Articles | Volume 26, issue 14
https://doi.org/10.5194/hess-26-3863-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-3863-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Jul 2022
Research article |
| 25 Jul 2022
| 25 Jul 2022
Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?
Department of Civil, Environmental and Mechanical Engineering,
University of Trento, 38123 Trento, Italy
Diego Avesani
Department of Civil, Environmental and Mechanical Engineering,
University of Trento, 38123 Trento, Italy
Patrick Zulian
Department of Civil, Environmental and Mechanical Engineering,
University of Trento, 38123 Trento, Italy
Aldo Fiori
Department of Engineering, Roma Tre University, 00154 Rome, Italy
Alberto Bellin
Department of Civil, Environmental and Mechanical Engineering,
University of Trento, 38123 Trento, Italy
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Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi
Earth Syst. Sci. Data, 17, 1367–1391, https://doi.org/10.5194/essd-17-1367-2025, https://doi.org/10.5194/essd-17-1367-2025, 2025
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EEAR-Clim is a new and unprecedented observational dataset gathering in situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and time series significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.
Andrea Galletti, Soroush Zarghami Dastjerdi, and Bruno Majone
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-521, https://doi.org/10.5194/essd-2024-521, 2025
Revised manuscript accepted for ESSD
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We propose IAR-HP, a detailed inventory of large hydropower systems in Italy's Alpine Region, aimed at improving hydrological modeling for climate impact studies by providing the most relevant information with a consistent level of detail. It includes structural, geographical, and operational data for over 300 hydropower plants and their related reservoirs and water intakes. Validated through modeling, IAR-HP accurately reproduces observed hydropower, capturing 96.2 % of actual production.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
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The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Sebastiano Piccolroaz, Michele Di Lazzaro, Antonio Zarlenga, Bruno Majone, Alberto Bellin, and Aldo Fiori
Hydrol. Earth Syst. Sci., 20, 2047–2061, https://doi.org/10.5194/hess-20-2047-2016, https://doi.org/10.5194/hess-20-2047-2016, 2016
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We present HYPERstream, an innovative, parsimonious, and computationally efficient streamflow routing scheme based on the width function instantaneous unit hydrograph theory. HYPERstream is designed to be easily coupled with climate models and to preserve the geomorphological dispersion of the river network, irrespective of the model grid size. This makes HYPERstream well suited for multi-scale applications (from catchment up to continental scale) and to investigate extreme events (e.g. floods).
Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi
Earth Syst. Sci. Data, 17, 1367–1391, https://doi.org/10.5194/essd-17-1367-2025, https://doi.org/10.5194/essd-17-1367-2025, 2025
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EEAR-Clim is a new and unprecedented observational dataset gathering in situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and time series significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.
Diego Avesani, Yi Nan, and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2025-664, https://doi.org/10.5194/egusphere-2025-664, 2025
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Our study explores how different data sources (snow cover, glacier mass balance, and water isotopes) can improve hydrological modeling in large mountain basins. Using a Bayesian framework, we show that isotopes are particularly useful for reducing uncertainty in low-flow conditions, while snow and glacier data help during melt seasons. By addressing equifinality, our approach enhances model reliability, improving water management and streamflow predictions in mountainous regions.
Andrea Galletti, Soroush Zarghami Dastjerdi, and Bruno Majone
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-521, https://doi.org/10.5194/essd-2024-521, 2025
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We propose IAR-HP, a detailed inventory of large hydropower systems in Italy's Alpine Region, aimed at improving hydrological modeling for climate impact studies by providing the most relevant information with a consistent level of detail. It includes structural, geographical, and operational data for over 300 hydropower plants and their related reservoirs and water intakes. Validated through modeling, IAR-HP accurately reproduces observed hydropower, capturing 96.2 % of actual production.
Luciano Pavesi, Elena Volpi, and Aldo Fiori
Nat. Hazards Earth Syst. Sci., 24, 4507–4522, https://doi.org/10.5194/nhess-24-4507-2024, https://doi.org/10.5194/nhess-24-4507-2024, 2024
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Several sources of uncertainty affect flood risk estimation for reliable assessment for investment, insurance and risk management. Here, we consider the uncertainty of large-scale flood hazard modeling, providing a range of risk values that show significant variability depending on geomorphic factors and land use types. This allows for identifying the critical points where single-value estimates may underestimate the risk and the areas of vulnerability for prioritizing risk reduction efforts.
Jiancong Chen, Bhavna Arora, Alberto Bellin, and Yoram Rubin
Hydrol. Earth Syst. Sci., 25, 4127–4146, https://doi.org/10.5194/hess-25-4127-2021, https://doi.org/10.5194/hess-25-4127-2021, 2021
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We developed a stochastic framework with indicator random variables to characterize the spatiotemporal distribution of environmental hot spots and hot moments (HSHMs) that represent rare locations and events exerting a disproportionate influence over the environment. HSHMs are characterized by static and dynamic indicators. This framework is advantageous as it allows us to calculate the uncertainty associated with HSHMs based on uncertainty associated with its contributors.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
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The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Elena Diamantini, Stefano Mallucci, and Alberto Bellin
Hydrol. Earth Syst. Sci., 23, 573–593, https://doi.org/10.5194/hess-23-573-2019, https://doi.org/10.5194/hess-23-573-2019, 2019
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The description of pharmaceutical fate and transport introduced into a watershed is a challenging topic, especially because of the possible adverse effects on human health. In addition, an accurate estimation of solute sources and routes is still missing. This study uses a new promising modeling approach to predict pharmaceutical concentrations in rivers. Results show an interesting relationship between solute concentrations in waters and touristic fluxes.
Flavia Tauro, Andrea Petroselli, Aldo Fiori, Nunzio Romano, Maria Cristina Rulli, Maurizio Porfiri, Mario Palladino, and Salvatore Grimaldi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-501, https://doi.org/10.5194/hess-2016-501, 2016
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Sebastiano Piccolroaz, Michele Di Lazzaro, Antonio Zarlenga, Bruno Majone, Alberto Bellin, and Aldo Fiori
Hydrol. Earth Syst. Sci., 20, 2047–2061, https://doi.org/10.5194/hess-20-2047-2016, https://doi.org/10.5194/hess-20-2047-2016, 2016
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We present HYPERstream, an innovative, parsimonious, and computationally efficient streamflow routing scheme based on the width function instantaneous unit hydrograph theory. HYPERstream is designed to be easily coupled with climate models and to preserve the geomorphological dispersion of the river network, irrespective of the model grid size. This makes HYPERstream well suited for multi-scale applications (from catchment up to continental scale) and to investigate extreme events (e.g. floods).
