Articles | Volume 27, issue 23
https://doi.org/10.5194/hess-27-4355-2023
© Author(s) 2023. 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-27-4355-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
Mehrad Rahimpour Asenjan
CORRESPONDING AUTHOR
Hydrology, Climate and Climate Change Laboratory, École de technologie supérieure, Université du Québec, 1100 Notre-Dame Street West, Montréal, Quebec, H3C 1K3, Canada
Francois Brissette
Hydrology, Climate and Climate Change Laboratory, École de technologie supérieure, Université du Québec, 1100 Notre-Dame Street West, Montréal, Quebec, H3C 1K3, Canada
Jean-Luc Martel
Hydrology, Climate and Climate Change Laboratory, École de technologie supérieure, Université du Québec, 1100 Notre-Dame Street West, Montréal, Quebec, H3C 1K3, Canada
Richard Arsenault
Hydrology, Climate and Climate Change Laboratory, École de technologie supérieure, Université du Québec, 1100 Notre-Dame Street West, Montréal, Quebec, H3C 1K3, Canada
Related authors
No articles found.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
Short summary
Short summary
Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
Short summary
Short summary
Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Mostafa Tarek, François Brissette, and Richard Arsenault
Hydrol. Earth Syst. Sci., 25, 3331–3350, https://doi.org/10.5194/hess-25-3331-2021, https://doi.org/10.5194/hess-25-3331-2021, 2021
Short summary
Short summary
It is not known how much uncertainty the choice of a reference data set may bring to impact studies. This study compares precipitation and temperature data sets to evaluate the uncertainty contribution to the results of climate change studies. Results show that all data sets provide good streamflow simulations over the reference period. The reference data sets also provided uncertainty that was equal to or larger than that related to general circulation models over most of the catchments.
Mostafa Tarek, François P. Brissette, and Richard Arsenault
Hydrol. Earth Syst. Sci., 24, 2527–2544, https://doi.org/10.5194/hess-24-2527-2020, https://doi.org/10.5194/hess-24-2527-2020, 2020
Short summary
Short summary
The ERA5 reanalysis dataset is characterized by its high spatial (0.25) and temporal (hourly) resolutions and has therefore a large potential to drive environmental models in regions where the network of stations is deficient. ERA5 performance is evaluated on 3138 North American catchments. Results indicate that for hydrological modelling, ERA5 precipitation and temperature are just as good as observation all over North America, with the exception of the eastern half of the US.
Richard Arsenault and Pascal Côté
Hydrol. Earth Syst. Sci., 23, 2735–2750, https://doi.org/10.5194/hess-23-2735-2019, https://doi.org/10.5194/hess-23-2735-2019, 2019
Short summary
Short summary
Hydrological forecasting allows hydropower system operators to make the most efficient use of the available water as possible. Accordingly, hydrologists have been aiming at improving the quality of these forecasts. This work looks at the impacts of improving systematic errors in a forecasting scheme on the hydropower generation using a few decision-aiding tools that are used operationally by hydropower utilities. We find that the impacts differ according to the hydropower system characteristics.
Pierre Brigode, François Brissette, Antoine Nicault, Luc Perreault, Anna Kuentz, Thibault Mathevet, and Joël Gailhard
Clim. Past, 12, 1785–1804, https://doi.org/10.5194/cp-12-1785-2016, https://doi.org/10.5194/cp-12-1785-2016, 2016
Short summary
Short summary
In this paper, we apply a new hydro-climatic reconstruction method on the Caniapiscau Reservoir (Canada), compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment, and study the natural streamflow variability over the 1881–2011 period. This new reconstruction is based on a historical reanalysis of global geopotential height fields and aims to produce daily streamflow time series (using a rainfall–runoff model).
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model
Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework
Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks
Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern US
Hybrid forecasting: blending climate predictions with AI models
Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin
Local moisture recycling across the globe
How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
Divergent future drought projections in UK river flows and groundwater levels
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models
Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
Spatial distribution of oceanic moisture contributions to precipitation over the Tibetan Plateau
Ensemble streamflow prediction considering the influence of reservoirs in Narmada River Basin, India
Accounting for Hydroclimatic Properties in Flood Frequency Analysis Procedures
Declining water resources in response to global warming and changes in atmospheric circulation patterns over southern Mediterranean France
Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia
Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 °C warmer worlds – how anthropogenic aerosols change the story
Pan evaporation is increased by submerged macrophytes
Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis
Characterizing basin-scale precipitation gradients in the Third Pole region using a high-resolution atmospheric simulation-based dataset
A comparison of hydrological models with different level of complexity in Alpine regions in the context of climate change
Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing
Hydrological concept formation inside long short-term memory (LSTM) networks
A two-step merging strategy for incorporating multi-source precipitation products and gauge observations using machine learning classification and regression over China
Hydrometeorological evaluation of two nowcasting systems for Mediterranean heavy precipitation events with operational considerations
On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe
Regional, multi-decadal analysis on the Loire River basin reveals that stream temperature increases faster than air temperature
Investigating the response of leaf area index to droughts in southern African vegetation using observations and model simulations
Recent decrease in summer precipitation over the Iberian Peninsula closely links to reduction in local moisture recycling
Exploring the possible role of satellite-based rainfall data in estimating inter- and intra-annual global rainfall erosivity
Critical transitions in the hydrological system: early-warning signals and network analysis
Testing a maximum evaporation theory over saturated land: implications for potential evaporation estimation
The role of morphology in the spatial distribution of short-duration rainfall extremes in Italy
Impact of correcting sub-daily climate model biases for hydrological studies
The Mesoamerican mid-summer drought: the impact of its definition on occurrences and recent changes
Reconstructing climate trends adds skills to seasonal reference crop evapotranspiration forecasting
