Articles | Volume 22, issue 4
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.
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
CORRESPONDING AUTHOR
Potsdam Institute for Climate Impact Research (PIK), Telegraphenberg A31, 14473 Potsdam, Germany
Julia Tecklenburg
Potsdam Institute for Climate Impact Research (PIK), Telegraphenberg A31, 14473 Potsdam, Germany
Henning Rust
Free University of Berlin (FUB), Institute of Meteorology, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
Andreas Dobler
Free University of Berlin (FUB), Institute of Meteorology, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
Madlen Fischer
Free University of Berlin (FUB), Institute of Meteorology, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
Tim Kruschke
GEOMAR Helmholtz Centre for Ocean Research Kiel, Wischhofstr. 1–3, 24148 Kiel, Germany
Hagen Koch
Potsdam Institute for Climate Impact Research (PIK), Telegraphenberg A31, 14473 Potsdam, Germany
Fred Fokko Hattermann
Potsdam Institute for Climate Impact Research (PIK), Telegraphenberg A31, 14473 Potsdam, Germany
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Rasmus E. Benestad, Abdelkader Mezghani, Julia Lutz, Andreas Dobler, Kajsa M. Parding, and Oskar A. Landgren
Geosci. Model Dev., 16, 2899–2913, https://doi.org/10.5194/gmd-16-2899-2023, https://doi.org/10.5194/gmd-16-2899-2023, 2023
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A mathematical method known as common EOFs is not widely used within the climate research community, but it offers innovative ways of evaluating climate models. We show how common EOFs can be used to evaluate large ensembles of global climate model simulations and distill information about their ability to reproduce salient features of the regional climate. We can say that they represent a kind of machine learning (ML) for dealing with big data.
Madlen Peter, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-62, https://doi.org/10.5194/nhess-2023-62, 2023
Preprint under review for NHESS
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The paper introduces a statistical modeling approach describing daily extreme precipitation in Germany more accurately by including changes within the year and between the years simultaneously. An altering seasonality with the years is regional divergent and mainly weak. However, some regions outstand with a more pronounced linear rise of summer intensities indicating a possible climate change signal. Improved modeling of extreme precipitation is beneficial for risk assessment and adaptation.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Matthew Forrest, and Michel Bechtold
EGUsphere, https://doi.org/10.5194/egusphere-2023-281, https://doi.org/10.5194/egusphere-2023-281, 2023
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Our paper provides an overview of all observational climate-related and socio-economic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes are already induced by climate change.
Johannes Riebold, Andy Richling, Uwe Ulbrich, Henning Rust, Tido Semmler, and Dörthe Handorf
EGUsphere, https://doi.org/10.5194/egusphere-2022-953, https://doi.org/10.5194/egusphere-2022-953, 2022
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Arctic sea ice loss might impact the atmospheric circulation outside the Arctic and therefore extremes over mid-latitudes. Here, we analyze model experiments to initially assess the influence of sea ice loss on occurrence frequencies of large-scale circulation patterns. Some of these detected circulation changes can be linked to changes in occurrences of European temperature extremes. Compared to future global temperature increases the sea ice-related impacts are however of secondary relevance.
Annika Drews, Wenjuan Huo, Katja Matthes, Kunihiko Kodera, and Tim Kruschke
Atmos. Chem. Phys., 22, 7893–7904, https://doi.org/10.5194/acp-22-7893-2022, https://doi.org/10.5194/acp-22-7893-2022, 2022
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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 it 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.
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.
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
Revisiting the hydrological basis of the Budyko framework with the principle of hydrologically similar groups
Reconstructing five decades of sediment export from two glacierized high-alpine catchments in Tyrol, Austria, using nonparametric regression
Water and energy budgets over hydrological basins on short and long timescales
Hydrological response to climate change and human activities in the Three-River Source Region
Incorporating experimentally derived streamflow contributions into model parameterization to improve discharge prediction
Machine-learning- and deep-learning-based streamflow prediction in a hilly catchment for future scenarios using CMIP6 GCM data
River hydraulic modeling with ICESat-2 land and water surface elevation
Hydrological modeling using the Soil and Water Assessment Tool in urban and peri-urban environments: the case of Kifisos experimental subbasin (Athens, Greece)
Technical note: How physically based is hydrograph separation by recursive digital filtering?
A comprehensive open-source course for teaching applied hydrological modelling in Central Asia
Impact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchment
Technical note: Extending the SWAT model to transport chemicals through tile and groundwater flow
Long-term reconstruction of satellite-based precipitation, soil moisture, and snow water equivalent in China
Disentangling scatter in long-term concentration–discharge relationships: the role of event types
Simulating the hydrological impacts of land use conversion from annual crop to perennial forage in the Canadian Prairies using the Cold Regions Hydrological Modelling platform
How can we benefit from regime information to make more effective use of long short-term memory (LSTM) runoff models?
