Articles | Volume 24, issue 1
https://doi.org/10.5194/hess-24-75-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-75-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jan 2020
Research article |
| 08 Jan 2020
| 08 Jan 2020
A global-scale evaluation of extreme event uncertainty in the eartH2Observe project
Centre for Ecology & Hydrology, Maclean Building, Wallingford, OX10 8BB, UK
Eleanor M. Blyth
Centre for Ecology & Hydrology, Maclean Building, Wallingford, OX10 8BB, UK
Alberto Martínez-de la Torre
Centre for Ecology & Hydrology, Maclean Building, Wallingford, OX10 8BB, UK
Ted I. E. Veldkamp
Institute for Environmental Studies, Vrije Universiteit Amsterdam,
1081 HV Amsterdam, the Netherlands
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Hollie M. Cooper, Emma Bennett, James Blake, Eleanor Blyth, David Boorman, Elizabeth Cooper, Jonathan Evans, Matthew Fry, Alan Jenkins, Ross Morrison, Daniel Rylett, Simon Stanley, Magdalena Szczykulska, Emily Trill, Vasileios Antoniou, Anne Askquith-Ellis, Lucy Ball, Milo Brooks, Michael A. Clarke, Nicholas Cowan, Alexander Cumming, Philip Farrand, Olivia Hitt, William Lord, Peter Scarlett, Oliver Swain, Jenna Thornton, Alan Warwick, and Ben Winterbourn
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COSMOS-UK is a UK network of environmental monitoring sites, with a focus on measuring field-scale soil moisture. Each site includes soil and hydrometeorological sensors providing data including air temperature, humidity, net radiation, neutron counts, snow water equivalent, and potential evaporation. These data can provide information for science, industry, and agriculture by improving existing understanding and data products in fields such as water resources, space sciences, and biodiversity.
Simon J. Dadson, Eleanor Blyth, Douglas Clark, Helen Davies, Richard Ellis, Huw Lewis, Toby Marthews, and Ponnambalan Rameshwaran
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-60, https://doi.org/10.5194/hess-2021-60, 2021
Manuscript not accepted for further review
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Flood prediction helps national and regional planning and real-time flood response. In this study we apply and test a new way to make wide area predictions of flooding which can be combined with weather forecasting and climate models to give faster predictions of flooded areas. By simplifying the detailed floodplain topography we can keep track of the fraction of land flooded for hazard mapping purposes. When tested this approach accurately reproduces benchmark datasets for England.
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
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Anaïs Couasnon, Dirk Eilander, Sanne Muis, Ted I. E. Veldkamp, Ivan D. Haigh, Thomas Wahl, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 20, 489–504, https://doi.org/10.5194/nhess-20-489-2020, https://doi.org/10.5194/nhess-20-489-2020, 2020
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Alberto Martínez-de la Torre and Gonzalo Miguez-Macho
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Huw W. Lewis, Juan Manuel Castillo Sanchez, Alex Arnold, Joachim Fallmann, Andrew Saulter, Jennifer Graham, Mike Bush, John Siddorn, Tamzin Palmer, Adrian Lock, John Edwards, Lucy Bricheno, Alberto Martínez-de la Torre, and James Clark
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Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
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Alberto Martínez-de la Torre, Eleanor M. Blyth, and Graham P. Weedon
Geosci. Model Dev., 12, 765–784, https://doi.org/10.5194/gmd-12-765-2019, https://doi.org/10.5194/gmd-12-765-2019, 2019
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Land–surface interactions with the atmosphere are key for weather and climate modelling studies, both in research and in the operational systems that provide scientific tools for decision makers. Regional assessments will be influenced by the characteristics of the land. We improved the representation of river flows in Great Britain by including a dependency on the terrain slope. This development will be reflected not only in river flows, but in the whole water cycle represented by the model.
Anouk I. Gevaert, Ted I. E. Veldkamp, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 4649–4665, https://doi.org/10.5194/hess-22-4649-2018, https://doi.org/10.5194/hess-22-4649-2018, 2018
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Drought is a natural hazard that has severe environmental and socioeconomic impacts around the globe. Here, we quantified the time taken for drought to propagate from precipitation droughts to soil moisture and streamflow droughts. Results show that propagation timescales are strongly related to climate type, with fast responses in tropical regions and slow responses in arid regions. Insight into the timescales of drought propagation globally may help improve seasonal drought forecasting.
Gaby J. Gründemann, Micha Werner, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 22, 4667–4683, https://doi.org/10.5194/hess-22-4667-2018, https://doi.org/10.5194/hess-22-4667-2018, 2018
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Flooding in vulnerable and data-sparse regions such as the Limpopo basin in Southern Africa is a key concern. Data available to local flood managers are often limited, inconsistent or asymmetrically distributed. We demonstrate that freely available global datasets are well suited to provide essential information. Despite the poor performance of simulated discharges, these datasets hold potential in identifying damaging flood events, particularly for higher-resolution datasets and larger basins.