Influence of initial soil moisture in a regional climate model study over West Africa – Part 1: Impact on the climate mean
Influence of initial soil moisture in a regional climate model study over West Africa – Part 2: Impact on the climate extremes
Compound flood impact forecasting: integrating fluvial and flash flood impact assessments into a unified system
Ensemble streamflow forecasting over a cascade reservoir catchment with integrated hydrometeorological modeling and machine learning
Machine-learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany
Extreme precipitation events in the Mediterranean area: contrasting two different models for moisture source identification
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
Short summary
Short summary
Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
Short summary
Short summary
Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
Short summary
Short summary
High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
Short summary
Short summary
In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
EGUsphere, https://doi.org/10.5194/egusphere-2023-811, https://doi.org/10.5194/egusphere-2023-811, 2023
Short summary
Short summary
Paleogeographical data allow to assert that 17–13 ka BP the Caspian Sea level was 80 m above the current one. There are significant disagreements regarding the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of glacial meltwater effect.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
Short summary
Short summary
This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
Short summary
Short summary
Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
Short summary
Short summary
For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
Short summary
Short summary
We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
Short summary
Short summary
We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
Short summary
Short summary
Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
Short summary
Short summary
The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
Short summary
Short summary
Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
Short summary
Short summary
Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
Short summary
Short summary
Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-59, https://doi.org/10.5194/hess-2023-59, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface and below ground water.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
Short summary
Short summary
Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
Short summary
Short summary
Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
Short summary
Short summary
Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao
Hydrol. Earth Syst. Sci., 26, 6413–6426, https://doi.org/10.5194/hess-26-6413-2022, https://doi.org/10.5194/hess-26-6413-2022, 2022
Short summary
Short summary
Spatial quantification of oceanic moisture contribution to the precipitation over the Tibetan Plateau (TP) contributes to the reliable assessments of regional water resources and the interpretation of paleo archives in the region. Based on atmospheric reanalysis datasets and numerical moisture tracking, this work reveals the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer.
Urmin Vegad and Vimal Mishra
Hydrol. Earth Syst. Sci., 26, 6361–6378, https://doi.org/10.5194/hess-26-6361-2022, https://doi.org/10.5194/hess-26-6361-2022, 2022
Short summary
Short summary
Floods cause enormous damage to infrastructure and agriculture in India. However, the utility of ensemble meteorological forecast for hydrologic prediction has not been examined. Moreover, Indian river basins have a considerable influence of reservoirs that alter the natural flow variability. We developed a hydrologic modelling-based streamflow prediction considering the influence of reservoirs in India.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-292, https://doi.org/10.5194/hess-2022-292, 2022
Revised manuscript accepted for HESS
Short summary
Short summary
Flooding presents a major hazard for people and infrastructure along waterways, however, it is challenging to study the likelihood of a flood magnitude occuring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives watermangers a tool to locally improve flood analysis.
Camille Labrousse, Wolfgang Ludwig, Sébastien Pinel, Mahrez Sadaoui, Andrea Toreti, and Guillaume Lacquement
Hydrol. Earth Syst. Sci., 26, 6055–6071, https://doi.org/10.5194/hess-26-6055-2022, https://doi.org/10.5194/hess-26-6055-2022, 2022
Short summary
Short summary
The interest of this study is to demonstrate that we identify two zones in our study area whose hydroclimatic behaviours are uneven. By investigating relationships between the hydroclimatic conditions in both clusters for past observations with the overall atmospheric functioning, we show that the inequalities are mainly driven by a different control of the atmospheric teleconnection patterns over the area.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022, https://doi.org/10.5194/hess-26-5955-2022, 2022
Short summary
Short summary
We proposed a practical method that predicts the evaporation rates on land surfaces (ET) where only atmospheric data are available. Using a traditional equation that describes partitioning of precipitation into ET and streamflow, we could approximately identify the key parameter of the predicting formulation based on land–atmosphere interactions. The simple method conditioned by local climates outperformed sophisticated models in reproducing water-balance estimates across Australia.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022, https://doi.org/10.5194/hess-26-5737-2022, 2022
Short summary
Short summary
Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.
Brigitta Simon-Gáspár, Gábor Soós, and Angela Anda
Hydrol. Earth Syst. Sci., 26, 4741–4756, https://doi.org/10.5194/hess-26-4741-2022, https://doi.org/10.5194/hess-26-4741-2022, 2022
Short summary
Short summary
Due to climate change, it is extremely important to determine evaporation as accurately as possible. In nature, there are sediments and macrophytes in the open waters; thus, one of the aims was to investigate their effect on evaporation. The second aim of this paper was to estimate daily evaporation by using different models, which, according to results, have high priority in the evaporation prediction. Water management can obtain useful information from the results of the current research.
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022, https://doi.org/10.5194/hess-26-4603-2022, 2022
Short summary
Short summary
There have been many machine learning simulation studies based on eddy-covariance observations for water flux and evapotranspiration. We performed a meta-analysis of such studies to clarify the impact of different algorithms and predictors, etc., on the reported prediction accuracy. It can, to some extent, guide future global water flux modeling studies and help us better understand the terrestrial ecosystem water cycle.