When best is the enemy of good – critical evaluation of performance criteria in hydrological models
On the value of satellite remote sensing to reduce uncertainties of regional simulations of the Colorado River
Assessing runoff sensitivity of North American Prairie Pothole Region basins to wetland drainage using a basin classification-based virtual modelling approach
A large-sample investigation into uncertain climate change impacts on high flows across Great Britain
Effects of passive-storage conceptualization on modeling hydrological function and isotope dynamics in the flow system of a cockpit karst landscape
Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks
Attribution of climate change and human activities to streamflow variations with a posterior distribution of hydrological simulations
A time-varying distributed unit hydrograph method considering soil moisture
Flood patterns in a catchment with mixed bedrock geology and a hilly landscape: identification of flashy runoff contributions during storm events
A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion
Improving hydrologic models for predictions and process understanding using neural ODEs
Response of active catchment water storage capacity to a prolonged meteorological drought and asymptotic climate variation
HESS Opinions: Participatory Digital eARth Twin Hydrology systems (DARTHs) for everyone – a blueprint for hydrologists
Development of a national 7-day ensemble streamflow forecasting service for Australia
Future snow changes and their impact on the upstream runoff in Salween
Technical note: Do different projections matter for the Budyko framework?
Representation of seasonal land use dynamics in SWAT+ for improved assessment of blue and green water consumption
Large-sample assessment of varying spatial resolution on the streamflow estimates of the wflow_sbm hydrological model
An algorithm for deriving the topology of belowground urban stormwater networks
Producing reliable hydrologic scenarios from raw climate model outputs without resorting to meteorological observations
Assessing the influence of water sampling strategy on the performance of tracer-aided hydrological modeling in a mountainous basin on the Tibetan Plateau
The suitability of differentiable, learnable hydrologic models for ungauged regions and climate change impact assessment
Flood forecasting with machine learning models in an operational framework
Precipitation fate and transport in a Mediterranean catchment through models calibrated on plant and stream water isotope data
High-resolution satellite products improve hydrological modeling in northern Italy
Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?
A conceptual-model-based sediment connectivity assessment for patchy agricultural catchments
The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL)
Spatial extrapolation of stream thermal peaks using heterogeneous time series at a national scale
Revisiting parameter sensitivities in the variable infiltration capacity model across a hydroclimatic gradient
Deep learning rainfall–runoff predictions of extreme events
Diel streamflow cycles suggest more sensitive snowmelt-driven streamflow to climate change than land surface modeling does
Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise
Effects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zone
Yuchan Chen, Xiuzhi Chen, Meimei Xue, Chuanxun Yang, Wei Zheng, Jun Cao, Wenting Yan, and Wenping Yuan
Hydrol. Earth Syst. Sci., 27, 1929–1943, https://doi.org/10.5194/hess-27-1929-2023, https://doi.org/10.5194/hess-27-1929-2023, 2023
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This study addresses the quantification and estimation of the watershed-characteristic-related parameter (Pw) in the Budyko framework with the principle of hydrologically similar groups. The results show that Pw is closely related to soil moisture and fractional vegetation cover, and the relationship varies across specific hydrologic similarity groups. The overall satisfactory performance of the Pw estimation model improves the applicability of the Budyko framework for global runoff estimation.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, Christoph Mayer, and Axel Bronstert
Hydrol. Earth Syst. Sci., 27, 1841–1863, https://doi.org/10.5194/hess-27-1841-2023, https://doi.org/10.5194/hess-27-1841-2023, 2023
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We present a suitable method to reconstruct sediment export from decadal records of hydroclimatic predictors (discharge, precipitation, temperature) and shorter suspended sediment measurements. This lets us fill the knowledge gap on how sediment export from glacierized high-alpine areas has responded to climate change. We find positive trends in sediment export from the two investigated nested catchments with step-like increases around 1981 which are linked to crucial changes in glacier melt.
Samantha Petch, Bo Dong, Tristan Quaife, Robert P. King, and Keith Haines
Hydrol. Earth Syst. Sci., 27, 1723–1744, https://doi.org/10.5194/hess-27-1723-2023, https://doi.org/10.5194/hess-27-1723-2023, 2023
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Gravitational measurements of water storage from GRACE (Gravity Recovery and Climate Experiment) can improve understanding of the water budget. We produce flux estimates over large river catchments based on observations that close the monthly water budget and ensure consistency with GRACE on short and long timescales. We use energy data to provide additional constraints and balance the long-term energy budget. These flux estimates are important for evaluating climate models.
