2021, 2021
Short summary
Short summary
The Swedish hydrological warning service is extending its use of seasonal forecasts, which requires an analysis of the available methods. We evaluate the simple ESP method and find out how and why forecasts vary in time and space. We find that forecasts are useful up to 3 months into the future, especially during winter and in northern Sweden. They tend to be good in slow-reacting catchments and bad in flashy and highly regulated ones. We finally link them with areas of similar behaviour.
Matteo Giuliani, Louise Crochemore, Ilias Pechlivanidis, and Andrea Castelletti
Hydrol. Earth Syst. Sci., 24, 5891–5902, https://doi.org/10.5194/hess-24-5891-2020, https://doi.org/10.5194/hess-24-5891-2020, 2020
Short summary
Short summary
This paper aims at quantifying the value of hydroclimatic forecasts in terms of potential economic benefit to end users in the Lake Como basin (Italy), which allows the inference of a relation between gains in forecast skill and gains in end user profit. We also explore the sensitivity of this benefit to both the forecast system setup and end user behavioral factors, showing that the estimated forecast value is potentially undermined by different levels of end user risk aversion.
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.
Berit Arheimer, Rafael Pimentel, Kristina Isberg, Louise Crochemore, Jafet C. M. Andersson, Abdulghani Hasan, and Luis Pineda
Hydrol. Earth Syst. Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, https://doi.org/10.5194/hess-24-535-2020, 2020
Short summary
Short summary
How far can we reach in predicting river flow globally, using integrated catchment modelling and open global data? For the first time, a catchment model was applied world-wide, covering the entire globe with a relatively high resolution. The results show that stepwise calibration provided better performance than traditional modelling of the globe. The study highlights that open data and models are crucial to advance hydrological sciences by sharing knowledge and enabling transparent evaluation.
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.
Theano Iliopoulou, Cristina Aguilar, Berit Arheimer, María Bermúdez, Nejc Bezak, Andrea Ficchì, Demetris Koutsoyiannis, Juraj Parajka, María José Polo, Guillaume Thirel, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 73–91, https://doi.org/10.5194/hess-23-73-2019, https://doi.org/10.5194/hess-23-73-2019, 2019
Short summary
Short summary
We investigate the seasonal memory properties of a large sample of European rivers in terms of high and low flows. We compute seasonal correlations between peak and low flows and average flows in the previous seasons and explore the links with various physiographic and hydro-climatic catchment descriptors. Our findings suggest that there is a traceable physical basis for river memory which in turn can be employed to reduce uncertainty and improve probabilistic predictions of floods and droughts.
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.
Alessio Pugliese, Simone Persiano, Stefano Bagli, Paolo Mazzoli, Juraj Parajka, Berit Arheimer, René Capell, Alberto Montanari, Günter Blöschl, and Attilio Castellarin
Hydrol. Earth Syst. Sci., 22, 4633–4648, https://doi.org/10.5194/hess-22-4633-2018, https://doi.org/10.5194/hess-22-4633-2018, 2018
Short summary
Short summary
This research work focuses on the development of an innovative method for enhancing the predictive capability of macro-scale rainfall–runoff models by means of a geostatistical apporach. In our method, one can get enhanced streamflow simulations without any further model calibration. Indeed, this method is neither computational nor data-intensive and is implemented only using observed streamflow data and a GIS vector layer with catchment boundaries. Assessments are performed in the Tyrol region.
Rafael Pimentel and Berit Arheimer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-387, https://doi.org/10.5194/hess-2018-387, 2018
Revised manuscript not accepted
Short summary
Short summary
The Västmanland wildfire, Sweden, burned 14 000 hectares and removed the Boreal forest in this area during the summer 2014. This empirical study evaluates the hydrological effects of this wildfire. A paired catchment methodology is used to evaluate 23 catchment characteristics of flow and physiography defined using in situ and remote sensing data. The results show a change in the snow dynamics over the burnt areas with shorter duration of the snow season and a higher stream flow during autumn.
Fernando Jaramillo, Neil Cory, Berit Arheimer, Hjalmar Laudon, Ype van der Velde, Thomas B. Hasper, Claudia Teutschbein, and Johan Uddling
Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, https://doi.org/10.5194/hess-22-567-2018, 2018
Short summary
Short summary
Which is the dominant effect on evapotranspiration in northern forests, an increase by recent forests expansion or a decrease by the water use response due to increasing CO2 concentrations? We determined the dominant effect during the period 1961–2012 in 65 Swedish basins. We used the Budyko framework to study the hydroclimatic movements in Budyko space. Our findings suggest that forest expansion is the dominant driver of long-term and large-scale evapotranspiration changes.
Anna Kuentz, Berit Arheimer, Yeshewatesfa Hundecha, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 21, 2863–2879, https://doi.org/10.5194/hess-21-2863-2017, https://doi.org/10.5194/hess-21-2863-2017, 2017
Short summary
Short summary
Our study aims to explore and understand the physical controls on spatial patterns of pan-European flow signatures by taking advantage of large open datasets. Using tools like correlation analysis, stepwise regressions and different types of catchment classifications, we explore the relationships between catchment descriptors and flow signatures across 35 215 catchments which cover a wide range of pan-European physiographic and anthropogenic characteristics.
Louise Crochemore, Maria-Helena Ramos, Florian Pappenberger, and Charles Perrin
Hydrol. Earth Syst. Sci., 21, 1573–1591, https://doi.org/10.5194/hess-21-1573-2017, https://doi.org/10.5194/hess-21-1573-2017, 2017
Short summary
Short summary
The use of general circulation model outputs for streamflow forecasting has developed in the last decade. In parallel, traditional streamflow forecasting is commonly based on historical data. This study investigates the impact of conditioning historical data based on circulation model precipitation forecasts on seasonal streamflow forecast quality. Results highlighted a trade-off between the sharpness and reliability of forecasts.
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
Short summary
Short summary
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).
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.
Louise Crochemore, Maria-Helena Ramos, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3601–3618, https://doi.org/10.5194/hess-20-3601-2016, https://doi.org/10.5194/hess-20-3601-2016, 2016
Short summary
Short summary
This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.
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.
I. G. Pechlivanidis and B. Arheimer
Hydrol. Earth Syst. Sci., 19, 4559–4579, https://doi.org/10.5194/hess-19-4559-2015, https://doi.org/10.5194/hess-19-4559-2015, 2015
Short summary
Short summary
We modify the recommendations for flow predictions in ungauged catchments to address the challenges at the large scale. We use examples from the HYPE hydrological model set-up across 6000 subbasins for the Indian subcontinent. Multi-basin modelling reveals the spatial patterns of catchment functioning and dominant flow processes across the hydroclimatic gradient. The model set-up procedure according to the PUB recommendations brought insights into where the single model structure is inadequate.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 2015
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
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
Short summary
Short summary
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.
B. Arheimer and G. Lindström
Hydrol. Earth Syst. Sci., 19, 771–784, https://doi.org/10.5194/hess-19-771-2015, https://doi.org/10.5194/hess-19-771-2015, 2015
Short summary
Short summary
Is the occurrence of floods changing in frequency or magnitude? We have analyzed 100 years of observed time series from 69 gauging sites and high-resolution modeling of climate change impact across Sweden for 140 years. The results indicate no significant trend in high flows in the past but some shifts in flood-generating processes at present and in the future. Rain-generated floods may have a more marked effect, and some specific rivers may be more affected by climate change than others.
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
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
Simulating the hydrological impacts of land use conversion from annual crop to perennial forage in the Canadian Prairies using the Cold Regions Hydrological Modelling platform
How can we benefit from regime information to make more effective use of long short-term memory (LSTM) runoff models?