Eleanor M. Blyth, Alberto Martinez-de la Torre, and Emma L. Robinson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-153, https://doi.org/10.5194/hess-2018-153, 2018
Manuscript not accepted for further review
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In a warming climate, the water budget of the land is subject to varying forces such as increasing evaporative demand, mainly through the increased temperature, and changes to the precipitation, which might go up or down. Using a verified, physically based model over with 55 years, an analysis of the water budget demonstrates that Great Britain is getting warmer and wetter. We demonstrated that amount of water captured on the trees has an impact on the overall trend.
Alberto Martínez-de la Torre, Eleanor M. Blyth, and Graham P. Weedon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-750, https://doi.org/10.5194/hess-2017-750, 2018
Manuscript not accepted for further review
Short summary
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Land surface interactions with the atmosphere are key for weather and climate modelling studies, both in research and in the operational systems that provide scientific tools for decision makers. Regional assessments will be influenced by the characteristics of the land. We improved the representation of Great Britain river flows by including a dependency on terrain slope. This development will be reflected not only in river flows, but in the whole water cycle represented by the model/system.
Konstantinos Bischiniotis, Bart van den Hurk, Brenden Jongman, Erin Coughlan de Perez, Ted Veldkamp, Hans de Moel, and Jeroen Aerts
Nat. Hazards Earth Syst. Sci., 18, 271–285, https://doi.org/10.5194/nhess-18-271-2018, https://doi.org/10.5194/nhess-18-271-2018, 2018
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Preparedness activities and flood forecasting have received increasing attention and have led towards new science-based early warning systems. Understanding the flood triggering mechanisms will result in increasing warning lead times, providing sufficient time for early action. Findings of this study indicate that the consideration of short- and long-term antecedent conditions can be used by humanitarian organizations and decision makers for improved flood risk management.
Huw W. Lewis, Juan Manuel Castillo Sanchez, Jennifer Graham, Andrew Saulter, Jorge Bornemann, Alex Arnold, Joachim Fallmann, Chris Harris, David Pearson, Steven Ramsdale, Alberto Martínez-de la Torre, Lucy Bricheno, Eleanor Blyth, Victoria A. Bell, Helen Davies, Toby R. Marthews, Clare O'Neill, Heather Rumbold, Enda O'Dea, Ashley Brereton, Karen Guihou, Adrian Hines, Momme Butenschon, Simon J. Dadson, Tamzin Palmer, Jason Holt, Nick Reynard, Martin Best, John Edwards, and John Siddorn
Geosci. Model Dev., 11, 1–42, https://doi.org/10.5194/gmd-11-1-2018, https://doi.org/10.5194/gmd-11-1-2018, 2018
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Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
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The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Joost Iwema, Rafael Rosolem, Mostaquimur Rahman, Eleanor Blyth, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 21, 2843–2861, https://doi.org/10.5194/hess-21-2843-2017, https://doi.org/10.5194/hess-21-2843-2017, 2017
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We investigated whether the simulation of water flux from the land surface to the atmosphere (using the Joint UK Land Environment Simulator model) could be improved by replacing traditional soil moisture sensor data with data from the more novel Cosmic-Ray Neutron soil moisture sensor. Despite observed differences between the two types of soil moisture measurement data, we found no substantial differences in improvement in water flux estimation, based on multiple calibration experiments.
Mook Bangalore, Andrew Smith, and Ted Veldkamp
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-100, https://doi.org/10.5194/nhess-2017-100, 2017
Preprint withdrawn
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This paper examines the exposure to current and future flooding in Vietnam and in Ho Chi Minh City, using new high-resolution flood hazard maps and spatial socioeconomic data on poverty. While floods already expose a third of the population today, climate change impacts may increase exposure by more than 20 %, with significant implications for poor households in urban areas. This paper provides implications regarding infrastructure development, land use planning, and strategies to manage floods.
Emma L. Robinson, Eleanor M. Blyth, Douglas B. Clark, Jon Finch, and Alison C. Rudd
Hydrol. Earth Syst. Sci., 21, 1189–1224, https://doi.org/10.5194/hess-21-1189-2017, https://doi.org/10.5194/hess-21-1189-2017, 2017
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We present a dataset of daily meteorological variables at 1 km resolution over Great Britain (1961–2012), calculated by spatially downscaling coarser resolution datasets, adjusting for local topography, along with derived potential evapotranspiration (PET). A positive trend in PET was identified and attributed to trends in the meteorology. The trend in PET is particularly driven by decreasing relative humidity and increasing shortwave radiation in the spring.
T. I. E. Veldkamp, S. Eisner, Y. Wada, J. C. J. H. Aerts, and P. J. Ward
Hydrol. Earth Syst. Sci., 19, 4081–4098, https://doi.org/10.5194/hess-19-4081-2015, https://doi.org/10.5194/hess-19-4081-2015, 2015
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Freshwater shortage is one of the most important risks, partially driven by climate variability. Here we present a first global scale sensitivity assessment of water scarcity events to El Niño-Southern Oscillation, the most dominant climate variability signal. Given the found correlations, covering a large share of the global land area, and seen the developments of water scarcity impacts under changing socioeconomic conditions, we show that there is large potential for ENSO-based risk reduction.