Yaozhi Jiang, Kun Yang, Hua Yang, Hui Lu, Yingying Chen, Xu Zhou, Jing Sun, Yuan Yang, and Yan Wang
Hydrol. Earth Syst. Sci., 26, 4587–4601, https://doi.org/10.5194/hess-26-4587-2022, https://doi.org/10.5194/hess-26-4587-2022, 2022
Short summary
Short summary
Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
Short summary
Short summary
High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
Ivan Vorobevskii, Thi Thanh Luong, Rico Kronenberg, Thomas Grünwald, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 26, 3177–3239, https://doi.org/10.5194/hess-26-3177-2022, https://doi.org/10.5194/hess-26-3177-2022, 2022
Short summary
Short summary
In the study we analysed the uncertainties of the meteorological data and model parameterization for evaporation modelling. We have taken a physically based lumped BROOK90 model and applied it in three different frameworks using global, regional and local datasets. Validating the simulations with eddy-covariance data from five stations in Germany, we found that the accuracy model parameterization plays a bigger role than the quality of the meteorological forcing.
Thomas Lees, Steven Reece, Frederik Kratzert, Daniel Klotz, Martin Gauch, Jens De Bruijn, Reetik Kumar Sahu, Peter Greve, Louise Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 26, 3079–3101, https://doi.org/10.5194/hess-26-3079-2022, https://doi.org/10.5194/hess-26-3079-2022, 2022
Short summary
Short summary
Despite the accuracy of deep learning rainfall-runoff models, we are currently uncertain of what these models have learned. In this study we explore the internals of one deep learning architecture and demonstrate that the model learns about intermediate hydrological stores of soil moisture and snow water, despite never having seen data about these processes during training. Therefore, we find evidence that the deep learning approach learns a physically realistic mapping from inputs to outputs.
Huajin Lei, Hongyu Zhao, and Tianqi Ao
Hydrol. Earth Syst. Sci., 26, 2969–2995, https://doi.org/10.5194/hess-26-2969-2022, https://doi.org/10.5194/hess-26-2969-2022, 2022
Short summary
Short summary
How to combine multi-source precipitation data effectively is one of the hot topics in hydrometeorological research. This study presents a two-step merging strategy based on machine learning for multi-source precipitation merging over China. The results demonstrate that the proposed method effectively distinguishes the occurrence of precipitation events and reduces the error in precipitation estimation. This method is robust and may be successfully applied to other areas even with scarce data.
Alexane Lovat, Béatrice Vincendon, and Véronique Ducrocq
Hydrol. Earth Syst. Sci., 26, 2697–2714, https://doi.org/10.5194/hess-26-2697-2022, https://doi.org/10.5194/hess-26-2697-2022, 2022
Short summary
Short summary
The hydrometeorological skills of two new nowcasting systems for forecasting Mediterranean intense rainfall events and floods are investigated. The results reveal that up to 75 or 90 min of forecast the performance of the nowcasting system blending numerical weather prediction and extrapolation of radar estimation is higher than the numerical weather model. For lead times up to 3 h the skills are equivalent in general. Using these nowcasting systems for flash flood forecasting is also promising.
Alexandre Tuel, Bettina Schaefli, Jakob Zscheischler, and Olivia Martius
Hydrol. Earth Syst. Sci., 26, 2649–2669, https://doi.org/10.5194/hess-26-2649-2022, https://doi.org/10.5194/hess-26-2649-2022, 2022
Short summary
Short summary
River discharge is strongly influenced by the temporal structure of precipitation. Here, we show how extreme precipitation events that occur a few days or weeks after a previous event have a larger effect on river discharge than events occurring in isolation. Windows of 2 weeks or less between events have the most impact. Similarly, periods of persistent high discharge tend to be associated with the occurrence of several extreme precipitation events in close succession.
Hanieh Seyedhashemi, Jean-Philippe Vidal, Jacob S. Diamond, Dominique Thiéry, Céline Monteil, Frédéric Hendrickx, Anthony Maire, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 2583–2603, https://doi.org/10.5194/hess-26-2583-2022, https://doi.org/10.5194/hess-26-2583-2022, 2022
Short summary
Short summary
Stream temperature appears to be increasing globally, but its rate remains poorly constrained due to a paucity of long-term data. Using a thermal model, this study provides a large-scale understanding of the evolution of stream temperature over a long period (1963–2019). This research highlights that air temperature and streamflow can exert joint influence on stream temperature trends, and riparian shading in small mountainous streams may mitigate warming in stream temperatures.
Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
Short summary
Short summary
To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
Yubo Liu, Monica Garcia, Chi Zhang, and Qiuhong Tang
Hydrol. Earth Syst. Sci., 26, 1925–1936, https://doi.org/10.5194/hess-26-1925-2022, https://doi.org/10.5194/hess-26-1925-2022, 2022
Short summary
Short summary
Our findings indicate that the reduction in contribution to the Iberian Peninsula (IP) summer precipitation is mainly concentrated in the IP and its neighboring grids. Compared with 1980–1997, both local recycling and external moisture were reduced during 1998–2019. The reduction in local recycling in the IP closely links to the disappearance of the wet years and the decreasing contribution in the dry years.