L. Carturan, C. Baroni, M. Becker, A. Bellin, O. Cainelli, A. Carton, C. Casarotto, G. Dalla Fontana, A. Godio, T. Martinelli, M. C. Salvatore, and R. Seppi
The Cryosphere, 7, 1819–1838, https://doi.org/10.5194/tc-7-1819-2013, https://doi.org/10.5194/tc-7-1819-2013, 2013
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Hydrologic models are needed to provide simulations of water availability, floods, and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models and thus cannot easily be used to select an appropriate model for a specific place.
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Hydrol. Earth Syst. Sci., 29, 2109–2132, https://doi.org/10.5194/hess-29-2109-2025, https://doi.org/10.5194/hess-29-2109-2025, 2025
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Land changes and landscape features critically impact water systems. Studying two watersheds in China’s Greater Bay Area, we found slope strongly influences water processes in mountainous areas. However, this relationship is weak in the lower regions of steeper watersheds. Urbanization leads to an increase in annual surface runoff, while flatter watersheds exhibit a buffering capacity against this effect. However, this buffering capacity diminishes with increasing annual rainfall intensity.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci., 29, 1981–2002, https://doi.org/10.5194/hess-29-1981-2025, https://doi.org/10.5194/hess-29-1981-2025, 2025
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Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite the fact that they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what they truly reflect in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and timescales for accurate drought characterization and monitoring.
Sebastian Gegenleithner, Manuel Pirker, Clemens Dorfmann, Roman Kern, and Josef Schneider
Hydrol. Earth Syst. Sci., 29, 1939–1962, https://doi.org/10.5194/hess-29-1939-2025, https://doi.org/10.5194/hess-29-1939-2025, 2025
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Accurate early-warning systems are crucial for reducing the damage caused by flooding events. In this study, we explored the potential of long short-term memory networks for enhancing the forecast accuracy of hydrologic models employed in operational flood forecasting. The presented approach elevated the investigated hydrologic model’s forecast accuracy for further ahead predictions and at flood event runoff.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025, https://doi.org/10.5194/hess-29-1919-2025, 2025
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Common intuition holds that higher input data resolution leads to better results. To assess the benefits of high-resolution data, we conduct simulation experiments using data with various temporal resolutions across multiple catchments and find that higher-resolution data do not always improve model performance, challenging the necessity of pursuing such data. In catchments with small areas or significant flow variability, high-resolution data is more valuable.
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025, https://doi.org/10.5194/hess-29-1703-2025, 2025
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The quantification of precipitation into evaporation and runoff is vital for water resources management. The Budyko framework, based on aridity and evaporative indices of a catchment, can be an ideal tool for that. However, recent research highlights deviations of catchments from the expected evaporative index, casting doubt on its reliability. This study quantifies deviations of 2387 catchments, finding them minor and predictable. Integrating these into predictions upholds the framework's efficacy.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025, https://doi.org/10.5194/hess-29-1725-2025, 2025
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In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until we observe overparameterization.
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025, https://doi.org/10.5194/hess-29-1685-2025, 2025
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We generate operational forecasts of daily maximum stream water temperature for 32 consecutive days at 54 stations in Switzerland with our best-performing data-driven model. The average forecast error is 0.38 °C for 1 d ahead and increases to 0.90 °C for 32 d ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1749–1758, https://doi.org/10.5194/hess-29-1749-2025, https://doi.org/10.5194/hess-29-1749-2025, 2025
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Long short-term memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modelling. However, most studies focus on predictions at a daily scale, limiting the benefits of sub-daily (e.g. hourly) predictions in applications like flood forecasting. In this study, we introduce a new architecture, multi-frequency LSTM (MF-LSTM), designed to use inputs of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci., 29, 1615–1636, https://doi.org/10.5194/hess-29-1615-2025, https://doi.org/10.5194/hess-29-1615-2025, 2025
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Our study projects how climate change will affect the drying of river segments and stream networks in Europe, using advanced modelling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent and intense and will start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists for evaluating the ecological health of river ecosystem.
Tariq Aziz, Steven K. Frey, David R. Lapen, Susan Preston, Hazen A. J. Russell, Omar Khader, Andre R. Erler, and Edward A. Sudicky
Hydrol. Earth Syst. Sci., 29, 1549–1568, https://doi.org/10.5194/hess-29-1549-2025, https://doi.org/10.5194/hess-29-1549-2025, 2025
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This study determines the value of subsurface water for ecosystem services' supply in an agricultural watershed in Ontario, Canada. Using a fully integrated water model and an economic valuation approach, the research highlights subsurface water's critical role in maintaining watershed ecosystem services. The study informs on the sustainable use of subsurface water and introduces a new method for managing watershed ecosystem services.
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1277–1294, https://doi.org/10.5194/hess-29-1277-2025, https://doi.org/10.5194/hess-29-1277-2025, 2025
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Data-driven techniques have shown the potential to outperform process-based models in rainfall–runoff simulations. Hybrid models, combining both approaches, aim to enhance accuracy and maintain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions, we test their generalization capabilities for extreme hydrological events.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
Hydrol. Earth Syst. Sci., 29, 1061–1082, https://doi.org/10.5194/hess-29-1061-2025, https://doi.org/10.5194/hess-29-1061-2025, 2025
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This study reconstructs daily runoff in Switzerland (1962–2023) using a deep-learning model, providing a spatially contiguous dataset on a medium-sized catchment grid. The model outperforms traditional hydrological methods, revealing shifts in Swiss water resources, including more frequent dry years and declining summer runoff. The reconstruction is publicly available.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1033–1060, https://doi.org/10.5194/hess-29-1033-2025, https://doi.org/10.5194/hess-29-1033-2025, 2025
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Owing to differences in the existing published results, we conducted a detailed analysis of the runoff components and future trends in the Yarlung Tsangpo River basin and found that the contributions of snowmelt and glacier melt runoff to streamflow (both ~5 %) are limited and much lower than previous results. The streamflow in this area will continuously increase in the future, but the overestimated contribution of glacier melt could lead to an underestimation of this increasing trend.