T. R. Marthews, S. J. Dadson, B. Lehner, S. Abele, and N. Gedney
Hydrol. Earth Syst. Sci., 19, 91–104, https://doi.org/10.5194/hess-19-91-2015, https://doi.org/10.5194/hess-19-91-2015, 2015
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Modelling land surface water flow is of critical importance in the context of climate change predictions. Many approaches are based on the popular hydrology model TOPMODEL, and the most important parameter of this model is the well-known topographic index. Here we present new, higher-resolution parameter maps of the topographic index, which are ideal for land surface modelling applications and show important improvements on the previous standard maps from HYDRO1k.
E. M. Blyth, R. Oliver, and N. Gedney
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-17967-2014, https://doi.org/10.5194/bgd-11-17967-2014, 2014
Revised manuscript has not been submitted
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By studying patterns of soil carbon in the Northern Latitudes alongside vegetation, soil temperatures and wetlands, it is apparent that the main cause of high values of soil carbon is the presence of saturated soils (wetlands). This link can only be modelled if the wetlands are assumed to completely suppress soil respiration. It is important to be able to model wetlands and their effect on soil carbon if we are to understand the long term future of the soil-carbon store in Northern Latitudes.
M. Réjou-Méchain, H. C. Muller-Landau, M. Detto, S. C. Thomas, T. Le Toan, S. S. Saatchi, J. S. Barreto-Silva, N. A. Bourg, S. Bunyavejchewin, N. Butt, W. Y. Brockelman, M. Cao, D. Cárdenas, J.-M. Chiang, G. B. Chuyong, K. Clay, R. Condit, H. S. Dattaraja, S. J. Davies, A. Duque, S. Esufali, C. Ewango, R. H. S. Fernando, C. D. Fletcher, I. A. U. N. Gunatilleke, Z. Hao, K. E. Harms, T. B. Hart, B. Hérault, R. W. Howe, S. P. Hubbell, D. J. Johnson, D. Kenfack, A. J. Larson, L. Lin, Y. Lin, J. A. Lutz, J.-R. Makana, Y. Malhi, T. R. Marthews, R. W. McEwan, S. M. McMahon, W. J. McShea, R. Muscarella, A. Nathalang, N. S. M. Noor, C. J. Nytch, A. A. Oliveira, R. P. Phillips, N. Pongpattananurak, R. Punchi-Manage, R. Salim, J. Schurman, R. Sukumar, H. S. Suresh, U. Suwanvecho, D. W. Thomas, J. Thompson, M. Uríarte, R. Valencia, A. Vicentini, A. T. Wolf, S. Yap, Z. Yuan, C. E. Zartman, J. K. Zimmerman, and J. Chave
Biogeosciences, 11, 6827–6840, https://doi.org/10.5194/bg-11-6827-2014, https://doi.org/10.5194/bg-11-6827-2014, 2014
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Forest carbon mapping may greatly reduce uncertainties in the global carbon budget. Accuracy of such maps depends however on the quality of field measurements. Using 30 large forest plots, we found large local spatial variability in biomass. When field calibration plots are smaller than the remote sensing pixels, this high local spatial variability results in an underestimation of the variance in biomass.
S. J. Sutanto, B. van den Hurk, P. A. Dirmeyer, S. I. Seneviratne, T. Röckmann, K. E. Trenberth, E. M. Blyth, J. Wenninger, and G. Hoffmann
Hydrol. Earth Syst. Sci., 18, 2815–2827, https://doi.org/10.5194/hess-18-2815-2014, https://doi.org/10.5194/hess-18-2815-2014, 2014
R. Lasage, T. I. E. Veldkamp, H. de Moel, T. C. Van, H. L. Phi, P. Vellinga, and J. C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 14, 1441–1457, https://doi.org/10.5194/nhess-14-1441-2014, https://doi.org/10.5194/nhess-14-1441-2014, 2014
T. R. Marthews, C. A. Quesada, D. R. Galbraith, Y. Malhi, C. E. Mullins, M. G. Hodnett, and I. Dharssi
Geosci. Model Dev., 7, 711–723, https://doi.org/10.5194/gmd-7-711-2014, https://doi.org/10.5194/gmd-7-711-2014, 2014
Related subject area
Subject: Global hydrology | Techniques and Approaches: Uncertainty analysis
Multi-variable parameter estimation for a global hydrological model: Comparison and evaluation of three ensemble-based calibration methods for the Mississippi River basin
Information content of soil hydrology in a west Amazon watershed as informed by GRACE
Diagnostic evaluation of river discharge into the Arctic Ocean and its impact on oceanic volume transports
The 63-year changes in annual streamflow volumes across Europe with a focus on the Mediterranean basin
Multivariable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL (Institute Pierre Simon Laplace) climate model
Implications of model selection: a comparison of publicly available, conterminous US-extent hydrologic component estimates
Historical and future changes in global flood magnitude – evidence from a model–observation investigation
Assessment of precipitation error propagation in multi-model global water resource reanalysis
The potential of global reanalysis datasets in identifying flood events in Southern Africa
Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model
Global change in streamflow extremes under climate change over the 21st century
Have precipitation extremes and annual totals been increasing in the world's dry regions over the last 60 years?