On the value of satellite remote sensing to reduce uncertainties of regional simulations of the Colorado River
Assessing runoff sensitivity of North American Prairie Pothole Region basins to wetland drainage using a basin classification-based virtual modelling approach
A large-sample investigation into uncertain climate change impacts on high flows across Great Britain
Effects of passive-storage conceptualization on modeling hydrological function and isotope dynamics in the flow system of a cockpit karst landscape
Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks
Attribution of climate change and human activities to streamflow variations with a posterior distribution of hydrological simulations
A time-varying distributed unit hydrograph method considering soil moisture
Flood patterns in a catchment with mixed bedrock geology and a hilly landscape: identification of flashy runoff contributions during storm events
A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion
Improving hydrologic models for predictions and process understanding using neural ODEs
Response of active catchment water storage capacity to a prolonged meteorological drought and asymptotic climate variation
HESS Opinions: Participatory Digital eARth Twin Hydrology systems (DARTHs) for everyone – a blueprint for hydrologists
Development of a national 7-day ensemble streamflow forecasting service for Australia
Future snow changes and their impact on the upstream runoff in Salween
Technical note: Do different projections matter for the Budyko framework?
Representation of seasonal land use dynamics in SWAT+ for improved assessment of blue and green water consumption
Large-sample assessment of varying spatial resolution on the streamflow estimates of the wflow_sbm hydrological model
An algorithm for deriving the topology of belowground urban stormwater networks
Assessing the influence of water sampling strategy on the performance of tracer-aided hydrological modeling in a mountainous basin on the Tibetan Plateau
Flood forecasting with machine learning models in an operational framework
Precipitation fate and transport in a Mediterranean catchment through models calibrated on plant and stream water isotope data
High-resolution satellite products improve hydrological modeling in northern Italy
Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?
A conceptual-model-based sediment connectivity assessment for patchy agricultural catchments
The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL)
Spatial extrapolation of stream thermal peaks using heterogeneous time series at a national scale
Revisiting parameter sensitivities in the variable infiltration capacity model across a hydroclimatic gradient
Deep learning rainfall–runoff predictions of extreme events
Diel streamflow cycles suggest more sensitive snowmelt-driven streamflow to climate change than land surface modeling does
Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise
Technical note: Hydrograph separation: How physically based is recursive digital filtering?
Effects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zone
On constraining a lumped hydrological model with both piezometry and streamflow: results of a large sample evaluation
Influences of land use changes on the dynamics of water quantity and quality in the German lowland catchment of the Stör
Impact of spatial distribution information of rainfall in runoff simulation using deep learning method
Towards effective drought monitoring in the Middle East and North Africa (MENA) region: implications from assimilating leaf area index and soil moisture into the Noah-MP land surface model for Morocco
The effects of spatial and temporal resolution of gridded meteorological forcing on watershed hydrological responses
Hydrological response of a peri-urban catchment exploiting conventional and unconventional rainfall observations: the case study of Lambro Catchment
Disentangling Scatter in Long-Term Concentration-Discharge Relationships: the Role of Event Types
Long-term reconstruction of satellite-based precipitation, soil moisture, and snow water equivalent in China
Assessing hydrological sensitivity of grassland basins in the Canadian Prairies to climate using a basin classification-based virtual modelling approach
The value of satellite soil moisture and snow cover data for the transfer of hydrological model parameters to ungauged sites
Storylines of UK drought based on the 2010–2012 event
Uncertainty estimation with deep learning for rainfall–runoff modeling
Applying non-parametric Bayesian networks to estimate maximum daily river discharge: potential and challenges
Contrasting changes in hydrological processes of the Volta River basin under global warming
A retrospective on hydrological catchment modelling based on half a century with the HBV model
Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters
Marcos R. C. Cordeiro, Kang Liang, Henry F. Wilson, Jason Vanrobaeys, David A. Lobb, Xing Fang, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 26, 5917–5931, https://doi.org/10.5194/hess-26-5917-2022, https://doi.org/10.5194/hess-26-5917-2022, 2022
Short summary
Short summary
This study addresses the issue of increasing interest in the hydrological impacts of converting cropland to perennial forage cover in the Canadian Prairies. By developing customized models using the Cold Regions Hydrological Modelling (CRHM) platform, this long-term (1992–2013) modelling study is expected to provide stakeholders with science-based information regarding the hydrological impacts of land use conversion from annual crop to perennial forage cover in the Canadian Prairies.
Reyhaneh Hashemi, Pierre Brigode, Pierre-André Garambois, and Pierre Javelle
Hydrol. Earth Syst. Sci., 26, 5793–5816, https://doi.org/10.5194/hess-26-5793-2022, https://doi.org/10.5194/hess-26-5793-2022, 2022
Short summary
Short summary
Hydrologists have long dreamed of a tool that could adequately predict runoff in catchments. Data-driven long short-term memory (LSTM) models appear very promising to the hydrology community in this respect. Here, we have sought to benefit from traditional practices in hydrology to improve the effectiveness of LSTM models. We discovered that one LSTM parameter has a hydrologic interpretation and that there is a need to increase the data and to tune two parameters, thereby improving predictions.
Mu Xiao, Giuseppe Mascaro, Zhaocheng Wang, Kristen M. Whitney, and Enrique R. Vivoni
Hydrol. Earth Syst. Sci., 26, 5627–5646, https://doi.org/10.5194/hess-26-5627-2022, https://doi.org/10.5194/hess-26-5627-2022, 2022
Short summary
Short summary
As the major water resource in the southwestern United States, the Colorado River is experiencing decreases in naturalized streamflow and is predicted to face severe challenges under future climate scenarios. Here, we demonstrate the value of Earth observing satellites to improve and build confidence in the spatiotemporal simulations from regional hydrologic models for assessing the sensitivity of the Colorado River to climate change and supporting regional water managers.
Christopher Spence, Zhihua He, Kevin R. Shook, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 5555–5575, https://doi.org/10.5194/hess-26-5555-2022, https://doi.org/10.5194/hess-26-5555-2022, 2022
Short summary
Short summary
We learnt how streamflow from small creeks could be altered by wetland removal in the Canadian Prairies, where this practice is pervasive. Every creek basin in the region was placed into one of seven groups. We selected one of these groups and used its traits to simulate streamflow. The model worked well enough so that we could trust the results even if we removed the wetlands. Wetland removal did not change low flow amounts very much, but it doubled high flow and tripled average flow.
Rosanna A. Lane, Gemma Coxon, Jim Freer, Jan Seibert, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 26, 5535–5554, https://doi.org/10.5194/hess-26-5535-2022, https://doi.org/10.5194/hess-26-5535-2022, 2022
Short summary
Short summary
This study modelled the impact of climate change on river high flows across Great Britain (GB). Generally, results indicated an increase in the magnitude and frequency of high flows along the west coast of GB by 2050–2075. In contrast, average flows decreased across GB. All flow projections contained large uncertainties; the climate projections were the largest source of uncertainty overall but hydrological modelling uncertainties were considerable in some regions.
Guangxuan Li, Xi Chen, Zhicai Zhang, Lichun Wang, and Chris Soulsby
Hydrol. Earth Syst. Sci., 26, 5515–5534, https://doi.org/10.5194/hess-26-5515-2022, https://doi.org/10.5194/hess-26-5515-2022, 2022
Short summary
Short summary
We developed a coupled flow–tracer model to understand the effects of passive storage on modeling hydrological function and isotope dynamics in a karst flow system. Models with passive storages show improvement in matching isotope dynamics performance, and the improved performance also strongly depends on the number and location of passive storages. Our results also suggested that the solute transport is primarily controlled by advection and hydrodynamic dispersion in the steep hillslope unit.