Moritz Maximilian Heuer, Hadysa Mohajerani, and Markus Christian Casper
EGUsphere, https://doi.org/10.5194/egusphere-2025-636, https://doi.org/10.5194/egusphere-2025-636, 2025
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This study presents a calibration approach for water balance models. The different calibration steps aim at calibrating different hydrological processes: evapotranspiration, the runoff partitioning into surface runoff, interflow and groundwater recharge, as well as the groundwater behaviour. This allows for selection of a model parameterisation that correctly predicts the discharge at catchment outlet and simultaneously correctly depicts the underlying hydrological processes.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025, https://doi.org/10.5194/hess-29-903-2025, 2025
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This study develops an integrated framework based on the novel Driving index for changes in Precipitation–Runoff Relationships (DPRR) to explore the controlling changes in precipitation–runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation–runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025, https://doi.org/10.5194/hess-29-785-2025, 2025
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Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine learning (ML) models are increasingly being applied for flood forecasting. Such models are typically trained on large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets that maximise the spatio-temporal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025, https://doi.org/10.5194/hess-29-753-2025, 2025
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This study presents the first distributed hydrological simulation which confirms claims raised by historians that the eastward diversion project of the Tone River in Japan was conducted 4 centuries ago to increase low flows and subsequent travelling possibilities surrounding the capital, Edo (Tokyo), using inland navigation. We showed that great steps forward can be made for improving quality of life with small human engineering waterworks and small interventions in the regime of natural flows.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025, https://doi.org/10.5194/hess-29-683-2025, 2025
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This work investigates how hydrological models are transferred to a period in which climate conditions are different to the ones of the period in which they were set up. The robustness assessment test built to detect dependencies between model error and climatic drivers was applied to three hydrological models in 352 catchments in Denmark, France and Sweden. Potential issues are seen in a significant number of catchments for the models, even though the catchments differ for each model.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025, https://doi.org/10.5194/hess-29-627-2025, 2025
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Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 29, 447–463, https://doi.org/10.5194/hess-29-447-2025, https://doi.org/10.5194/hess-29-447-2025, 2025
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Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small catchments compared to large catchments, and spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show effects. The results can improve estimations of probabilities of extreme floods.
Ngo Nghi Truyen Huynh, Pierre-André Garambois, Benjamin Renard, François Colleoni, Jérôme Monnier, and Hélène Roux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3665, https://doi.org/10.5194/egusphere-2024-3665, 2025
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Understanding and modeling flash flood-prone areas remains challenging due to limited data and scale-relevant hydrological theory. While machine learning shows promise, its integration with process-based models is difficult. We present an approach incorporating machine learning into a high-resolution hydrological model to correct internal fluxes and transfer parameters between watersheds. Results show improved accuracy, advancing development of learnable and interpretable process-based models.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht H. Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci., 29, 335–360, https://doi.org/10.5194/hess-29-335-2025, https://doi.org/10.5194/hess-29-335-2025, 2025
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Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping to better prepare for and respond to floods.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
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To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their physical realism, which is measured by the ability of the model to reproduce observed system dynamics. Using a model to represent the dynamics of water and nitrate and dissolved organic carbon concentrations in an agricultural catchment, we showed that using solute-concentration data for calibration is useful to improve the hydrological consistency of the model.
Haley A. Canham, Belize Lane, Colin B. Phillips, and Brendan P. Murphy
Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025, https://doi.org/10.5194/hess-29-27-2025, 2025
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The influence of watershed disturbances has proved challenging to disentangle from natural streamflow variability. This study evaluates the influence of time-varying hydrologic controls on rainfall–runoff in undisturbed and wildfire-disturbed watersheds using a novel time-series event separation method. Across watersheds, water year type and season influenced rainfall–runoff patterns. Accounting for these controls enabled clearer isolation of wildfire effects.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci., 28, 5511–5539, https://doi.org/10.5194/hess-28-5511-2024, https://doi.org/10.5194/hess-28-5511-2024, 2024
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Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
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This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Laia Estrada, Xavier Garcia, Joan Saló-Grau, Rafael Marcé, Antoni Munné, and Vicenç Acuña
Hydrol. Earth Syst. Sci., 28, 5353–5373, https://doi.org/10.5194/hess-28-5353-2024, https://doi.org/10.5194/hess-28-5353-2024, 2024
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Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological model, integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, https://doi.org/10.5194/hess-28-5331-2024, 2024
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Daniel T. Myers, David Jones, Diana Oviedo-Vargas, John Paul Schmit, Darren L. Ficklin, and Xuesong Zhang
Hydrol. Earth Syst. Sci., 28, 5295–5310, https://doi.org/10.5194/hess-28-5295-2024, https://doi.org/10.5194/hess-28-5295-2024, 2024
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We studied how streamflow and water quality models respond to land cover data collected by satellites during the growing season versus the non-growing season. The land cover data showed more trees during the growing season and more built areas during the non-growing season. We next found that the use of non-growing season data resulted in a higher modeled nutrient export to streams. Knowledge of these sensitivities would be particularly important when models inform water resource management.
Hatice Türk, Christine Stumpp, Markus Hrachowitz, Karsten Schulz, Peter Strauss, Günter Blöschl, and Michael Stockinger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-359, https://doi.org/10.5194/hess-2024-359, 2024
Revised manuscript accepted for HESS
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Using advances in transit time estimation and tracer data, we tested if fast-flow transit times are controlled solely by soil moisture or are also controlled by precipitation intensity. We used soil moisture-dependent and precipitation intensity-conditional transfer functions. We showed that significant portion of event water bypasses the soil matrix through fast flow paths (overland flow, tile drains, preferential flow paths) in dry soil conditions for both low and high-intensity precipitation.
Kevin R. Shook, Paul H. Whitfield, Christopher Spence, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 28, 5173–5192, https://doi.org/10.5194/hess-28-5173-2024, https://doi.org/10.5194/hess-28-5173-2024, 2024
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Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Pablo Fernando Dornes and Rocío Noelia Comas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-338, https://doi.org/10.5194/hess-2024-338, 2024
Revised manuscript accepted for HESS
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The Desaguadero-Salado-Chadiluevú-Curacó (DSCC) River is a semiarid river which is severely dammed in its tributaries which collect the snowmelt runoff. This runoff feeds mostly gravitational irrigation systems of very low efficiency. As a result, the DSCC River does not have natural runoff. The proposed Hydrological Regime Index (HRI) is able to discriminate and quantify regime alterations under permanent and non-permanent flow conditions and with low and high impoundment conditions.