Sensitivity of future continental United States water deficit projections to general circulation models, the evapotranspiration estimation method, and the greenhouse gas emission scenario
Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use
Evaluating uncertainty in estimates of soil moisture memory with a reverse ensemble approach
Flood and drought hydrologic monitoring: the role of model parameter uncertainty
Sensitivity of simulated global-scale freshwater fluxes and storages to input data, hydrological model structure, human water use and calibration
Climate change impacts on runoff in West Africa: a review
Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis
Disinformative data in large-scale hydrological modelling
The impact of climate mitigation on projections of future drought
Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data
Monitoring and quantifying future climate projections of dryness and wetness extremes: SPI bias
Improving runoff estimates from regional climate models: a performance analysis in Spain
A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models
Error characterisation of global active and passive microwave soil moisture datasets
Assessment of soil moisture fields from imperfect climate models with uncertain satellite observations
Petra Döll, H. M. Mehedi Hasan, Kerstin Schulze, Helena Gerdener, Lara Börger, Somayeh Shadkam, Sebastian Ackermann, Seyed-Mohammad Hosseini-Moghari, Hannes Müller Schmied, Andreas Güntner, and Jürgen Kusche
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-18, https://doi.org/10.5194/hess-2023-18, 2023
Revised manuscript accepted for HESS
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For the pilot region Mississippi River basin, we explored three model calibration approaches for using both streamflow and total water storage anomaly (TWSA) observations to adjust parameter sets of a global hydrological model. We developed a method for considering the observation uncertainties to determine not only optimal but also behavioral parameter sets and model output uncertainty. Model performance was improved but trade-offs between optimal fits to streamflow and TWSA may be large.
Elias C. Massoud, A. Anthony Bloom, Marcos Longo, John T. Reager, Paul A. Levine, and John R. Worden
Hydrol. Earth Syst. Sci., 26, 1407–1423, https://doi.org/10.5194/hess-26-1407-2022, https://doi.org/10.5194/hess-26-1407-2022, 2022
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The water balance on river basin scales depends on a number of soil physical processes. Gaining information on these quantities using observations is a key step toward improving the skill of land surface hydrology models. In this study, we use data from the Gravity Recovery and Climate Experiment (NASA-GRACE) to inform and constrain these hydrologic processes. We show that our model is able to simulate the land hydrologic cycle for a watershed in the Amazon from January 2003 to December 2012.
Susanna Winkelbauer, Michael Mayer, Vanessa Seitner, Ervin Zsoter, Hao Zuo, and Leopold Haimberger
Hydrol. Earth Syst. Sci., 26, 279–304, https://doi.org/10.5194/hess-26-279-2022, https://doi.org/10.5194/hess-26-279-2022, 2022
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We evaluate Arctic river discharge using in situ observations and state-of-the-art reanalyses, inter alia the most recent Global Flood Awareness System (GloFAS) river discharge reanalysis version 3.1. Furthermore, we combine reanalysis data, in situ observations, ocean reanalyses, and satellite data and use a Lagrangian optimization scheme to close the Arctic's volume budget on annual and seasonal scales, resulting in one reliable and up-to-date estimate of every volume budget term.
Daniele Masseroni, Stefania Camici, Alessio Cislaghi, Giorgio Vacchiano, Christian Massari, and Luca Brocca
Hydrol. Earth Syst. Sci., 25, 5589–5601, https://doi.org/10.5194/hess-25-5589-2021, https://doi.org/10.5194/hess-25-5589-2021, 2021
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We evaluate 63 years of changes in annual streamflow volume across Europe, using a data set of more than 3000 stations, with a special focus on the Mediterranean basin. The results show decreasing (increasing) volumes in the southern (northern) regions. These trends are strongly consistent with the changes in temperature and precipitation.
Hiroki Mizuochi, Agnès Ducharne, Frédérique Cheruy, Josefine Ghattas, Amen Al-Yaari, Jean-Pierre Wigneron, Vladislav Bastrikov, Philippe Peylin, Fabienne Maignan, and Nicolas Vuichard
Hydrol. Earth Syst. Sci., 25, 2199–2221, https://doi.org/10.5194/hess-25-2199-2021, https://doi.org/10.5194/hess-25-2199-2021, 2021
Samuel Saxe, William Farmer, Jessica Driscoll, and Terri S. Hogue
Hydrol. Earth Syst. Sci., 25, 1529–1568, https://doi.org/10.5194/hess-25-1529-2021, https://doi.org/10.5194/hess-25-1529-2021, 2021
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We compare simulated values from 47 models estimating surface water over the USA. Results show that model uncertainty is substantial over much of the conterminous USA and especially high in the west. Applying the studied models to a simple water accounting equation shows that model selection can significantly affect research results. This paper concludes that multimodel ensembles help to best represent uncertainty in conclusions and suggest targeted research efforts in arid regions.
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020, https://doi.org/10.5194/hess-24-1543-2020, 2020
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We presented a global comparison between observed and simulated trends in a flood index over the 1971–2005 period using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high-flood-risk areas, however, are under-sampled by the current global streamflow databases.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, https://doi.org/10.5194/hess-23-1973-2019, 2019
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This study investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modeling, in global water resource reanalysis. Analysis is based on ensemble hydrologic simulations for a period of 11 years based on six global hydrologic models and five precipitation datasets. Results show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure.