Nejc Bezak, Pasquale Borrelli, and Panos Panagos
Hydrol. Earth Syst. Sci., 26, 1907–1924, https://doi.org/10.5194/hess-26-1907-2022, https://doi.org/10.5194/hess-26-1907-2022, 2022
Short summary
Short summary
Rainfall erosivity is one of the main factors in soil erosion. A satellite-based global map of rainfall erosivity was constructed using data with a 30 min time interval. It was shown that the satellite-based precipitation products are an interesting option for estimating rainfall erosivity, especially in regions with limited ground data. However, ground-based high-frequency precipitation measurements are (still) essential for accurate estimates of rainfall erosivity.
Xueli Yang, Zhi-Hua Wang, and Chenghao Wang
Hydrol. Earth Syst. Sci., 26, 1845–1856, https://doi.org/10.5194/hess-26-1845-2022, https://doi.org/10.5194/hess-26-1845-2022, 2022
Short summary
Short summary
In this study, we investigated potentially catastrophic transitions in hydrological processes by identifying the early-warning signals which manifest as a
critical slowing downin complex dynamic systems. We then analyzed the precipitation network of cities in the contiguous United States and found that key network parameters, such as the nodal density and the clustering coefficient, exhibit similar dynamic behaviour, which can serve as novel early-warning signals for the hydrological system.
Zhuoyi Tu, Yuting Yang, and Michael L. Roderick
Hydrol. Earth Syst. Sci., 26, 1745–1754, https://doi.org/10.5194/hess-26-1745-2022, https://doi.org/10.5194/hess-26-1745-2022, 2022
Short summary
Short summary
Here we test a maximum evaporation theory that acknowledges the interdependence between radiation, surface temperature, and evaporation over saturated land. We show that the maximum evaporation approach recovers observed evaporation and surface temperature under non-water-limited conditions across a broad range of bio-climates. The implication is that the maximum evaporation concept can be used to predict potential evaporation that has long been a major difficulty for the hydrological community.
Paola Mazzoglio, Ilaria Butera, Massimiliano Alvioli, and Pierluigi Claps
Hydrol. Earth Syst. Sci., 26, 1659–1672, https://doi.org/10.5194/hess-26-1659-2022, https://doi.org/10.5194/hess-26-1659-2022, 2022
Short summary
Short summary
We have analyzed the spatial dependence of rainfall extremes upon elevation and morphology in Italy. Regression analyses show that previous rainfall–elevation relations at national scale can be substantially improved with new data, both using topography attributes and constraining the analysis within areas stemming from geomorphological zonation. Short-duration mean rainfall depths can then be estimated, all over Italy, using different parameters in each area of the geomorphological subdivision.
Mina Faghih, François Brissette, and Parham Sabeti
Hydrol. Earth Syst. Sci., 26, 1545–1563, https://doi.org/10.5194/hess-26-1545-2022, https://doi.org/10.5194/hess-26-1545-2022, 2022
Short summary
Short summary
The diurnal cycles of precipitation and temperature generated by climate models are biased. This work investigates whether or not impact modellers should correct the diurnal cycle biases prior to conducting hydrological impact studies at the sub-daily scale. The results show that more accurate streamflows are obtained when the diurnal cycles biases are corrected. This is noticeable for smaller catchments, which have a quicker reaction time to changes in precipitation and temperature.
Edwin P. Maurer, Iris T. Stewart, Kenneth Joseph, and Hugo G. Hidalgo
Hydrol. Earth Syst. Sci., 26, 1425–1437, https://doi.org/10.5194/hess-26-1425-2022, https://doi.org/10.5194/hess-26-1425-2022, 2022
Short summary
Short summary
The mid-summer drought (MSD) is common in Mesoamerica. It is a short (weeks-long) period of reduced rainfall near the middle of the rainy season. When it occurs, how long it lasts, and how dry it is all have important implications for smallholder farmers. Studies of changes in MSD characteristics rely on defining characteristics of an MSD. Different definitions affect whether an area would be considered to experience an MSD as well as the changes that have happened in the last 40 years.
Qichun Yang, Quan J. Wang, Andrew W. Western, Wenyan Wu, Yawen Shao, and Kirsti Hakala
Hydrol. Earth Syst. Sci., 26, 941–954, https://doi.org/10.5194/hess-26-941-2022, https://doi.org/10.5194/hess-26-941-2022, 2022
Short summary
Short summary
Forecasts of evaporative water loss in the future are highly valuable for water resource management. These forecasts are often produced using the outputs of climate models. We developed an innovative method to correct errors in these forecasts, particularly the errors caused by deficiencies of climate models in modeling the changing climate. We apply this method to seasonal forecasts of evaporative water loss across Australia and achieve significant improvements in the forecast quality.
Brahima Koné, Arona Diedhiou, Adama Diawara, Sandrine Anquetin, N'datchoh Evelyne Touré, Adama Bamba, and Arsene Toka Kobea
Hydrol. Earth Syst. Sci., 26, 711–730, https://doi.org/10.5194/hess-26-711-2022, https://doi.org/10.5194/hess-26-711-2022, 2022
Short summary
Short summary
The impact of initial soil moisture anomalies can persist for up to 3–4 months and is greater on temperature than on precipitation over West Africa. The strongest homogeneous impact on temperature is located over the Central Sahel, with a peak change of −1.5 and 0.5 °C in the wet and dry experiments, respectively. The strongest impact on precipitation in the wet and dry experiments is found over the West and Central Sahel, with a peak change of about 40 % and −8 %, respectively.
