Articles | Volume 22, issue 4
Hydrol. Earth Syst. Sci., 22, 2163–2185, 2018
https://doi.org/10.5194/hess-22-2163-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 22, 2163–2185, 2018
https://doi.org/10.5194/hess-22-2163-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
09 Apr 2018
Research article
| 09 Apr 2018
Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile
Stefan Liersch et al.
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Erika Médus, Emma D. Thomassen, Danijel Belušić, Petter Lind, Peter Berg, Jens H. Christensen, Ole B. Christensen, Andreas Dobler, Erik Kjellström, Jonas Olsson, and Wei Yang
Nat. Hazards Earth Syst. Sci., 22, 693–711, https://doi.org/10.5194/nhess-22-693-2022, https://doi.org/10.5194/nhess-22-693-2022, 2022
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We evaluate the skill of a regional climate model, HARMONIE-Climate, to capture the present-day characteristics of heavy precipitation in the Nordic region and investigate the added value provided by a convection-permitting model version. The higher model resolution improves the representation of hourly heavy- and extreme-precipitation events and their diurnal cycle. The results indicate the benefits of convection-permitting models for constructing climate change projections over the region.
Klaus Wyser, Torben Koenigk, Uwe Fladrich, Ramon Fuentes-Franco, Mehdi Pasha Karami, and Tim Kruschke
Geosci. Model Dev., 14, 4781–4796, https://doi.org/10.5194/gmd-14-4781-2021, https://doi.org/10.5194/gmd-14-4781-2021, 2021
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This paper describes the large ensemble done by SMHI with the EC-Earth3 climate model. The ensemble comprises 50 realizations for each of the historical experiments after 1970 and four different future projections for CMIP6. We describe the creation of the initial states for the ensemble and the reduced set of output variables. A first look at the results illustrates the changes in the climate during this century and puts them in relation to the uncertainty from the model's internal variability.
Alexander Pasternack, Jens Grieger, Henning W. Rust, and Uwe Ulbrich
Geosci. Model Dev., 14, 4335–4355, https://doi.org/10.5194/gmd-14-4335-2021, https://doi.org/10.5194/gmd-14-4335-2021, 2021
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Decadal climate ensemble forecasts are increasingly being used to guide adaptation measures. To ensure the applicability of these probabilistic predictions, inherent systematic errors of the prediction system must be adjusted. Since it is not clear which statistical model is optimal for this purpose, we propose a recalibration strategy with a systematic model selection based on non-homogeneous boosting for identifying the most relevant features for both ensemble mean and ensemble spread.
Tian Tian, Shuting Yang, Mehdi Pasha Karami, François Massonnet, Tim Kruschke, and Torben Koenigk
Geosci. Model Dev., 14, 4283–4305, https://doi.org/10.5194/gmd-14-4283-2021, https://doi.org/10.5194/gmd-14-4283-2021, 2021
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Three decadal prediction experiments with EC-Earth3 are performed to investigate the impact of ocean, sea ice concentration and thickness initialization, respectively. We find that the persistence of perennial thick ice in the central Arctic can affect the sea ice predictability in its adjacent waters via advection process or wind, despite those regions being seasonally ice free during two recent decades. This has implications for the coming decades as the thinning of Arctic sea ice continues.
Annika Drews, Wenjuan Huo, Katja Matthes, Kunihiko Kodera, and Tim Kruschke
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-241, https://doi.org/10.5194/acp-2021-241, 2021
Revised manuscript accepted for ACP
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Solar irradiance varies with a period of approximately 11 years. Using a unique large chemistry climate model dataset, we investigate the solar surface signal in the North Atlantic and European region, and find that changes over time, depending on the strength of the solar cycle. For the first time, we estimate the potential predictability associated with including realistic solar forcing in a model. These results may improve seasonal to decadal predictions of European climate.
Sabine Haase, Jaika Fricke, Tim Kruschke, Sebastian Wahl, and Katja Matthes
Atmos. Chem. Phys., 20, 14043–14061, https://doi.org/10.5194/acp-20-14043-2020, https://doi.org/10.5194/acp-20-14043-2020, 2020
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Ozone depletion over Antarctica was shown to influence the tropospheric jet in the Southern Hemisphere. We investigate the atmospheric response to ozone depletion comparing climate model ensembles with interactive and prescribed ozone fields. We show that allowing feedbacks between ozone chemistry and model physics as well as including asymmetries in ozone leads to a strengthened ozone depletion signature in the stratosphere but does not significantly affect the tropospheric jet position.
Markus Kunze, Tim Kruschke, Ulrike Langematz, Miriam Sinnhuber, Thomas Reddmann, and Katja Matthes
Atmos. Chem. Phys., 20, 6991–7019, https://doi.org/10.5194/acp-20-6991-2020, https://doi.org/10.5194/acp-20-6991-2020, 2020
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Modelling the response of the atmosphere and its constituents to 11-year solar variations is subject to a certain uncertainty arising from the solar irradiance data set used in the chemistry–climate model (CCM) and the applied CCM itself.
This study reveals significant influences from both sources on the variations in the solar response in the stratosphere and mesosphere.
However, there are also regions where the random, unexplained part of the variations in the solar response is largest.
Danijel Belušić, Hylke de Vries, Andreas Dobler, Oskar Landgren, Petter Lind, David Lindstedt, Rasmus A. Pedersen, Juan Carlos Sánchez-Perrino, Erika Toivonen, Bert van Ulft, Fuxing Wang, Ulf Andrae, Yurii Batrak, Erik Kjellström, Geert Lenderink, Grigory Nikulin, Joni-Pekka Pietikäinen, Ernesto Rodríguez-Camino, Patrick Samuelsson, Erik van Meijgaard, and Minchao Wu
Geosci. Model Dev., 13, 1311–1333, https://doi.org/10.5194/gmd-13-1311-2020, https://doi.org/10.5194/gmd-13-1311-2020, 2020
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A new regional climate modelling system, HCLIM38, is presented and shown to be applicable in different regions ranging from the tropics to the Arctic. The main focus is on climate simulations at horizontal resolutions between 1 and 4 km, the so-called convection-permitting scales, even though the model can also be used at coarser resolutions. The benefits of simulating climate at convection-permitting scales are shown and are particularly evident for climate extremes.
Cristian Lussana, Ole Einar Tveito, Andreas Dobler, and Ketil Tunheim
Earth Syst. Sci. Data, 11, 1531–1551, https://doi.org/10.5194/essd-11-1531-2019, https://doi.org/10.5194/essd-11-1531-2019, 2019
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seNorge_2018 is a collection of observational gridded datasets for daily total precipitation and daily mean, minimum, and maximum temperature for the Norwegian mainland covering the time period from 1957 to the present day. The fields have 1 km of grid spacing. The data are used for applications in climatology, hydrology, and meteorology. seNorge_2018 provides a "gridded truth", especially in data-dense regions. The uncertainty increases with decreasing data density.
Edmund P. Meredith, Henning W. Rust, and Uwe Ulbrich
Hydrol. Earth Syst. Sci., 22, 4183–4200, https://doi.org/10.5194/hess-22-4183-2018, https://doi.org/10.5194/hess-22-4183-2018, 2018
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Kilometre-scale climate-model data are of great benefit to both hydrologists and end users studying extreme precipitation, though often unavailable due to the computational expense associated with such high-resolution simulations. We develop a method which identifies days with enhanced risk of extreme rainfall over a catchment, so that high-resolution simulations can be performed only when such a risk exists, reducing computational expense by over 90 % while still well capturing the extremes.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
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This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Abdelkader Mezghani, Andreas Dobler, Jan Erik Haugen, Rasmus E. Benestad, Kajsa M. Parding, Mikołaj Piniewski, Ignacy Kardel, and Zbigniew W. Kundzewicz
Earth Syst. Sci. Data, 9, 905–925, https://doi.org/10.5194/essd-9-905-2017, https://doi.org/10.5194/essd-9-905-2017, 2017
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Projected changes estimated from an ensemble of nine model simulations showed that annual means of temperature are expected to increase steadily by 1 °C until 2021–2050 and by 2 °C until 2071–2100 assuming the RCP4.5, which is accelerating assuming the RCP8.5 scenario and can reach up to almost 4 °C by 2071–2100. Similarly to temperature, projected changes in regional annual means of precipitation are expected to increase by 6 to 10 % and by 8 to 16 % for the two future horizons and RCPs.