Ting Su, Chiyuan Miao, Qingyun Duan, Jiaojiao Gou, Xiaoying Guo, and Xi Zhao
Hydrol. Earth Syst. Sci., 27, 1477–1492, https://doi.org/10.5194/hess-27-1477-2023, https://doi.org/10.5194/hess-27-1477-2023, 2023
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The Three-River Source Region (TRSR) plays an extremely important role in water resources security and ecological and environmental protection in China and even all of Southeast Asia. This study used the variable infiltration capacity (VIC) land surface hydrologic model linked with the degree-day factor algorithm to simulate the runoff change in the TRSR. These results will help to guide current and future regulation and management of water resources in the TRSR.
Andreas Hartmann, Jean-Lionel Payeur-Poirier, and Luisa Hopp
Hydrol. Earth Syst. Sci., 27, 1325–1341, https://doi.org/10.5194/hess-27-1325-2023, https://doi.org/10.5194/hess-27-1325-2023, 2023
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We advance our understanding of including information derived from environmental tracers into hydrological modeling. We present a simple approach that integrates streamflow observations and tracer-derived streamflow contributions for model parameter estimation. We consider multiple observed streamflow components and their variation over time to quantify the impact of their inclusion for streamflow prediction at the catchment scale.
Dharmaveer Singh, Manu Vardhan, Rakesh Sahu, Debrupa Chatterjee, Pankaj Chauhan, and Shiyin Liu
Hydrol. Earth Syst. Sci., 27, 1047–1075, https://doi.org/10.5194/hess-27-1047-2023, https://doi.org/10.5194/hess-27-1047-2023, 2023
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This study examines, for the first time, the potential of various machine learning models in streamflow prediction over the Sutlej River basin (rainfall-dominated zone) in western Himalaya during the period 2041–2070 (2050s) and 2071–2100 (2080s) and its relationship to climate variability. The mean ensemble of the model results shows that the mean annual streamflow of the Sutlej River is expected to rise between the 2050s and 2080s by 0.79 to 1.43 % for SSP585 and by 0.87 to 1.10 % for SSP245.
Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Ranndal, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 27, 1011–1032, https://doi.org/10.5194/hess-27-1011-2023, https://doi.org/10.5194/hess-27-1011-2023, 2023
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This paper uses remote sensing data from ICESat-2 to calibrate a 1D hydraulic model. With the model, we can make estimations of discharge and water surface elevation, which are important indicators in flooding risk assessment. ICESat-2 data give an added value, thanks to the 0.7 m resolution, which allows the measurement of narrow river streams. In addition, ICESat-2 provides measurements on the river dry portion geometry that can be included in the model.
Evgenia Koltsida, Nikos Mamassis, and Andreas Kallioras
Hydrol. Earth Syst. Sci., 27, 917–931, https://doi.org/10.5194/hess-27-917-2023, https://doi.org/10.5194/hess-27-917-2023, 2023
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Daily and hourly rainfall observations were inputted to a Soil and Water Assessment Tool (SWAT) hydrological model to investigate the impacts of rainfall temporal resolution on a discharge simulation. Results indicated that groundwater flow parameters were more sensitive to daily time intervals, and channel routing parameters were more influential for hourly time intervals. This study suggests that the SWAT model appears to be a reliable tool to predict discharge in a mixed-land-use basin.
Klaus Eckhardt
Hydrol. Earth Syst. Sci., 27, 495–499, https://doi.org/10.5194/hess-27-495-2023, https://doi.org/10.5194/hess-27-495-2023, 2023
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An important hydrological issue is to identify components of streamflow that react to precipitation with different degrees of attenuation and delay. From the multitude of methods that have been developed for this so-called hydrograph separation, a specific, frequently used one is singled out here. It is shown to be derived from plausible physical principles. This increases confidence in its results.
Beatrice Sabine Marti, Aidar Zhumabaev, and Tobias Siegfried
Hydrol. Earth Syst. Sci., 27, 319–330, https://doi.org/10.5194/hess-27-319-2023, https://doi.org/10.5194/hess-27-319-2023, 2023
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Numerical modelling is often used for climate impact studies in water resources management. It is, however, not yet highly accessible to many students of hydrology in Central Asia. One big hurdle for new learners is the preparation of relevant data prior to the actual modelling. We present a robust, open-source workflow and comprehensive teaching material that can be used by teachers and by students for self study.
Aniket Gupta, Alix Reverdy, Jean-Martial Cohard, Basile Hector, Marc Descloitres, Jean-Pierre Vandervaere, Catherine Coulaud, Romain Biron, Lucie Liger, Reed Maxwell, Jean-Gabriel Valay, and Didier Voisin
Hydrol. Earth Syst. Sci., 27, 191–212, https://doi.org/10.5194/hess-27-191-2023, https://doi.org/10.5194/hess-27-191-2023, 2023
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Patchy snow cover during spring impacts mountainous ecosystems on a large range of spatio-temporal scales. A hydrological model simulated such snow patchiness at 10 m resolution. Slope and orientation controls precipitation, radiation, and wind generate differences in snowmelt, subsurface storage, streamflow, and evapotranspiration. The snow patchiness increases the duration of the snowmelt to stream and subsurface storage, which sustains the plants and streamflow later in the summer.