Brahima Koné, Arona Diedhiou, Adama Diawara, Sandrine Anquetin, N'datchoh Evelyne Touré, Adama Bamba, and Arsene Toka Kobea
Hydrol. Earth Syst. Sci., 26, 731–754, https://doi.org/10.5194/hess-26-731-2022, https://doi.org/10.5194/hess-26-731-2022, 2022
Short summary
Short summary
The impact of initial soil moisture is more significant on temperature extremes than on precipitation extremes. A stronger impact is found on maximum temperature than on minimum temperature. The impact on extreme precipitation indices is homogeneous, especially over the Central Sahel, and dry (wet) experiments tend to decrease (increase) the number of precipitation extreme events but not their intensity.
Josias Láng-Ritter, Marc Berenguer, Francesco Dottori, Milan Kalas, and Daniel Sempere-Torres
Hydrol. Earth Syst. Sci., 26, 689–709, https://doi.org/10.5194/hess-26-689-2022, https://doi.org/10.5194/hess-26-689-2022, 2022
Short summary
Short summary
During flood events, emergency managers such as civil protection authorities rely on flood forecasts to make informed decisions. In the current practice, they monitor several separate forecasts, each one of them covering a different type of flooding. This can be time-consuming and confusing, ultimately compromising the effectiveness of the emergency response. This work illustrates how the automatic combination of flood type-specific impact forecasts can improve decision support systems.
Junjiang Liu, Xing Yuan, Junhan Zeng, Yang Jiao, Yong Li, Lihua Zhong, and Ling Yao
Hydrol. Earth Syst. Sci., 26, 265–278, https://doi.org/10.5194/hess-26-265-2022, https://doi.org/10.5194/hess-26-265-2022, 2022
Short summary
Short summary
Hourly streamflow ensemble forecasts with the CSSPv2 land surface model and ECMWF meteorological forecasts reduce both the probabilistic and deterministic forecast error compared with the ensemble streamflow prediction approach during the first week. The deterministic forecast error can be further reduced in the first 72 h when combined with the long short-term memory (LSTM) deep learning method. The forecast skill for LSTM using only historical observations drops sharply after the first 24 h.
Michael Peichl, Stephan Thober, Luis Samaniego, Bernd Hansjürgens, and Andreas Marx
Hydrol. Earth Syst. Sci., 25, 6523–6545, https://doi.org/10.5194/hess-25-6523-2021, https://doi.org/10.5194/hess-25-6523-2021, 2021
Short summary
Short summary
Using a statistical model that can also take complex systems into account, the most important factors affecting wheat yield in Germany are determined. Different spatial damage potentials are taken into account. In many parts of Germany, yield losses are caused by too much soil water in spring. Negative heat effects as well as damaging soil drought are identified especially for north-eastern Germany. The model is able to explain years with exceptionally high yields (2014) and losses (2003, 2018).
Sara Cloux, Daniel Garaboa-Paz, Damián Insua-Costa, Gonzalo Miguez-Macho, and Vicente Pérez-Muñuzuri
Hydrol. Earth Syst. Sci., 25, 6465–6477, https://doi.org/10.5194/hess-25-6465-2021, https://doi.org/10.5194/hess-25-6465-2021, 2021
Short summary
Short summary
We examine the performance of a widely used Lagrangian method for moisture tracking by comparing it with a highly accurate Eulerian tool, both operating on the same WRF atmospheric model fields. Although the Lagrangian approach is very useful for a qualitative analysis of moisture sources, it has important limitations in quantifying the contribution of individual sources to precipitation. These drawbacks should be considered by other authors in the future so as to not draw erroneous conclusions.
Cited articles
Arsenault, R., Brissette, F., Chen, J., Guo, Q., and Dallaire, G.: NAC 2 H: The North American Climate Change and Hydroclimatology Data Set, Water Resour. Res., 56, e2020WR027097, https://doi.org/10.1029/2020WR027097, 2020a.
Arsenault, R., Brissette, F., Martel, J.-L., Troin, M., Lévesque, G., Davidson-Chaput, J., Gonzalez, M. C., Ameli, A., and Poulin, A.: A comprehensive, multisource database for hydrometeorological modeling of 14,425 North American watersheds, Sci. Data, 7, 243, https://doi.org/10.1038/s41597-020-00583-2, 2020b.
Arsenault, R., Brissette, F., Martel, J.-L., Troin, M., Lévesque, G., Davidson-Chaput, J., Castañeda Gonzalez, M., Ameli, A., and Poulin, A.: HYSETS – A 14425 watershed Hydrometeorological Sandbox over North America, OSF [data set], https://doi.org/10.17605/OSF.IO/RPC3W, 2022.
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A.-L., Dufresne, J.-L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D. T., Myhre, G., Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.: Bounding Global Aerosol Radiative Forcing of Climate Change, Re. Geophys., 58, e2019RG000660, https://doi.org/10.1029/2019RG000660, 2020.
Cannon, A. J.: Multivariate quantile mapping bias correction: An N-dimensional probability density function transform for climate model simulations of multiple variables, Clim. Dynam., 50, 31–49, https://doi.org/10.1007/s00382-017-3580-6, 2018.
Cannon, A. J., Piani, C., and Sippel, S.: Bias correction of climate model output for impact models, in: Climate Extremes and Their Implications for Impact and Risk Assessment, Elsevier, 77–104, https://doi.org/10.1016/B978-0-12-814895-2.00005-7, 2020.