Katja Matthes, Bernd Funke, Monika E. Andersson, Luke Barnard, Jürg Beer, Paul Charbonneau, Mark A. Clilverd, Thierry Dudok de Wit, Margit Haberreiter, Aaron Hendry, Charles H. Jackman, Matthieu Kretzschmar, Tim Kruschke, Markus Kunze, Ulrike Langematz, Daniel R. Marsh, Amanda C. Maycock, Stergios Misios, Craig J. Rodger, Adam A. Scaife, Annika Seppälä, Ming Shangguan, Miriam Sinnhuber, Kleareti Tourpali, Ilya Usoskin, Max van de Kamp, Pekka T. Verronen, and Stefan Versick
Geosci. Model Dev., 10, 2247–2302, https://doi.org/10.5194/gmd-10-2247-2017, https://doi.org/10.5194/gmd-10-2247-2017, 2017
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The solar forcing dataset for climate model experiments performed for the upcoming IPCC report is described. This dataset provides the radiative and particle input of solar variability on a daily basis from 1850 through to 2300. With this dataset a better representation of natural climate variability with respect to the output of the Sun is provided which provides the most sophisticated and comprehensive respresentation of solar variability that has been used in climate model simulations so far.
Tobias Pardowitz, Robert Osinski, Tim Kruschke, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 16, 2391–2402, https://doi.org/10.5194/nhess-16-2391-2016, https://doi.org/10.5194/nhess-16-2391-2016, 2016
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This paper describes an approach to derive probabilistic predictions of local winter storm damage occurrences. Such predictions are subject to large uncertainty due to meteorological forecast uncertainty and uncertainties in modelling weather impacts. The paper aims to quantify these uncertainties and demonstrate that valuable predictions can be made on the district level several days ahead.
Andreas Dobler, Jan Erik Haugen, and Rasmus Emil Benestad
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2016-27, https://doi.org/10.5194/esd-2016-27, 2016
Revised manuscript has not been submitted
Fred Fokko Hattermann, Shaochun Huang, Olaf Burghoff, Peter Hoffmann, and Zbigniew W. Kundzewicz
Nat. Hazards Earth Syst. Sci., 16, 1617–1622, https://doi.org/10.5194/nhess-16-1617-2016, https://doi.org/10.5194/nhess-16-1617-2016, 2016
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We report that a considerable increase in flood-related losses can be expected in Germany in a future warmer climate. The general significance of the study is supported by the fact that the outcome of an ensemble of global climate models (GCMs) and regional climate models (RCMs) was used as a climate driver for a hydrological model considering more than 3000 river basins in Germany.
D. J. Befort, M. Fischer, G. C. Leckebusch, U. Ulbrich, A. Ganske, G. Rosenhagen, and H. Heinrich
Nat. Hazards Earth Syst. Sci., 15, 1437–1447, https://doi.org/10.5194/nhess-15-1437-2015, https://doi.org/10.5194/nhess-15-1437-2015, 2015
T. Vetter, S. Huang, V. Aich, T. Yang, X. Wang, V. Krysanova, and F. Hattermann
Earth Syst. Dynam., 6, 17–43, https://doi.org/10.5194/esd-6-17-2015, https://doi.org/10.5194/esd-6-17-2015, 2015
N. Akhtar, J. Brauch, A. Dobler, K. Béranger, and B. Ahrens
Nat. Hazards Earth Syst. Sci., 14, 2189–2201, https://doi.org/10.5194/nhess-14-2189-2014, https://doi.org/10.5194/nhess-14-2189-2014, 2014
V. Aich, B. Koné, F. F. Hattermann, and E. N. Müller
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-2-5171-2014, https://doi.org/10.5194/nhessd-2-5171-2014, 2014
Revised manuscript not accepted
V. Aich, S. Liersch, T. Vetter, S. Huang, J. Tecklenburg, P. Hoffmann, H. Koch, S. Fournet, V. Krysanova, E. N. Müller, and F. F. Hattermann
Hydrol. Earth Syst. Sci., 18, 1305–1321, https://doi.org/10.5194/hess-18-1305-2014, https://doi.org/10.5194/hess-18-1305-2014, 2014
J. Steppeler, S.-H. Park, and A. Dobler
Geosci. Model Dev., 6, 875–882, https://doi.org/10.5194/gmd-6-875-2013, https://doi.org/10.5194/gmd-6-875-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
The effects of spatial and temporal resolution of gridded meteorological forcing on watershed hydrological responses
Hydrological response of a peri-urban catchment exploiting conventional and unconventional rainfall observations: the case study of Lambro Catchment
Assessing hydrological sensitivity of grassland basins in the Canadian Prairies to climate using a basin classification-based virtual modelling approach
The value of satellite soil moisture and snow cover data for the transfer of hydrological model parameters to ungauged sites
Storylines of UK drought based on the 2010–2012 event
Uncertainty estimation with deep learning for rainfall–runoff modeling
Applying non-parametric Bayesian networks to estimate maximum daily river discharge: potential and challenges
Contrasting changes in hydrological processes of the Volta River basin under global warming
A retrospective on hydrological catchment modelling based on half a century with the HBV model
Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters
Rainfall–runoff relationships at event scale in western Mediterranean ephemeral streams
Combined impacts of uncertainty in precipitation and air temperature on simulated mountain system recharge from an integrated hydrologic model
Simultaneous assimilation of water levels from river gauges and satellite flood maps for near-real-time flood mapping
Remote sensing-aided rainfall–runoff modeling in the tropics of Costa Rica
Drivers of drought-induced shifts in the water balance through a Budyko approach
Regionalization of hydrological model parameters using gradient boosting machine
Aquifer recharge in the Piedmont Alpine zone: historical trends and future scenarios
Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+
How well are we able to close the water budget at the global scale?
Bending of the concentration discharge relationship can inform about in-stream nitrate removal
Quantifying the impacts of land cover change on hydrological responses in the Mahanadi river basin in India
Identification of the contributing area to river discharge during low-flow periods
Simulating sediment discharge at water treatment plants under different land use scenarios using cascade modelling with an expert-based erosion-runoff model and a deep neural network
In-stream Escherichia coli modeling using high-temporal-resolution data with deep learning and process-based models
Can we use precipitation isotope outputs of isotopic general circulation models to improve hydrological modeling in large mountainous catchments on the Tibetan Plateau?
Small-scale topography explains patterns and dynamics of dissolved organic carbon exports from the riparian zone of a temperate, forested catchment
Effects of spatial resolution of terrain models on modelled discharge and soil loss in Oaxaca, Mexico
Benchmarking data-driven rainfall–runoff models in Great Britain: a comparison of long short-term memory (LSTM)-based models with four lumped conceptual models
Numerical daemons of hydrological models are summoned by extreme precipitation
How is Baseflow Index (BFI) impacted by water resource management practices?
Influences of land use changes on the dynamics of water quantity and quality in the German lowland catchment of the Stör
Technical note: RAT – a robustness assessment test for calibrated and uncalibrated hydrological models
Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment
Combining split-sample testing and hidden Markov modelling to assess the robustness of hydrological models
Impact of Spatial Distribution Information of Rainfall in Runoff Simulation Using Deep-Learning Methods
Deep learning rainfall-runoff predictions of extreme events
On constraining a lumped hydrological model with both piezometry and streamflow: results of a large sample evaluation
Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling
Development and evaluation of 0.05° terrestrial water storage estimates using Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and assimilation of GRACE data
Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times
Stream discharge depends more on the temporal distribution of water inputs than on yearly snowfall fractions for a headwater catchment at the rain-snow transition zone
Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective
A new fractal-theory-based criterion for hydrological model calibration
The value of water isotope data on improving process understanding in a glacierized catchment on the Tibetan Plateau
Quantifying pluriannual hydrological memory with Catchment Forgetting Curves
Machine learning deciphers CO2 sequestration and subsurface flowpaths from stream chemistry
Future changes in annual, seasonal and monthly runoff signatures in contrasting Alpine catchments in Austria
Using hydrologic landscape classification and climatic time series to assess hydrologic vulnerability of the western U.S. to climate
Evaluation of random forests for short-term daily streamflow forecasting in rainfall- and snowmelt-driven watersheds
Performance of automated methods for flash flood inundation mapping: a comparison of a digital terrain model (DTM) filling and two hydrodynamic methods
Pin Shuai, Xingyuan Chen, Utkarsh Mital, Ethan T. Coon, and Dipankar Dwivedi
Hydrol. Earth Syst. Sci., 26, 2245–2276, https://doi.org/10.5194/hess-26-2245-2022, https://doi.org/10.5194/hess-26-2245-2022, 2022
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Using an integrated watershed model, we compared simulated watershed hydrologic variables driven by three publicly available gridded meteorological forcings (GMFs) at various spatial and temporal resolutions. Our results demonstrated that spatially distributed variables are sensitive to the spatial resolution of the GMF. The temporal resolution of the GMF impacts the dynamics of watershed responses. The choice of GMF depends on the quantity of interest and its spatial and temporal scales.
