Articles | Volume 17, issue 10
Hydrol. Earth Syst. Sci., 17, 4227–4239, 2013
https://doi.org/10.5194/hess-17-4227-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 17, 4227–4239, 2013
https://doi.org/10.5194/hess-17-4227-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article 29 Oct 2013
Research article | 29 Oct 2013
The influence of conceptual model structure on model performance: a comparative study for 237 French catchments
W. R. van Esse et al.
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Oleksandr Mialyk, Joep F. Schyns, Martijn J. Booij, and Rick J. Hogeboom
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-329, https://doi.org/10.5194/hess-2021-329, 2021
Preprint under review for HESS
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The growing demand for crops brings us to sustainable limits of water use. Thus, to stay within these limits, we need to decrease crop water footprints (WF). To see how crop WFs change in time, we develop a new global crop model (called ACEA) and apply it to study maize during 1986–2016. We see that average maize WF has decreased by ~35 %, but total water consumption has increased by ~49 %. Other crops should be studied to see the overall dynamics in WFs of crop production worldwide.
Hongkai Gao, Chuntan Han, Rensheng Chen, Zijing Feng, Kang Wang, Fabrizio Fenicia, and Hubert Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-264, https://doi.org/10.5194/hess-2021-264, 2021
Manuscript not accepted for further review
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Permafrost hydrology is one of the 23 major unsolved problems in hydrology. In this study, we used a stepwise modeling and dynamic parameter method to examine the impact of permafrost on streamflow in the Hulu catchment in western China. We found that: topography and landscape are dominant controls on catchment response; baseflow recession is slower than other regions; precipitation-runoff relationship is non-stationary; permafrost impacts on streamflow mostly at the beginning of melting season.
Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, https://doi.org/10.5194/hess-25-1069-2021, 2021
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We quantify the differences in internal states and fluxes of 12 process-based models with similar streamflow performance and assess their plausibility using remotely sensed estimates of evaporation, snow cover, soil moisture and total storage anomalies. The dissimilarities in internal process representation imply that these models cannot all simultaneously be close to reality. Therefore, we invite modelers to evaluate their models using multiple variables and to rely on multi-model studies.
Renaud Hostache, Dominik Rains, Kaniska Mallick, Marco Chini, Ramona Pelich, Hans Lievens, Fabrizio Fenicia, Giovanni Corato, Niko E. C. Verhoest, and Patrick Matgen
Hydrol. Earth Syst. Sci., 24, 4793–4812, https://doi.org/10.5194/hess-24-4793-2020, https://doi.org/10.5194/hess-24-4793-2020, 2020
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Our objective is to investigate how satellite microwave sensors, particularly Soil Moisture and Ocean Salinity (SMOS), may help to reduce errors and uncertainties in soil moisture simulations with a large-scale conceptual hydro-meteorological model. We assimilated a long time series of SMOS observations into a hydro-meteorological model and showed that this helps to improve model predictions. This work therefore contributes to the development of faster and more accurate drought prediction tools.
Chao Gao, Martijn J. Booij, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 24, 3251–3269, https://doi.org/10.5194/hess-24-3251-2020, https://doi.org/10.5194/hess-24-3251-2020, 2020
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This paper studies the impact of climate change on high and low flows and quantifies the contribution of uncertainty sources from representative concentration pathways (RCPs), global climate models (GCMs) and internal climate variability in extreme flows. Internal climate variability was reflected in a stochastic rainfall model. The results show the importance of internal climate variability and GCM uncertainty in high flows and GCM and RCP uncertainty in low flows especially for the far future.
Lionel Berthet, François Bourgin, Charles Perrin, Julie Viatgé, Renaud Marty, and Olivier Piotte
Hydrol. Earth Syst. Sci., 24, 2017–2041, https://doi.org/10.5194/hess-24-2017-2020, https://doi.org/10.5194/hess-24-2017-2020, 2020
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An increasing number of flood forecasting services assess and communicate the uncertainty associated with their forecasts. We present a crash-testing framework that evaluates the quality of hydrological forecasts in an extrapolation context. Overall, the results highlight the challenge of uncertainty quantification when forecasting high flows. They show a significant drop in reliability when forecasting high flows and considerable variability among catchments and across lead times.
Léonard Santos, Guillaume Thirel, and Charles Perrin
Hydrol. Earth Syst. Sci., 22, 4583–4591, https://doi.org/10.5194/hess-22-4583-2018, https://doi.org/10.5194/hess-22-4583-2018, 2018
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The Kling and Gupta efficiency (KGE) is a score used in hydrology to evaluate flow simulation compared to observations. In order to force the evaluation on the low flows, some authors used the log-transformed flow to calculate the KGE. In this technical note, we show that this transformation should be avoided because it produced numerical flaws that lead to difficulties in the score value interpretation.
Léonard Santos, Guillaume Thirel, and Charles Perrin
Geosci. Model Dev., 11, 1591–1605, https://doi.org/10.5194/gmd-11-1591-2018, https://doi.org/10.5194/gmd-11-1591-2018, 2018
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Many rainfall–runoff models are based on stores. However, the differential equations that describe the stores' evolution are rarely presented in literature.
This represents an issue when the temporal resolution changes. In this work, we propose and evaluate a state-space version of a simple rainfall–runoff model within a robust resolution scheme. The results show that the proposed model performs equally well or slightly better than the original one and is independent of the temporal resolution.