Hendrik Rathjens, Jens Kiesel, Michael Winchell, Jeffrey Arnold, and Robin Sur
Hydrol. Earth Syst. Sci., 27, 159–167, https://doi.org/10.5194/hess-27-159-2023, https://doi.org/10.5194/hess-27-159-2023, 2023
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The SWAT model can simulate the transport of water-soluble chemicals through the landscape but neglects the transport through groundwater or agricultural tile drains. These transport pathways are, however, important to assess the amount of chemicals in streams. We added this capability to the model, which significantly improved the simulation. The representation of all transport pathways in the model enables watershed managers to develop robust strategies for reducing chemicals in streams.
Wencong Yang, Hanbo Yang, Changming Li, Taihua Wang, Ziwei Liu, Qingfang Hu, and Dawen Yang
Hydrol. Earth Syst. Sci., 26, 6427–6441, https://doi.org/10.5194/hess-26-6427-2022, https://doi.org/10.5194/hess-26-6427-2022, 2022
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We produced a daily 0.1° dataset of precipitation, soil moisture, and snow water equivalent in 1981–2017 across China via reconstructions. The dataset used global background data and local on-site data as forcing input and satellite-based data as reconstruction benchmarks. This long-term high-resolution national hydrological dataset is valuable for national investigations of hydrological processes.
Felipe A. Saavedra, Andreas Musolff, Jana von Freyberg, Ralf Merz, Stefano Basso, and Larisa Tarasova
Hydrol. Earth Syst. Sci., 26, 6227–6245, https://doi.org/10.5194/hess-26-6227-2022, https://doi.org/10.5194/hess-26-6227-2022, 2022
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Nitrate contamination of rivers from agricultural sources is a challenge for water quality management. During runoff events, different transport paths within the catchment might be activated, generating a variety of responses in nitrate concentration in stream water. Using nitrate samples from 184 German catchments and a runoff event classification, we show that hydrologic connectivity during runoff events is a key control of nitrate transport from catchments to streams in our study domain.
Marcos R. C. Cordeiro, Kang Liang, Henry F. Wilson, Jason Vanrobaeys, David A. Lobb, Xing Fang, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 26, 5917–5931, https://doi.org/10.5194/hess-26-5917-2022, https://doi.org/10.5194/hess-26-5917-2022, 2022
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This study addresses the issue of increasing interest in the hydrological impacts of converting cropland to perennial forage cover in the Canadian Prairies. By developing customized models using the Cold Regions Hydrological Modelling (CRHM) platform, this long-term (1992–2013) modelling study is expected to provide stakeholders with science-based information regarding the hydrological impacts of land use conversion from annual crop to perennial forage cover in the Canadian Prairies.
Reyhaneh Hashemi, Pierre Brigode, Pierre-André Garambois, and Pierre Javelle
Hydrol. Earth Syst. Sci., 26, 5793–5816, https://doi.org/10.5194/hess-26-5793-2022, https://doi.org/10.5194/hess-26-5793-2022, 2022
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Hydrologists have long dreamed of a tool that could adequately predict runoff in catchments. Data-driven long short-term memory (LSTM) models appear very promising to the hydrology community in this respect. Here, we have sought to benefit from traditional practices in hydrology to improve the effectiveness of LSTM models. We discovered that one LSTM parameter has a hydrologic interpretation and that there is a need to increase the data and to tune two parameters, thereby improving predictions.
Guillaume Cinkus, Naomi Mazzilli, Hervé Jourde, Andreas Wunsch, Tanja Liesch, Nataša Ravbar, Zhao Chen, and Nico Goldscheider
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-380, https://doi.org/10.5194/hess-2022-380, 2022
Revised manuscript accepted for HESS
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The Kling-Gupta Efficiency (KGE) is a performance criterion extensively used to evaluate hydrological models. We conduct a critical study on the KGE and its variant to examine counterbalancing errors. Results show that, assessing a simulation, concurrent over- and underestimation of discharge can lead to an overall higher criterion score without being associated to an increase in model relevance. We suggest to carefully choose performance criteria and to use scaling factors.
Mu Xiao, Giuseppe Mascaro, Zhaocheng Wang, Kristen M. Whitney, and Enrique R. Vivoni
Hydrol. Earth Syst. Sci., 26, 5627–5646, https://doi.org/10.5194/hess-26-5627-2022, https://doi.org/10.5194/hess-26-5627-2022, 2022
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As the major water resource in the southwestern United States, the Colorado River is experiencing decreases in naturalized streamflow and is predicted to face severe challenges under future climate scenarios. Here, we demonstrate the value of Earth observing satellites to improve and build confidence in the spatiotemporal simulations from regional hydrologic models for assessing the sensitivity of the Colorado River to climate change and supporting regional water managers.