Greta Cazzaniga, Carlo De Michele, Michele D'Amico, Cristina Deidda, Antonio Ghezzi, and Roberto Nebuloni
Hydrol. Earth Syst. Sci., 26, 2093–2111, https://doi.org/10.5194/hess-26-2093-2022, https://doi.org/10.5194/hess-26-2093-2022, 2022
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Rainfall estimates are usually obtained from rain gauges, weather radars, or satellites. An alternative is the measurement of the signal loss induced by rainfall on commercial microwave links (CMLs). In this work, we assess the hydrologic response of Lambro Basin when CML-retrieved rainfall is used as model input. CML estimates agree with rain gauge data. CML-driven discharge simulations show performance comparable to that from rain gauges if a CML-based calibration of the model is undertaken.
Christopher Spence, Zhihua He, Kevin R. Shook, Balew A. Mekonnen, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 1801–1819, https://doi.org/10.5194/hess-26-1801-2022, https://doi.org/10.5194/hess-26-1801-2022, 2022
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We determined how snow and flow in small creeks change with temperature and precipitation in the Canadian Prairie, a region where water resources are often under stress. We tried something new. Every watershed in the region was placed in one of seven groups based on their landscape traits. We selected one of these groups and used its traits to build a model of snow and streamflow. It worked well, and by the 2040s there may be 20 %–40 % less snow and 30 % less streamflow than the 1980s.
Rui Tong, Juraj Parajka, Borbála Széles, Isabella Greimeister-Pfeil, Mariette Vreugdenhil, Jürgen Komma, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 1779–1799, https://doi.org/10.5194/hess-26-1779-2022, https://doi.org/10.5194/hess-26-1779-2022, 2022
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The role and impact of using additional data (other than runoff) for the prediction of daily hydrographs in ungauged basins are not well understood. In this study, we assessed the model performance in terms of runoff, soil moisture, and snow cover predictions with the existing regionalization approaches. Results show that the best transfer methods are the similarity and the kriging approaches. The performance of the transfer methods differs between lowland and alpine catchments.
Wilson C. H. Chan, Theodore G. Shepherd, Katie Facer-Childs, Geoff Darch, and Nigel W. Arnell
Hydrol. Earth Syst. Sci., 26, 1755–1777, https://doi.org/10.5194/hess-26-1755-2022, https://doi.org/10.5194/hess-26-1755-2022, 2022
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We select the 2010–2012 UK drought and investigate an alternative unfolding of the drought from changes to its attributes. We created storylines of drier preconditions, alternative seasonal contributions, a third dry winter, and climate change. Storylines of the 2010–2012 drought show alternative situations that could have resulted in worse conditions than observed. Event-based storylines exploring plausible situations are used that may lead to high impacts and help stress test existing systems.
Daniel Klotz, Frederik Kratzert, Martin Gauch, Alden Keefe Sampson, Johannes Brandstetter, Günter Klambauer, Sepp Hochreiter, and Grey Nearing
Hydrol. Earth Syst. Sci., 26, 1673–1693, https://doi.org/10.5194/hess-26-1673-2022, https://doi.org/10.5194/hess-26-1673-2022, 2022
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This contribution evaluates distributional runoff predictions from deep-learning-based approaches. We propose a benchmarking setup and establish four strong baselines. The results show that accurate, precise, and reliable uncertainty estimation can be achieved with deep learning.
Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711, https://doi.org/10.5194/hess-26-1695-2022, https://doi.org/10.5194/hess-26-1695-2022, 2022
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We explore the ability of non-parametric Bayesian networks to reproduce maximum daily discharge in a given month in a catchment when the remaining hydro-meteorological and catchment attributes are known. We show that a saturated network evaluated in an individual catchment can reproduce statistical characteristics of discharge in about ~ 40 % of the cases, while challenges remain when a saturated network considering all the catchments together is evaluated.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022, https://doi.org/10.5194/hess-26-1481-2022, 2022
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Climate change impacts on water resources in the Volta River basin are investigated under various global warming scenarios. Results reveal contrasting changes in future hydrological processes and water availability, depending on greenhouse gas emission scenarios, with implications for floods and drought occurrence over the 21st century. These findings provide insights for the elaboration of regional adaptation and mitigation strategies for climate change.
Jan Seibert and Sten Bergström
Hydrol. Earth Syst. Sci., 26, 1371–1388, https://doi.org/10.5194/hess-26-1371-2022, https://doi.org/10.5194/hess-26-1371-2022, 2022
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Hydrological catchment models are commonly used as the basis for water resource management planning. The HBV model, which is a typical example of such a model, was first applied about 50 years ago in Sweden. We describe and reflect on the model development and applications. The aim is to provide an understanding of the background of model development and a basis for addressing the balance between model complexity and data availability that will continue to face hydrologists in the future.
Laurène J. E. Bouaziz, Emma E. Aalbers, Albrecht H. Weerts, Mark Hegnauer, Hendrik Buiteveld, Rita Lammersen, Jasper Stam, Eric Sprokkereef, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 26, 1295–1318, https://doi.org/10.5194/hess-26-1295-2022, https://doi.org/10.5194/hess-26-1295-2022, 2022
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Assuming stationarity of hydrological systems is no longer appropriate when considering land use and climate change. We tested the sensitivity of hydrological predictions to changes in model parameters that reflect ecosystem adaptation to climate and potential land use change. We estimated a 34 % increase in the root zone storage parameter under +2 K global warming, resulting in up to 15 % less streamflow in autumn, due to 14 % higher summer evaporation, compared to a stationary system.
Roberto Serrano-Notivoli, Alberto Martínez-Salvador, Rafael García-Lorenzo, David Espín-Sánchez, and Carmelo Conesa-García
Hydrol. Earth Syst. Sci., 26, 1243–1260, https://doi.org/10.5194/hess-26-1243-2022, https://doi.org/10.5194/hess-26-1243-2022, 2022
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Ephemeral streams in the western Mediterranean area are driven by the duration, magnitude, and intensity of rainfall events (REs). A detailed statistical analysis showed that the average RE (1.2 d and 1.5 mm) is not enough to generate new flow, which is only guaranteed by events occurring in return periods from 2 to > 50 years. REs explain near to 75 % of new flow, meaning that terrain and lithological characteristics play a fundamental role.
Adam P. Schreiner-McGraw and Hoori Ajami
Hydrol. Earth Syst. Sci., 26, 1145–1164, https://doi.org/10.5194/hess-26-1145-2022, https://doi.org/10.5194/hess-26-1145-2022, 2022
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We assess the impact of uncertainty in measurements of precipitation and air temperature on simulated groundwater processes in a mountainous watershed. We illustrate the role of topography in controlling how uncertainty in the input datasets propagates through the soil and into the groundwater. While the focus of previous investigations has been on the impact of precipitation uncertainty, we show that air temperature uncertainty is equally important in controlling the groundwater recharge.
Antonio Annis, Fernando Nardi, and Fabio Castelli
Hydrol. Earth Syst. Sci., 26, 1019–1041, https://doi.org/10.5194/hess-26-1019-2022, https://doi.org/10.5194/hess-26-1019-2022, 2022
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In this work, we proposed a multi-source data assimilation framework for near-real-time flood mapping. We used a quasi-2D hydraulic model to update model states by injecting both stage gauge observations and satellite-derived flood extents. Results showed improvements in terms of water level prediction and reduction of flood extent uncertainty when assimilating both stage gauges and satellite images with respect to the disjoint assimilation of both observations.
Saúl Arciniega-Esparza, Christian Birkel, Andrés Chavarría-Palma, Berit Arheimer, and José Agustín Breña-Naranjo
Hydrol. Earth Syst. Sci., 26, 975–999, https://doi.org/10.5194/hess-26-975-2022, https://doi.org/10.5194/hess-26-975-2022, 2022
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In the humid tropics, a notoriously data-scarce region, we need to find alternatives in order to reasonably apply hydrological models. Here, we tested remotely sensed rainfall data in order to drive a model for Costa Rica, and we evaluated the simulations against evapotranspiration satellite products. We found that our model was able to reasonably simulate the water balance and streamflow dynamics of over 600 catchments where the satellite data helped to reduce the model uncertainties.