Grey S. Nearing, Daniel Klotz, Jonathan M. Frame, Martin Gauch, Oren Gilon, Frederik Kratzert, Alden Keefe Sampson, Guy Shalev, and Sella Nevo
Hydrol. Earth Syst. Sci., 26, 5493–5513, https://doi.org/10.5194/hess-26-5493-2022, https://doi.org/10.5194/hess-26-5493-2022, 2022
Short summary
Short summary
When designing flood forecasting models, it is necessary to use all available data to achieve the most accurate predictions possible. This manuscript explores two basic ways of ingesting near-real-time streamflow data into machine learning streamflow models. The point we want to make is that when working in the context of machine learning (instead of traditional hydrology models that are based on
bio-geophysics), it is not necessary to use complex statistical methods for injecting sparse data.
Xiongpeng Tang, Guobin Fu, Silong Zhang, Chao Gao, Guoqing Wang, Zhenxin Bao, Yanli Liu, Cuishan Liu, and Junliang Jin
Hydrol. Earth Syst. Sci., 26, 5315–5339, https://doi.org/10.5194/hess-26-5315-2022, https://doi.org/10.5194/hess-26-5315-2022, 2022
Short summary
Short summary
In this study, we proposed a new framework that considered the uncertainties of model simulations in quantifying the contribution rate of climate change and human activities to streamflow changes. Then, the Lancang River basin was selected for the case study. The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was mainly human activities.
Bin Yi, Lu Chen, Hansong Zhang, Vijay P. Singh, Ping Jiang, Yizhuo Liu, Hexiang Guo, and Hongya Qiu
Hydrol. Earth Syst. Sci., 26, 5269–5289, https://doi.org/10.5194/hess-26-5269-2022, https://doi.org/10.5194/hess-26-5269-2022, 2022
Short summary
Short summary
An improved GIS-derived distributed unit hydrograph routing method considering time-varying soil moisture was proposed for flow routing. The method considered the changes of time-varying soil moisture and rainfall intensity. The response of underlying surface to the soil moisture content was considered an important factor in this study. The SUH, DUH, TDUH and proposed routing methods (TDUH-MC) were used for flood forecasts, and the simulated results were compared and discussed.
Audrey Douinot, Jean François Iffly, Cyrille Tailliez, Claude Meisch, and Laurent Pfister
Hydrol. Earth Syst. Sci., 26, 5185–5206, https://doi.org/10.5194/hess-26-5185-2022, https://doi.org/10.5194/hess-26-5185-2022, 2022
Short summary
Short summary
The objective of the paper is to highlight the seasonal and singular shift of the transfer time distributions of two catchments (≅10 km2).
Based on 2 years of rainfall and discharge observations, we compare variations in the properties of TTDs with the physiographic characteristics of catchment areas and the eco-hydrological cycle. The paper eventually aims to deduce several factors conducive to particularly rapid and concentrated water transfers, which leads to flash floods.
Alexander Y. Sun, Peishi Jiang, Zong-Liang Yang, Yangxinyu Xie, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 26, 5163–5184, https://doi.org/10.5194/hess-26-5163-2022, https://doi.org/10.5194/hess-26-5163-2022, 2022
Short summary
Short summary
High-resolution river modeling is of great interest to local governments and stakeholders for flood-hazard mitigation. This work presents a physics-guided, machine learning (ML) framework for combining the strengths of high-resolution process-based river network models with a graph-based ML model capable of modeling spatiotemporal processes. Results show that the ML model can approximate the dynamics of the process model with high fidelity, and data fusion further improves the forecasting skill.
Marvin Höge, Andreas Scheidegger, Marco Baity-Jesi, Carlo Albert, and Fabrizio Fenicia
Hydrol. Earth Syst. Sci., 26, 5085–5102, https://doi.org/10.5194/hess-26-5085-2022, https://doi.org/10.5194/hess-26-5085-2022, 2022
Short summary
Short summary
Neural ODEs fuse physics-based models with deep learning: neural networks substitute terms in differential equations that represent the mechanistic structure of the system. The approach combines the flexibility of machine learning with physical constraints for inter- and extrapolation. We demonstrate that neural ODE models achieve state-of-the-art predictive performance while keeping full interpretability of model states and processes in hydrologic modelling over multiple catchments.
Jing Tian, Zhengke Pan, Shenglian Guo, Jiabo Yin, Yanlai Zhou, and Jun Wang
Hydrol. Earth Syst. Sci., 26, 4853–4874, https://doi.org/10.5194/hess-26-4853-2022, https://doi.org/10.5194/hess-26-4853-2022, 2022
Short summary
Short summary
Most of the literature has focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change.
Riccardo Rigon, Giuseppe Formetta, Marialaura Bancheri, Niccolò Tubini, Concetta D'Amato, Olaf David, and Christian Massari
Hydrol. Earth Syst. Sci., 26, 4773–4800, https://doi.org/10.5194/hess-26-4773-2022, https://doi.org/10.5194/hess-26-4773-2022, 2022
Short summary
Short summary
The
Digital Earth(DE) metaphor is very useful for both end users and hydrological modelers. We analyse different categories of models, with the view of making them part of a Digital eARth Twin Hydrology system (called DARTH). We also stress the idea that DARTHs are not models in and of themselves, rather they need to be built on an appropriate information technology infrastructure. It is remarked that DARTHs have to, by construction, support the open-science movement and its ideas.
Hapu Arachchige Prasantha Hapuarachchi, Mohammed Abdul Bari, Aynul Kabir, Mohammad Mahadi Hasan, Fitsum Markos Woldemeskel, Nilantha Gamage, Patrick Daniel Sunter, Xiaoyong Sophie Zhang, David Ewen Robertson, James Clement Bennett, and Paul Martinus Feikema
Hydrol. Earth Syst. Sci., 26, 4801–4821, https://doi.org/10.5194/hess-26-4801-2022, https://doi.org/10.5194/hess-26-4801-2022, 2022
Short summary
Short summary
Methodology for developing an operational 7-day ensemble streamflow forecasting service for Australia is presented. The methodology is tested for 100 catchments to learn the characteristics of different NWP rainfall forecasts, the effect of post-processing, and the optimal ensemble size and bootstrapping parameters. Forecasts are generated using NWP rainfall products post-processed by the CHyPP model, the GR4H hydrologic model, and the ERRIS streamflow post-processor inbuilt in the SWIFT package
Chenhao Chai, Lei Wang, Deliang Chen, Jing Zhou, Hu Liu, Jingtian Zhang, Yuanwei Wang, Tao Chen, and Ruishun Liu
Hydrol. Earth Syst. Sci., 26, 4657–4683, https://doi.org/10.5194/hess-26-4657-2022, https://doi.org/10.5194/hess-26-4657-2022, 2022
Short summary
Short summary
This work quantifies future snow changes and their impacts on hydrology in the upper Salween River (USR) under SSP126 and SSP585 using a cryosphere–hydrology model. Future warm–wet climate is not conducive to the development of snow. The rain–snow-dominated pattern of runoff will shift to a rain-dominated pattern after the 2040s under SSP585 but is unchanged under SSP126. The findings improve our understanding of cryosphere–hydrology processes and can assist water resource management in the USR.
Remko C. Nijzink and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 4575–4585, https://doi.org/10.5194/hess-26-4575-2022, https://doi.org/10.5194/hess-26-4575-2022, 2022
Short summary
Short summary
Most catchments plot close to the empirical Budyko curve, which allows for the estimation of the long-term mean annual evaporation and runoff. The Budyko curve can be defined as a function of a wetness index or a dryness index. We found that differences can occur and that there is an uncertainty due to the different formulations.
