Articles | Volume 25, issue 12
Research article 13 Dec 2021
Research article | 13 Dec 2021
Identification of the contributing area to river discharge during low-flow periods
Maxime Gillet et al.
No articles found.
William Amponsah, Pierre-Alain Ayral, Brice Boudevillain, Christophe Bouvier, Isabelle Braud, Pascal Brunet, Guy Delrieu, Jean-François Didon-Lescot, Eric Gaume, Laurent Lebouc, Lorenzo Marchi, Francesco Marra, Efrat Morin, Guillaume Nord, Olivier Payrastre, Davide Zoccatelli, and Marco Borga
Earth Syst. Sci. Data, 10, 1783–1794,Short summary
The EuroMedeFF database comprises 49 events that occurred in France, Israel, Germany, Slovenia, Romania, and Italy. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the verification of flash flood hydrological models and for hydro-meteorological forecast systems. It provides, moreover, a sample of rainfall and flood discharge extremes in different climates.
I. Braud, P.-A. Ayral, C. Bouvier, F. Branger, G. Delrieu, J. Le Coz, G. Nord, J.-P. Vandervaere, S. Anquetin, M. Adamovic, J. Andrieu, C. Batiot, B. Boudevillain, P. Brunet, J. Carreau, A. Confoland, J.-F. Didon-Lescot, J.-M. Domergue, J. Douvinet, G. Dramais, R. Freydier, S. Gérard, J. Huza, E. Leblois, O. Le Bourgeois, R. Le Boursicaud, P. Marchand, P. Martin, L. Nottale, N. Patris, B. Renard, J.-L. Seidel, J.-D. Taupin, O. Vannier, B. Vincendon, and A. Wijbrans
Hydrol. Earth Syst. Sci., 18, 3733–3761,
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approachesImproved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+How well are we able to close the water budget at the global scale?Bending of the concentration discharge relationship can inform about in-stream nitrate removalQuantifying the impacts of land cover change on hydrological responses in the Mahanadi river basin in IndiaSimulating sediment discharge at water treatment plants under different land use scenarios using cascade modelling with an expert-based erosion-runoff model and a deep neural networkIn-stream Escherichia coli modeling using high-temporal-resolution data with deep learning and process-based modelsCan we use precipitation isotope outputs of isotopic general circulation models to improve hydrological modeling in large mountainous catchments on the Tibetan Plateau?Small-scale topography explains patterns and dynamics of dissolved organic carbon exports from the riparian zone of a temperate, forested catchmentEffects of spatial resolution of terrain models on modelled discharge and soil loss in Oaxaca, MexicoBenchmarking data-driven rainfall–runoff models in Great Britain: a comparison of long short-term memory (LSTM)-based models with four lumped conceptual modelsNumerical daemons of hydrological models are summoned by extreme precipitationHow is Baseflow Index (BFI) impacted by water resource management practices?Technical note: RAT – a robustness assessment test for calibrated and uncalibrated hydrological modelsReduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchmentCombining split-sample testing and hidden Markov modelling to assess the robustness of hydrological modelsHydrologically informed machine learning for rainfall–runoff modelling: towards distributed modellingRegionalization of hydrological model parameters using gradient boosting machineDevelopment and evaluation of 0.05° terrestrial water storage estimates using Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and assimilation of GRACE dataConditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead timesTechnical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspectiveA new fractal-theory-based criterion for hydrological model calibrationThe value of water isotope data on improving process understanding in a glacierized catchment on the Tibetan PlateauMachine learning deciphers CO2 sequestration and subsurface flowpaths from stream chemistryFuture changes in annual, seasonal and monthly runoff signatures in contrasting Alpine catchments in AustriaUsing hydrologic landscape classification and climatic time series to assess hydrologic vulnerability of the western U.S. to climateEvaluation of random forests for short-term daily streamflow forecasting in rainfall- and snowmelt-driven watershedsPerformance of automated methods for flash flood inundation mapping: a comparison of a digital terrain model (DTM) filling and two hydrodynamic methodsA novel method for cold-region streamflow hydrograph separation using GRACE satellite observationsA Bayesian approach to understanding the key factors influencing temporal variability in stream water quality – a case study in the Great Barrier Reef catchmentsProjected changes in Rhine River flood seasonality under global warmingTechnical note: Diagnostic efficiency – specific evaluation of model performanceHow catchment characteristics influence hydrological pathways and travel times in a boreal landscapeRainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory networkUser-oriented hydrological indices for early warning systems with validation using post-event surveys: flood case studies in the Central Apennine DistrictSpace–time variability in soil moisture droughts in the Himalayan regionDrivers of drought-induced shifts in the water balance through a Budyko approachA multi-sourced assessment of the spatiotemporal dynamics of soil moisture in the MARINE flash flood modelClimate change impacts model parameter