Tessa Maurer, Francesco Avanzi, Steven D. Glaser, and Roger C. Bales
Hydrol. Earth Syst. Sci., 26, 589–607, https://doi.org/10.5194/hess-26-589-2022, https://doi.org/10.5194/hess-26-589-2022, 2022
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Predicting how much water will end up in rivers is more difficult during droughts because the relationship between precipitation and streamflow can change in unexpected ways. We differentiate between changes that are predictable based on the weather patterns and those harder to predict because they depend on the land and vegetation of a particular region. This work helps clarify why models are less accurate during droughts and helps predict how much water will be available for human use.
Zhihong Song, Jun Xia, Gangsheng Wang, Dunxian She, Chen Hu, and Si Hong
Hydrol. Earth Syst. Sci., 26, 505–524, https://doi.org/10.5194/hess-26-505-2022, https://doi.org/10.5194/hess-26-505-2022, 2022
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We performed a machine learning approach to regionalize the parameters of a China-wide hydrological model by linking six model parameters with 10 physical attributes (terrain and soil properties). The results show the superiority of machine-learning-based regionalization approach compared with the traditional linear regression method in ungauged regions. We also obtained the relative importance of attributes against model parameters.
Elisa Brussolo, Elisa Palazzi, Jost von Hardenberg, Giulio Masetti, Gianna Vivaldo, Maurizio Previati, Davide Canone, Davide Gisolo, Ivan Bevilacqua, Antonello Provenzale, and Stefano Ferraris
Hydrol. Earth Syst. Sci., 26, 407–427, https://doi.org/10.5194/hess-26-407-2022, https://doi.org/10.5194/hess-26-407-2022, 2022
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In this study, we evaluate the past, present and future quantity of groundwater potentially available for drinking purposes in the metropolitan area of Turin, north-western Italy. In order to effectively manage water resources, a knowledge of the water cycle components is necessary, including precipitation, evapotranspiration and subsurface reservoirs. All these components have been carefully evaluated in this paper, using observational datasets and modelling approaches.
Albert Nkwasa, Celray James Chawanda, Jonas Jägermeyr, and Ann van Griensven
Hydrol. Earth Syst. Sci., 26, 71–89, https://doi.org/10.5194/hess-26-71-2022, https://doi.org/10.5194/hess-26-71-2022, 2022
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We present an approach on how to incorporate crop phenology in a regional hydrological model using decision tables and global datasets of rainfed and irrigated cropland with the associated cropping calendar and management practices. Results indicate improved temporal patterns of leaf area index (LAI) and evapotranspiration (ET) simulations in comparison with remote sensing data. In addition, the improvement of the cropping season also helps to improve soil erosion estimates in cultivated areas.
Fanny Lehmann, Bramha Dutt Vishwakarma, and Jonathan Bamber
Hydrol. Earth Syst. Sci., 26, 35–54, https://doi.org/10.5194/hess-26-35-2022, https://doi.org/10.5194/hess-26-35-2022, 2022
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Many data sources are available to evaluate components of the water cycle (precipitation, evapotranspiration, runoff, and terrestrial water storage). Despite this variety, it remains unclear how different combinations of datasets satisfy the conservation of mass. We conducted the most comprehensive analysis of water budget closure on a global scale to date. Our results can serve as a basis to select appropriate datasets for regional hydrological studies.
Joni Dehaspe, Fanny Sarrazin, Rohini Kumar, Jan H. Fleckenstein, and Andreas Musolff
Hydrol. Earth Syst. Sci., 25, 6437–6463, https://doi.org/10.5194/hess-25-6437-2021, https://doi.org/10.5194/hess-25-6437-2021, 2021
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Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low-frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
Shaini Naha, Miguel Angel Rico-Ramirez, and Rafael Rosolem
Hydrol. Earth Syst. Sci., 25, 6339–6357, https://doi.org/10.5194/hess-25-6339-2021, https://doi.org/10.5194/hess-25-6339-2021, 2021
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Rapid growth in population in developing countries leads to an increase in food demand, and as a consequence, percentages of land are being converted to cropland which alters river flow processes. This study describes how the hydrology of a flood-prone river basin in India would respond to the current and future changes in land cover. Our findings indicate that the recurrent flood events occurring in the basin might be influenced by these changes in land cover at the catchment scale.
Maxime Gillet, Corinne Le Gal La Salle, Pierre Alain Ayral, Somar Khaska, Philippe Martin, and Patrick Verdoux
Hydrol. Earth Syst. Sci., 25, 6261–6281, https://doi.org/10.5194/hess-25-6261-2021, https://doi.org/10.5194/hess-25-6261-2021, 2021
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This paper aims at identifying the key reservoirs sustaining river low flow during dry summer. The reservoirs are discriminated based on the geological nature of the formations and the geochemical signature of groundwater. Results show the increasing importance to low-flow support of a specific reservoir, showing only a limited outcrop area and becoming preponderant in the heart of the dry season. This finding will contribute to improving the protective measures for preserving low flows.
Edouard Patault, Valentin Landemaine, Jérôme Ledun, Arnaud Soulignac, Matthieu Fournier, Jean-François Ouvry, Olivier Cerdan, and Benoit Laignel
Hydrol. Earth Syst. Sci., 25, 6223–6238, https://doi.org/10.5194/hess-25-6223-2021, https://doi.org/10.5194/hess-25-6223-2021, 2021
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The goal of this study was to assess the sediment discharge variability at a water treatment plant (Normandy, France) according to multiple realistic land use scenarios. We developed a new cascade modelling approach and simulations suggested that coupling eco-engineering and best farming practices can significantly reduce the sediment discharge (up to 80 %).
Ather Abbas, Sangsoo Baek, Norbert Silvera, Bounsamay Soulileuth, Yakov Pachepsky, Olivier Ribolzi, Laurie Boithias, and Kyung Hwa Cho
Hydrol. Earth Syst. Sci., 25, 6185–6202, https://doi.org/10.5194/hess-25-6185-2021, https://doi.org/10.5194/hess-25-6185-2021, 2021
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Correct estimation of fecal indicator bacteria in surface waters is critical for public health. Process-driven models and recently data-driven models have been applied for water quality modeling; however, a systematic comparison for simulation of E. coli is missing in the literature. We compared performance of process-driven (HSPF) and data-driven (LSTM) models for E. coli simulation. We show that LSTM can be an alternative to process-driven models for estimation of E. coli in surface waters.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 25, 6151–6172, https://doi.org/10.5194/hess-25-6151-2021, https://doi.org/10.5194/hess-25-6151-2021, 2021
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Hydrological modeling has large problems of uncertainty in cold regions. Tracer-aided hydrological models are increasingly used to reduce uncertainty and refine the parameterizations of hydrological processes, with limited application in large basins due to the unavailability of spatially distributed precipitation isotopes. This study explored the utility of isotopic general circulation models in driving a tracer-aided hydrological model in a large basin on the Tibetan Plateau.
Benedikt J. Werner, Oliver J. Lechtenfeld, Andreas Musolff, Gerrit H. de Rooij, Jie Yang, Ralf Gründling, Ulrike Werban, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 25, 6067–6086, https://doi.org/10.5194/hess-25-6067-2021, https://doi.org/10.5194/hess-25-6067-2021, 2021
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Export of dissolved organic carbon (DOC) from riparian zones (RZs) is an important yet poorly understood component of the catchment carbon budget. This study chemically and spatially classifies DOC source zones within a RZ of a small catchment to assess DOC export patterns. Results highlight that DOC export from only a small fraction of the RZ with distinct DOC composition dominates overall DOC export. The application of a spatial, topographic proxy can be used to improve DOC export models.
Sergio Naranjo, Francelino A. Rodrigues Jr., Georg Cadisch, Santiago Lopez-Ridaura, Mariela Fuentes Ponce, and Carsten Marohn
Hydrol. Earth Syst. Sci., 25, 5561–5588, https://doi.org/10.5194/hess-25-5561-2021, https://doi.org/10.5194/hess-25-5561-2021, 2021
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We integrate a spatially explicit soil erosion model with plot- and watershed-scale characterization and high-resolution drone imagery to assess the effect of spatial resolution digital terrain models (DTMs) on discharge and soil loss. Results showed reduction in slope due to resampling down of DTM. Higher resolution translates to higher slope, denser fluvial system, and extremer values of soil loss, reducing concentration time and increasing soil loss at the outlet. The best resolution was 4 m.
Thomas Lees, Marcus Buechel, Bailey Anderson, Louise Slater, Steven Reece, Gemma Coxon, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 5517–5534, https://doi.org/10.5194/hess-25-5517-2021, https://doi.org/10.5194/hess-25-5517-2021, 2021
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We used deep learning (DL) models to simulate the amount of water moving through a river channel (discharge) based on the rainfall, temperature and potential evaporation in the previous days. We tested the DL models on catchments across Great Britain finding that the model can accurately simulate hydrological systems across a variety of catchment conditions. Ultimately, the model struggled most in areas where there is chalky bedrock and where human influence on the catchment is large.