Harm-Jan F. Benninga, Martijn J. Booij, Renata J. Romanowicz, and Tom H. M. Rientjes
Hydrol. Earth Syst. Sci., 21, 5273–5291, https://doi.org/10.5194/hess-21-5273-2017, https://doi.org/10.5194/hess-21-5273-2017, 2017
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Accurate flood and low-streamflow forecasting are important. The paper presents a methodology to evaluate ensemble streamflow-forecasting systems for different lead times; low, medium and high streamflow; and related runoff-generating processes. We applied the methodology to a study forecasting system of the Biała Tarnowska River in Poland. The results provide valuable information about the forecasting system: in which conditions it can be used and how the system can be improved effectively.
Tom Brouwer, Dirk Eilander, Arnejan van Loenen, Martijn J. Booij, Kathelijne M. Wijnberg, Jan S. Verkade, and Jurjen Wagemaker
Nat. Hazards Earth Syst. Sci., 17, 735–747, https://doi.org/10.5194/nhess-17-735-2017, https://doi.org/10.5194/nhess-17-735-2017, 2017
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The increasing number and severity of floods, driven by e.g. urbanization, subsidence and climate change, create a growing need for accurate and timely flood maps. At the same time social media is a source of much real-time data that is still largely untapped in flood disaster management. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding.
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
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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.
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
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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.
J. F. Schyns, A. Y. Hoekstra, and M. J. Booij
Hydrol. Earth Syst. Sci., 19, 4581–4608, https://doi.org/10.5194/hess-19-4581-2015, https://doi.org/10.5194/hess-19-4581-2015, 2015
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The paper draws attention to the fact that green water (soil moisture returning to the atmosphere through evaporation) is a scarce resource, because its availability is limited and there are competing demands for green water. Around 80 indicators of green water availability and scarcity are reviewed and classified based on their scope and purpose of measurement. This is useful in order to properly include limitations in green water availability in water scarcity assessments.
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
M. C. Demirel, M. J. Booij, and A. Y. Hoekstra
Hydrol. Earth Syst. Sci., 19, 275–291, https://doi.org/10.5194/hess-19-275-2015, https://doi.org/10.5194/hess-19-275-2015, 2015
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This paper investigates the skill of 90-day low-flow forecasts using three models. From the results, it appears that all models are prone to over-predict runoff during low-flow periods using ensemble seasonal meteorological forcing. The largest range for 90-day low-flow forecasts is found for the GR4J model. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low-flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.
S. Gharari, M. Hrachowitz, F. Fenicia, H. Gao, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4839–4859, https://doi.org/10.5194/hess-18-4839-2014, https://doi.org/10.5194/hess-18-4839-2014, 2014
S. Gharari, M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4861–4870, https://doi.org/10.5194/hess-18-4861-2014, https://doi.org/10.5194/hess-18-4861-2014, 2014
P. Nicolle, R. Pushpalatha, C. Perrin, D. François, D. Thiéry, T. Mathevet, M. Le Lay, F. Besson, J.-M. Soubeyroux, C. Viel, F. Regimbeau, V. Andréassian, P. Maugis, B. Augeard, and E. Morice
Hydrol. Earth Syst. Sci., 18, 2829–2857, https://doi.org/10.5194/hess-18-2829-2014, https://doi.org/10.5194/hess-18-2829-2014, 2014
H. Gao, M. Hrachowitz, F. Fenicia, S. Gharari, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 1895–1915, https://doi.org/10.5194/hess-18-1895-2014, https://doi.org/10.5194/hess-18-1895-2014, 2014
L. Coron, V. Andréassian, C. Perrin, M. Bourqui, and F. Hendrickx
Hydrol. Earth Syst. Sci., 18, 727–746, https://doi.org/10.5194/hess-18-727-2014, https://doi.org/10.5194/hess-18-727-2014, 2014
F. Lobligeois, V. Andréassian, C. Perrin, P. Tabary, and C. Loumagne
Hydrol. Earth Syst. Sci., 18, 575–594, https://doi.org/10.5194/hess-18-575-2014, https://doi.org/10.5194/hess-18-575-2014, 2014
H. V. Gupta, C. Perrin, G. Blöschl, A. Montanari, R. Kumar, M. Clark, and V. Andréassian
Hydrol. Earth Syst. Sci., 18, 463–477, https://doi.org/10.5194/hess-18-463-2014, https://doi.org/10.5194/hess-18-463-2014, 2014
M. C. Demirel, M. J. Booij, and A. Y. Hoekstra
Hydrol. Earth Syst. Sci., 17, 4241–4257, https://doi.org/10.5194/hess-17-4241-2013, https://doi.org/10.5194/hess-17-4241-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Numerical daemons of hydrological models are summoned by extreme precipitation
How is Baseflow Index (BFI) impacted by water resource management practices?