Anna Msigwa, Celray James Chawanda, Hans C. Komakech, Albert Nkwasa, and Ann van Griensven
Hydrol. Earth Syst. Sci., 26, 4447–4468, https://doi.org/10.5194/hess-26-4447-2022, https://doi.org/10.5194/hess-26-4447-2022, 2022
Short summary
Short summary
Studies using agro-hydrological models, like the Soil and Water Assessment Tool (SWAT), to map evapotranspiration (ET) do not account for cropping seasons. A comparison between the default SWAT+ set-up (with static land use representation) and a dynamic SWAT+ model set-up (with seasonal land use representation) is made by spatial mapping of the ET. The results show that ET with seasonal representation is closer to remote sensing estimates, giving better performance than ET with static land use.
Jerom P. M. Aerts, Rolf W. Hut, Nick C. van de Giesen, Niels Drost, Willem J. van Verseveld, Albrecht H. Weerts, and Pieter Hazenberg
Hydrol. Earth Syst. Sci., 26, 4407–4430, https://doi.org/10.5194/hess-26-4407-2022, https://doi.org/10.5194/hess-26-4407-2022, 2022
Short summary
Short summary
In recent years gridded hydrological modelling moved into the realm of hyper-resolution modelling (<10 km). In this study, we investigate the effect of varying grid-cell sizes for the wflow_sbm hydrological model. We used a large sample of basins from the CAMELS data set to test the effect that varying grid-cell sizes has on the simulation of streamflow at the basin outlet. Results show that there is no single best grid-cell size for modelling streamflow throughout the domain.
Taher Chegini and Hong-Yi Li
Hydrol. Earth Syst. Sci., 26, 4279–4300, https://doi.org/10.5194/hess-26-4279-2022, https://doi.org/10.5194/hess-26-4279-2022, 2022
Short summary
Short summary
Belowground urban stormwater networks (BUSNs) play a critical and irreplaceable role in preventing or mitigating urban floods. However, they are often not available for urban flood modeling at regional or larger scales. We develop a novel algorithm to estimate existing BUSNs using ubiquitously available aboveground data at large scales based on graph theory. The algorithm has been validated in different urban areas; thus, it is well transferable.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 26, 4147–4167, https://doi.org/10.5194/hess-26-4147-2022, https://doi.org/10.5194/hess-26-4147-2022, 2022
Short summary
Short summary
Tracer-aided hydrological models are useful tool to reduce uncertainty of hydrological modeling in cold basins, but there is little guidance on the sampling strategy for isotope analysis, which is important for large mountainous basins. This study evaluated the reliance of the tracer-aided modeling performance on the availability of isotope data in the Yarlung Tsangpo river basin, and provides implications for collecting water isotope data for running tracer-aided hydrological models.
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, and Yossi Matias
Hydrol. Earth Syst. Sci., 26, 4013–4032, https://doi.org/10.5194/hess-26-4013-2022, https://doi.org/10.5194/hess-26-4013-2022, 2022
Short summary
Short summary
Early flood warnings are one of the most effective tools to save lives and goods. Machine learning (ML) models can improve flood prediction accuracy but their use in operational frameworks is limited. The paper presents a flood warning system, operational in India and Bangladesh, that uses ML models for forecasting river stage and flood inundation maps and discusses the models' performances. In 2021, more than 100 million flood alerts were sent to people near rivers over an area of 470 000 km2.
Matthias Sprenger, Pilar Llorens, Francesc Gallart, Paolo Benettin, Scott T. Allen, and Jérôme Latron
Hydrol. Earth Syst. Sci., 26, 4093–4107, https://doi.org/10.5194/hess-26-4093-2022, https://doi.org/10.5194/hess-26-4093-2022, 2022
Short summary
Short summary
Our catchment-scale transit time modeling study shows that including stable isotope data on evapotranspiration in addition to the commonly used stream water isotopes helps constrain the model parametrization and reveals that the water taken up by plants has resided longer in the catchment storage than the water leaving the catchment as stream discharge. This finding is important for our understanding of how water is stored and released, which impacts the water availability for plants and humans.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
Short summary
Short summary
This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Bruno Majone, Diego Avesani, Patrick Zulian, Aldo Fiori, and Alberto Bellin
Hydrol. Earth Syst. Sci., 26, 3863–3883, https://doi.org/10.5194/hess-26-3863-2022, https://doi.org/10.5194/hess-26-3863-2022, 2022
Short summary
Short summary
In this work, we introduce a methodology for devising reliable future high streamflow scenarios from climate change simulations. The calibration of a hydrological model is carried out to maximize the probability that the modeled and observed high flow extremes belong to the same statistical population. Application to the Adige River catchment (southeastern Alps, Italy) showed that this procedure produces reliable quantiles of the annual maximum streamflow for use in assessment studies.
Pedro V. G. Batista, Peter Fiener, Simon Scheper, and Christine Alewell
Hydrol. Earth Syst. Sci., 26, 3753–3770, https://doi.org/10.5194/hess-26-3753-2022, https://doi.org/10.5194/hess-26-3753-2022, 2022
Short summary
Short summary
Patchy agricultural landscapes have a large number of small fields, which are separated by linear features such as roads and field borders. When eroded sediments are transported out of the agricultural fields by surface runoff, these features can influence sediment connectivity. By use of measured data and a simulation model, we demonstrate how a dense road network (and its drainage system) facilitates sediment transport from fields to water courses in a patchy Swiss agricultural catchment.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
Short summary
Short summary
Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Aurélien Beaufort, Jacob S. Diamond, Eric Sauquet, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 3477–3495, https://doi.org/10.5194/hess-26-3477-2022, https://doi.org/10.5194/hess-26-3477-2022, 2022
Short summary
Short summary
We developed one of the largest stream temperature databases to calculate a simple, ecologically relevant metric – the thermal peak – that captures the magnitude of summer thermal extremes. Using statistical models, we extrapolated the thermal peak to nearly every stream in France, finding the hottest thermal peaks along large rivers without forested riparian zones and groundwater inputs. Air temperature was a poor proxy for the thermal peak, highlighting the need to grow monitoring networks.
Ulises M. Sepúlveda, Pablo A. Mendoza, Naoki Mizukami, and Andrew J. Newman
Hydrol. Earth Syst. Sci., 26, 3419–3445, https://doi.org/10.5194/hess-26-3419-2022, https://doi.org/10.5194/hess-26-3419-2022, 2022
Short summary
Short summary
This paper characterizes parameter sensitivities across more than 5500 grid cells for a commonly used macroscale hydrological model, including a suite of eight performance metrics and 43 soil, vegetation and snow parameters. The results show that the model is highly overparameterized and, more importantly, help to provide guidance on the most relevant parameters for specific target processes across diverse climatic types.
Jonathan M. Frame, Frederik Kratzert, Daniel Klotz, Martin Gauch, Guy Shalev, Oren Gilon, Logan M. Qualls, Hoshin V. Gupta, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 26, 3377–3392, https://doi.org/10.5194/hess-26-3377-2022, https://doi.org/10.5194/hess-26-3377-2022, 2022
Short summary
Short summary
The most accurate rainfall–runoff predictions are currently based on deep learning. There is a concern among hydrologists that deep learning models may not be reliable in extrapolation or for predicting extreme events. This study tests that hypothesis. The deep learning models remained relatively accurate in predicting extreme events compared with traditional models, even when extreme events were not included in the training set.