Chen, J., Brissette, F. P., Poulin, A., and Leconte, R.: Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed, Water Resour. Res., 47, W12509, https://doi.org/10.1029/2011WR010602, 2011.
Chen, J., Brissette, F. P., and Lucas-Picher, P.: Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology, Clim. Dynam., 47, 3359–3372, https://doi.org/10.1007/s00382-016-3030-x, 2016.
Chen, J., Brissette, F. P., Lucas-Picher, P., and Caya, D.: Impacts of weighting climate models for hydro-meteorological climate change studies, J. Hydrol., 549, 534–546, https://doi.org/10.1016/j.jhydrol.2017.04.025, 2017.
Chen, J., Li, C., Brissette, F. P., Chen, H., Wang, M., and Essou, G. R.: Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling, J. Hydrol., 560, 326–341, https://doi.org/10.1016/j.jhydrol.2018.03.040, 2018.
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Gao, X., Gutowski Jr., W. J., Johns, T., Krinner, G., Shongwe, M., Weaver, A. J., Wehner, M., Allen, M. R., Andrews, T., Beyerle, U., Bitz, C. M., Bony, S., Booth, B. B. B., Brooks, H. E., Brovkin, V., Browne, O., Brutel-Vuilmet, C., Cane, M., Chadwick, R., Cook, E., Cook, K. H., Eby, M., Fasullo, J., Forest, C. E., Forster, P., Good, P., Goosse, H., Gregory, J. M., Hegerl, G. C., Hezel, P. J., Hodges, K. I., Holland, M. M., Huber, M., Joshi, M., Kharin, V., Kushnir, Y., Lawrence, D. M., Lee, R. W., Liddicoat, S., Lucas, C., Lucht, W., Marotzke, J., Massonnet, F., Matthews, H. D., Meinshausen, M., Morice, C., Otto, A., Patricola, C. M., Philippon, G., Rahmstorf, S., Riley, W. J., Saenko, O., Seager, R., Sedláček, J., Shaffrey, L. C., Shindell, D., Sillmann, J., Stevens, B., Stott, P. A., Webb, R., Zappa, G., Zickfeld, K., Joussaume, S., Mokssit, A., Taylor, K., and Tett, S.: Long-term Climate Change: Projections, Commitments and Irreversibility, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK and New York, NY, USA, 1029–1136, https://www.ipcc.ch/report/ar5/wg1 (last access: 12 November 2022), 2013.
Cox, P. M., Huntingford, C., and Williamson, M. S.: Emergent constraint on equilibrium climate sensitivity from global temperature variability, Nature, 553, 319–322, https://doi.org/10.1038/nature25450, 2018.
dos Santos, F. M., de Oliveira, R. P., and Mauad, F. F.: Lumped versus distributed hydrological modeling of the Jacaré-Guaçu Basin, Brazil, J. Environ. Eng., 144, 04018056, https://doi.org/10.1061/(ASCE)EE.1943-7870.0001397, 2018.
ESGF – Earth System Grid Federation: CMIP6 GCM data, https://esgf-node.llnl.gov/search/cmip6/ (last access: 18 July 2022), 2022.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Eyring, V., Cox, P. M., Flato, G. M., Gleckler, P. J., Abramowitz, G., Caldwell, P., Collins, W. D., Gier, B. K., Hall, A. D., Hoffman, F. M., Hurtt, G. C., Jahn, A., Jones, C. D., Klein, S. A., Krasting, J. P., Kwiatkowski, L., Lorenz, R., Maloney, E., Meehl, G. A., Pendergrass, A. G., Pincus, R., Ruane, A. C., Russell, J. L., Sanderson, B. M., Santer, B. D., Sherwood, S. C., Simpson, I. R., Stouffer, R. J., and Williamson, M. S.: Taking climate model evaluation to the next level, Nat. Clim. Change, 9, 102–110, https://doi.org/10.1038/s41558-018-0355-y, 2019.
Flynn, C. M. and Mauritsen, T.: On the climate sensitivity and historical warming evolution in recent coupled model ensembles, Atmos. Chem. Phys., 20, 7829–7842, https://doi.org/10.5194/acp-20-7829-2020, 2020.
Forster, P. M., Andrews, T., Good, P., Gregory, J. M., Jackson, L. S., and Zelinka, M.: Evaluating adjusted forcing and model spread for historical and future scenarios in the CMIP5 generation of climate models, J. Geophys. Res.-Atmos., 118, 1139–1150, https://doi.org/10.1002/jgrd.50174, 2013.
Giuntoli, I., Villarini, G., Prudhomme, C., and Hannah, D. M.: Uncertainties in projected runoff over the conterminous United States, Climatic Change, 150, 149–162, https://doi.org/10.1007/s10584-018-2280-5, 2018.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Hausfather, Z. and Peters, G. P.: Emissions – the `business as usual' story is misleading, Nature, 577, 618–620, https://doi.org/10.1038/d41586-020-00177-3, 2020.
Hausfather, Z., Marvel, K., Schmidt, G. A., Nielsen-Gammon, J. W., and Zelinka, M.: Climate simulations: recognize the `hot model' problem, Nature, 605, 26–29, https://doi.org/10.1038/d41586-022-01192-2, 2022.
Hirabayashi, Y., Tanoue, M., Sasaki, O., Zhou, X., and Yamazaki, D.: Global exposure to flooding from the new CMIP6 climate model projections, Sci. Rep., 11, 3740, https://doi.org/10.1038/s41598-021-83279-w, 2021.