Peter T. La Follette, Adriaan J. Teuling, Nans Addor, Martyn Clark, Koen Jansen, and Lieke A. Melsen
Hydrol. Earth Syst. Sci., 25, 5425–5446, https://doi.org/10.5194/hess-25-5425-2021, https://doi.org/10.5194/hess-25-5425-2021, 2021
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Hydrological models are useful tools that allow us to predict distributions and movement of water. A variety of numerical methods are used by these models. We demonstrate which numerical methods yield large errors when subject to extreme precipitation. As the climate is changing such that extreme precipitation is more common, we find that some numerical methods are better suited for use in hydrological models. Also, we find that many current hydrological models use relatively inaccurate methods.
John P. Bloomfield, Mengyi Gong, Benjamin P. Marchant, Gemma Coxon, and Nans Addor
Hydrol. Earth Syst. Sci., 25, 5355–5379, https://doi.org/10.5194/hess-25-5355-2021, https://doi.org/10.5194/hess-25-5355-2021, 2021
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Groundwater provides flow, known as baseflow, to surface streams and rivers. It is important as it sustains the flow of many rivers at times of water stress. However, it may be affected by water management practices. Statistical models have been used to show that abstraction of groundwater may influence baseflow. Consequently, it is recommended that information on groundwater abstraction is included in future assessments and predictions of baseflow.
Chaogui Lei, Paul D. Wagner, and Nicola Fohrer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-476, https://doi.org/10.5194/hess-2021-476, 2021
Revised manuscript accepted for HESS
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We present an integrated approach of hydrologic modeling and partial least squares regression quantifying land use change impacts on water and nutrient balance over three decades. Results highlights that most variations (70–80 %) in water quantity and quality variables are explained by changes in land use class-specific area and landscape metrics. Arable land influences water quantity and quality the most. The study provides insights on land-water resources management in rural lowland catchments.
Pierre Nicolle, Vazken Andréassian, Paul Royer-Gaspard, Charles Perrin, Guillaume Thirel, Laurent Coron, and Léonard Santos
Hydrol. Earth Syst. Sci., 25, 5013–5027, https://doi.org/10.5194/hess-25-5013-2021, https://doi.org/10.5194/hess-25-5013-2021, 2021
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In this note, a new method (RAT) is proposed to assess the robustness of hydrological models. The RAT method is particularly interesting because it does not require multiple calibrations (it is therefore applicable to uncalibrated models), and it can be used to determine whether a hydrological model may be safely used for climate change impact studies. Success at the robustness assessment test is a necessary (but not sufficient) condition of model robustness.
Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp
Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, https://doi.org/10.5194/hess-25-4887-2021, 2021
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Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.
Etienne Guilpart, Vahid Espanmanesh, Amaury Tilmant, and François Anctil
Hydrol. Earth Syst. Sci., 25, 4611–4629, https://doi.org/10.5194/hess-25-4611-2021, https://doi.org/10.5194/hess-25-4611-2021, 2021
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The stationary assumption in hydrology has become obsolete because of climate changes. In that context, it is crucial to assess the performance of a hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. We illustrate the method on the Senegal River.
Yang Wang and Hassan A. Karimi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-371, https://doi.org/10.5194/hess-2021-371, 2021
Revised manuscript accepted for HESS
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Different look-back windows should be explored to obtain the optimal results when using LSTM for rainfall-runoff simulations. Adding the spatial distribution information of rainfall can improve the results of the LSTM model, especially peak discharge. The results of our proposed LSTM+1D CNN on 'n time step output' and 'one time step output' are comparable to those of the LSTM model driven by basin mean rainfall data, and slightly worse than those of spatially distributed rainfall data.
Jonathan Frame, Frederik Kratzert, Daniel Klotz, Martin Gauch, Guy Shelev, Oren Gilon, Logan M. Qualls, Hoshin V. Gupta, and Grey S. Nearing
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-423, https://doi.org/10.5194/hess-2021-423, 2021
Preprint under review for HESS
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The most accurate rainfall-runoff predictions are currently based on deep learning. There is a concern among hydrologists that deep learning models may not be reliable in extrapolation or for predicting extreme events. This study tests that hypothesis. The deep learning models remained relatively accurate in predicting extreme events compared traditional models, even when extreme events are not included in the training set.
Antoine Pelletier and Vazken Andréassian
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-413, https://doi.org/10.5194/hess-2021-413, 2021
Revised manuscript accepted for HESS
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A large part of the water cycle takes place underground. In many places, the soil stores water during the wet periods and can release it all year long, which is particularly visible when the river level is low. Modelling tools, that are used to simulate and forecast the behaviour of the river, struggle to represent this. We improved an existing model to take underground water into account, using measurements of the soil water content. Results allow us make recommendations for model users.
Herath Mudiyanselage Viraj Vidura Herath, Jayashree Chadalawada, and Vladan Babovic
Hydrol. Earth Syst. Sci., 25, 4373–4401, https://doi.org/10.5194/hess-25-4373-2021, https://doi.org/10.5194/hess-25-4373-2021, 2021
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Existing hydrological knowledge has been integrated with genetic programming based on a machine learning algorithm (MIKA-SHA) to induce readily interpretable distributed rainfall–runoff models. At present, the model building components of two flexible modelling frameworks (FUSE and SUPERFLEX) represent the elements of hydrological knowledge. The proposed toolkit captures spatial variabilities and automatically induces semi-distributed rainfall–runoff models without any explicit user selections.
Natthachet Tangdamrongsub, Michael F. Jasinski, and Peter J. Shellito
Hydrol. Earth Syst. Sci., 25, 4185–4208, https://doi.org/10.5194/hess-25-4185-2021, https://doi.org/10.5194/hess-25-4185-2021, 2021
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Accurate estimation of terrestrial water storage (TWS) is essential for reliable water resource assessments. TWS can be estimated from the Community Atmosphere–Biosphere Land Exchange model (CABLE), but the resolution is limited to 0.5°. We reconfigure CABLE to improve TWS spatial details from 0.5° to 0.05°. GRACE satellite data are assimilated into CABLE to improve TWS accuracy. Our workflow relies only on publicly accessible data, allowing reproduction of 0.05° TWS in any region.
Seán Donegan, Conor Murphy, Shaun Harrigan, Ciaran Broderick, Dáire Foran Quinn, Saeed Golian, Jeff Knight, Tom Matthews, Christel Prudhomme, Adam A. Scaife, Nicky Stringer, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 4159–4183, https://doi.org/10.5194/hess-25-4159-2021, https://doi.org/10.5194/hess-25-4159-2021, 2021
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We benchmarked the skill of ensemble streamflow prediction (ESP) for a diverse sample of 46 Irish catchments. We found that ESP is skilful in the majority of catchments up to several months ahead. However, the level of skill was strongly dependent on lead time, initialisation month, and individual catchment location and storage properties. We also conditioned ESP with the winter North Atlantic Oscillation and show that improvements in forecast skill, reliability, and discrimination are possible.
Leonie Kiewiet, Ernesto Trujillo, Andrew Hedrick, Scott Havens, Katherine Hale, Mark Seyfried, Stephanie Kampf, and Sarah E. Godsey
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-362, https://doi.org/10.5194/hess-2021-362, 2021
Revised manuscript accepted for HESS
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Mountainous regions are receiving more rain and less snow due to climate change. We investigated how that change affects stream discharge in a region that already receives a mix of rain and snow, by simulating rainfall and snowmelt for four contrasting years. We found that stream discharge depended more on the temporal distribution of precipitation than on yearly snowfall fractions. This highlights the importance of distributed modelling of rainfall and snowmelt in headwater-scale studies.
Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven
Hydrol. Earth Syst. Sci., 25, 3937–3973, https://doi.org/10.5194/hess-25-3937-2021, https://doi.org/10.5194/hess-25-3937-2021, 2021
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The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.
Zhixu Bai, Yao Wu, Di Ma, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 25, 3675–3690, https://doi.org/10.5194/hess-25-3675-2021, https://doi.org/10.5194/hess-25-3675-2021, 2021
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To test our hypothesis that the fractal dimensions of streamflow series can be used to improve the calibration of hydrological models, we designed the E–RD efficiency ratio of fractal dimensions strategy and examined its usability in the calibration of lumped models. The results reveal that, in most aspects, introducing RD into model calibration makes the simulation of streamflow components more reasonable. Also, pursuing a better RD during calibration leads to only a minor decrease in E.