Sebastian A. Krogh, Lucia Scaff, James W. Kirchner, Beatrice Gordon, Gary Sterle, and Adrian Harpold
Hydrol. Earth Syst. Sci., 26, 3393–3417, https://doi.org/10.5194/hess-26-3393-2022, https://doi.org/10.5194/hess-26-3393-2022, 2022
Short summary
Short summary
We present a new way to detect snowmelt using daily cycles in streamflow driven by solar radiation. Results show that warmer sites have earlier and more intermittent snowmelt than colder sites, and the timing of early snowmelt events is strongly correlated with the timing of streamflow volume. A space-for-time substitution shows greater sensitivity of streamflow timing to climate change in colder rather than in warmer places, which is then contrasted with land surface simulations.
Wouter J. M. Knoben and Diana Spieler
Hydrol. Earth Syst. Sci., 26, 3299–3314, https://doi.org/10.5194/hess-26-3299-2022, https://doi.org/10.5194/hess-26-3299-2022, 2022
Short summary
Short summary
This paper introduces educational materials that can be used to teach students about model structure uncertainty in hydrological modelling. There are many different hydrological models and differences between these models impact their usefulness in different places. Such models are often used to support decision making about water resources and to perform hydrological science, and it is thus important for students to understand that model choice matters.
Klaus Eckhardt
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-186, https://doi.org/10.5194/hess-2022-186, 2022
Revised manuscript accepted for HESS
Short summary
Short summary
An important hydrological question is what proportion of the runoff in a surface water body comes from groundwater. This proportion is also called baseflow. Among the multitude of methods that have been developed to identify baseflow, a specific, frequently used one is singled out here. It is shown to be derived from plausible physical principles. This increases confidence in its results.
Leonie Kiewiet, Ernesto Trujillo, Andrew Hedrick, Scott Havens, Katherine Hale, Mark Seyfried, Stephanie Kampf, and Sarah E. Godsey
Hydrol. Earth Syst. Sci., 26, 2779–2796, https://doi.org/10.5194/hess-26-2779-2022, https://doi.org/10.5194/hess-26-2779-2022, 2022
Short summary
Short summary
Climate change affects precipitation phase, which can propagate into changes in streamflow timing and magnitude. This study examines how variations in rainfall and snowmelt affect discharge. We found that annual discharge and stream cessation depended on the magnitude and timing of rainfall and snowmelt and on the snowpack melt-out date. This highlights the importance of precipitation timing and emphasizes the need for spatiotemporally distributed simulations of snowpack and rainfall dynamics.
Antoine Pelletier and Vazken Andréassian
Hydrol. Earth Syst. Sci., 26, 2733–2758, https://doi.org/10.5194/hess-26-2733-2022, https://doi.org/10.5194/hess-26-2733-2022, 2022
Short summary
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.
Chaogui Lei, Paul D. Wagner, and Nicola Fohrer
Hydrol. Earth Syst. Sci., 26, 2561–2582, https://doi.org/10.5194/hess-26-2561-2022, https://doi.org/10.5194/hess-26-2561-2022, 2022
Short summary
Short summary
We presented an integrated approach to hydrologic modeling and partial least squares regression quantifying land use change impacts on water and nutrient balance over 3 decades. Results highlight that most variations (70 %–80 %) in water quantity and quality variables are explained by changes in land use class-specific areas and landscape metrics. Arable land influences water quantity and quality the most. The study provides insights on water resources management in rural lowland catchments.
Yang Wang and Hassan A. Karimi
Hydrol. Earth Syst. Sci., 26, 2387–2403, https://doi.org/10.5194/hess-26-2387-2022, https://doi.org/10.5194/hess-26-2387-2022, 2022
Short summary
Short summary
We found that rainfall data with spatial information can improve the model's performance, especially when simulating the future multi-day discharges. We did not observe that regional LSTM as a regional model achieved better results than LSTM as individual model. This conclusion applies to both one-day and multi-day simulations. However, we found that using spatially distributed rainfall data can reduce the difference between individual LSTM and regional LSTM.
Wanshu Nie, Sujay V. Kumar, Kristi R. Arsenault, Christa D. Peters-Lidard, Iliana E. Mladenova, Karim Bergaoui, Abheera Hazra, Benjamin F. Zaitchik, Sarith P. Mahanama, Rachael McDonnell, David M. Mocko, and Mahdi Navari
Hydrol. Earth Syst. Sci., 26, 2365–2386, https://doi.org/10.5194/hess-26-2365-2022, https://doi.org/10.5194/hess-26-2365-2022, 2022
Short summary
Short summary
The MENA (Middle East and North Africa) region faces significant food and water insecurity and hydrological hazards. Here we investigate the value of assimilating remote sensing data sets into an Earth system model to help build an effective drought monitoring system and support risk mitigation and management by countries in the region. We highlight incorporating satellite-informed vegetation conditions into the model as being one of the key processes for a successful application for the region.
Pin Shuai, Xingyuan Chen, Utkarsh Mital, Ethan T. Coon, and Dipankar Dwivedi
Hydrol. Earth Syst. Sci., 26, 2245–2276, https://doi.org/10.5194/hess-26-2245-2022, https://doi.org/10.5194/hess-26-2245-2022, 2022
Short summary
Short summary
Using an integrated watershed model, we compared simulated watershed hydrologic variables driven by three publicly available gridded meteorological forcings (GMFs) at various spatial and temporal resolutions. Our results demonstrated that spatially distributed variables are sensitive to the spatial resolution of the GMF. The temporal resolution of the GMF impacts the dynamics of watershed responses. The choice of GMF depends on the quantity of interest and its spatial and temporal scales.
Greta Cazzaniga, Carlo De Michele, Michele D'Amico, Cristina Deidda, Antonio Ghezzi, and Roberto Nebuloni
Hydrol. Earth Syst. Sci., 26, 2093–2111, https://doi.org/10.5194/hess-26-2093-2022, https://doi.org/10.5194/hess-26-2093-2022, 2022
Short summary
Short summary
Rainfall estimates are usually obtained from rain gauges, weather radars, or satellites. An alternative is the measurement of the signal loss induced by rainfall on commercial microwave links (CMLs). In this work, we assess the hydrologic response of Lambro Basin when CML-retrieved rainfall is used as model input. CML estimates agree with rain gauge data. CML-driven discharge simulations show performance comparable to that from rain gauges if a CML-based calibration of the model is undertaken.
Felipe Saavedra, Andreas Musolff, Jana von Freyberg, Ralf Merz, Stefano Basso, and Larisa Tarasova
EGUsphere, https://doi.org/10.5194/egusphere-2022-205, https://doi.org/10.5194/egusphere-2022-205, 2022
Short summary
Short summary
Nitrate contamination of rivers from agricultural sources is a challenging problem for water quality management. During runoff events of different generation processes, different transport paths within the catchment might be activated, generating a variety of responses in nitrate concentration in stream water. Using data for 184 German catchments we demonstrate that wetness conditions during runoff events at the time of sampling are a key control of nitrate transport from catchments to streams.
Wencong Yang, Hanbo Yang, Changming Li, Taihua Wang, Ziwei Liu, Qingfang Hu, and Dawen Yang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-135, https://doi.org/10.5194/hess-2022-135, 2022
Revised manuscript accepted for HESS
Short summary
Short summary
We produced a daily 0.1° dataset of precipitation, soil moisture, and snow water equivalent in 1981–2017 across China via reconstructions. The dataset used global background data and local onsite data as forcing input and satellite-based data as reconstruction benchmarks. This long-term high-resolution national hydrological dataset is valuable for national investigations of hydrological processes.
Christopher Spence, Zhihua He, Kevin R. Shook, Balew A. Mekonnen, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 1801–1819, https://doi.org/10.5194/hess-26-1801-2022, https://doi.org/10.5194/hess-26-1801-2022, 2022
Short summary
Short summary
We determined how snow and flow in small creeks change with temperature and precipitation in the Canadian Prairie, a region where water resources are often under stress. We tried something new. Every watershed in the region was placed in one of seven groups based on their landscape traits. We selected one of these groups and used its traits to build a model of snow and streamflow. It worked well, and by the 2040s there may be 20 %–40 % less snow and 30 % less streamflow than the 1980s.