Gaby J. Gründemann, Micha Werner, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 22, 4667–4683, https://doi.org/10.5194/hess-22-4667-2018, https://doi.org/10.5194/hess-22-4667-2018, 2018
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Flooding in vulnerable and data-sparse regions such as the Limpopo basin in Southern Africa is a key concern. Data available to local flood managers are often limited, inconsistent or asymmetrically distributed. We demonstrate that freely available global datasets are well suited to provide essential information. Despite the poor performance of simulated discharges, these datasets hold potential in identifying damaging flood events, particularly for higher-resolution datasets and larger basins.
Emiliano Gelati, Bertrand Decharme, Jean-Christophe Calvet, Marie Minvielle, Jan Polcher, David Fairbairn, and Graham P. Weedon
Hydrol. Earth Syst. Sci., 22, 2091–2115, https://doi.org/10.5194/hess-22-2091-2018, https://doi.org/10.5194/hess-22-2091-2018, 2018
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We compared land surface model simulations forced by several meteorological datasets with observations over the Euro-Mediterranean area, for the 1979–2012 period. Precipitation was the most uncertain forcing variable. The impacts of forcing uncertainty were larger on the mean and standard deviation rather than the timing, shape and inter-annual variability of simulated discharge. Simulated leaf area index and surface soil moisture were relatively insensitive to these uncertainties.
Behzad Asadieh and Nir Y. Krakauer
Hydrol. Earth Syst. Sci., 21, 5863–5874, https://doi.org/10.5194/hess-21-5863-2017, https://doi.org/10.5194/hess-21-5863-2017, 2017
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Multi-model analysis of global streamflow extremes for the 20th and 21st centuries under two warming scenarios is performed. About 37 and 43 % of global land areas show potential for increases in flood and drought events. Nearly 10 % of global land areas, holding around 30 % of world’s population, reflect a potentially worsening hazard of flood and drought. A significant increase in streamflow of the regions near and above the Arctic Circle, and decrease in subtropical arid areas, is projected.
Sebastian Sippel, Jakob Zscheischler, Martin Heimann, Holger Lange, Miguel D. Mahecha, Geert Jan van Oldenborgh, Friederike E. L. Otto, and Markus Reichstein
Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, https://doi.org/10.5194/hess-21-441-2017, 2017
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The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Seungwoo Chang, Wendy D. Graham, Syewoon Hwang, and Rafael Muñoz-Carpena
Hydrol. Earth Syst. Sci., 20, 3245–3261, https://doi.org/10.5194/hess-20-3245-2016, https://doi.org/10.5194/hess-20-3245-2016, 2016
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Projecting water deficit depends on how researchers combine possible future climate scenarios such as general circulation models (GCMs), evapotranspiration estimation method (ET), and greenhouse gas emission scenarios. Using global sensitivity analysis, we found the relative contribution of each of these factors to projecting future water deficit and the choice of ET estimation method are as important as the choice of GCM, and greenhouse gas emission scenario is less influential than the others.
Hannes Müller Schmied, Linda Adam, Stephanie Eisner, Gabriel Fink, Martina Flörke, Hyungjun Kim, Taikan Oki, Felix Theodor Portmann, Robert Reinecke, Claudia Riedel, Qi Song, Jing Zhang, and Petra Döll
Hydrol. Earth Syst. Sci., 20, 2877–2898, https://doi.org/10.5194/hess-20-2877-2016, https://doi.org/10.5194/hess-20-2877-2016, 2016
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The assessment of water balance components of the global land surface by means of hydrological models is affected by large uncertainties, in particular related to meteorological forcing. We analyze the effect of five state-of-the-art forcings on water balance components at different spatial and temporal scales modeled with WaterGAP. Furthermore, the dominant effect (precipitation/human alteration) for long-term changes in river discharge is assessed.
Dave MacLeod, Hannah Cloke, Florian Pappenberger, and Antje Weisheimer
Hydrol. Earth Syst. Sci., 20, 2737–2743, https://doi.org/10.5194/hess-20-2737-2016, https://doi.org/10.5194/hess-20-2737-2016, 2016
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Soil moisture memory is a key aspect of seasonal climate predictions, through feedback between the land surface and the atmosphere. Estimates have been made of the length of soil moisture memory; however, we show here how estimates of memory show large variation with uncertain model parameters. Explicit representation of model uncertainty may then improve the realism of simulations and seasonal climate forecasts.