Yi Nan, Lide Tian, Zhihua He, Fuqiang Tian, and Lili Shao
Hydrol. Earth Syst. Sci., 25, 3653–3673, https://doi.org/10.5194/hess-25-3653-2021, https://doi.org/10.5194/hess-25-3653-2021, 2021
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This study integrated a water isotope module into the hydrological model THREW. The isotope-aided model was subsequently applied for process understanding in the glacierized watershed of Karuxung river on the Tibetan Plateau. The model was used to quantify the contribution of runoff component and estimate the water travel time in the catchment. Model uncertainties were significantly constrained by using additional isotopic data, improving the process understanding in the catchment.
Alban de Lavenne, Vazken Andréassian, Louise Crochemore, Göran Lindström, and Berit Arheimer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-331, https://doi.org/10.5194/hess-2021-331, 2021
Revised manuscript accepted for HESS
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As a human being, a watershed remembers the past to some extent, and this memory influences its behaviour. This memory is defined by its ability to store past rainfall for several years. By releasing this water into the river or the atmosphere, it tends to forget. We describe how this memory fades over time in France and Sweden. A minority shows a multi-year memory. It increases with the influence of groundwater or dry conditions. After 3 or 4 years, they all behave independently of the past.
Andrew R. Shaughnessy, Xin Gu, Tao Wen, and Susan L. Brantley
Hydrol. Earth Syst. Sci., 25, 3397–3409, https://doi.org/10.5194/hess-25-3397-2021, https://doi.org/10.5194/hess-25-3397-2021, 2021
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It is often difficult to determine the sources of solutes in streams and how much each source contributes. We developed a new method of unmixing stream chemistry via machine learning. We found that sulfate in three watersheds is related to groundwater flowpaths. Our results emphasize that acid rain reduces a watershed's capacity to remove CO2 from the atmosphere, a key geological control on climate. Our method will help scientists unmix stream chemistry in watersheds where sources are unknown.
Sarah Hanus, Markus Hrachowitz, Harry Zekollari, Gerrit Schoups, Miren Vizcaino, and Roland Kaitna
Hydrol. Earth Syst. Sci., 25, 3429–3453, https://doi.org/10.5194/hess-25-3429-2021, https://doi.org/10.5194/hess-25-3429-2021, 2021
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This study investigates the effects of climate change on runoff patterns in six Alpine catchments in Austria at the end of the 21st century. Our results indicate a substantial shift to earlier occurrences in annual maximum and minimum flows in high-elevation catchments. Magnitudes of annual extremes are projected to increase under a moderate emission scenario in all catchments. Changes are generally more pronounced for high-elevation catchments.
Chas E. Jones Jr., Scott G. Leibowitz, Keith A. Sawicz, Randy L. Comeleo, Laurel E. Stratton, Philip E. Morefield, and Christopher P. Weaver
Hydrol. Earth Syst. Sci., 25, 3179–3206, https://doi.org/10.5194/hess-25-3179-2021, https://doi.org/10.5194/hess-25-3179-2021, 2021
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Our research assesses the hydrologic vulnerability of the western U.S. to climate by classifying the landscape based on its physical and climatic characteristics and analyzing climate data. We also apply the approach to examine the vulnerabilities of case studies in the ski and wine industries. We show that the west and its ski areas are vulnerable to changes in snow, while vineyard vulnerability varies. This allows us to consider climatic impacts across landscapes, industries, and stakeholders.
Leo Triet Pham, Lifeng Luo, and Andrew Finley
Hydrol. Earth Syst. Sci., 25, 2997–3015, https://doi.org/10.5194/hess-25-2997-2021, https://doi.org/10.5194/hess-25-2997-2021, 2021
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Model evaluation metrics suggest that RF performs better in snowmelt-driven watersheds. The largest improvements in forecasts compared to benchmark models are found among rainfall-driven watersheds. RF performance deteriorates with increases in catchment slope and soil sandiness. We note disagreement between two popular measures of RF variable importance and recommend jointly considering these measures with the physical processes under study.
Nabil Hocini, Olivier Payrastre, François Bourgin, Eric Gaume, Philippe Davy, Dimitri Lague, Lea Poinsignon, and Frederic Pons
Hydrol. Earth Syst. Sci., 25, 2979–2995, https://doi.org/10.5194/hess-25-2979-2021, https://doi.org/10.5194/hess-25-2979-2021, 2021
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Efficient flood mapping methods are needed for large-scale, comprehensive identification of flash flood inundation hazards caused by small upstream rivers. An evaluation of three automated mapping approaches of increasing complexity, i.e., a digital terrain model (DTM) filling and two 1D–2D hydrodynamic approaches, is presented based on three major flash floods in southeastern France. The results illustrate some limits of the DTM filling method and the value of using a 2D hydrodynamic approach.
Cited articles
Abdo, K. S., Fiseha, B. M., Rientjes, T. H. M., Gieske, A. S. M., and Haile,
A. T.: Assessment of climate change impacts on the hydrology of Gilgel Abay
catchment in Lake Tana basin, Ethiopia, Hydrol. Process., 23,
3661–3669, https://doi.org/10.1002/hyp.7363, 2009. a
Addor, N. and Seibert, J.: Bias correction for hydrological impact studies –
beyond the daily perspective, Hydrol. Process., 28, 4823–4828,
https://doi.org/10.1002/hyp.10238, 2014. a, b, c, d
Aich, V., Liersch, S., Vetter, T., Huang, S., Tecklenburg, J., Hoffmann, P.,
Koch, H., Fournet, S., Krysanova, V., Müller, E. N., and Hattermann, F.
F.: Comparing impacts of climate change on streamflow in four large African
river basins, Hydrol. Earth Syst. Sci., 18, 1305–1321,
https://doi.org/10.5194/hess-18-1305-2014, 2014. a, b, c
Anandhi, A., Frei, A., Pierson, D. C., Schneiderman, E. M., Zion, M. S.,
Lounsbury, D., and Matonse, A. H.: Examination of change factor methodologies
for climate change impact assessment, Water Resour. Res., 47,
https://doi.org/10.1029/2010WR009104, 2011. a, b
Arnold, J., Allen, P., and Bernhardt, G.: A comprehensive surface groundwater
flow model, J. Hydrol., 142, 47–69, 1993. a
Bartholomé, E. and Belward, A.: GLC2000: a new approach to global land
cover
mapping from Earth observation data, Int. J. Remote
Sens., 26, 1959–1977, https://doi.org/10.1080/01431160412331291297, 2005. a
Berg, P., Feldmann, H., and Panitz, H.-J.: Bias correction of high resolution
regional climate model data, J. Hydrol., 448–449, 80–92,
https://doi.org/10.1016/j.jhydrol.2012.04.026, 2012. a
Beyene, T., Lettenmaier, D., and Kabat, P.: Hydrologic impacts of climate
change on the Nile River Basin: implications of the 2007 IPCC scenarios,
Climatic Change, 100, 433–461, https://doi.org/10.1007/s10584-009-9693-0, 2010. a, b
Bosshard, T., Kotlarski, S., Ewen, T., and Schär, C.: Spectral
representation of the annual cycle in the climate change signal, Hydrol.
Earth Syst. Sci., 15, 2777–2788, https://doi.org/10.5194/hess-15-2777-2011,
2011. a, b
Bryan, E., Deressa, T. T., Gbetibouo, G. A., and Ringler, C.: Adaptation to
climate change in Ethiopia and South Africa: options and constraints,
Environ. Sci. Policy, 12, 413–426,
https://doi.org/10.1016/j.envsci.2008.11.002, 2009. a
Busby, J., Cook, K., Vizy, E., Smith, T., and Bekalo, M.: Identifying hot
spots of security vulnerability associated with climate change in Africa,
Climatic Change, 124, 717–731, https://doi.org/10.1007/s10584-014-1142-z, 2014. a
Chiew, F. H. S., Teng, J., Vaze, J., Post, D. A., Perraud, J. M., Kirono, D.
G. C., and Viney, N. R.: 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. a, b
Christensen, J. H., Boberg, F., Christensen, O. B., and Lucas-Picher, P.: On
the need for bias correction of regional climate change projections of
temperature and precipitation, Geophys. Res. Lett., 35, L20709,
https://doi.org/10.1029/2008GL035694, 2008. a
Conway, D. and Hulme, M.: Recent fluctuations in precipitation and runoff over
the Nile sub-basins and their impact on main Nile discharge, Climatic
Change, 25, 127–151, https://doi.org/10.1007/BF01661202, 1993. a
Conway, D. and Schipper, E. L. F.: Adaptation to climate change in Africa:
Challenges and opportunities identified from Ethiopia, Global Environ.