Christopher Spence, Zhihua He, Kevin R. Shook, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 5555–5575, https://doi.org/10.5194/hess-26-5555-2022, https://doi.org/10.5194/hess-26-5555-2022, 2022
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We learnt how streamflow from small creeks could be altered by wetland removal in the Canadian Prairies, where this practice is pervasive. Every creek basin in the region was placed into one of seven groups. We selected one of these groups and used its traits to simulate streamflow. The model worked well enough so that we could trust the results even if we removed the wetlands. Wetland removal did not change low flow amounts very much, but it doubled high flow and tripled average flow.
Rosanna A. Lane, Gemma Coxon, Jim Freer, Jan Seibert, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 26, 5535–5554, https://doi.org/10.5194/hess-26-5535-2022, https://doi.org/10.5194/hess-26-5535-2022, 2022
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This study modelled the impact of climate change on river high flows across Great Britain (GB). Generally, results indicated an increase in the magnitude and frequency of high flows along the west coast of GB by 2050–2075. In contrast, average flows decreased across GB. All flow projections contained large uncertainties; the climate projections were the largest source of uncertainty overall but hydrological modelling uncertainties were considerable in some regions.
Guangxuan Li, Xi Chen, Zhicai Zhang, Lichun Wang, and Chris Soulsby
Hydrol. Earth Syst. Sci., 26, 5515–5534, https://doi.org/10.5194/hess-26-5515-2022, https://doi.org/10.5194/hess-26-5515-2022, 2022
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We developed a coupled flow–tracer model to understand the effects of passive storage on modeling hydrological function and isotope dynamics in a karst flow system. Models with passive storages show improvement in matching isotope dynamics performance, and the improved performance also strongly depends on the number and location of passive storages. Our results also suggested that the solute transport is primarily controlled by advection and hydrodynamic dispersion in the steep hillslope unit.
Grey S. Nearing, Daniel Klotz, Jonathan M. Frame, Martin Gauch, Oren Gilon, Frederik Kratzert, Alden Keefe Sampson, Guy Shalev, and Sella Nevo
Hydrol. Earth Syst. Sci., 26, 5493–5513, https://doi.org/10.5194/hess-26-5493-2022, https://doi.org/10.5194/hess-26-5493-2022, 2022
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When designing flood forecasting models, it is necessary to use all available data to achieve the most accurate predictions possible. This manuscript explores two basic ways of ingesting near-real-time streamflow data into machine learning streamflow models. The point we want to make is that when working in the context of machine learning (instead of traditional hydrology models that are based on
bio-geophysics), it is not necessary to use complex statistical methods for injecting sparse data.
Xiongpeng Tang, Guobin Fu, Silong Zhang, Chao Gao, Guoqing Wang, Zhenxin Bao, Yanli Liu, Cuishan Liu, and Junliang Jin
Hydrol. Earth Syst. Sci., 26, 5315–5339, https://doi.org/10.5194/hess-26-5315-2022, https://doi.org/10.5194/hess-26-5315-2022, 2022
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In this study, we proposed a new framework that considered the uncertainties of model simulations in quantifying the contribution rate of climate change and human activities to streamflow changes. Then, the Lancang River basin was selected for the case study. The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was mainly human activities.
Bin Yi, Lu Chen, Hansong Zhang, Vijay P. Singh, Ping Jiang, Yizhuo Liu, Hexiang Guo, and Hongya Qiu
Hydrol. Earth Syst. Sci., 26, 5269–5289, https://doi.org/10.5194/hess-26-5269-2022, https://doi.org/10.5194/hess-26-5269-2022, 2022
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An improved GIS-derived distributed unit hydrograph routing method considering time-varying soil moisture was proposed for flow routing. The method considered the changes of time-varying soil moisture and rainfall intensity. The response of underlying surface to the soil moisture content was considered an important factor in this study. The SUH, DUH, TDUH and proposed routing methods (TDUH-MC) were used for flood forecasts, and the simulated results were compared and discussed.
Audrey Douinot, Jean François Iffly, Cyrille Tailliez, Claude Meisch, and Laurent Pfister
Hydrol. Earth Syst. Sci., 26, 5185–5206, https://doi.org/10.5194/hess-26-5185-2022, https://doi.org/10.5194/hess-26-5185-2022, 2022
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The objective of the paper is to highlight the seasonal and singular shift of the transfer time distributions of two catchments (≅10 km2).
Based on 2 years of rainfall and discharge observations, we compare variations in the properties of TTDs with the physiographic characteristics of catchment areas and the eco-hydrological cycle. The paper eventually aims to deduce several factors conducive to particularly rapid and concentrated water transfers, which leads to flash floods.