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
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Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
H. Müller Schmied, S. Eisner, D. Franz, M. Wattenbach, F. T. Portmann, M. Flörke, and P. Döll
Hydrol. Earth Syst. Sci., 18, 3511–3538, https://doi.org/10.5194/hess-18-3511-2014, https://doi.org/10.5194/hess-18-3511-2014, 2014
P. Roudier, A. Ducharne, and L. Feyen
Hydrol. Earth Syst. Sci., 18, 2789–2801, https://doi.org/10.5194/hess-18-2789-2014, https://doi.org/10.5194/hess-18-2789-2014, 2014
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
A. Kauffeldt, S. Halldin, A. Rodhe, C.-Y. Xu, and I. K. Westerberg
Hydrol. Earth Syst. Sci., 17, 2845–2857, https://doi.org/10.5194/hess-17-2845-2013, https://doi.org/10.5194/hess-17-2845-2013, 2013
I. H. Taylor, E. Burke, L. McColl, P. D. Falloon, G. R. Harris, and D. McNeall
Hydrol. Earth Syst. Sci., 17, 2339–2358, https://doi.org/10.5194/hess-17-2339-2013, https://doi.org/10.5194/hess-17-2339-2013, 2013
H. Xie, L. Longuevergne, C. Ringler, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 16, 3083–3099, https://doi.org/10.5194/hess-16-3083-2012, https://doi.org/10.5194/hess-16-3083-2012, 2012
F. Sienz, O. Bothe, and K. Fraedrich
Hydrol. Earth Syst. Sci., 16, 2143–2157, https://doi.org/10.5194/hess-16-2143-2012, https://doi.org/10.5194/hess-16-2143-2012, 2012
D. González-Zeas, L. Garrote, A. Iglesias, and A. Sordo-Ward
Hydrol. Earth Syst. Sci., 16, 1709–1723, https://doi.org/10.5194/hess-16-1709-2012, https://doi.org/10.5194/hess-16-1709-2012, 2012
S. N. Gosling, R. G. Taylor, N. W. Arnell, and M. C. Todd
Hydrol. Earth Syst. Sci., 15, 279–294, https://doi.org/10.5194/hess-15-279-2011, https://doi.org/10.5194/hess-15-279-2011, 2011
W. A. Dorigo, K. Scipal, R. M. Parinussa, Y. Y. Liu, W. Wagner, R. A. M. de Jeu, and V. Naeimi
Hydrol. Earth Syst. Sci., 14, 2605–2616, https://doi.org/10.5194/hess-14-2605-2010, https://doi.org/10.5194/hess-14-2605-2010, 2010
G. Schumann, D. J. Lunt, P. J. Valdes, R. A. M. de Jeu, K. Scipal, and P. D. Bates
Hydrol. Earth Syst. Sci., 13, 1545–1553, https://doi.org/10.5194/hess-13-1545-2009, https://doi.org/10.5194/hess-13-1545-2009, 2009
Cited articles
Ali, H. and Mishra, V.: Contrasting response of rainfall extremes to increase in surface air and dewpoint temperatures at urban locations in India, Sci. Rep.-Uk, 7, 1228, https://doi.org/10.1038/S41598-017-01306-1, 2017.
Arduini, G., Boussetta, S., Dutra, E., and Martínez de la Torre, A.:
Report on the Ensemble Water Resources Reanalysis, available at: http://earth2observe.eu/files/Public Deliverables/D5.4 - Report on the Ensemble-based Multi-Model Water Resources
(last access: 7 January 2020), 2017.
Balsamo, G., Viterbo, P., Beljaars, A., van den Hurk, B., Hirschi, M., Betts, A. K., and Scipal, K.: A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009.
Bates, B., Kundzewicz, Z. W., Wu, S., and Palutikof, J.: Climate Change and
Water, IPCC Technical Paper 6, IPCC, Geneva, Switzerland, 2008.
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25∘ global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017a.
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M.,
Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, 2017b.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N.,
Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C.
S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES),
model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bhuiyan, M. A. E., Nikolopoulos, E. I., Anagnostou, E. N., Quintana-Segui, P., and Barella-Ortiz, A.: A nonparametric statistical technique for combining global precipitation datasets: development and hydrological evaluation over the Iberian Peninsula, Hydrol. Earth Syst. Sci., 22, 1371–1389, https://doi.org/10.5194/hess-22-1371-2018, 2018.
Bierkens, M. F. P.: Global hydrology 2015: State, trends, and directions,
Water Resour. Res., 51, 4923–4947, https://doi.org/10.1002/2015WR017173, 2015.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M.
J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O.,
Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes
and vegetation dynamics, Geosci. Model Dev., 4, 701–722,
https://doi.org/10.5194/gmd-4-701-2011, 2011.
Dadson, S. J., Hall, J. W., Murgatroyd, A., Acreman, M., Bates, P., Beven, K., Heathwaite, L., Holden, J., Holman, I. P., Lane, S. N., O'Connell, E.,
Penning-Rowsell, E., Reynard, N., Sear, D., Thorne, C., and Wilby, R.: A
restatement of the natural science evidence concerning catchment-based
`natural' flood management in the UK, P. Roy. Soc. A, 473, 2199, https://doi.org/10.1098/Rspa.2016.0706, 2017.
Decharme, B., Boone, A., Delire, C., and Noilhan, J.: Local evaluation of
the Interaction between Soil Biosphere Atmosphere soil multilayer diffusion
scheme using four pedotransfer functions, J. Geophys. Res.-Atmos., 116,
D20126, https://doi.org/10.1029/2011jd016002, 2011.
Decharme, B., Martin, E., and Faroux, S.: Reconciling soil thermal and hydrological lower boundary conditions in land surface models, J. Geophys.
Res.-Atmos., 118, 7819–7834, https://doi.org/10.1002/jgrd.50631, 2013.