Rui Tong, Juraj Parajka, Borbála Széles, Isabella Greimeister-Pfeil, Mariette Vreugdenhil, Jürgen Komma, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 1779–1799, https://doi.org/10.5194/hess-26-1779-2022, https://doi.org/10.5194/hess-26-1779-2022, 2022
Short summary
Short summary
The role and impact of using additional data (other than runoff) for the prediction of daily hydrographs in ungauged basins are not well understood. In this study, we assessed the model performance in terms of runoff, soil moisture, and snow cover predictions with the existing regionalization approaches. Results show that the best transfer methods are the similarity and the kriging approaches. The performance of the transfer methods differs between lowland and alpine catchments.
Wilson C. H. Chan, Theodore G. Shepherd, Katie Facer-Childs, Geoff Darch, and Nigel W. Arnell
Hydrol. Earth Syst. Sci., 26, 1755–1777, https://doi.org/10.5194/hess-26-1755-2022, https://doi.org/10.5194/hess-26-1755-2022, 2022
Short summary
Short summary
We select the 2010–2012 UK drought and investigate an alternative unfolding of the drought from changes to its attributes. We created storylines of drier preconditions, alternative seasonal contributions, a third dry winter, and climate change. Storylines of the 2010–2012 drought show alternative situations that could have resulted in worse conditions than observed. Event-based storylines exploring plausible situations are used that may lead to high impacts and help stress test existing systems.
Daniel Klotz, Frederik Kratzert, Martin Gauch, Alden Keefe Sampson, Johannes Brandstetter, Günter Klambauer, Sepp Hochreiter, and Grey Nearing
Hydrol. Earth Syst. Sci., 26, 1673–1693, https://doi.org/10.5194/hess-26-1673-2022, https://doi.org/10.5194/hess-26-1673-2022, 2022
Short summary
Short summary
This contribution evaluates distributional runoff predictions from deep-learning-based approaches. We propose a benchmarking setup and establish four strong baselines. The results show that accurate, precise, and reliable uncertainty estimation can be achieved with deep learning.
Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711, https://doi.org/10.5194/hess-26-1695-2022, https://doi.org/10.5194/hess-26-1695-2022, 2022
Short summary
Short summary
We explore the ability of non-parametric Bayesian networks to reproduce maximum daily discharge in a given month in a catchment when the remaining hydro-meteorological and catchment attributes are known. We show that a saturated network evaluated in an individual catchment can reproduce statistical characteristics of discharge in about ~ 40 % of the cases, while challenges remain when a saturated network considering all the catchments together is evaluated.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022, https://doi.org/10.5194/hess-26-1481-2022, 2022
Short summary
Short summary
Climate change impacts on water resources in the Volta River basin are investigated under various global warming scenarios. Results reveal contrasting changes in future hydrological processes and water availability, depending on greenhouse gas emission scenarios, with implications for floods and drought occurrence over the 21st century. These findings provide insights for the elaboration of regional adaptation and mitigation strategies for climate change.
Jan Seibert and Sten Bergström
Hydrol. Earth Syst. Sci., 26, 1371–1388, https://doi.org/10.5194/hess-26-1371-2022, https://doi.org/10.5194/hess-26-1371-2022, 2022
Short summary
Short summary
Hydrological catchment models are commonly used as the basis for water resource management planning. The HBV model, which is a typical example of such a model, was first applied about 50 years ago in Sweden. We describe and reflect on the model development and applications. The aim is to provide an understanding of the background of model development and a basis for addressing the balance between model complexity and data availability that will continue to face hydrologists in the future.
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
Hydrol. Earth Syst. Sci., 26, 1295–1318, https://doi.org/10.5194/hess-26-1295-2022, https://doi.org/10.5194/hess-26-1295-2022, 2022
Short summary
Short summary
Assuming stationarity of hydrological systems is no longer appropriate when considering land use and climate change. We tested the sensitivity of hydrological predictions to changes in model parameters that reflect ecosystem adaptation to climate and potential land use change. We estimated a 34 % increase in the root zone storage parameter under +2 K global warming, resulting in up to 15 % less streamflow in autumn, due to 14 % higher summer evaporation, compared to a stationary system.
Cited articles
Amogu, O., Descroix, L., Yéro, K. S., Breton, E. L., Mamadou, I., Ali,
A., Vischel, T., Bader, J.-C., Moussa, I. B., Gautier, E., Boubkraoui, S.,
and Belleudy, P.: Increasing River Flows in the Sahel?, Water, 2, 170–199,
https://doi.org/10.3390/w2020170, 2010. a
Andersson, L. and Arheimer, B.: Modelling of human and climatic impact on
nitrogen load in a Swedish river 1885-1994, Hydrobiologia, 497, 63–77,
https://doi.org/10.1023/a:1025409620738, 2003. a
Andréassian, V. and Perrin, C.: On the ambiguous interpretation of the
Turc-Budyko nondimensional graph, Water Resour. Res., 48,
https://doi.org/10.1029/2012wr012532, 2012. a
Andréassian, V., Coron, L., Lerat, J., and Le Moine, N.: Climate elasticity of streamflow revisited – an elasticity index based on long-term hydrometeorological records, Hydrol. Earth Syst. Sci., 20, 4503–4524, https://doi.org/10.5194/hess-20-4503-2016, 2016. a, b
Ballabio, C., Panagos, P., and Monatanarella, L.: Mapping topsoil physical
properties at European scale using the LUCAS database, Geoderma, 261,
110–123, https://doi.org/10.1016/j.geoderma.2015.07.006, 2016. a
Berghuijs, W. R. and Kirchner, J. W.: The relationship between contrasting ages
of groundwater and streamflow, Geophys. Res. Lett., 44, 8925–8935,
https://doi.org/10.1002/2017gl074962, 2017. a
Bierkens, M. F. P. and van Beek, L. P. H.: Seasonal Predictability of European
Discharge: NAO and Hydrological Response Time, J. Hydrometeorol.,
10, 953–968, https://doi.org/10.1175/2009jhm1034.1, 2009. a
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, b
Delaigue, O., Génot, B., Lebecherel, L., Brigode, P., and Bourgin, P. Y.: Database of watershed-scale hydroclimatic observations in France, Université Paris-Saclay, INRAE, HYCAR Research Unit, Hydrology group, Antony, https://webgr.inrae.fr/base-de-donnees, last access: 29 March 2019. a
Descroix, L., Mahé, G., Lebel, T., Favreau, G., Galle, S., Gautier, E.,
Olivry, J.-C., Albergel, J., Amogu, O., Cappelaere, B., Dessouassi, R.,
Diedhiou, A., Breton, E. L., Mamadou, I., and Sighomnou, D.: Spatio-temporal