Sylvain Payraudeau, Pablo Alvarez-Zaldivar, Paul van Dijk, and Gwenaël Imfeld
EGUsphere, https://doi.org/10.5194/egusphere-2024-2840, https://doi.org/10.5194/egusphere-2024-2840, 2024
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Our study focuses on the rising concern of pesticides damaging aquatic ecosystems, which puts drinking water, the environment, and human health at risk. We provided more accurate estimates of how pesticides break down and spread in small water systems, helping to improve pesticide management practices. By using unique chemical markers in our analysis, we enhanced the accuracy of our predictions, offering important insights for better protection of water sources and natural ecosystems.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
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We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Nan Wu, Ke Zhang, Amir Naghibi, Hossein Hashemi, Zhongrui Ning, Qinuo Zhang, Xuejun Yi, Haijun Wang, Wei Liu, Wei Gao, and Jerker Jarsjö
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-324, https://doi.org/10.5194/hess-2024-324, 2024
Revised manuscript accepted for HESS
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The hydrology of cold regions in the human population is poorly understood due to complex motion and limited data, hindering streamflow analysis. Using existing models, we compared runoff from an extended model with snowmelt and frozen ground, validating its reliability and integration. This study focuses on the effects of snowmelt and frozen ground on runoff, affecting precipitation type, surface-groundwater partitioning, and evapotranspiration.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
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We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
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This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2024-2966, https://doi.org/10.5194/egusphere-2024-2966, 2024
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We assessed the value of high-resolution data and parameters transferability across temporal scales based on 7 catchments in northern China. We found that higher resolution data does not always improve model performance, questioning the need for such data; Model parameters are transferable across different data resolutions, but not across computational time steps. It is recommended to utilize smaller computational time step when building hydrological models even without high-resolution data.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
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This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Francesco Zignol, William Lidberg, Caroline Greiser, Johannes Larson, Raúl Hoffrén, and Anneli M. Ågren
EGUsphere, https://doi.org/10.5194/egusphere-2024-2909, https://doi.org/10.5194/egusphere-2024-2909, 2024
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We investigated the factors influencing soil moisture variations across a boreal forest catchment in northern Sweden, where data is usually scarce. We found that soil moisture is shaped by topographical features, vegetation and soil characteristics, and weather conditions. The insights presented in this study will help improve models that predict soil moisture over space and time, which is crucial for forest management and nature conservation in the face of climate change and biodiversity loss.
Maria Elenius, Charlotta Pers, Sara Schützer, and Berit Arheimer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-271, https://doi.org/10.5194/hess-2024-271, 2024
Revised manuscript accepted for HESS
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Simulations of peatland rewetting in Sweden under various conditions of climate, local hydrology and rewetting practices showed insubstantial changes in landscape flow extremes due to mixing with runoff from various landcover. The impact on local hydrological extremes are governed by groundwater levels prior to rewetting and reduced tree cover, hence wetland allocation and management practices are crucial if the purpose is to reduce flow extremes in peatland streams.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
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A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
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Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
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We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
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Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Cited articles
Aich, V., Liersch, S., Vetter, T., Fournet, S., Andersson, J. C. M., Calmanti,
S., Van Weert, F. H. A., Hattermann, F. F., and Paton, E. N.: Flood projections
within the Niger River Basin under future land use and climate change, Sci.
Total Environ., 562, 666–677, https://doi.org/10.1016/j.scitotenv.2016.04.021, 2016.
Arnell, N. W.: Uncertainty in the relationship between climate forcing and hydrological response in UK catchments, Hydrol. Earth Syst. Sci., 15, 897–912, https://doi.org/10.5194/hess-15-897-2011, 2011.
Avesani, D., Galletti, A., Piccolroaz, S., Bellin, A., and Majone, B.: A dual
layer MPI continuous large-scale hydrological model including Human Systems,
Environ. Model. Softw., 139, 105003, https://doi.org/10.1016/j.envsoft.2021.105003,
2021.
Avesani, D., Zanfei, A., Di Marco, N., Galletti, A., Ravazzolo, F., Righetti, M.,
and Majone, B.: Short-term hydropower optimization driven by innovative
time-adapting econometric model, Appl. Energy, 310, 118510, https://doi.org/10.1016/j.apenergy.2021.118510, 2022.
Bard, A., Renard, B., Lang, M., Giuntoli, I., Korck, J., Koboltschnig, G.,
Janža, M., D'Amico, M., and Volken, D.: Trends in the hydrologic regime of
Alpine rivers, J. Hydrol., 529, 1823–1837,
https://doi.org/10.1016/j.jhydrol.2015.07.052, 2015.
Bellin, A., Majone, B., Cainelli, O., Alberici, D., and Villa, F.: A
continuous coupled hydrological and water resources management model,
Environ. Model. Softw., 75, 176–192, https://doi.org/10.1016/j.envsoft.2015.10.013,
2016.
Beven, K. J. and Binley, A.: The future of distributed models: Model
calibration and uncertainty prediction, Hydrol. Process., 6, 279–298,
https://doi.org/10.1002/hyp.3360060305, 1992.
Beven, K. and Westerberg, I.: On red herrings and real herrings:
disinformation and information in hydrological inference, Hydrol. Process.,
25, 1676–1680, https://doi.org/10.1002/hyp.7963, 2011.
Blazkova, S. and Beven, K.: A limits of acceptability approach to model
evaluation and uncertainty estimation in flood frequency estimation by
continuous simulation: Skalka catchment, Czech Republic, Water Resour. Res.,
45, W00B16, https://doi.org/10.1029/2007WR006726, 2009.
Bouwer, L. M.: Projections of Future Extreme Weather Losses Under Changes in
Climate and Exposure, Risk Anal., 33, 915–930,
https://doi.org/10.1111/j.1539-6924.2012.01880.x, 2013.
Brigode, P., Oudin, L., and Perrin, C.: Hydrological model parameter
instability: a source of additional uncertainty in estimating the
hydrological impacts of climate change?, J. Hydrol., 476, 410–425,
https://doi.org/10.1016/j.jhydrol.2012.11.012, 2013.
Brigode, P., Paquet, E., Bernardara, P., Gailhard, J., Garavaglia, F.,
Ribstein, P., Bourgin, F., Perrin, C., and Andréassian, V.: Dependence of
model-based extreme flood estimation on the calibration period: the case
study of the Kamp River (Austria), Hydrolog. Sci. J., 60,
1424–1437, doi.org/10.1080/02626667.2015.1006632, 2015.