Derin, Y., Anagnostou, E., Berne, A., Borga, M., Boudevillain, B., Buytaert,
W., Chang, C. H., Delrieu, G., Hong, Y., Hsu, Y. C., Lavado-Casimiro, W.,
Manz, B., Moges, S., Nikolopoulos, E. I., Sahlu, D., Salerno, F., Rodriguez-Sanchez, J. P., Vergara, H. J., and Yilmaz, K. K.: Multiregional
Satellite Precipitation Products Evaluation over Complex Terrain, J. Hydrometeorol., 17, 1817–1836, 2016.
d'Orgeval, T., Polcher, J., and de Rosnay, P.: Sensitivity of the West African hydrological cycle in ORCHIDEE to infiltration processes, Hydrol.
Earth Syst. Sci., 12, 1387–1401, https://doi.org/10.5194/hess-12-1387-2008, 2008.
Dorigo, W., Levizzani, V., Aires, F., Cattani, E., Claud, C., de Jeu, R., Groom, S., Jindrova, M., Laviola, S., Marzano, F. S., Melotte, I., Miguez Macho, G., Panegrossi, G., Westerhoff, R., and Winsemius, H.: Earth Observation Dataset Inventory, Earth2Observe Report D3.1, Earth2Observe, the Netherlands, 2014.
Dutra, E., Balsamo, G., Calvet, J., Minvielle, M., Eisner, S., Fink, G.,
Peßenteiner, S., Orth, R., Burke, S., van Dijk, A., Polcher, J., Beck, H., and Martínez-de la Torre, A.: Report on the current state-of-the-art Water Resources Reanalysis, available at: http://earth2observe.eu/files/Public Deliverables/D5.1_Report on the WRR1 tier1.pdf (last access: 7 January 2020), 2015.
Ehsan Bhuiyan, M. A., Nikolopoulos, E. I., Anagnostou, E. N., Polcher, J., Albergel, C., Dutra, E., Fink, G., Martínez-de la Torre, A., and Munier, S.: Assessment of precipitation error propagation in multi-model global water resource reanalysis, Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, 2019.
He, J., Deser, C., and Soden, B. J.: Atmospheric and Oceanic Origins of Tropical Precipitation Variability, J. Climate, 30, 3197–3217,
https://doi.org/10.1175/Jcli-D-16-0714.1, 2017.
Hirpa, F. A., Salamon, P., Alfieri, L., Thielen-del Pozo, J., Zsoter, E., and Pappenberger, F.: The Effect of Reference Climatology on Global Flood
Forecasting, J. Hydrometeorol., 17, 1131–1145, https://doi.org/10.1175/Jhm-D-15-0044.1, 2016.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G. J., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F., and Wolff, D. B.: The TRMM
multisatellite precipitation analysis (TMPA): Quasi-global, multiyear,
combined-sensor precipitation estimates at fine scales, J. Hydrometeorol., 8, 38–55, https://doi.org/10.1175/JHM560.1, 2007.
Huntingford, C., Zelazowski, P., Galbraith, D., Mercado, L. M., Sitch, S.,
Fisher, R., Lomas, M., Walker, A. P., Jones, C. D., Booth, B. B. B., Malhi,
Y., Hemming, D., Kay, G., Good, P., Lewis, S. L., Phillips, O. L., Atkin, O.
K., Lloyd, J., Gloor, E., Zaragoza-Castells, J., Meir, P., Betts, R., Harris, P. P., Nobre, C., Marengo, J., and Cox, P. M.: Simulated resilience of tropical rainforests to CO2-induced climate change, Nat. Geosci., 6, 268–273, https://doi.org/10.1038/NGEO1741, 2013.
IPCC: Managing the Risks of Extreme Events and Disasters to Advance Climate
Change Adaptation, Cambridge, UK, 2012.
IPCC: Climate Change 2014: The Physical Science Basis, Intergovernmental
Panel on Climate Change (IPCC), Cambridge, UK, 2014.
Joyce, R. J., Janowiak, J. E., Arkin, P. A., and Xie, P. P.: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution, J.
Hydrometeorol., 5, 487–503, https://doi.org/10.1175/1525-7541(2004)005<0487:Camtpg>2.0.Co;2, 2004.
Kimani, M. W., Hoedjes, J. C. B., and Su, Z. B.: An Assessment of
Satellite-Derived Rainfall Products Relative to Ground Observations over
East Africa, Remote. Sens.-Basel, 9, 430–451, https://doi.org/10.3390/Rs9050430, 2017.
Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J., Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic
global vegetation model for studies of the coupled atmosphere-biosphere
system, Global Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003gb002199, 2005.
Kundzewicz, Z. W. and Stakhiv, E. Z.: Are climate models “ready for prime
time” in water resources management applications, or is more research needed?, Hydrolog. Sci. J., 55, 1085–1089, https://doi.org/10.1080/02626667.2010.513211, 2010.
Levizzani, V., Kidd, C., Aonashi, K., Bennartz, R., Ferraro, R. R., Huffman,
G. J., Roca, R., Turk, F. J., and Wang, N. Y.: The activities of the International Precipitation Working Group, Q. J. Roy. Meteorol. Soc., 144,
3–5, https://doi.org/10.1002/qj.3214, 2018.