Alexander Y. Sun, Peishi Jiang, Zong-Liang Yang, Yangxinyu Xie, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 26, 5163–5184, https://doi.org/10.5194/hess-26-5163-2022, https://doi.org/10.5194/hess-26-5163-2022, 2022
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High-resolution river modeling is of great interest to local governments and stakeholders for flood-hazard mitigation. This work presents a physics-guided, machine learning (ML) framework for combining the strengths of high-resolution process-based river network models with a graph-based ML model capable of modeling spatiotemporal processes. Results show that the ML model can approximate the dynamics of the process model with high fidelity, and data fusion further improves the forecasting skill.
Marvin Höge, Andreas Scheidegger, Marco Baity-Jesi, Carlo Albert, and Fabrizio Fenicia
Hydrol. Earth Syst. Sci., 26, 5085–5102, https://doi.org/10.5194/hess-26-5085-2022, https://doi.org/10.5194/hess-26-5085-2022, 2022
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Neural ODEs fuse physics-based models with deep learning: neural networks substitute terms in differential equations that represent the mechanistic structure of the system. The approach combines the flexibility of machine learning with physical constraints for inter- and extrapolation. We demonstrate that neural ODE models achieve state-of-the-art predictive performance while keeping full interpretability of model states and processes in hydrologic modelling over multiple catchments.
Jing Tian, Zhengke Pan, Shenglian Guo, Jiabo Yin, Yanlai Zhou, and Jun Wang
Hydrol. Earth Syst. Sci., 26, 4853–4874, https://doi.org/10.5194/hess-26-4853-2022, https://doi.org/10.5194/hess-26-4853-2022, 2022
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Most of the literature has focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change.
Riccardo Rigon, Giuseppe Formetta, Marialaura Bancheri, Niccolò Tubini, Concetta D'Amato, Olaf David, and Christian Massari
Hydrol. Earth Syst. Sci., 26, 4773–4800, https://doi.org/10.5194/hess-26-4773-2022, https://doi.org/10.5194/hess-26-4773-2022, 2022
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The
Digital Earth(DE) metaphor is very useful for both end users and hydrological modelers. We analyse different categories of models, with the view of making them part of a Digital eARth Twin Hydrology system (called DARTH). We also stress the idea that DARTHs are not models in and of themselves, rather they need to be built on an appropriate information technology infrastructure. It is remarked that DARTHs have to, by construction, support the open-science movement and its ideas.
Hapu Arachchige Prasantha Hapuarachchi, Mohammed Abdul Bari, Aynul Kabir, Mohammad Mahadi Hasan, Fitsum Markos Woldemeskel, Nilantha Gamage, Patrick Daniel Sunter, Xiaoyong Sophie Zhang, David Ewen Robertson, James Clement Bennett, and Paul Martinus Feikema
Hydrol. Earth Syst. Sci., 26, 4801–4821, https://doi.org/10.5194/hess-26-4801-2022, https://doi.org/10.5194/hess-26-4801-2022, 2022
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Methodology for developing an operational 7-day ensemble streamflow forecasting service for Australia is presented. The methodology is tested for 100 catchments to learn the characteristics of different NWP rainfall forecasts, the effect of post-processing, and the optimal ensemble size and bootstrapping parameters. Forecasts are generated using NWP rainfall products post-processed by the CHyPP model, the GR4H hydrologic model, and the ERRIS streamflow post-processor inbuilt in the SWIFT package
Chenhao Chai, Lei Wang, Deliang Chen, Jing Zhou, Hu Liu, Jingtian Zhang, Yuanwei Wang, Tao Chen, and Ruishun Liu
Hydrol. Earth Syst. Sci., 26, 4657–4683, https://doi.org/10.5194/hess-26-4657-2022, https://doi.org/10.5194/hess-26-4657-2022, 2022
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This work quantifies future snow changes and their impacts on hydrology in the upper Salween River (USR) under SSP126 and SSP585 using a cryosphere–hydrology model. Future warm–wet climate is not conducive to the development of snow. The rain–snow-dominated pattern of runoff will shift to a rain-dominated pattern after the 2040s under SSP585 but is unchanged under SSP126. The findings improve our understanding of cryosphere–hydrology processes and can assist water resource management in the USR.
Remko C. Nijzink and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 4575–4585, https://doi.org/10.5194/hess-26-4575-2022, https://doi.org/10.5194/hess-26-4575-2022, 2022
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Most catchments plot close to the empirical Budyko curve, which allows for the estimation of the long-term mean annual evaporation and runoff. The Budyko curve can be defined as a function of a wetness index or a dryness index. We found that differences can occur and that there is an uncertainty due to the different formulations.