Brunner, M. I., Farinotti, D., Zekollari, H., Huss, M., and Zappa, M.: Future shifts in extreme flow regimes in Alpine regions, Hydrol. Earth Syst. Sci., 23, 4471–4489, https://doi.org/10.5194/hess-23-4471-2019, 2019.
Buytaert, W. and De Bièvre, B.: Water for cities: the impact of climate
change and demographic growth in the tropical Andes, Water Resour. Res., 48,
W08503, https://doi.org/10.1029/2011WR011755, 2012.
Calenda, G., Mancini, C. P., and Volpi, E.: Selection of the probabilistic
model of extreme floods: The case of the River Tiber in Rome, J. Hydrol.,
371, 1–11, https://doi.org/10.1016/j.jhydrol.2009.03.010, 2009.
Chiew, F., Teng, J., Vaze, J., Post, D., Perraud, J., Kirono, D., and Viney,
N.: Estimating climate change impact on runoff across southeast Australia,
Method, results, and implications of the modeling method, Water Resour.
Res., 45, W10414, https://doi.org/10.1029/2008WR007338, 2009.
Chiogna, G., Majone, B., Cano Paoli, K., Diamantini, E., Stella, E.,
Mallucci, S., Lencioni, V., Zandonai, F., and Bellin, A.: A review of
hydrological and chemical stressors in the Adige basin and its ecological
status, Sci. Tot. Env., 540, 429–443, https://doi.org/10.1016/j.scitotenv.2015.06.149,
2016.
Clark, M. P., Wilby, R. L., Gutmann, E. D., Vano, J. A., Gangopadhyay, S.,
Wood, A. W., Fowler, H. J., Prudhomme, C., Arnold, J. R., and Brekke, L. D.:
Characterizing Uncertainty of the Hydrologic Impacts of Climate Change,
Curr. Clim. Change Rep., 2, 55–64, https://doi.org/10.1007/s40641-016-0034-x, 2016.
Conover, W. J.: Practical Nonparametric Statistics, Third edition, Wiley
Series in Probability and Statistics: Applied Probability and Statistics
Section, John Wiley & Sons. INC., New York, ISBN 9780471160687, 1999.
Diamantini, E., Lutz, S. R., Mallucci, S., Majone, B., Merz, R., and Bellin,
A.: Driver detection of water quality trends in three large European river
basins, Sci. Total Environ., 612, 49–62,
doi.org/10.1016/j.scitotenv.2017.08.172, 2018.
Di Sante, F., Coppola, E., and Giorgi, F.: Projections of river floods in
Europe using EURO-CORDEX, CMIP5 and CMIP6 simulations, Int. J. Climatol., 41, 3203–3221, https://doi.org/10.1002/joc.7014, 2019.
Earth System Grid Federation: EURO-CORDEX, euro-cordex [data set], https://www.euro-cordex.net/060378/index.php.en, last access: 15 July 2022.
Eden, J. M., Widmann, M., Maraun, D., and Vrac, M.: Comparison of GCM- and
RCM-simulated precipitation following stochastic postprocessing, J. Geophys.
Res.-Atmos., 119, 11040–11053, https://doi.org/10.1002/2014JD021732, 2014.
Efron, B.: The jackknife, the bootstrap, and other resampling plans,
Society of Industrial and Applied Mathematics CBMS-NSF Monographs, 38, ISBN 0898711797, 1982.
Fenicia, F., Kavetski, D., Reichert, P., and Albert, C.: Signature-domain
calibration of hydrological models using approximate Bayesian computation:
Empirical analysis of fundamental properties. Water Resour. Res., 54,
3958–3987, https://doi.org/10.1002/2017WR021616, 2018.
Fiori, A., Cvetkovic, V., Dagan, G., Attinger, S., Bellin, A., Dietrich, P.,
Zech, A., and Teutsch, G.: Debates-stochastic subsurface hydrology from theory to practice: The
relevance of stochastic subsurface hydrology to practical problems of
contaminant transport and remediation. What is characterization and
stochastic theory good for?, Water Resour. Res., 52, 9228–9234,
https://doi.org/10.1002/2015WR017525, 2016.
Galletti, A., Avesani, D., Bellin, A., and Majone, B.: Detailed simulation of
storage hydropower systems in large Alpine watersheds, J. Hydrol., 603,
127125, https://doi.org/10.1016/j.jhydrol.2021.127125, 2021.
Gampe, D., Nikulin, G., and Ludwig, R.: Using an ensemble of regional climate
models to assess climate change impacts on water scarcity in European river
basins, Sci. Total Environ., 573, 1503–1518, https://doi.org/10.1016/j.scitotenv.2016.08.053, 2016.
Gobiet, A., Kotlarski, S., Beniston, M., Heinrich, G., Rajczak, J. and
Stoffel, M.: 21st century climate change in the European Alps, A
review, Sci. Total Environ., 493, 1138–1151, https://doi.org/10.1016/j.scitotenv.2013.07.050, 2014.
Goovaerts, P.: Geostatistics for natural resources evaluation, Oxford
University Press, 483 p., ISBN 9780195115383, 1997.
Grubbs, F. E.: Procedures for Detecting Outlying Observations in Samples,
Technometrics 11, 1–21, https://doi.org/10.1080/00401706.1969.10490657, 1969.
Gumbel, E. J.: The return period of flood flows, Ann. Math Stat., 12,
163–190, 1941.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition
of the mean squared error and NSE performance criteria: Implications for
improving hydrological modelling, J. Hydrol., 377, 80–91, 2009.
Guthke, A.: Defensible model complexity: A call for data-based and
goal-oriented model choice, Groundwater, 55, 646–650,
https://doi.org/10.1111/gwat.12554, 2017.
Hargreaves, G. H. and Samani, Z. A.: Estimating potential evapotranspiration,
J. Irrig. Drain. Eng., 108, 225–230, 1989.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated
high-resolution grids of monthly climatic observations – the CRU TS3.10
dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Hattermann, F. F., Vetter, T., Breuer, L., Su, B., Daggupati, P., Donnelly,
C., Fekete, B., Florke F., Gosling, S.N., Hoffmann, P., Liersch, S., Masaki,
Y., Motovilov, Y., Muller, C., Samaniego, L., Stacke, T., Wada, Y., Yang,
T., and Krysnaova, V.: Environ. Res. Lett., 13, 015006,
https://doi.org/10.1088/1748-9326/aa9938, 2018.