variability of hydrological regimes around the boundaries between Sahelian
and Sudanian areas of West Africa: A synthesis, J. Hydrol., 375,
90–102, https://doi.org/10.1016/j.jhydrol.2008.12.012, 2009. a
Dunn, S. M., Birkel, C., Tetzlaff, D., and Soulsby, C.: Transit time
distributions of a conceptual model: their characteristics and sensitivities,
Hydrol. Process., 24, 1719–1729, https://doi.org/10.1002/hyp.7560, 2010. a
Fowler, K., Knoben, W., Peel, M., Peterson, T., Ryu, D., Saft, M., Seo, K.-W.,
and Western, A.: Many commonly used rainfall-runoff models lack long, slow
dynamics: implications for runoff projections, Water Resour. Res., 56, e2019WR025286, https://doi.org/10.1029/2019wr025286, 2020. a, b
Gharari, S. and Razavi, S.: A review and synthesis of hysteresis in hydrology
and hydrological modeling: Memory, path-dependency, or missing physics?,
J. Hydrol., 566, 500–519, https://doi.org/10.1016/j.jhydrol.2018.06.037,
2018. a
Godsey, S. E., Aas, W., Clair, T. A., de Wit, H. A., Fernandez, I. J., Kahl,
J. S., Malcolm, I. A., Neal, C., Neal, M., Nelson, S. J., Norton, S. A.,
Palucis, M. C., Skjelkvåle, B. L., Soulsby, C., Tetzlaff, D., and
Kirchner, J. W.: Generality of fractal 1/f scaling in catchment tracer time
series, and its implications for catchment travel time distributions,
Hydrol. Process., 24, 1660–1671, https://doi.org/10.1002/hyp.7677, 2010. a
Grigg, A. H. and Hughes, J. D.: Nonstationarity driven by multidecadal change
in catchment groundwater storage: A test of modifications to a common
rainfall-run-off model, Hydrol. Process., 32, 3675–3688,
https://doi.org/10.1002/hyp.13282, 2018. a, b
Harrigan, S., Prudhomme, C., Parry, S., Smith, K., and Tanguy, M.: Benchmarking ensemble streamflow prediction skill in the UK, Hydrol. Earth Syst. Sci., 22, 2023–2039, https://doi.org/10.5194/hess-22-2023-2018, 2018. a, b
Heidbüchel, I., Troch, P. A., Lyon, S. W., and Weiler, M.: The master transit
time distribution of variable flow systems, Water Resour. Res., 48,
W06520, https://doi.org/10.1029/2011wr011293, 2012. a
Hirpa, F. A., Gebremichael, M., and Over, T. M.: River flow fluctuation
analysis: Effect of watershed area, Water Resour. Res., 46, W12529,
https://doi.org/10.1029/2009wr009000, 2010. a
Hrachowitz, M., Soulsby, C., Tetzlaff, D., Malcolm, I. A., and Schoups, G.:
Gamma distribution models for transit time estimation in catchments: Physical
interpretation of parameters and implications for time-variant transit time
assessment, Water Resour. Res., 46, W10536,
https://doi.org/10.1029/2010wr009148, 2010. a
Hrachowitz, M., Fovet, O., Ruiz, L., and Savenije, H. H. G.: Transit time
distributions, legacy contamination and variability in biogeochemical
1/fα scaling: how are hydrological response dynamics linked to water
quality at the catchment scale?, Hydrol. Process., 29, 5241–5256,
https://doi.org/10.1002/hyp.10546, 2015. a
Hrachowitz, M., Benettin, P., van Breukelen, B. M., Fovet, O., Howden, N. J.,
Ruiz, L., van der Velde, Y., and Wade, A. J.: Transit times-the link between
hydrology and water quality at the catchment scale, WIRES Water, 3, 629–657, https://doi.org/10.1002/wat2.1155, 2016. a
Hughes, J. D., Petrone, K. C., and Silberstein, R. P.: Drought, groundwater
storage and stream flow decline in southwestern Australia, Geophys. Res. Lett., 39, L03408, https://doi.org/10.1029/2011gl050797, 2012. a
Hurst, H. E.: Long-term storage capacity of reservoirs, Trans. Amer. Soc. Civil
Eng., 116, 770–799, 1951. a
Ilampooranan, I., Van Meter, K. J., and Basu, N. B.: A Race Against Time:
Modeling Time Lags in Watershed Response, Water Resour. Res., 55,
3941–3959, https://doi.org/10.1029/2018WR023815, 2019. a
Iliopoulou, T., Aguilar, C., Arheimer, B., Bermúdez, M., Bezak, N., Ficchì, A., Koutsoyiannis, D., Parajka, J., Polo, M. J., Thirel, G., and Montanari, A.: A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers, Hydrol. Earth Syst. Sci., 23, 73–91, https://doi.org/10.5194/hess-23-73-2019, 2019. a, b, c, d
Johansson, B.: Estimation of areal precipitation for hydrological modelling in
Sweden, Doctoral Thesis, University of Gothenburg, Gothenburg,
http://hdl.handle.net/2077/15575 (last access: 29 April 2022), 2002. a
Kirchner, J. W., Feng, X., and Neal, C.: Fractal stream chemistry and its
implications for contaminant transport in catchments, Nature, 403, 524–527,
https://doi.org/10.1038/35000537, 2000. a, b
Kirchner, J. W., Feng, X., and Neal, C.: Catchment-scale advection and
dispersion as a mechanism for fractal scaling in stream tracer
concentrations, J. Hydrol., 254, 82–101,
https://doi.org/10.1016/s0022-1694(01)00487-5, 2001. a
Klemeš, V., Srikanthan, R., and McMahon, T. A.: Long-memory flow models
in reservoir analysis: What is their practical value?, Water Resour. Res., 17, 737–751, https://doi.org/10.1029/wr017i003p00737, 1981. a
Kratzert, F., Klotz, D., Shalev, G., Klambauer, G., Hochreiter, S., and Nearing, G.: Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets, Hydrol. Earth Syst. Sci., 23, 5089–5110, https://doi.org/10.5194/hess-23-5089-2019, 2019. a
Leleu, I., Tonnelier, I., Puechberty, R., Gouin, P., Viquendi, I., Cobos, L.,
Foray, A., Baillon, M., and Ndima, P.-O.: Re-founding the national
information system designed to manage and give access to hydrometric data, La
Houille Blanche, 25–32, https://doi.org/10.1051/lhb/2014004, 2014(in French). a
Lins, H. F.: Interannual streamflow variability in the United States based on
principal components, Water Resour. Res., 21, 691–701,
https://doi.org/10.1029/wr021i005p00691, 1985. a
Lo, M.-H. and Famiglietti, J. S.: Effect of water table dynamics on land
surface hydrologic memory, J. Geophys. Res., 115,
https://doi.org/10.1029/2010jd014191, 2010. a
Girons Lopez, M., Crochemore, L., and Pechlivanidis, I. G.: Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden, Hydrol. Earth Syst. Sci., 25, 1189–1209, https://doi.org/10.5194/hess-25-1189-2021, 2021. a, b, c
Marshall, A.: Principles of Economics, Palgrave Macmillan, London, 802 pp., https://doi.org/10.1057/9781137375261, 1890. a
McDonnell, J. J.: Beyond the water balance, Nat. Geosci., 10, 396–396,
https://doi.org/10.1038/ngeo2964, 2017. 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
Merz, B., Nguyen, V. D., and Vorogushyn, S.: Temporal clustering of floods in
Germany: Do flood-rich and flood-poor periods exist?, J. Hydrol.,
541, 824–838, https://doi.org/10.1016/j.jhydrol.2016.07.041, 2016. a, b
Montanari, A., Rosso, R., and Taqqu, M. S.: Fractionally differenced ARIMA
models applied to hydrologic time series: Identification, estimation, and
simulation, Water Resour. Res., 33, 1035–1044,
https://doi.org/10.1029/97wr00043, 1997. a
Mudelsee, M.: Long memory of rivers from spatial aggregation, Water Resour. Res., 43, https://doi.org/10.1029/2006wr005721, 2007. a, b, c