Technical note: RAT – a robustness assessment test for calibrated and uncalibrated hydrological models
Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment
Combining split-sample testing and hidden Markov modelling to assess the robustness of hydrological models
Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling
Development and evaluation of 0.05° terrestrial water storage estimates using Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and assimilation of GRACE data
Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times
Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective
A new fractal-theory-based criterion for hydrological model calibration
The value of water isotope data on improving process understanding in a glacierized catchment on the Tibetan Plateau
Machine learning deciphers CO2 sequestration and subsurface flowpaths from stream chemistry
Future changes in annual, seasonal and monthly runoff signatures in contrasting Alpine catchments in Austria
Using hydrologic landscape classification and climatic time series to assess hydrologic vulnerability of the western U.S. to climate
Evaluation of random forests for short-term daily streamflow forecasting in rainfall- and snowmelt-driven watersheds
Performance of automated methods for flash flood inundation mapping: a comparison of a digital terrain model (DTM) filling and two hydrodynamic methods
A novel method for cold-region streamflow hydrograph separation using GRACE satellite observations
A Bayesian approach to understanding the key factors influencing temporal variability in stream water quality – a case study in the Great Barrier Reef catchments
Projected changes in Rhine River flood seasonality under global warming
Technical note: Diagnostic efficiency – specific evaluation of model performance
How catchment characteristics influence hydrological pathways and travel times in a boreal landscape
Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network
User-oriented hydrological indices for early warning systems with validation using post-event surveys: flood case studies in the Central Apennine District
In-stream Escherichia Coli Modeling Using high-temporal-resolution data with deep learning and process-based models
Space–time variability in soil moisture droughts in the Himalayan region
A multi-sourced assessment of the spatiotemporal dynamics of soil moisture in the MARINE flash flood model
Climate change impacts model parameter sensitivity – implications for calibration strategy and model diagnostic evaluation
Impact of karst areas on runoff generation, lateral flow and interbasin groundwater flow at the storm-event timescale
Benchmarking Data-Driven Rainfall-Runoff Models in Great Britain: A comparison of LSTM-based models with four lumped conceptual models
Triple oxygen isotope systematics of evaporation and mixing processes in a dynamic desert lake system
Irrigation, damming, and streamflow fluctuations of the Yellow River
Behind the scenes of streamflow model performance
Learning from satellite observations: increased understanding of catchment processes through stepwise model improvement
Diagnosis toward predicting mean annual runoff in ungauged basins
The era of infiltration
A time-varying parameter estimation approach using split-sample calibration based on dynamic programming
A history of TOPMODEL
Progressive water deficits during multiyear droughts in basins with long hydrological memory in Chile
A comparison of catchment travel times and storage deduced from deuterium and tritium tracers using StorAge Selection functions
Bending of the concentration discharge relationship can inform about in-stream nitrate removal
The role and value of distributed precipitation data in hydrological models
Flood spatial coherence, triggers, and performance in hydrological simulations: large-sample evaluation of four streamflow-calibrated models
Effects of spatial resolution of terrain models on modelled discharge and soil loss in Oaxaca, Mexico
Flexible vector-based spatial configurations in land models
Two-stage variational mode decomposition and support vector regression for streamflow forecasting
Predicting probabilities of streamflow intermittency across a temperate mesoscale catchment
Importance of the informative content in the study area when regionalising rainfall-runoff model parameters: the role of nested catchments and gauging station density
Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe
Assimilation of Soil Moisture and Ocean Salinity (SMOS) brightness temperature into a large-scale distributed conceptual hydrological model to improve soil moisture predictions: the Murray–Darling basin in Australia as a test case
Frequency and magnitude variability of Yalu River flooding: numerical analyses for the last 1000 years
Peter T. La Follette, Adriaan J. Teuling, Nans Addor, Martyn Clark, Koen Jansen, and Lieke A. Melsen
Hydrol. Earth Syst. Sci., 25, 5425–5446, https://doi.org/10.5194/hess-25-5425-2021, https://doi.org/10.5194/hess-25-5425-2021, 2021
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Hydrological models are useful tools that allow us to predict distributions and movement of water. A variety of numerical methods are used by these models. We demonstrate which numerical methods yield large errors when subject to extreme precipitation. As the climate is changing such that extreme precipitation is more common, we find that some numerical methods are better suited for use in hydrological models. Also, we find that many current hydrological models use relatively inaccurate methods.
John P. Bloomfield, Mengyi Gong, Benjamin P. Marchant, Gemma Coxon, and Nans Addor
Hydrol. Earth Syst. Sci., 25, 5355–5379, https://doi.org/10.5194/hess-25-5355-2021, https://doi.org/10.5194/hess-25-5355-2021, 2021
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Groundwater provides flow, known as baseflow, to surface streams and rivers. It is important as it sustains the flow of many rivers at times of water stress. However, it may be affected by water management practices. Statistical models have been used to show that abstraction of groundwater may influence baseflow. Consequently, it is recommended that information on groundwater abstraction is included in future assessments and predictions of baseflow.
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
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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.
Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp
Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, https://doi.org/10.5194/hess-25-4887-2021, 2021
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Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.
Etienne Guilpart, Vahid Espanmanesh, Amaury Tilmant, and François Anctil
Hydrol. Earth Syst. Sci., 25, 4611–4629, https://doi.org/10.5194/hess-25-4611-2021, https://doi.org/10.5194/hess-25-4611-2021, 2021
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The stationary assumption in hydrology has become obsolete because of climate changes. In that context, it is crucial to assess the performance of a hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. We illustrate the method on the Senegal River.
Herath Mudiyanselage Viraj Vidura Herath, Jayashree Chadalawada, and Vladan Babovic
Hydrol. Earth Syst. Sci., 25, 4373–4401, https://doi.org/10.5194/hess-25-4373-2021, https://doi.org/10.5194/hess-25-4373-2021, 2021
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Existing hydrological knowledge has been integrated with genetic programming based on a machine learning algorithm (MIKA-SHA) to induce readily interpretable distributed rainfall–runoff models. At present, the model building components of two flexible modelling frameworks (FUSE and SUPERFLEX) represent the elements of hydrological knowledge. The proposed toolkit captures spatial variabilities and automatically induces semi-distributed rainfall–runoff models without any explicit user selections.