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P.
D., and New, M.: A European daily high-resolution gridded dataset of
surface temperature and precipitation, J. Geophys. Res., 113, D20119,
https://doi.org/10.1029/2008JD010201, 2008.
Heistermann, M. and Kneis, D.: Benchmarking quantitative precipitation
estimation by conceptual rainfall-runoff modeling, Water Resour. Res., 47,
W06514, https://doi.org/10.1029/2010WR009153, 2011.
Hock, R.: Temperature index melt modelling in mountain areas, J. Hydrol.,
282, 104–115, https://doi.org/10.1016/S0022-1694(03)00257-9, 2003.
Hoeting, J. A., Madigan, D., Raftery, A. E., and Volinsky, C. T.: Bayesian
model averaging: A tutorial, Stat. Sci., 14, 382–417, 1999.
Hofstra, N., Haylock, M., New, M., and Jones, P. D.: Testing E-OBS European
high-resolution gridded data set of daily precipitation and surface
temperature, J. Geophys. Res., 114, D21101, https://doi.org/10.1029/2009JD011799, 2009.
Hofstra, N., New, M., and McSweeney, C.: The influence of interpolation and
station network density on the distributions and trends of climate variables
in gridded daily data, Clim. Dyn. 35, 841–858, https://doi.org/10.1007/s00382-009-0698-1, 2010.
Honti, M., Scheidegger, A., and Stamm, C.: The importance of hydrological uncertainty assessment methods in climate change impact studies, Hydrol. Earth Syst. Sci., 18, 3301–3317, https://doi.org/10.5194/hess-18-3301-2014, 2014.
Hosking, J. R.: Maximum-likelihood estimation of the parameters of the
generalized extreme-value distribution, Appl. Stat., 34, 301–310,
https://doi.org/10.2307/2347483, 1985.
Isotta, F. A., Frei, C., Weilguni, V., Perčec Tadić, M.,
Lassègues, P., Rudolf, B., Pavan, V., Cacciamani, C., Antolini, G.,
Ratto, S.M., Munari, M., Micheletti, S., Bonati, V., Lussana, C., Ronchi,
C., Panettieri, E., Marigo, G., and Vertačnik, G.: The climate of daily
precipitation in the Alps: development and analysis of a high-resolution
grid dataset from pan-Alpine rain-gauge data, Int. J. Climatol., 34,
1657–1675, https://doi.org/10.1002/joc.3794, 2014.
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer,
L. M., Braun, A., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G.,
Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S.,
Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S.,
Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S.,
Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiuou, P.: EURO-CORDEX: new high-resolution
climate change projections for European impact research, Reg. Environ.
Chang., 14, 563–578, 2014.
Journel, A. G. and Rossi, M. E.: When do we need a trend model in kriging?,
Math. Geol., 21, 715–739, https://doi.org/10.1007/BF00893318, 1989.
Kennedy, J. and Eberhart, R.: Particle swarm optimization, Proceedings of
IEEE International Conference on Neural Networks, Institute of Electrical
& Electronics Engineering, University of Western Australia, Perth,
Western Australia, 1942–1948, https://doi.org/10.1109/ICNN.1995.488968, 1995.
Kleinen, T. and Petschel-Held, G.: Integrated assessment of changes in
flooding probabilities due to climate change, Clim. Change, 81, 283–312,
https://doi.org/10.1007/s10584-006-9159-6, 2007.
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué, M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E., Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014.
Kundzewicz, Z., Mata, L., Arnell, N., Döll, P., Kabat, P., Jiménez,
B., Miller, K., Oki, T., Shen, Z., and Shiklomanov, I.: Freshwater resources
and their management, in: Climate change: Impacts, adaptation and
vulnerability, Contribution of Working Group II to the Fourth Assessment
Report of the Intergovernmental Panel of Climate Change, edited by: Parry,
M., Canziani, O., Palutikof, J., van der Linden, P., and Hanson, C., Cambridge University Press, Cambridge, UK, 173–210, 2007.
Laio, F., Allamano, P., and Claps, P.: Exploiting the information content of hydrological ”outliers” for goodness-of-fit testing, Hydrol. Earth Syst. Sci., 14, 1909–1917, https://doi.org/10.5194/hess-14-1909-2010, 2010.
Laiti, L., Mallucci, S., Piccolroaz, S., Bellin, A., Zardi, D., Fiori, A.,
Nikulin, G., and Majone, B.: Testing the hydrological coherence of
high-resolution gridded precipitation and temperature datasets, Water Resour. Res., 54, 1999–2016, https://doi.org/10.1002/2017WR021633, 2018.
Landelius, T., Dahlgren, P., Gollvik, S., Jansson, A., and Olsson, E.: A
high-resolution regional reanalysis for Europe, Part 2: 2D analysis of
surface temperature, precipitation and wind, Q. J. R. Meteorol. Soc., https://doi.org/10.1002/qj.2813, 2016.
Larsen, S., Majone, B., Zulian, P., Stella, E., Bellin, A., Bruno, M. C.,
and Zolezzi, G.: Combining hydrologic simulations and stream-network models
to reveal flow-ecology relationships in a large Alpine catchment, Water Resour. Res., 57, e2020WR028496, https://doi.org/10.1029/2020WR028496,
2021.
Lespinas, F., Ludwig, W., and Heussner, S.: Hydrological and climatic
uncertainties associated with modeling the impact of climate change on water
resources of small Mediterranean coastal rivers, J. Hydrol., 511, 403–422,
https://doi.org/10.1016/j.jhydrol.2014.01.033, 2014.
Lindenschmidt, K. E.: Using stage frequency distributions as objective
functions for model calibration and global sensitivity analyses, Environ.
Model. Softw., 92, 169–175, https://doi.org/10.1016/j.envsoft.2017.02.027,
2017.
Lutz, S. R., Mallucci, S., Diamantini, E., Majone, B., Bellin, A., and Merz,
R.: Hydroclimatic and water quality trends across three Mediterranean river
basins, Sci. Tot. Env., 571, 1392–1406, https://doi.org/10.1016/j.scitotenv.2016.07.102,
2016.
Majone, B., Bertagnoli, A., and Bellin, A.: A non-linear runoff generation
model in small Alpine catchments, J. Hydrol., 385, 300–312, https://doi.org/10.1016/j.jhydrol.2010.02.033, 2010.