Nippgen, F., McGlynn, B. L., Emanuel, R. E., and Vose, J. M.: Watershed memory
at the Coweeta Hydrologic Laboratory: The effect of past precipitation and
storage on hydrologic response, Water Resour. Res., 52, 1673–1695,
https://doi.org/10.1002/2015wr018196, 2016. a
O'Connell, P., Koutsoyiannis, D., Lins, H. F., Markonis, Y., Montanari, A., and
Cohn, T.: The scientific legacy of Harold Edwin Hurst
(1880–1978), Hydrolog. Sci. J., 61, 1571–1590,
https://doi.org/10.1080/02626667.2015.1125998, 2016. a
Orth, R. and Seneviratne, S. I.: Propagation of soil moisture memory to streamflow and evapotranspiration in Europe, Hydrol. Earth Syst. Sci., 17, 3895–3911, https://doi.org/10.5194/hess-17-3895-2013, 2013. a, b
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? Part 2 – Towards a simple and efficient
potential evapotranspiration model for rainfall–runoff modelling, J. Hydrol., 303, 290–306, https://doi.org/10.1016/j.jhydrol.2004.08.026, 2005. a
Pechlivanidis, I. G., Crochemore, L., Rosberg, J., and Bosshard, T.: What Are
the Key Drivers Controlling the Quality of Seasonal Streamflow Forecasts?,
Water Resour. Res., 56, e2019WR026987, https://doi.org/10.1029/2019wr026987, 2020. 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, 2020a. a, b, c
Pelletier, A. and Andréassian, V.: Caractérisation de la
mémoire des bassins versants par approche croisée entre
piézométrie et séparation d′hydrogramme,
La Houille Blanche, 106, 30–37, https://doi.org/10.1051/lhb/2020032,
2020b. a
Pelletier, A., Andréassian, V., and Delaigue, O.: baseflow: Computes
Hydrograph Separation, https://doi.org/10.15454/Z9IK5N, r package version 0.13.2, 2021. a
Quinn, D. F., Murphy, C., Wilby, R. L., Matthews, T., Broderick, C., Golian,
S., Donegan, S., and Harrigan, S.: Benchmarking seasonal forecasting skill
using river flow persistence in Irish catchments, Hydrolog. Sci. J., https://doi.org/10.1080/02626667.2021.1874612, 2021. a, b
Rao, A. and Bhattacharya, D.: Hypothesis testing for long-term memory in
hydrologic series, J. Hydrol., 216, 183–196,
https://doi.org/10.1016/s0022-1694(99)00005-0, 1999. a
Risbey, J. S. and Entekhabi, D.: Observed Sacramento Basin streamflow response
to precipitation and temperature changes and its relevance to climate impact
studies, J. Hydrol., 184, 209–223,
https://doi.org/10.1016/0022-1694(95)02984-2, 1996. a, b
Schaake, J. and Liu, C.: Development and application of simple water balance models to understand the relationship between climate and water resources, in: New Directions for Surface Water Modeling (Proceedings of the Baltimore Symposium), edited by: IAHS Publication, 181, 343–352, ISBN 0-947571-96-5, 1989. a, b
Shukla, S., Sheffield, J., Wood, E. F., and Lettenmaier, D. P.: On the sources of global land surface hydrologic predictability, Hydrol. Earth Syst. Sci., 17, 2781–2796, https://doi.org/10.5194/hess-17-2781-2013, 2013. a
SMHI: Vattenwebb, https://vattenweb.smhi.se/station/, last access: 26 June 2019. a
Sprenger, M., Stumpp, C., Weiler, M., Aeschbach, W., Allen, S. T., Benettin,
P., Dubbert, M., Hartmann, A., Hrachowitz, M., Kirchner, J. W., McDonnell,
J. J., Orlowski, N., Penna, D., Pfahl, S., Rinderer, M., Rodriguez, N.,
Schmidt, M., and Werner, C.: The Demographics of Water: A Review of Water
Ages in the Critical Zone, Rev. Geophys., 57, 800–834,
https://doi.org/10.1029/2018rg000633, 2019. a
Staudinger, M., Stoelzle, M., Seeger, S., Seibert, J., Weiler, M., and Stahl,
K.: Catchment water storage variation with elevation, Hydrol. Process.,
31, 2000–2015, https://doi.org/10.1002/hyp.11158, 2017. a, b
Svensson, C.: Seasonal river flow forecasts for the United Kingdom using
persistence and historical analogues, Hydrolog. Sci. J., 61,
19–35, https://doi.org/10.1080/02626667.2014.992788, 2015. a, b
Szolgayova, E., Laaha, G., Blöschl, G., and Bucher, C.: Factors influencing
long range dependence in streamflow of European rivers, Hydrol.
Process., 28, 1573–1586, https://doi.org/10.1002/hyp.9694, 2013. a, b, c, d
Tetzlaff, D., Soulsby, C., Hrachowitz, M., and Speed, M.: Relative influence of
upland and lowland headwaters on the isotope hydrology and transit times of
larger catchments, J. Hydrol., 400, 438–447,
https://doi.org/10.1016/j.jhydrol.2011.01.053, 2011. a
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
Trask, J. C., Fogg, G. E., and Puente, C. E.: Resolving hydrologic water
balances through a novel error analysis approach, with application to the
Tahoe basin, J. Hydrol., 546, 326–340,
https://doi.org/10.1016/j.jhydrol.2016.12.029, 2017. a
van Dijk, A. I. J. M., Peña-Arancibia, J. L., Wood, E. F., Sheffield, J.,
and Beck, H. E.: Global analysis of seasonal streamflow predictability using
an ensemble prediction system and observations from 6192 small catchments
worldwide, Water Resour. Res., 49, 2729–2746,
https://doi.org/10.1002/wrcr.20251, 2013. a, b
Van Meter, K. J., Basu, N. B., Veenstra, J. J., and Burras, C. L.: The
nitrogen legacy: emerging evidence of nitrogen accumulation in anthropogenic
landscapes, Environ. Res. Lett., 11, 035014,
https://doi.org/10.1088/1748-9326/11/3/035014, 2016. 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, 2010. a, b
Vogel, R. M., Tsai, Y., and Limbrunner, J. F.: The regional persistence and
variability of annual streamflow in the United States, Water Resour. Res., 34, 3445–3459, https://doi.org/10.1029/98wr02523, 1998. a
Wang, W., Van Gelder, P. H. A. J. M., Vrijling, J. K., and Chen, X.: Detecting long-memory: Monte Carlo simulations and application to daily streamflow processes, Hydrol. Earth Syst. Sci., 11, 851–862, https://doi.org/10.5194/hess-11-851-2007, 2007.
a
Yang, Y., McVicar, T. R., Donohue, R. J., Zhang, Y., Roderick, M. L., Chiew,
F. H., Zhang, L., and Zhang, J.: Lags in hydrologic recovery following an
extreme drought: Assessing the roles of climate and catchment
characteristics, Water Resour. Res., 53, 4821–4837,
https://doi.org/10.1002/2017wr020683, 2017. a
Yossef, N. C., Winsemius, H., Weerts, A., van Beek, R., and Bierkens, M. F. P.:
Skill of a global seasonal streamflow forecasting system, relative roles of
initial conditions and meteorological forcing, Water Resour. Res., 49,
4687–4699, https://doi.org/10.1002/wrcr.20350, 2013. a
Yuan, X. and Zhu, E.: A First Look at Decadal Hydrological Predictability by
Land Surface Ensemble Simulations, Geophys. Res. Lett., 45,
2362–2369, https://doi.org/10.1002/2018gl077211, 2018. a
Zambrano-Bigiarini, M. and Rojas, R.: A model-independent Particle Swarm
Optimisation software for model calibration, Environ. Modell. Softw., 43, 5–25, https://doi.org/10.1016/j.envsoft.2013.01.004, 2013. a
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.
A watershed remembers the past to some extent, and this memory influences its behavior. This...