Anna Msigwa, Celray James Chawanda, Hans C. Komakech, Albert Nkwasa, and Ann van Griensven
Hydrol. Earth Syst. Sci., 26, 4447–4468, https://doi.org/10.5194/hess-26-4447-2022, https://doi.org/10.5194/hess-26-4447-2022, 2022
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Studies using agro-hydrological models, like the Soil and Water Assessment Tool (SWAT), to map evapotranspiration (ET) do not account for cropping seasons. A comparison between the default SWAT+ set-up (with static land use representation) and a dynamic SWAT+ model set-up (with seasonal land use representation) is made by spatial mapping of the ET. The results show that ET with seasonal representation is closer to remote sensing estimates, giving better performance than ET with static land use.
Jerom P. M. Aerts, Rolf W. Hut, Nick C. van de Giesen, Niels Drost, Willem J. van Verseveld, Albrecht H. Weerts, and Pieter Hazenberg
Hydrol. Earth Syst. Sci., 26, 4407–4430, https://doi.org/10.5194/hess-26-4407-2022, https://doi.org/10.5194/hess-26-4407-2022, 2022
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In recent years gridded hydrological modelling moved into the realm of hyper-resolution modelling (<10 km). In this study, we investigate the effect of varying grid-cell sizes for the wflow_sbm hydrological model. We used a large sample of basins from the CAMELS data set to test the effect that varying grid-cell sizes has on the simulation of streamflow at the basin outlet. Results show that there is no single best grid-cell size for modelling streamflow throughout the domain.
Taher Chegini and Hong-Yi Li
Hydrol. Earth Syst. Sci., 26, 4279–4300, https://doi.org/10.5194/hess-26-4279-2022, https://doi.org/10.5194/hess-26-4279-2022, 2022
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Belowground urban stormwater networks (BUSNs) play a critical and irreplaceable role in preventing or mitigating urban floods. However, they are often not available for urban flood modeling at regional or larger scales. We develop a novel algorithm to estimate existing BUSNs using ubiquitously available aboveground data at large scales based on graph theory. The algorithm has been validated in different urban areas; thus, it is well transferable.
Simon Ricard, Philippe Lucas-Picher, Antoine Thiboult, and François Anctil
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-264, https://doi.org/10.5194/hess-2022-264, 2022
Revised manuscript accepted for HESS
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A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. Results confirm the proposed workflow produces equivalent projections of the seasonal mean flows in comparison to a conventional hydroclimatic modelling approach. The proposed approach supports the participation of end-users in interpreting the impact of climate change on water resources.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 26, 4147–4167, https://doi.org/10.5194/hess-26-4147-2022, https://doi.org/10.5194/hess-26-4147-2022, 2022
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Tracer-aided hydrological models are useful tool to reduce uncertainty of hydrological modeling in cold basins, but there is little guidance on the sampling strategy for isotope analysis, which is important for large mountainous basins. This study evaluated the reliance of the tracer-aided modeling performance on the availability of isotope data in the Yarlung Tsangpo river basin, and provides implications for collecting water isotope data for running tracer-aided hydrological models.
Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-245, https://doi.org/10.5194/hess-2022-245, 2022
Revised manuscript accepted for HESS
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Hybrid models (we call δ models) that embrace the fundamental learning capability of AI but can explain all the physical processes can be powerful. In this paper we assess how they perform when applied in regions not in the training data. δ models rivaled the accuracy of state-of-the-art AI models under the data-dense scenario and even surpassed them for the data-sparse one. They generalize well due to the physical structure. δ models could be ideal candidates for global hydrologic assessments.
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, and Yossi Matias
Hydrol. Earth Syst. Sci., 26, 4013–4032, https://doi.org/10.5194/hess-26-4013-2022, https://doi.org/10.5194/hess-26-4013-2022, 2022
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Early flood warnings are one of the most effective tools to save lives and goods. Machine learning (ML) models can improve flood prediction accuracy but their use in operational frameworks is limited. The paper presents a flood warning system, operational in India and Bangladesh, that uses ML models for forecasting river stage and flood inundation maps and discusses the models' performances. In 2021, more than 100 million flood alerts were sent to people near rivers over an area of 470 000 km2.
Matthias Sprenger, Pilar Llorens, Francesc Gallart, Paolo Benettin, Scott T. Allen, and Jérôme Latron
Hydrol. Earth Syst. Sci., 26, 4093–4107, https://doi.org/10.5194/hess-26-4093-2022, https://doi.org/10.5194/hess-26-4093-2022, 2022
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Our catchment-scale transit time modeling study shows that including stable isotope data on evapotranspiration in addition to the commonly used stream water isotopes helps constrain the model parametrization and reveals that the water taken up by plants has resided longer in the catchment storage than the water leaving the catchment as stream discharge. This finding is important for our understanding of how water is stored and released, which impacts the water availability for plants and humans.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
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This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Bruno Majone, Diego Avesani, Patrick Zulian, Aldo Fiori, and Alberto Bellin
Hydrol. Earth Syst. Sci., 26, 3863–3883, https://doi.org/10.5194/hess-26-3863-2022, https://doi.org/10.5194/hess-26-3863-2022, 2022
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In this work, we introduce a methodology for devising reliable future high streamflow scenarios from climate change simulations. The calibration of a hydrological model is carried out to maximize the probability that the modeled and observed high flow extremes belong to the same statistical population. Application to the Adige River catchment (southeastern Alps, Italy) showed that this procedure produces reliable quantiles of the annual maximum streamflow for use in assessment studies.