Majone, B., Bovolo, C. I., Bellin, A., Blenkinsop, S., and Fowler, J.:
Modeling the impacts of future climate change on water resources for the
Gállego river basin, Spain, Water Resour. Res., 48, W01512,
https://doi.org/10.1029/2011WR010985, 2012.
Majone, B., Villa, F., Deidda, R., and Bellin, A.: Impact of climate change and
water use policies on hydropower potential in the south-eastern Alpine
region, Sci. Tot. Env., 543, 965–980,
https://doi.org/10.1016/j.scitotenv.2015.05.009, 2016.
Mallucci, S., Majone, B., and Bellin, A.: Detection and attribution of
hydrological changes in a large Alpine river basin, J. Hydrol.,
575, 1214–1229, https://doi.org/10.1016/j.jhydrol.2019.06.020, 2019.
Mcmillan, H., Westerberg, I., and Branger, F.: Five guidelines for
selecting hydrological signatures. Hydrol. Process., 31,
4757–4761, https://doi.org/10.1002/hyp.11300, 2017.
Meresa, H. K. and Romanowicz, R. J.: The critical role of uncertainty in projections of hydrological extremes, Hydrol. Earth Syst. Sci., 21, 4245–4258, https://doi.org/10.5194/hess-21-4245-2017, 2017.
Michel, C., Andreassian, V., and Perrin, C.: Soil Conservation Service Curve
Number method: How to mend a wrong soil moisture accounting procedure?,
Water Resour. Res., 41, W02011, https://doi.org/10.1029/2004WR003191, 2005.
Mizukami, N., Rakovec, O., Newman, A. J., Clark, M. P., Wood, A. W., Gupta, H. V., and Kumar, R.: On the choice of calibration metrics for “high-flow” estimation using hydrologic models, Hydrol. Earth Syst. Sci., 23, 2601–2614, https://doi.org/10.5194/hess-23-2601-2019, 2019.
Montanari, A. and Toth, E.: Calibration of hydrological models in the
spectral domain: An opportunity for scarcely gauged basins?, Water Resour.
Res., 43, W05434, https://doi.org/10.1029/2006WR005184, 2007.
Montanari, A., Young, G., Savenije, H. H. G., Hughes, D., Wagener, T., Ren,
L. L., Koutsoyiannis, D., Cudennec, C., Toth, E., Grimaldi, S., Blöschl, G., Sivapalan, M., Beven, K.,
Gupta, H., Hipsey, M., Schaefli, B., Arheimer, B., Boegh, E., Schymanski, S. J., Di Baldassarre, G.,
Yu, B., Hubert, P., Huang, Y., Schumann, A., Post, D. A., Srinivasan, V., Harman, C.,
Thompson, S., Rogger, M., Viglione, A., McMillan, H., Characklis, G., Pang, Z., and Belyaev. V.: “Panta Rhei-Everything Flows”: Change in
hydrology and society – The IAHS Scientific Decade 2013–2022, Hydrol. Sci. J., 58, 1256–1275, https://doi.org/10.1080/02626667.2013.809088,
2013.
Muñoz, E., Arumí, J. L., and Rivera, D.: Watersheds are not static:
Implications of climate variability and hydrologic dynamics in modelling,
Bosque (Valdivia), 34, 7–11, https://doi.org/10.4067/S0717-92002013000100002,
2013.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models part I. A discussion of principles, J. Hydrol., 10, 282–290,
https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Ngongondo, C., Li, L., Gong, L., Xu, C., and Alemawm, B. F: Flood frequency
under changing climate in the upper Kafue River basin, southern Africa: a
large scale hydrological model application, Stoch. Environ. Res. Risk.
Assess., 27, 1883–1898, https://doi.org/10.1007/s00477-013-0724-z, 2013.
Pearson, K.: On the criterion that a given system of deviations from the
probable in the case of a correlated system of variables is such that it can
be reasonably supposed to have arisen from random sampling, Philosophical
Magazine Series 5, 302, 157–175, 1900.
Pechlivanidis, I. G., Arheimer, B., Donnelly, C., Hundecha, Y., Huang, S.,
Aich, V., Samaniego, L., Eisner, S., and Shi, P.: Analysis of hydrological
extremes at different hydro-climatic regimes under present and future
conditions, Clim. Change, 141, 467–481, https://doi.org/10.1007/s10584-016-1723-0,
2017.
Peel, M. C. and Blöschl, G.: Hydrological modelling in a changing
world, Prog. Phys. Geog., 35, 249–261,
https://doi.org/10.1177/0309133311402550, 2011.
Perrin, C., Oudin, L., Andreassian, V., Rojas-Serna, C., Michel, C., and
Mathevet, T.: Impact of limited streamflow data on the efficiency and the
parameters of rainfall-runoff models, Hydrolog. Sci. J., 52,
131–151, https://doi.org/10.1623/hysj.52.1.131, 2007.
Piccolroaz, S., Majone, B., Palmieri, F., Cassiani, G., and Bellin, A.: On
the use of spatially distributed, time-lapse microgravity surveys to inform
hydrological modeling, Water Resour. Res., 51, 7270–7288,
https://doi.org/10.1002/2015WR016994, 2015.
Piccolroaz, S., Di Lazzaro, M., Zarlenga, A., Majone, B., Bellin, A., and Fiori, A.: HYPERstream: a multi-scale framework for streamflow routing in large-scale hydrological model, Hydrol. Earth Syst. Sci., 20, 2047–2061, https://doi.org/10.5194/hess-20-2047-2016, 2016.
Protter, M. H. and Morrey, C. B.: College Calculus with Analytic Geometry, Second Edition (1 January 1970),
Addison-Wesley VLSI Systems Series, Addison-Wesley Publishing Company, ISBN 9780201060010, 1977.
Rango, A. and Martinec, J.: Revisiting the degree-day method for snowmelt
computations, J. Am. Water Resour. Assoc., 31, 657–669,
https://doi.org/10.1111/j.1752-1688.1995.tb03392.x, 1995.
Rinaldo, A., Marani, A., and Rigon, R.: Geomorphological dispersion, Water
Resour. Res., 27, 513–525, https://doi.org/10.1029/90WR02501, 1991.
Schaefli, B. and Gupta, H. V.: Do Nash values have value?, Hydrol.
Process., 21, 2075–2080, https://doi.org/10.1002/hyp.6825, 2007.