Change, 21, 227–237, https://doi.org/10.1016/j.gloenvcha.2010.07.013, 2011. a, b, c
Deressa, T. T., Hassan, R. M., and Ringler, C.: Perception of and adaptation
to climate change by farmers in the Nile basin of Ethiopia, J.
Agr. Sci., 149, 23–31, https://doi.org/10.1017/S0021859610000687, 2011. a
Di Baldassarre, G., Elshamy, M., van Griensven, A., Soliman, E., Kigobe, M.,
Ndomba, P., Mutemi, J., Mutua, F., Moges, S., Xuan, Y., Solomatine, D., and
Uhlenbrook, S.: Future hydrology and climate in the River Nile basin: a
review, Hydrolog. Sci. J.,
56, 199–211, https://doi.org/10.1080/02626667.2011.557378, 2011. a
Dile, Y. T., Berndtsson, R., and Setegn, S. G.: Hydrological Response to
Climate Change for Gilgel Abay River, in the Lake Tana Basin – Upper Blue
Nile Basin of Ethiopia, PLOS ONE, 8,
https://doi.org/10.1371/journal.pone.0079296, 2013. a, b, c, d
Diro, G. T., Grimes, D. I. F., Black, E., O'Neill, A., and Pardo-Iguzquiza, E.:
Evaluation of reanalysis rainfall estimates over Ethiopia, Int.
J. Climatol., 29, 67–78, https://doi.org/10.1002/joc.1699, 2009. a
Diro, G. T., Toniazzo, T., and Shaffrey, L.: Ethiopian Rainfall in Climate
Models, in: African Climate and Climate Change, edited by: Williams, C. J. R.
and Kniveton, D. R., Vol. 43 of Advances in Global Change Research,
51–69, Springer Netherlands, https://doi.org/10.1007/978-90-481-3842-5_3, 2011. a, b
Dobler, A., Yaoming, M., Sharma, N., Kienberger, S., and Ahrens, B.: Regional
climate projections in two alpine river basins: Upper Danube and Upper
Brahmaputra, Adv. Sci. Res., 7, 11–20,
https://doi.org/10.5194/asr-7-11-2011, 2011. a
Dosio, A. and Paruolo, P.: Bias correction of the ENSEMBLES high-resolution
climate change projections for use by impact models: Evaluation on the
present climate, J. Geophys. Res.-Atmos., 116, D16106,
https://doi.org/10.1029/2011JD015934, 2011. a
Elshamy, M., di Baldassarre, G., and van Griensven, A.: Characterizing Climate
Model Uncertainty Using an Informal Bayesian Framework: Application to the
River Nile, J. Hydrol. Eng. ASCE, 18, 582–589,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0000656, 2013. a
Elshamy, M. E., Seierstad, I. A., and Sorteberg, A.: Impacts of climate
change on Blue Nile flows using bias-corrected GCM scenarios, Hydrol. Earth
Syst. Sci., 13, 551–565, https://doi.org/10.5194/hess-13-551-2009, 2009. a, b, c, d
FAO, IIASA, ISRIC, ISSCAS, and JRC: Harmonized World Soil Database (version
1.1), FAO, Rome, Italy and IIASA, Laxenburg, Austria, 2009. a
Gebreluel, G.: Ethiopia's Grand Renaissance Dam: Ending Africa's Oldest
Geopolitical Rivalry?, Wash. Quart., 37, 25–37,
https://doi.org/10.1080/0163660X.2014.926207, 2014. a, b
Gudmundsson, L., Bremnes, J. B., Haugen, J. E., and Engen-Skaugen, T.:
Technical Note: Downscaling RCM precipitation to the station scale using
statistical transformations – a comparison of methods, Hydrol. Earth Syst.
Sci., 16, 3383–3390, https://doi.org/10.5194/hess-16-3383-2012, 2012. a
Hagemann, S., Chen, C., Haerter, J. O., Heinke, J., Gerten, D., and Piani, C.:
Impact of a Statistical Bias Correction on the Projected Hydrological Changes
Obtained from Three GCMs and Two Hydrology Models, J.
Hydrometeorol., 12, 556–578, https://doi.org/10.1175/2011JHM1336.1, 2011. a
Hargreaves, G. and Samani, Z.: Reference crop evapotranspiration from
temperature, T. ASAE, 11, 96–99, 1985. a
Hattermann, F. F., Huang, S., Burghoff, O., Hoffmann, P., and Kundzewicz, Z.
W.: Brief Communication: An update of the article “Modelling flood damages
under climate change conditions – a case study for Germany”, Nat. Hazards
Earth Syst. Sci., 16, 1617–1622, https://doi.org/10.5194/nhess-16-1617-2016,
2016. a
Headey, D., Taffesse, A. S., and You, L.: Diversification and Development in
Pastoralist Ethiopia, World Dev., 56, 200–213,
https://doi.org/10.1016/j.worlddev.2013.10.015, 2014. a
Hempel, S., Frieler, K., Warszawski, L., Schewe, J., and Piontek, F.: A
trend-preserving bias correction – the ISI-MIP approach, Earth Syst. Dynam.,
4, 219–236, https://doi.org/10.5194/esd-4-219-2013, 2013. a, b
Ibrahim, A.: The Nile Basin Cooperative Framework Agreement: The Beginning of
the End of Egyptian Hydro-Political Hegemony, Missouri Environmental Law and
Policy Review, 18, 284–312, available at:
https://scholarship.law.missouri.edu/cgi/viewcontent.cgi?article=1395&context=jesl
(last access: 24 January 2018),
2012. a
IPCC: Climate Change 2013. The Physical Science Basis. Working Group I
Contribution to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, Tech. rep., IPCC, available at: http://www.ipcc.ch/report/ar5/wg1/ (last access: 14 April 2016), 2013. a
Jarvis, A., Reuter, H., Nelson, A., and Guevara, E.: Hole-filled seamless SRTM
data V4, International Centre for Tropical Agriculture (CIAT), available
at: http://srtm.csi.cgiar.org (last access: 9 February 2016), 2008. a
Jeuland, M. and Whittington, D.: Water resources planning under climate
change: Assessing the robustness of real options for the Blue Nile, Water
Resour. Res., 50, 2086–2107, https://doi.org/10.1002/2013WR013705, 2014. a
King, A.: An Assessment of Reservoir Filling Policies under a Changing Climate
for Ethiopias Grand Renaissance Dam, PhD thesis, Drexel University, 2013. a
Koch, H., Liersch, S., and Hattermann, F.: Integrating water resources
management in eco-hydrological modelling, Water Sci. Technol., 67,
1525–1533, https://doi.org/10.2166/wst.2013.022, 2013. a
Krysanova, V., Meiner, A., Roosaare, J., and Vasilyev, A.: Simulation modelling
of the coastal waters pollution from agricultural watershed, Ecol.
Model., 49, 7–29, 1989. a
Krysanova, V., Hattermann, F., and Wechsung, F.: Development of the
ecohydrological model SWIM for regional impact studies and vulnerability
assessment, Hydrol. Process., 19, 763–783, https://doi.org/10.1002/hyp.5619,
2005. a, b
Krysanova, V., Hattermann, F., Huang, S., Hesse, C., Vetter, T., Liersch, S.,
Koch, H., and Kundzewicz, Z. W.: Modelling climate and land use change
impacts with SWIM: lessons learnt from multiple applications, Hydrolog.
Sci. J., 60, 606–635, https://doi.org/10.1080/02626667.2014.925560, 2015. a
Liersch, S.: Discharge simulations for the Blue Nile at gauge El Diem based
on uncorrected and bias-corrected GCM and RCM inputs, Potsdam Institute for
Climate Impact Research, Dataset,
https://doi.org/10.4121/uuid:05b9f40f-583d-479b-a79e-f961f72436db, 2018. a
Liersch, S., Cools, J., Kone, B., Koch, H., Diallo, M., Aich, V., Fournet, S.,
and Hattermann, F.: Vulnerability of food production in the Inner Niger
Delta to water resources management under climate variability and change,
Environ. Sci. Policy, 34, 18–33,
https://doi.org/10.1016/j.envsci.2012.10.014, 2013. a
Liersch, S., Koch, H., and Hattermann, F. F.: Management Scenarios of the
Grand Ethiopian Renaissance Dam and Their Impacts under Recent and Future
Climates, Water, 9, 728, https://doi.org/10.3390/w9100728, 2017. a, b
Liersch, S., Rust, H., Dobler, A., Kruschke, T., and Fischer, M.:
Bias-corrected CORDEX precipitation, min/mean/max temperature for Ethiopia,
RCP 4.5 and RCP 8.5, GFZ Data Services, https://doi.org/10.5880/PIK.2018.009, 2018. a
Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J.,
Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Themeßl, M., Venema, V.