Pedro V. G. Batista, Peter Fiener, Simon Scheper, and Christine Alewell
Hydrol. Earth Syst. Sci., 26, 3753–3770, https://doi.org/10.5194/hess-26-3753-2022, https://doi.org/10.5194/hess-26-3753-2022, 2022
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Patchy agricultural landscapes have a large number of small fields, which are separated by linear features such as roads and field borders. When eroded sediments are transported out of the agricultural fields by surface runoff, these features can influence sediment connectivity. By use of measured data and a simulation model, we demonstrate how a dense road network (and its drainage system) facilitates sediment transport from fields to water courses in a patchy Swiss agricultural catchment.
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
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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.
Aurélien Beaufort, Jacob S. Diamond, Eric Sauquet, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 3477–3495, https://doi.org/10.5194/hess-26-3477-2022, https://doi.org/10.5194/hess-26-3477-2022, 2022
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We developed one of the largest stream temperature databases to calculate a simple, ecologically relevant metric – the thermal peak – that captures the magnitude of summer thermal extremes. Using statistical models, we extrapolated the thermal peak to nearly every stream in France, finding the hottest thermal peaks along large rivers without forested riparian zones and groundwater inputs. Air temperature was a poor proxy for the thermal peak, highlighting the need to grow monitoring networks.
Ulises M. Sepúlveda, Pablo A. Mendoza, Naoki Mizukami, and Andrew J. Newman
Hydrol. Earth Syst. Sci., 26, 3419–3445, https://doi.org/10.5194/hess-26-3419-2022, https://doi.org/10.5194/hess-26-3419-2022, 2022
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This paper characterizes parameter sensitivities across more than 5500 grid cells for a commonly used macroscale hydrological model, including a suite of eight performance metrics and 43 soil, vegetation and snow parameters. The results show that the model is highly overparameterized and, more importantly, help to provide guidance on the most relevant parameters for specific target processes across diverse climatic types.
Jonathan M. Frame, Frederik Kratzert, Daniel Klotz, Martin Gauch, Guy Shalev, Oren Gilon, Logan M. Qualls, Hoshin V. Gupta, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 26, 3377–3392, https://doi.org/10.5194/hess-26-3377-2022, https://doi.org/10.5194/hess-26-3377-2022, 2022
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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 with traditional models, even when extreme events were not included in the training set.
Sebastian A. Krogh, Lucia Scaff, James W. Kirchner, Beatrice Gordon, Gary Sterle, and Adrian Harpold
Hydrol. Earth Syst. Sci., 26, 3393–3417, https://doi.org/10.5194/hess-26-3393-2022, https://doi.org/10.5194/hess-26-3393-2022, 2022
Short summary
Short summary
We present a new way to detect snowmelt using daily cycles in streamflow driven by solar radiation. Results show that warmer sites have earlier and more intermittent snowmelt than colder sites, and the timing of early snowmelt events is strongly correlated with the timing of streamflow volume. A space-for-time substitution shows greater sensitivity of streamflow timing to climate change in colder rather than in warmer places, which is then contrasted with land surface simulations.
Wouter J. M. Knoben and Diana Spieler
Hydrol. Earth Syst. Sci., 26, 3299–3314, https://doi.org/10.5194/hess-26-3299-2022, https://doi.org/10.5194/hess-26-3299-2022, 2022
Short summary
Short summary
This paper introduces educational materials that can be used to teach students about model structure uncertainty in hydrological modelling. There are many different hydrological models and differences between these models impact their usefulness in different places. Such models are often used to support decision making about water resources and to perform hydrological science, and it is thus important for students to understand that model choice matters.
Leonie Kiewiet, Ernesto Trujillo, Andrew Hedrick, Scott Havens, Katherine Hale, Mark Seyfried, Stephanie Kampf, and Sarah E. Godsey
Hydrol. Earth Syst. Sci., 26, 2779–2796, https://doi.org/10.5194/hess-26-2779-2022, https://doi.org/10.5194/hess-26-2779-2022, 2022
Short summary
Short summary
Climate change affects precipitation phase, which can propagate into changes in streamflow timing and magnitude. This study examines how variations in rainfall and snowmelt affect discharge. We found that annual discharge and stream cessation depended on the magnitude and timing of rainfall and snowmelt and on the snowpack melt-out date. This highlights the importance of precipitation timing and emphasizes the need for spatiotemporally distributed simulations of snowpack and rainfall dynamics.
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...