Natthachet Tangdamrongsub, Michael F. Jasinski, and Peter J. Shellito
Hydrol. Earth Syst. Sci., 25, 4185–4208, https://doi.org/10.5194/hess-25-4185-2021, https://doi.org/10.5194/hess-25-4185-2021, 2021
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Accurate estimation of terrestrial water storage (TWS) is essential for reliable water resource assessments. TWS can be estimated from the Community Atmosphere–Biosphere Land Exchange model (CABLE), but the resolution is limited to 0.5°. We reconfigure CABLE to improve TWS spatial details from 0.5° to 0.05°. GRACE satellite data are assimilated into CABLE to improve TWS accuracy. Our workflow relies only on publicly accessible data, allowing reproduction of 0.05° TWS in any region.
Seán Donegan, Conor Murphy, Shaun Harrigan, Ciaran Broderick, Dáire Foran Quinn, Saeed Golian, Jeff Knight, Tom Matthews, Christel Prudhomme, Adam A. Scaife, Nicky Stringer, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 4159–4183, https://doi.org/10.5194/hess-25-4159-2021, https://doi.org/10.5194/hess-25-4159-2021, 2021
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We benchmarked the skill of ensemble streamflow prediction (ESP) for a diverse sample of 46 Irish catchments. We found that ESP is skilful in the majority of catchments up to several months ahead. However, the level of skill was strongly dependent on lead time, initialisation month, and individual catchment location and storage properties. We also conditioned ESP with the winter North Atlantic Oscillation and show that improvements in forecast skill, reliability, and discrimination are possible.
Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven
Hydrol. Earth Syst. Sci., 25, 3937–3973, https://doi.org/10.5194/hess-25-3937-2021, https://doi.org/10.5194/hess-25-3937-2021, 2021
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The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.
Zhixu Bai, Yao Wu, Di Ma, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 25, 3675–3690, https://doi.org/10.5194/hess-25-3675-2021, https://doi.org/10.5194/hess-25-3675-2021, 2021
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To test our hypothesis that the fractal dimensions of streamflow series can be used to improve the calibration of hydrological models, we designed the E–RD efficiency ratio of fractal dimensions strategy and examined its usability in the calibration of lumped models. The results reveal that, in most aspects, introducing RD into model calibration makes the simulation of streamflow components more reasonable. Also, pursuing a better RD during calibration leads to only a minor decrease in E.
Yi Nan, Lide Tian, Zhihua He, Fuqiang Tian, and Lili Shao
Hydrol. Earth Syst. Sci., 25, 3653–3673, https://doi.org/10.5194/hess-25-3653-2021, https://doi.org/10.5194/hess-25-3653-2021, 2021
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This study integrated a water isotope module into the hydrological model THREW. The isotope-aided model was subsequently applied for process understanding in the glacierized watershed of Karuxung river on the Tibetan Plateau. The model was used to quantify the contribution of runoff component and estimate the water travel time in the catchment. Model uncertainties were significantly constrained by using additional isotopic data, improving the process understanding in the catchment.
Andrew R. Shaughnessy, Xin Gu, Tao Wen, and Susan L. Brantley
Hydrol. Earth Syst. Sci., 25, 3397–3409, https://doi.org/10.5194/hess-25-3397-2021, https://doi.org/10.5194/hess-25-3397-2021, 2021
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It is often difficult to determine the sources of solutes in streams and how much each source contributes. We developed a new method of unmixing stream chemistry via machine learning. We found that sulfate in three watersheds is related to groundwater flowpaths. Our results emphasize that acid rain reduces a watershed's capacity to remove CO2 from the atmosphere, a key geological control on climate. Our method will help scientists unmix stream chemistry in watersheds where sources are unknown.
Sarah Hanus, Markus Hrachowitz, Harry Zekollari, Gerrit Schoups, Miren Vizcaino, and Roland Kaitna
Hydrol. Earth Syst. Sci., 25, 3429–3453, https://doi.org/10.5194/hess-25-3429-2021, https://doi.org/10.5194/hess-25-3429-2021, 2021
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This study investigates the effects of climate change on runoff patterns in six Alpine catchments in Austria at the end of the 21st century. Our results indicate a substantial shift to earlier occurrences in annual maximum and minimum flows in high-elevation catchments. Magnitudes of annual extremes are projected to increase under a moderate emission scenario in all catchments. Changes are generally more pronounced for high-elevation catchments.
Chas E. Jones Jr., Scott G. Leibowitz, Keith A. Sawicz, Randy L. Comeleo, Laurel E. Stratton, Philip E. Morefield, and Christopher P. Weaver
Hydrol. Earth Syst. Sci., 25, 3179–3206, https://doi.org/10.5194/hess-25-3179-2021, https://doi.org/10.5194/hess-25-3179-2021, 2021
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Our research assesses the hydrologic vulnerability of the western U.S. to climate by classifying the landscape based on its physical and climatic characteristics and analyzing climate data. We also apply the approach to examine the vulnerabilities of case studies in the ski and wine industries. We show that the west and its ski areas are vulnerable to changes in snow, while vineyard vulnerability varies. This allows us to consider climatic impacts across landscapes, industries, and stakeholders.
Leo Triet Pham, Lifeng Luo, and Andrew Finley
Hydrol. Earth Syst. Sci., 25, 2997–3015, https://doi.org/10.5194/hess-25-2997-2021, https://doi.org/10.5194/hess-25-2997-2021, 2021
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Model evaluation metrics suggest that RF performs better in snowmelt-driven watersheds. The largest improvements in forecasts compared to benchmark models are found among rainfall-driven watersheds. RF performance deteriorates with increases in catchment slope and soil sandiness. We note disagreement between two popular measures of RF variable importance and recommend jointly considering these measures with the physical processes under study.