sensitivity – implications for calibration strategy and model diagnostic evaluationImpact of karst areas on runoff generation, lateral flow and interbasin groundwater flow at the storm-event timescaleTriple oxygen isotope systematics of evaporation and mixing processes in a dynamic desert lake systemIrrigation, damming, and streamflow fluctuations of the Yellow RiverBehind the scenes of streamflow model performanceAquifer recharge in the Piedmont Alpine zone: Historical trends and future scenariosLearning from satellite observations: increased understanding of catchment processes through stepwise model improvementDiagnosis toward predicting mean annual runoff in ungauged basinsThe era of infiltrationA time-varying parameter estimation approach using split-sample calibration based on dynamic programmingA history of TOPMODELProgressive water deficits during multiyear droughts in basins with long hydrological memory in ChileA comparison of catchment travel times and storage deduced from deuterium and tritium tracers using StorAge Selection functions
Albert Nkwasa, Celray James Chawanda, Jonas Jägermeyr, and Ann van Griensven
Hydrol. Earth Syst. Sci., 26, 71–89,Short summary
We present an approach on how to incorporate crop phenology in a regional hydrological model using decision tables and global datasets of rainfed and irrigated cropland with the associated cropping calendar and management practices. Results indicate improved temporal patterns of leaf area index (LAI) and evapotranspiration (ET) simulations in comparison with remote sensing data. In addition, the improvement of the cropping season also helps to improve soil erosion estimates in cultivated areas.
Fanny Lehmann, Bramha Dutt Vishwakarma, and Jonathan Bamber
Hydrol. Earth Syst. Sci., 26, 35–54,Short summary
Many data sources are available to evaluate components of the water cycle (precipitation, evapotranspiration, runoff, and terrestrial water storage). Despite this variety, it remains unclear how different combinations of datasets satisfy the conservation of mass. We conducted the most comprehensive analysis of water budget closure on a global scale to date. Our results can serve as a basis to select appropriate datasets for regional hydrological studies.
Joni Dehaspe, Fanny Sarrazin, Rohini Kumar, Jan H. Fleckenstein, and Andreas Musolff
Hydrol. Earth Syst. Sci., 25, 6437–6463,Short summary
Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low-frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
Shaini Naha, Miguel Angel Rico-Ramirez, and Rafael Rosolem
Hydrol. Earth Syst. Sci., 25, 6339–6357,Short summary
Rapid growth in population in developing countries leads to an increase in food demand, and as a consequence, percentages of land are being converted to cropland which alters river flow processes. This study describes how the hydrology of a flood-prone river basin in India would respond to the current and future changes in land cover. Our findings indicate that the recurrent flood events occurring in the basin might be influenced by these changes in land cover at the catchment scale.
Edouard Patault, Valentin Landemaine, Jérôme Ledun, Arnaud Soulignac, Matthieu Fournier, Jean-François Ouvry, Olivier Cerdan, and Benoit Laignel
Hydrol. Earth Syst. Sci., 25, 6223–6238,Short summary
The goal of this study was to assess the sediment discharge variability at a water treatment plant (Normandy, France) according to multiple realistic land use scenarios. We developed a new cascade modelling approach and simulations suggested that coupling eco-engineering and best farming practices can significantly reduce the sediment discharge (up to 80 %).
Ather Abbas, Sangsoo Baek, Norbert Silvera, Bounsamay Soulileuth, Yakov Pachepsky, Olivier Ribolzi, Laurie Boithias, and Kyung Hwa Cho
Hydrol. Earth Syst. Sci., 25, 6185–6202,Short summary
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 the literature. We compared performance of process-driven (HSPF) and data-driven (LSTM) models for E. coli simulation. We show that LSTM can be an alternative to process-driven models for estimation of E. coli in surface waters.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 25, 6151–6172,Short summary
Hydrological modeling has large problems of uncertainty in cold regions. Tracer-aided hydrological models are increasingly used to reduce uncertainty and refine the parameterizations of hydrological processes, with limited application in large basins due to the unavailability of spatially distributed precipitation isotopes. This study explored the utility of isotopic general circulation models in driving a tracer-aided hydrological model in a large basin on the Tibetan Plateau.
Benedikt J. Werner, Oliver J. Lechtenfeld, Andreas Musolff, Gerrit H. de Rooij, Jie Yang, Ralf Gründling, Ulrike Werban, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 25, 6067–6086,Short summary
Export of dissolved organic carbon (DOC) from riparian zones (RZs) is an important yet poorly understood component of the catchment carbon budget. This study chemically and spatially classifies DOC source zones within a RZ of a small catchment to assess DOC export patterns. Results highlight that DOC export from only a small fraction of the RZ with distinct DOC composition dominates overall DOC export. The application of a spatial, topographic proxy can be used to improve DOC export models.