K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and
Thiele-Eich, I.: Precipitation downscaling under climate change: Recent
developments to bridge the gap between dynamical models and the end user,
Rev. Geophys., 48, RG3003, https://doi.org/10.1029/2009RG000314, 2010. a, b
McCartney, M. P. and Menker Girma, M.: Evaluating the downstream implications
of planned water resource development in the Ethiopian portion of the Blue
Nile River, Water Int., 37, 362–379,
https://doi.org/10.1080/02508060.2012.706384, 2012. a, b
Megersa, B., Markemann, A., Angassa, A., Ogutu, J. O., Piepho, H.-P., and
Zarate, A. V.: Impacts of climate change and variability on cattle
production in southern Ethiopia: Perceptions and empirical evidence,
Agr. Syst., 130, 23–34, https://doi.org/10.1016/j.agsy.2014.06.002, 2014. a
Meinshausen, M., Smith, S., Calvin, K., Daniel, J., Kainuma, M., Lamarque,
J.-F., Matsumoto, K., Montzka, S., Raper, S., Riahi, K., Thomson, A.,
Velders, G., and Vuuren, D.: The RCP greenhouse gas concentrations and their
extensions from 1765 to 2300, Climatic Change, 109, 213–241,
https://doi.org/10.1007/s10584-011-0156-z, 2011. a, b
Mengistu, D., Bewket, W., and Lal, R.: Recent spatiotemporal temperature and
rainfall variability and trends over the Upper Blue Nile River Basin,
Ethiopia, Int. J. Climatol., 34, 2278–2292, https://doi.org/10.1002/joc.3837, 2014. a
Nash, J. and Sutcliffe, J.: River flow forecasting through conceptual models,
Part 1 – a discussion of principles, J. Hydrol., 10, 282–290,
https://doi.org/10.1016/0022-1694(70)90255-6, 1970. a
Piani, C., Weedon, G., Best, M., Gomes, S., Viterbo, P., Hagemann, S., and
Haerter, J.: Statistical bias correction of global simulated daily
precipitation and temperature for the application of hydrological models,
J. Hydrol., 395, 199–215, https://doi.org/10.1016/j.jhydrol.2010.10.024,
2010. a, b
Pierce, D. W., Barnett, T. P., Santer, B. D., and Gleckler, P. J.: Selecting
global climate models for regional climate change studies, P. Natl. Acad. Sci. USA, 106,
8441–8446, https://doi.org/10.1073/pnas.0900094106, 2009. a
Rust, H. W., Kruschke, T., Dobler, A., Fischer, M., and Ulbrich, U.:
Discontinuous daily Temperatures in the WATCH forcing data setes, J.
Hydrometeorol., 16, 465–472, https://doi.org/10.1175/JHM-D-14-0123.1, 2015. a
Schmidli, J., Frei, C., and Vidale, P. L.: Downscaling from GCM precipitation:
A benchmark for dynamical and statistical downscaling methods, Int.
J. Climatol., 26, 679–689, https://doi.org/10.1002/joc.1287, 2006. a
Simane, B., Zaitchik, B. F., and Mesfin, D.: Building Climate Resilience in
the Blue Nile/Abay Highlands: A Framework for Action, Int. J. Environ.
Res. Pu., 9, 610–631, https://doi.org/10.3390/ijerph9020610, 2012. a
Smakhtin, V.: Estimating daily flow duration curves from monthly streamflow
data, Water SA, 26, 13–18, 2000. a
Soliman, E. S., Sayed, M. A. A., and Jeuland, M.: Impact Assessment of Future
Climate Change for the Blue Nile Basin, Using a RCM Nested in a GCM, Nile
Basin Water Engineering Scientific Magazine, 2, 15–30, 2009. a
Stagl, J. C. and Hattermann, F. F.: Impacts of Climate Change on the
Hydrological Regime of the Danube River and Its Tributaries Using an Ensemble
of Climate Scenarios, Water, 7, 6139–6172, https://doi.org/10.3390/w7116139, 2015. a
Taye, M. T. and Willems, P.: Temporal variability of hydroclimatic extremes in
the Blue Nile basin, Water. Resour. Res., 48, W03513, https://doi.org/10.1029/2011WR011466,
2012. a, b, c
Taye, M. T., Willems, P., and Block, P.: Implications of climate change on
hydrological extremes in the Blue Nile basin: A review, Journal of Hydrology:
Regional Studies, 4, 280–293, https://doi.org/10.1016/j.ejrh.2015.07.001,
2015. a
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192,
https://doi.org/10.1029/2000JD900719, 2001. a
Teklesadik, A. D., Alemayehu, T., van Griensven, A., Kumar, R., Liersch, S.,
Eisner, S., Tecklenburg, J., Ewunte, S., and Wang, X.: Inter-model
comparison of hydrological impacts of climate change on the Upper Blue Nile
basin using ensemble of hydrological models and global climate models,
Climatic Change, 141, 517–532, https://doi.org/10.1007/s10584-017-1913-4, 2017. a, b, c
Teutschbein, C. and Seibert, J.: Regional Climate Models for Hydrological
Impact Studies at the Catchment Scale: A Review of Recent Modeling
Strategies, Geography Compass, 4, 834–860,
https://doi.org/10.1111/j.1749-8198.2010.00357.x, 2010. a
Teutschbein, C. and Seibert, J.: Bias correction of regional climate model
simulations for hydrological climate-change impact studies: Review and
evaluation of different methods, J. Hydrol., 456–457, 12–29,
https://doi.org/10.1016/j.jhydrol.2012.05.052, 2012.
a
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Da Costa
Bechtold, V., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly,
G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson,
E.,
Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Van De Berg, L.,
Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac,
M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J.,
Isaksen, L., Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F.,
Morcrette, J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A.,
Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.:
The ERA-40
re-analysis, Q. J. Roy. Meteor. Soc., 131,
2961–3012, https://doi.org/10.1256/qj.04.176, 2005. a
van Vuuren, D., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K.,
Hurtt, G., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M.,
Nakicenovic, N., Smith, S., and Rose, S.: The representative concentration
pathways: an overview, Climatic Change, 109, 5–31,
https://doi.org/10.1007/s10584-011-0148-z, 2011. a, b
Vetter, T., Huang, S., Aich, V., Yang, T., Wang, X., Krysanova, V., and
Hattermann, F.: Multi-model climate impact assessment and intercomparison for
three large-scale river basins on three continents, Earth Syst. Dynam., 6,
17–43, https://doi.org/10.5194/esd-6-17-2015, 2015. a
Vrac, M. and Friederichs, P.: Multivariate–intervariable, spatial, and
temporal–bias correction, J. Climate, 28, 218–237, 2015. a
Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., and Schewe,
J.: The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP):
Project framework, P. Natl. Acad. Sci. USA, 111,
3228–3232, https://doi.org/10.1073/pnas.1312330110, 2014. a
Weedon, G. P., Gomes, S., Viterbo, P., Shuttleworth, W. J., Blyth, E.,
Österle, H., Adam, J. C., Bellouin, N., Boucher, O., and Best, M.: Creation
of the WATCH Forcing Data and its use to assess global and regional reference
crop evaporation over land during the twentieth century, J.
Hydrometeorol., 12, 823–848, https://doi.org/10.1175/2011JHM1369.1, 2011. a
Wilks, D. S.: Statistical methods in the atmospheric sciences, Academic Press,
San Diego, CA, 3rd Edn., 2011. a
Yee, T. W.: Vector Generalized Linear and Additive Models: With an
Implementation in R, Springer, New York, 2015. a
Zaitchik, B. F., Simane, B., Habib, S., Anderson, M. C., Ozdogan, M., and
Foltz, J. D.: Building Climate Resilience in the Blue Nile/Abay Highlands: A
Role for Earth System Sciences, Int. J. Environ. Res. Pu., 9,
435–461, https://doi.org/10.3390/ijerph9020435, 2012. a, b
Short summary
Application-oriented regional impact studies require accurate simulations of future climate variables and water availability. We analyse the quality of global and regional climate projections and discuss potentials of correction methods that partly overcome this quality issue. The model ensemble used in this study projects increasing average annual discharges and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.
Application-oriented regional impact studies require accurate simulations of future climate...