Nabil Hocini, Olivier Payrastre, François Bourgin, Eric Gaume, Philippe Davy, Dimitri Lague, Lea Poinsignon, and Frederic Pons
Hydrol. Earth Syst. Sci., 25, 2979–2995, https://doi.org/10.5194/hess-25-2979-2021, https://doi.org/10.5194/hess-25-2979-2021, 2021
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Efficient flood mapping methods are needed for large-scale, comprehensive identification of flash flood inundation hazards caused by small upstream rivers. An evaluation of three automated mapping approaches of increasing complexity, i.e., a digital terrain model (DTM) filling and two 1D–2D hydrodynamic approaches, is presented based on three major flash floods in southeastern France. The results illustrate some limits of the DTM filling method and the value of using a 2D hydrodynamic approach.
Shusen Wang, Junhua Li, and Hazen A. J. Russell
Hydrol. Earth Syst. Sci., 25, 2649–2662, https://doi.org/10.5194/hess-25-2649-2021, https://doi.org/10.5194/hess-25-2649-2021, 2021
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Separating river flow into baseflow and surface runoff provides useful information for hydrology and climate studies, but traditional methods have critical limitations in the lack of physics, identifying snowmelt runoff and watershed size. This study developed a novel model using the GRACE satellite observations to address these limitations. It also includes estimates for watershed hydraulic conductivity and drainable water storage, which help assess aquifer properties and water resources.
Shuci Liu, Dongryeol Ryu, J. Angus Webb, Anna Lintern, Danlu Guo, David Waters, and Andrew W. Western
Hydrol. Earth Syst. Sci., 25, 2663–2683, https://doi.org/10.5194/hess-25-2663-2021, https://doi.org/10.5194/hess-25-2663-2021, 2021
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Riverine water quality can change markedly at one particular location. This study developed predictive models to represent the temporal variation in stream water quality across the Great Barrier Reef catchments, Australia. The model structures were informed by a data-driven approach, which is useful for identifying important factors determining temporal changes in water quality and, in turn, providing critical information for developing management strategies.
Erwin Rottler, Axel Bronstert, Gerd Bürger, and Oldrich Rakovec
Hydrol. Earth Syst. Sci., 25, 2353–2371, https://doi.org/10.5194/hess-25-2353-2021, https://doi.org/10.5194/hess-25-2353-2021, 2021
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The mesoscale hydrological model (mHM) forced with an ensemble of climate projection scenarios was used to assess potential future changes in flood seasonality in the Rhine River basin. Results indicate that future changes in flood characteristics are controlled by increases in precipitation sums and diminishing snowpacks. The decreases in snowmelt can counterbalance increasing precipitation, resulting in only small and transient changes in streamflow maxima.
Robin Schwemmle, Dominic Demand, and Markus Weiler
Hydrol. Earth Syst. Sci., 25, 2187–2198, https://doi.org/10.5194/hess-25-2187-2021, https://doi.org/10.5194/hess-25-2187-2021, 2021
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A better understanding of the reasons why model performance is unsatisfying represents a crucial part for meaningful model evaluation. We propose the novel diagnostic efficiency (DE) measure and diagnostic polar plots. The proposed evaluation approach provides a diagnostic tool for model developers and model users and facilitates interpretation of model performance.
Elin Jutebring Sterte, Fredrik Lidman, Emma Lindborg, Ylva Sjöberg, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 25, 2133–2158, https://doi.org/10.5194/hess-25-2133-2021, https://doi.org/10.5194/hess-25-2133-2021, 2021
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A numerical model was used to estimate annual and seasonal mean travel times across 14 long-term nested monitored catchments in the boreal region. The estimated travel times and young water fractions were consistent with observed variations of base cation concentration and stable water isotopes, δ18O. Soil type was the most important factor regulating the variation in mean travel times among sub-catchments, while the areal coverage of mires increased the young water fraction.
Martin Gauch, Frederik Kratzert, Daniel Klotz, Grey Nearing, Jimmy Lin, and Sepp Hochreiter
Hydrol. Earth Syst. Sci., 25, 2045–2062, https://doi.org/10.5194/hess-25-2045-2021, https://doi.org/10.5194/hess-25-2045-2021, 2021
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We present multi-timescale Short-Term Memory (MTS-LSTM), a machine learning approach that predicts discharge at multiple timescales within one model. MTS-LSTM is significantly more accurate than the US National Water Model and computationally more efficient than an individual LSTM model per timescale. Further, MTS-LSTM can process different input variables at different timescales, which is important as the lead time of meteorological forecasts often depends on their temporal resolution.
Annalina Lombardi, Valentina Colaiuda, Marco Verdecchia, and Barbara Tomassetti
Hydrol. Earth Syst. Sci., 25, 1969–1992, https://doi.org/10.5194/hess-25-1969-2021, https://doi.org/10.5194/hess-25-1969-2021, 2021
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The paper presents a modelling approach for the assessment of extremes in the hydrological cycle at a multi-catchment scale. It describes two new hydrological stress indices, innovative instruments that could be used by Civil Protection operators, for flood mapping in early warning systems. The main advantage in using the proposed indices is the possibility of displaying hydrological-stress information over any geographical domain.