Sergio Naranjo, Francelino A. Rodrigues Jr., Georg Cadisch, Santiago Lopez-Ridaura, Mariela Fuentes Ponce, and Carsten Marohn
Hydrol. Earth Syst. Sci., 25, 5561–5588,Short summary
We integrate a spatially explicit soil erosion model with plot- and watershed-scale characterization and high-resolution drone imagery to assess the effect of spatial resolution digital terrain models (DTMs) on discharge and soil loss. Results showed reduction in slope due to resampling down of DTM. Higher resolution translates to higher slope, denser fluvial system, and extremer values of soil loss, reducing concentration time and increasing soil loss at the outlet. The best resolution was 4 m.
Thomas Lees, Marcus Buechel, Bailey Anderson, Louise Slater, Steven Reece, Gemma Coxon, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 5517–5534,Short summary
We used deep learning (DL) models to simulate the amount of water moving through a river channel (discharge) based on the rainfall, temperature and potential evaporation in the previous days. We tested the DL models on catchments across Great Britain finding that the model can accurately simulate hydrological systems across a variety of catchment conditions. Ultimately, the model struggled most in areas where there is chalky bedrock and where human influence on the catchment is large.
Peter T. La Follette, Adriaan J. Teuling, Nans Addor, Martyn Clark, Koen Jansen, and Lieke A. Melsen
Hydrol. Earth Syst. Sci., 25, 5425–5446,Short summary
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,Short summary
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,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.
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,Short summary
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,Short summary
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,Short summary
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.
Zhihong Song, Jun Xia, Gangsheng Wang, Dunxian She, Chen Hu, and Si Hong
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
We performed a machine learning approach to regionalize parameters of a China-wide hydrological model by linking six model parameters with ten physical attributes (terrain and soil properties). The results show the superiority of machine-learning-based regionalization approach compared with the traditional linear regression method in ungauged regions. We also obtained the relative importance of attributes against model parameters.
Natthachet Tangdamrongsub, Michael F. Jasinski, and Peter J. Shellito
Hydrol. Earth Syst. Sci., 25, 4185–4208,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
Santosh Nepal, Saurav Pradhananga, Narayan Kumar Shrestha, Sven Kralisch, Jayandra P. Shrestha, and Manfred Fink
Hydrol. Earth Syst. Sci., 25, 1761–1783,Short summary
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.
Tessa Maurer, Francesco Avanzi, Steven D. Glaser, and Roger C. Bales
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
Predicting how much water will end up in rivers is more difficult during droughts because the relationship between precipitation and streamflow can change in unexpected ways. We differentiate between changes that are predictable based on the weather patterns and those that harder to predict because they depend on the land and vegetation of a particular region. This work helps clarify why models are less accurate during droughts and helps predict how much water will be available for human use.
Judith Eeckman, Hélène Roux, Audrey Douinot, Bertrand Bonan, and Clément Albergel
Hydrol. Earth Syst. Sci., 25, 1425–1446,Short summary
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,Short summary
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,Short summary
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.
Claudia Voigt, Daniel Herwartz, Cristina Dorador, and Michael Staubwasser
Hydrol. Earth Syst. Sci., 25, 1211–1228,Short summary
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,Short summary
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,Short summary
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.
Elisa Brussolo, Elisa Palazzi, Jost von Hardenberg, Giulio Masetti, Gianna Vivaldo, Maurizio Previati, Davide Canone, Davide Gisolo, Ivan Bevilacqua, Antonello Provenzale, and Stefano Ferraris
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
In this study we evaluate the past, present and future quantity of groundwater potentially available for drinking purposes in the metropolitan area of Turin, northwestern Italy. In order to effectively manage water resources, a knowledge of the water cycle components is necessary, including precipitation, evapotranspiration and subsurface reservoirs. All these components have been carefully evaluated in this paper, using observational datasets and modelling approaches.
Petra Hulsman, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 957–982,Short summary
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,Short summary
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.
Hydrol. Earth Syst. Sci., 25, 851–866,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
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This paper aims at identifying the key reservoirs sustaining river low flow during dry summer. The reservoirs are discriminated based on the geological nature of the formations and the geochemical signature of groundwater. Results show the increasing importance to low-flow support of a specific reservoir, showing only a limited outcrop area and becoming preponderant in the heart of the dry season. This finding will contribute to improving the protective measures for preserving low flows.
This paper aims at identifying the key reservoirs sustaining river low flow during dry summer....