IPCC: Climate Change 2014: Synthesis Report, in: Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC, Geneva, Switzerland, https://www.ipcc.ch/report/ar5/syr (last access: 18 October 2022), 2014.
IPCC: Intergovernmental Panel on Climate Change, Technical Summary, in: Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, 35–144, https://doi.org/10.1017/9781009157896.002, 2023.
Karlsson, I. B., Sonnenborg, T. O., Refsgaard, J. C., Trolle, D., Børgesen, C. D., Olesen, J. E., Jeppesen, E., and Jensen, K. H.: Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change, J. Hydrol., 535, 301–317, https://doi.org/10.1016/j.jhydrol.2016.01.069, 2016.
Knoben, W. J. M., Freer, J. E., and Woods, R. A.: Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, 2019.
Knutti, R.: The end of model democracy?: An editorial comment, Climatic Change, 102, 395–404, https://doi.org/10.1007/s10584-010-9800-2, 2010.
Knutti, R., Rugenstein, M. A. A., and Hegerl, G. C.: Beyond equilibrium climate sensitivity, Nat. Geosci., 10, 727–736, https://doi.org/10.1038/ngeo3017, 2017.
Kreienkamp, F., Lorenz, P., and Geiger, T.: Statistically Downscaled CMIP6 Projections Show Stronger Warming for Germany, Atmosphere, 11, 1245, https://doi.org/10.3390/atmos11111245, 2020.
Krysanova, V., Donnelly, C., Gelfan, A., Gerten, D., Arheimer, B., Hattermann, F., and Kundzewicz, Z. W.: How the performance of hydrological models relates to credibility of projections under climate change, Hydrolog. Sci. J., 63, 696–720, https://doi.org/10.1080/02626667.2018.1446214, 2018.
Liang, Y., Gillett, N. P., and Monahan, A. H.: Climate Model Projections of 21st Century Global Warming Constrained Using the Observed Warming Trend, Geophys. Res. Lett., 47, e2019GL086757, https://doi.org/10.1029/2019GL086757, 2020.
Maraun, D.: Bias correcting climate change simulations – a critical review, Curr. Clim. Change Rep., 2, 211–220, https://doi.org/10.1007/s40641-016-0050-x, 2016.
Martel, J.-L., Brissette, F., Troin, M., Arsenault, R., Chen, J., Su, T., and Lucas-Picher, P.: CMIP5 and CMIP6 Model Projection Comparison for Hydrological Impacts Over North America, Geophys. Res. Lett., 49, e2022GL098364, https://doi.org/10.1029/2022GL098364, 2022.
Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B., Mitchell, J. F. B., Stouffer, R. J., and Taylor, K. E.: THE WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research, B. Am. Meteorol. Soc., 88, 1383–1394, https://doi.org/10.1175/BAMS-88-9-1383, 2007.
Miara, A., Macknick, J. E., Vörösmarty, C. J., Tidwell, V. C., Newmark, R., and Fekete, B.: Climate and water resource change impacts and adaptation potential for US power supply, Nat. Clim. Change, 7, 793–798, https://doi.org/10.1038/nclimate3417, 2017.
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.
Nijsse, F. J. M. M., Cox, P. M., and Williamson, M. S.: Emergent constraints on transient climate response (TCR) and equilibrium climate sensitivity (ECS) from historical warming in CMIP5 and CMIP6 models, Earth Syst. Dynam., 11, 737–750, https://doi.org/10.5194/esd-11-737-2020, 2020.
Palmer, T. E., McSweeney, C. F., Booth, B. B. B., Priestley, M. D. K., Davini, P., Brunner, L., Borchert, L., and Menary, M. B.: Performance-based sub-selection of CMIP6 models for impact assessments in Europe, Earth Syst. Dynam., 14, 457–483, https://doi.org/10.5194/esd-14-457-2023, 2023.
Perrin, C., Michel, C., and Andréassian, V.: Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275–289, https://doi.org/10.1016/S0022-1694(03)00225-7, 2003.
Prajapati, S., Sabokruhie, P., Brinkmann, M., and Lindenschmidt, K.-E.: Modelling Transport and Fate of Copper and Nickel across the South Saskatchewan River Using WASP–TOXI, Water, 15, 2, https://doi.org/10.3390/w15020265, 2023.
Reed, S., Koren, V., Smith, M., Zhang, Z., Moreda, F., Seo, D.-J., and Participants, D.: Overall distributed model intercomparison project results, J. Hydrol., 298, 27–60, https://doi.org/10.1016/j.jhydrol.2004.03.031, 2004.
Reichler, T. and Kim, J.: How Well Do Coupled Models Simulate Today's Climate?, B. Am. Meteorol. Soc., 89, 303–312, https://doi.org/10.1175/BAMS-89-3-303, 2008.
Ribes, A., Qasmi, S., and Gillett, N. P.: Making climate projections conditional on historical observations, Sci. Adv., 7, eabc0671, https://doi.org/10.1126/sciadv.abc0671, 2021.
Riboust, P., Thirel, G., Le Moine, N., and Ribstein, P.: Revisiting a simple degree-day model for integrating satellite data: Implementation of SWE-SCA hysteresis, J. Hydrol. Hydromech., 67, 70–81, https://doi.org/10.2478/johh-2018-0004, 2019.