Ather Abbas, Sangsoo Baek, Norbert Silvera, Bounsamay Soulileuth, Yakov Pachepsky, Olivier Ribolzi, Laurie Boithias, and Kyung Hwa Cho
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-98, https://doi.org/10.5194/hess-2021-98, 2021
Revised manuscript accepted for HESS
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Correct estimation of fecal indicator bacteria in surface waters is critical for public health. Process driven models and recently data-driven models have been applied for water quality modeling however a systematic comparison for simulation of E. coli is missing in literature. We compared the performance of a process driven (HSPF) and a data-driven (LSTM) model for E. coli simulation. We show that LSTM can be an alternative to process driven models for estimation of E. coli in surface waters.
Santosh Nepal, Saurav Pradhananga, Narayan Kumar Shrestha, Sven Kralisch, Jayandra P. Shrestha, and Manfred Fink
Hydrol. Earth Syst. Sci., 25, 1761–1783, https://doi.org/10.5194/hess-25-1761-2021, https://doi.org/10.5194/hess-25-1761-2021, 2021
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This paper examines soil moisture drought in the central Himalayan region by applying a process-based hydrological model. Our results suggest that both the occurrence and severity of droughts have increased over the last 3 decades, especially in the winter and
pre-monsoon seasons. The insights provided into the frequency, spatial coverage, and severity of the drought conditions can provide valuable inputs towards improved management of water resources and greater agricultural productivity.
Judith Eeckman, Hélène Roux, Audrey Douinot, Bertrand Bonan, and Clément Albergel
Hydrol. Earth Syst. Sci., 25, 1425–1446, https://doi.org/10.5194/hess-25-1425-2021, https://doi.org/10.5194/hess-25-1425-2021, 2021
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The risk of flash flood is of growing importance for populations, particularly in the Mediterranean area in the context of a changing climate. The representation of soil processes in models is a key factor for flash flood simulation. The importance of the various methods for soil moisture estimation are highlighted in this work. Local measurements from the field as well as data derived from satellite imagery can be used to assess the performance of model outputs.
Lieke Anna Melsen and Björn Guse
Hydrol. Earth Syst. Sci., 25, 1307–1332, https://doi.org/10.5194/hess-25-1307-2021, https://doi.org/10.5194/hess-25-1307-2021, 2021
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Certain hydrological processes become more or less relevant when the climate changes. This should also be visible in the models that are used for long-term predictions of river flow as a consequence of climate change. We investigated this using three different models. The change in relevance should be reflected in how the parameters of the models are determined. In the different models, different processes become more relevant in the future: they disagree with each other.
Martin Le Mesnil, Roger Moussa, Jean-Baptiste Charlier, and Yvan Caballero
Hydrol. Earth Syst. Sci., 25, 1259–1282, https://doi.org/10.5194/hess-25-1259-2021, https://doi.org/10.5194/hess-25-1259-2021, 2021
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We present an innovative approach consisting of the statistical analysis and comparison of 15 hydrological descriptors, characterizing catchment response to rainfall events. The distribution of these descriptors is analysed according to the occurrence of karst areas inside 108 catchments. It shows that karst impacts on storm events mainly result in river losses and that interbasin groundwater flows can represent a significant part of the catchment water budget ah the event timescale.
Thomas Lees, Marcus Buechel, Bailey Anderson, Louise Slater, Steven Reece, Gemma Coxon, and Simon J. Dadson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-127, https://doi.org/10.5194/hess-2021-127, 2021
Revised manuscript accepted for HESS
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We used deep learning models to simulate the amount of water travelling through a river channel (discharge), based on the rainfall, temperature and potential evaporation in the previous days. We compared the performance of these deep learning models to four models that are currently used by hydrologists and engineers. We tested how these different methods simulate discharge at 518 points around Great Britain. Ultimately, we found that the deep learning models produced more accurate simulations.
Claudia Voigt, Daniel Herwartz, Cristina Dorador, and Michael Staubwasser
Hydrol. Earth Syst. Sci., 25, 1211–1228, https://doi.org/10.5194/hess-25-1211-2021, https://doi.org/10.5194/hess-25-1211-2021, 2021
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Evaporation trends in the stable isotope composition (18O/16O, 17O/16O, 2H/1H) of throughflow ponds in a hydrologically complex and seasonally dynamic lake system can be reliably predicted by the classic Craig–Gordon isotope evaporation model. We demonstrate that the novel 17O-excess parameter is capable of resolving different types of evaporation with and without recharge and of identifying mixing processes that cannot be resolved using the classic δ2H–δ18O system alone.
Zun Yin, Catherine Ottlé, Philippe Ciais, Feng Zhou, Xuhui Wang, Polcher Jan, Patrice Dumas, Shushi Peng, Laurent Li, Xudong Zhou, Yan Bo, Yi Xi, and Shilong Piao
Hydrol. Earth Syst. Sci., 25, 1133–1150, https://doi.org/10.5194/hess-25-1133-2021, https://doi.org/10.5194/hess-25-1133-2021, 2021
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We improved the irrigation module in a land surface model ORCHIDEE and developed a dam operation model with the aim to investigate how irrigation and dams affect the streamflow fluctuations of the Yellow River. Results show that irrigation mainly reduces the annual river flow. The dam operation, however, mainly affects streamflow variation. By considering two generic operation rules, flood control and base flow guarantee, our dam model can sustainably improve the simulation accuracy.
Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, https://doi.org/10.5194/hess-25-1069-2021, 2021
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We quantify the differences in internal states and fluxes of 12 process-based models with similar streamflow performance and assess their plausibility using remotely sensed estimates of evaporation, snow cover, soil moisture and total storage anomalies. The dissimilarities in internal process representation imply that these models cannot all simultaneously be close to reality. Therefore, we invite modelers to evaluate their models using multiple variables and to rely on multi-model studies.