Seibert, J. and Beven, K. J.: Gauging the ungauged basin: how many discharge measurements are needed?, Hydrol. Earth Syst. Sci., 13, 883–892, https://doi.org/10.5194/hess-13-883-2009, 2009.
Smirnov, N. V.: Estimate of deviation between empirical distribution
functions in two independent samples, (Russian) Bull. Moscow Univ., 2,
3–16, 1939.
Taye, M. T., Ntegeka, V., Ogiramoi, N. P., and Willems, P.: Assessment of climate change impact on hydrological extremes in two source regions of the Nile River Basin, Hydrol. Earth Syst. Sci., 15, 209–222, https://doi.org/10.5194/hess-15-209-2011, 2011.
Thirel, G., Andréassian, V., Perrin, C., Audouy, J.-N., Berthet, L.,
Edwards, P., Folton, N.,
Furusho, C., Kuentz, A., Lerat, J., Lindström, G., Martin, E., Mathevet, T., Merz, R., Parajka, J.,
Ruelland, D., and Vaze, J.: Hydrology under change: an evaluation
protocol to investigate how hydrological models deal with changing
catchments, Hydrol. Sci. J., 60, 1184–1199,
https://doi.org/10.1080/02626667.2014.967248, 2014.
Thornton, P. K., Ericksen P. J., Herrero M., and Challinor, A. J.: Climate
variability and vulnerability to climate change: a review, Glob. Change
Biol., 20, 3313–3328, https://doi.org/10.1111/gcb.12581, 2014.
Todd, M. C., Taylor, R. G., Osborn, T. J., Kingston, D. G., Arnell, N. W., and Gosling, S. N.: Uncertainty in climate change impacts on basin-scale freshwater resources – preface to the special issue: the QUEST-GSI methodology and synthesis of results, Hydrol. Earth Syst. Sci., 15, 1035–1046, https://doi.org/10.5194/hess-15-1035-2011, 2011.
Vaze, J., Post, D. A., Chiew, F. H. S., Perraud, J. M., Viney, N. R., and Teng, J.:
Climate non-stationarity – validity of calibrated rainfall-runoff models for
use in climate change studies, J. Hydrol. 394, 447–457,
https://doi.org/10.1016/j.jhydrol.2010.09.018, 2010.
Vetter, T., Reinhardt, J., Flörke, M., van Griensven, A., Hattermann,
F., Huang, S., Koch, H., Pechlivanidis, I.G., Plötner, S., Seidou, O.,
Su, B., Vervoort, R. W., and Krysanova, V.: Evaluation of sources of
uncertainty in projected hydrological changes under climate change in
large-scale river basins, Clim. Change, 141, 419–433,
https://doi.org/10.1007/s10584-016-1794-y, 2017.
Vogel, R. M. and Fennessey, N. M.: Flow-Duration Curves. 1: New
Interpretation and Confidence-Intervals, Planning and
Management, J. Water Res., 120, 485–504, https://doi.org/10.1061/(ASCE)0733-9496(1994)120:4(485),
1994.
Vrzel, J., Ludwig, R., Gampe, D., and Ogrinc, N.: Hydrological system
behavior of an alluvial aquifer under climate change, Sci. Total Environ.,
649, 1179–1188, https://doi.org/10.1016/j.scitotenv.2018.08.396, 2019.
Wang, W., Chen, X., Shi, P., and van Gelder, P. H. A. J. M.: Detecting changes in extreme precipitation and extreme streamflow in the Dongjiang River Basin in southern China, Hydrol. Earth Syst. Sci., 12, 207–221, https://doi.org/10.5194/hess-12-207-2008, 2008.
Wang, A. and Solomatine, D. P.: Practical Experience of Sensitivity
Analysis: Comparing Six Methods, on Three Hydrological Models, with Three
Performance Criteria, Water, 11, 1062, https://doi.org/10.3390/w11051062, 2019.
Weibull, W.: A statistical theory of strength of materials., Ing. Vetensk.
Akad. Handl., 151, 1–45, 1939.
Westerberg, I. K., Guerrero, J.-L., Younger, P. M., Beven, K. J., Seibert, J., Halldin, S., Freer, J. E., and Xu, C.-Y.: Calibration of hydrological models using flow-duration curves, Hydrol. Earth Syst. Sci., 15, 2205–2227, https://doi.org/10.5194/hess-15-2205-2011, 2011.
Wilby, R. L. and Harris, I.: A framework for assessing uncertainties in
climate change impacts: Low-flow scenarios for the River Thames, UK, Water
Resour. Res., 42, W02419, https://doi.org/10.1029/2005WR004065, 2006.
Wilcke, R. A. I. and Bärring, L.: Selecting regional climate scenarios for
impact modelling studies, Environ. Model. Softw., 78, 191–201,
10.1016/j.envsoft.2016.01.002, 2016.
Wu, Q., Liu, S., Cai, Y., Li, X., and Jiang, Y.: Improvement of hydrological model calibration by selecting multiple parameter ranges, Hydrol. Earth Syst. Sci., 21, 393–407, https://doi.org/10.5194/hess-21-393-2017, 2017.
Yang, W., Andréasson, J., Graham, L. P., Olsson, J., Rosberg, J., and
Wetterhall, F.: Distribution based scaling to improve usability of regional
climate model projections for hydrological climate change impacts studies,
Hydrol. Res., 41, 211–229, 10.2166/nh.2010.004, 2010.
Yapo, P. O., Gupta, H. V., Sorooshian, S.: Automatic calibration of conceptual
rainfall-runoff models: sensitivity to calibration data. J. Hydrol. 181,
23–48, https://doi.org/10.1016/0022-1694(95)02918-4, 1996.
Zolezzi, G., Bellin, A., Bruno, M. C., Maiolini, B., and Siviglia, A.:
Assessing hydrological alterations at multiple temporal scales: Adige River,
Italy, Water Resour. Res., 45, W12421, https://doi.org/10.1029/2008WR007266, 2009.
Short summary
In this work, we introduce a methodology for devising reliable future high streamflow scenarios from climate change simulations. The calibration of a hydrological model is carried out to maximize the probability that the modeled and observed high flow extremes belong to the same statistical population. Application to the Adige River catchment (southeastern Alps, Italy) showed that this procedure produces reliable quantiles of the annual maximum streamflow for use in assessment studies.
In this work, we introduce a methodology for devising reliable future high streamflow scenarios...