Ross, A. C. and Najjar, R. G.: Evaluation of methods for selecting climate models to simulate future hydrological change, Climatic Change, 157, 407–428, https://doi.org/10.1007/s10584-019-02512-8, 2019.
Sabokruhie, P., Akomeah, E., Rosner, T., and Lindenschmidt, K.-E.: Proof-of-concept of a quasi-2d water-quality modelling approach to simulate transverse mixing in rivers, Water, 13, 307, https://doi.org/10.3390/w13213071, 2021.
Sherwood, S. C., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M., Hargreaves, J. C., Hegerl, G., Klein, S. A., Marvel, K. D., Rohling, E. J., Watanabe, M., Andrews, T., Braconnot, P., Bretherton, C. S., Foster, G. L., Hausfather, Z., von der Heydt, A. S., Knutti, R., Mauritsen, T., Norris, J. R., Proistosescu, C., Rugenstein, M., Schmidt, G. A., Tokarska, K. B., and Zelinka, M. D.: An Assessment of Earth's Climate Sensitivity Using Multiple Lines of Evidence, Rev. Geophys., 58, e2019RG000678, https://doi.org/10.1029/2019RG000678, 2020.
Shiogama, H., Ishizaki, N. N., Hanasaki, N., Takahashi, K., Emori, S., Ito, R., Nakaegawa, T., Takayabu, I., Hijioka, Y., Takayabu, Y. N., and Shibuya, R.: Selecting CMIP6-Based Future Climate Scenarios for Impact and Adaptation Studies, SOLA, 17, 57–62, https://doi.org/10.2151/sola.2021-009, 2021.
Shiogama, H., Takakura, J., and Takahashi, K.: Uncertainty constraints on economic impact assessments of climate change simulated by an impact emulator, Environ. Res. Lett., 17, 124028, https://doi.org/10.1088/1748-9326/aca68d, 2022a.
Shiogama, H., Watanabe, M., Kim, H., and Hirota, N.: Emergent constraints on future precipitation changes, Nature, 602, 612–616, https://doi.org/10.1038/s41586-021-04310-8, 2022b.
Smith, C. J., Harris, G. R., Palmer, M. D., Bellouin, N., Collins, W., Myhre, G., Schulz, M., Golaz, J.-C., Ringer, M., Storelvmo, T., and Forster, P. M.: Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity, J. Geophys. Res.-Atmos., 126, e2020JD033622, https://doi.org/10.1029/2020JD033622, 2021.
Su, T., Chen, J., Cannon, A. J., Xie, P., and Guo, Q.: Multi-site bias correction of climate model outputs for hydro-meteorological impact studies: An application over a watershed in China, Hydrol. Process., 34, 2575–2598, https://doi.org/10.1002/hyp.13750, 2020.
Tabari, H.: Climate change impact on flood and extreme precipitation increases with water availability, Sci. Rep., 10, 13768, https://doi.org/10.1038/s41598-020-70816-2, 2020.
Tarek, M., Brissette, F. P., and Arsenault, R.: Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America, Hydrol. Earth Syst. Sci., 24, 2527–2544, https://doi.org/10.5194/hess-24-2527-2020, 2020.
Tokarska, K. B., Stolpe, M. B., Sippel, S., Fischer, E. M., Smith, C. J., Lehner, F., and Knutti, R.: Past warming trend constrains future warming in CMIP6 models, Sci. Adv., 6, eaaz9549, https://doi.org/10.1126/sciadv.aaz9549, 2020.
Troin, M., Martel, J. L., Arsenault, R., and Brissette, F.: Large-sample study of uncertainty of hydrological model components over North America, J. Hydrol., 609, 127766, https://doi.org/10.1016/j.jhydrol.2022.127766, 2022.
Trudel, M., Doucet-Généreux, P. L., and Leconte, R.: Assessing river low-flow uncertainties related to hydrological model calibration and structure under climate change conditions, Climate, 5, 19, https://doi.org/10.3390/cli5010019, 2017.
Valéry, A., Andréassian, V., and Perrin, C.: `As simple as possible but not simpler': What is useful in a temperature-based snow-accounting routine? Part 2 – Sensitivity analysis of the Cemaneige snow accounting routine on 380 catchments, J. Hydrol., 517, 1176–1187, https://doi.org/10.1016/j.jhydrol.2014.04.058, 2014.
Wang, H.-M., Chen, J., Xu, C.-Y., Chen, H., Guo, S., Xie, P., and Li, X.: Does the weighting of climate simulations result in a better quantification of hydrological impacts?, Hydrol. Earth Syst. Sci., 23, 4033–4050, https://doi.org/10.5194/hess-23-4033-2019, 2019.
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.
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M., Ceppi, P., Klein, S. A., and Taylor, K. E.: Causes of Higher Climate Sensitivity in CMIP6 Models, Geophys. Res. Lett., 47, e2019GL085782, https://doi.org/10.1029/2019GL085782, 2020.
Zhang, Y., Liu, H., Qi, J., Feng, P., Zhang, X., Liu, D. L., Marek, G. W., Srinivasan, R., and Chen, Y.: Assessing impacts of global climate change on water and food security in the black soil region of Northeast China using an improved SWAT-CO2 model, Sci. Total Environ., 857, 159482, https://doi.org/10.1016/j.scitotenv.2022.159482, 2023.
Short summary
Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Climate models are central to climate change impact studies. Some models project a future deemed...