Petra Hulsman, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 957–982, https://doi.org/10.5194/hess-25-957-2021, https://doi.org/10.5194/hess-25-957-2021, 2021
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Satellite observations have increasingly been used for model calibration, while model structural developments largely rely on discharge data. For large river basins, this often results in poor representations of system internal processes. This study explores the combined use of satellite-based evaporation and total water storage data for model structural improvement and spatial–temporal model calibration for a large, semi-arid and data-scarce river system.
Yuan Gao, Lili Yao, Ni-Bin Chang, and Dingbao Wang
Hydrol. Earth Syst. Sci., 25, 945–956, https://doi.org/10.5194/hess-25-945-2021, https://doi.org/10.5194/hess-25-945-2021, 2021
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Mean annual runoff prediction is of great interest but still poses a challenge in ungauged basins. The purpose of this study is to diagnose the data requirement for predicting mean annual runoff in ungauged basins based on a water balance model, in which the effects of climate variability are explicitly represented. The performance of predicting mean annual runoff can be improved by employing better estimation of soil water storage capacity including the effects of soil, topography, and bedrock.
Keith Beven
Hydrol. Earth Syst. Sci., 25, 851–866, https://doi.org/10.5194/hess-25-851-2021, https://doi.org/10.5194/hess-25-851-2021, 2021
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Inspired by a quotation from Howard Cook in 1946, this paper traces the evolution of the infiltration theory of runoff from the work of Robert Horton and LeRoy Sherman in the 1930s to the early digital computer models of the 1970s and 1980s. Reconsideration of the perceptual model for many catchments, partly as a result of the greater appreciation of the contribution of subsurface flows to the hydrograph indicated by tracer studies, suggests a reconsideration of hydrological nomenclature.
Xiaojing Zhang and Pan Liu
Hydrol. Earth Syst. Sci., 25, 711–733, https://doi.org/10.5194/hess-25-711-2021, https://doi.org/10.5194/hess-25-711-2021, 2021
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Rainfall–runoff models are useful tools for streamflow simulation. However, efforts are needed to investigate how their parameters vary in response to climate changes and human activities. Thus, this study proposes a new method for estimating time-varying parameters, by considering both simulation accuracy and parameter continuity. The results show the proposed method is effective for identifying temporal variations of parameters and can simultaneously provide good streamflow simulation.
Keith J. Beven, Mike J. Kirkby, Jim E. Freer, and Rob Lamb
Hydrol. Earth Syst. Sci., 25, 527–549, https://doi.org/10.5194/hess-25-527-2021, https://doi.org/10.5194/hess-25-527-2021, 2021
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The theory that forms the basis of TOPMODEL was first outlined by Mike Kirkby some 45 years ago. This paper recalls some of the early developments: the rejection of the first journal paper, the early days of digital terrain analysis, model calibration and validation, the various criticisms of the simplifying assumptions, and the relaxation of those assumptions in the dynamic forms of TOPMODEL, and it considers what we might do now with the benefit of hindsight.
Camila Alvarez-Garreton, Juan Pablo Boisier, René Garreaud, Jan Seibert, and Marc Vis
Hydrol. Earth Syst. Sci., 25, 429–446, https://doi.org/10.5194/hess-25-429-2021, https://doi.org/10.5194/hess-25-429-2021, 2021
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The megadrought experienced in Chile (2010–2020) has led to larger than expected water deficits. By analysing 106 basins with snow-/rainfall regimes, we relate such intensification with the hydrological memory of the basins, explained by snow and groundwater. Snow-dominated basins have larger memory and thus accumulate the effect of persistent precipitation deficits more strongly than pluvial basins. This notably affects central Chile, a water-limited region where most of the population lives.
Nicolas Björn Rodriguez, Laurent Pfister, Erwin Zehe, and Julian Klaus
Hydrol. Earth Syst. Sci., 25, 401–428, https://doi.org/10.5194/hess-25-401-2021, https://doi.org/10.5194/hess-25-401-2021, 2021
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Different parts of water have often been used as tracers to determine the age of water in streams. The stable tracers, such as deuterium, are thought to be unable to reveal old water compared to the radioactive tracer called tritium. We used both tracers, measured in precipitation and in a stream in Luxembourg, to show that this is not necessarily true. It is, in fact, advantageous to use the two tracers together, and we recommend systematically using tritium in future studies.
Joni Dehaspe, Fanny Sarrazin, Rohini Kumar, Jan H. Fleckenstein, and Andreas Musolff
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-16, https://doi.org/10.5194/hess-2021-16, 2021
Revised manuscript accepted for HESS
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Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
Ralf Loritz, Markus Hrachowitz, Malte Neuper, and Erwin Zehe
Hydrol. Earth Syst. Sci., 25, 147–167, https://doi.org/10.5194/hess-25-147-2021, https://doi.org/10.5194/hess-25-147-2021, 2021
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This study investigates the role and value of distributed rainfall in the runoff generation of a mesoscale catchment. We compare the performance of different hydrological models at different periods and show that a distributed model driven by distributed rainfall yields improved performances only during certain periods. We then step beyond this finding and develop a spatially adaptive model that is capable of dynamically adjusting its spatial model structure in time.
Manuela I. Brunner, Lieke A. Melsen, Andrew W. Wood, Oldrich Rakovec, Naoki Mizukami, Wouter J. M. Knoben, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 105–119, https://doi.org/10.5194/hess-25-105-2021, https://doi.org/10.5194/hess-25-105-2021, 2021
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Assessments of current, local, and regional flood hazards and their future changes often involve the use of hydrologic models. A reliable model ideally reproduces both local flood characteristics and regional aspects of flooding. In this paper we investigate how such characteristics are represented by hydrologic models. Our results show that both the modeling of local and regional flood characteristics are challenging, especially under changing climate conditions.
Sergio Naranjo, Francelino A. Rodrigues Jr., Georg Cadisch, Santiago Lopez-Ridaura, Mariela Fuentes, and Carsten Marohn
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-641, https://doi.org/10.5194/hess-2020-641, 2020
Revised manuscript accepted for HESS
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This study pioneers in the integration of a spatially explicit soil erosion model with plot and watershed scale characterization and high resolution drone imagery to assess the effect of spatial resolution DTM on discharge and soil loss. Results showed reduction of slope due to resampling-down of DTM. High resolution translates into higher slope, denser fluvial system, and extremer values of soil loss reducing time of concentration and increasing soil loss at the outlet. Best resolution was 4 m.
Shervan Gharari, Martyn P. Clark, Naoki Mizukami, Wouter J. M. Knoben, Jefferson S. Wong, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 24, 5953–5971, https://doi.org/10.5194/hess-24-5953-2020, https://doi.org/10.5194/hess-24-5953-2020, 2020
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This work explores the trade-off between the accuracy of the representation of geospatial data, such as land cover, soil type, and elevation zones, in a land (surface) model and its performance in the context of modeling. We used a vector-based setup instead of the commonly used grid-based setup to identify this trade-off. We also assessed the often neglected parameter uncertainty and its impact on the land model simulations.
Ganggang Zuo, Jungang Luo, Ni Wang, Yani Lian, and Xinxin He
Hydrol. Earth Syst. Sci., 24, 5491–5518, https://doi.org/10.5194/hess-24-5491-2020, https://doi.org/10.5194/hess-24-5491-2020, 2020
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A two-stage variational mode decomposition and support vector regression is designed to reduce the influence of boundary effects without removing or correcting boundary-affected decompositions. The proposed model significantly reduces the boundary effect consequences, saves modeling time and computation resources, barely overfits the calibration samples, and forecasts monthly runoff reasonably well compared to the benchmark models.
Nils Hinrich Kaplan, Theresa Blume, and Markus Weiler
Hydrol. Earth Syst. Sci., 24, 5453–5472, https://doi.org/10.5194/hess-24-5453-2020, https://doi.org/10.5194/hess-24-5453-2020, 2020
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In recent decades the demand for detailed information of spatial and temporal dynamics of the stream network has grown in the fields of eco-hydrology and extreme flow prediction. We use temporal streamflow intermittency data obtained at various sites using innovative sensing technology as well as spatial predictors to predict and map probabilities of streamflow intermittency. This approach has the potential to provide intermittency maps for hydrological modelling and management practices.
Mattia Neri, Juraj Parajka, and Elena Toth
Hydrol. Earth Syst. Sci., 24, 5149–5171, https://doi.org/10.5194/hess-24-5149-2020, https://doi.org/10.5194/hess-24-5149-2020, 2020
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One of the most informative ways to gain information on ungauged river sections is through the implementation of a rainfall-runoff model, exploiting the information collected in gauged catchments in the study area. This study analyses how the performances of different model regionalisation approaches are influenced by the informative content of the available regional data set, in order to identify the methods that are more suitable for the data availability in the region.
Stefania Camici, Christian Massari, Luca Ciabatta, Ivan Marchesini, and Luca Brocca
Hydrol. Earth Syst. Sci., 24, 4869–4885, https://doi.org/10.5194/hess-24-4869-2020, https://doi.org/10.5194/hess-24-4869-2020, 2020
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The paper performs the most comprehensive European-scale evaluation to date of satellite rainfall products for river flow prediction. In doing so, how errors transfer from satellite-based rainfall products into flood simulation is investigated in depth and, for the first time, quantitative guidelines on the use of these products for hydrological applications are provided. This result can represent a keystone in the use of satellite rainfall products, especially in data-scarce regions.
Renaud Hostache, Dominik Rains, Kaniska Mallick, Marco Chini, Ramona Pelich, Hans Lievens, Fabrizio Fenicia, Giovanni Corato, Niko E. C. Verhoest, and Patrick Matgen
Hydrol. Earth Syst. Sci., 24, 4793–4812, https://doi.org/10.5194/hess-24-4793-2020, https://doi.org/10.5194/hess-24-4793-2020, 2020
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Our objective is to investigate how satellite microwave sensors, particularly Soil Moisture and Ocean Salinity (SMOS), may help to reduce errors and uncertainties in soil moisture simulations with a large-scale conceptual hydro-meteorological model. We assimilated a long time series of SMOS observations into a hydro-meteorological model and showed that this helps to improve model predictions. This work therefore contributes to the development of faster and more accurate drought prediction tools.
Hui Sheng, Xiaomei Xu, Jian Hua Gao, Albert J. Kettner, Yong Shi, Chengfeng Xue, Ya Ping Wang, and Shu Gao
Hydrol. Earth Syst. Sci., 24, 4743–4761, https://doi.org/10.5194/hess-24-4743-2020, https://doi.org/10.5194/hess-24-4743-2020, 2020
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This paper investigates the variability of past flooding by applying a numerical model coupled with historical records of regional climate and anthropogenic activity under the deficiency of observations. We conclude that trends in flooding frequency were predominantly modulated by the intensity and frequency of extreme rainfall events, which highlights the need for the implementation of effective river engineering measures to counteract increasing flood risks as a result of the future.
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