Li, H. B. and Wu, J. G.: Uncertainty analysis in ecological studies: An
overview, in: Scaling and Uncertainty Analysis in Ecology: Methods and
Applications, Springer, the Netherlands, 2006.
Long, D., Longuevergne, L., and Scanlon, B. R.: Uncertainty in
evapotranspiration from land surface modeling, remote sensing, and GRACE
satellites, Water Resour. Res., 50, 1131–1151, https://doi.org/10.1002/2013wr014581, 2014.
Lopez, O., Houborg, R., and McCabe, M. F.: Evaluating the hydrological
consistency of evaporation products using satellite-based gravity and rainfall data, Hydrol. Earth Syst. Sci., 21, 323–343,
https://doi.org/10.5194/hess-21-323-2017, 2017.
Luo, Z. J., Anderson, R. C., Rossow, W. B., and Takahashi, H.: Tropical cloud and precipitation regimes as seen from near-simultaneous TRMM, CloudSat, and CALIPSO observations and comparison with ISCCP, J. Geophys. Res.-Atmos., 122, 5988–6003, 2017.
Marshall, T. J., Holmes, J. W., and Rose, C. W.: Soil Physics, Cambridge
University Press, Cambridge, UK, 1996.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017.
Marthews, T. R., Malhi, Y., Girardin, C. A., Silva Espejo, J. E., Aragao, L.
E., Metcalfe, D. B., Rapp, J. M., Mercado, L. M., Fisher, R. A., Galbraith,
D. R., Fisher, J. B., Salinas-Revilla, N., Friend, A. D., Restrepo-Coupe, N., and Williams, R. J.: Simulating forest productivity along a neotropical
elevational transect: temperature variation and carbon use efficiency, Global
Change Biol., 18, 2882–2898, https://doi.org/10.1111/j.1365-2486.2012.02728.x, 2012.
Marthews, T. R., Jones, R. G., Dadson, S. J., Otto, F. E. L., Mitchell, D.,
Guillod, B. P., and Allen, M. R.: The Impact of Human-Induced Climate Change
on Regional Drought in the Horn of Africa, J. Geophys. Res.-Atmos., 124,
4549–4566, https://doi.org/10.1029/2018JD030085, 2019.
McGregor, G. R. and Nieuwolt, S.: Tropical Climatology, Wiley, Chichester,
UK, 1998.
Mehran, A. and AghaKouchak, A.: Capabilities of satellite precipitation
datasets to estimate heavy precipitation rates at different temporal
accumulations, Hydrol. Process., 28, 2262–2270, https://doi.org/10.1002/hyp.9779, 2014.
Munier, S., Minvielle, M., Decharme, B., Calvet, J., Blyth, E., Veldkamp, T.
I. E., and Nikolopolous, T.: Report on uncertainty characterization of the
WP5 WRR tier 2 products, available at: http://earth2observe.eu/files/Public Deliverables/D4.4 - Report on uncertainty characterisation of the WP5 WRR tier product.pdf (last access: 7 January 2020), 2018.
Nikolopoulos, E., Anagnostou, M., Albergel, C., Dutra, E., Fink, G.,
Martínez-de la Torre, A., Munier, S., Polcher, J., and Quintana-Segui, P.: Report on precipitation error modeling and ensemble error propagation
using LSM and GHM models from tier 1 reanalysis, available at: http://earth2observe.eu/files/Public Deliverables/D4.2_Report_on_precipitation_error_modeling_and_ensemble_error_propagation_using_LSM_and_GHM_models.pdf (last access: 7 January 2020), 2016.
Oberkampf, W. L. and Roy, C. J.: Verification and Validation in Scientific
Computing, Cambridge University Press, Cambridge, 2010.
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tolle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S., Schmidli, J., van Lipzig, N. P. M., and Leung, R.: A review on regional
convection-permitting climate modeling: Demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015.
Prudhomme, C., Giuntoli, I., Robinson, E. L., Clark, D. B., Arnell, N. W.,
Dankers, R., Fekete, B. M., Franssen, W., Gerten, D., Gosling, S. N., Hagemann, S., Hannah, D. M., Kim, H., Masaki, Y., Satoh, Y., Stacke, T.,
Wada, Y., and Wisser, D.: Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment, P. Natl. Acad. Sci. USA, 111, 3262–3267, https://doi.org/10.1073/pnas.1222473110, 2014.
Riley, K., Thompson, M., Webley, P., and Hyde, K. D.: Uncertainty in Natural
Hazards, Modeling and Decision Support, in: Natural Hazard Uncertainty Assessment: Modeling and-Decision Support, edited by: Riley, K., Webley, P., and Thompson, M., Wiley, Hoboken, New Jersey, 2017.
Santanello, J. A., Dirmeyer, P. A., Ferguson, C. R., Findell, K. L., Tawfik, A. B., Berg, A., Ek, M., Gentine, P., Guillod, B. P., van Heerwaarden, C., Roundy, J., and Wulfmeyer, V.: Land–atmosphere interactions The LoCo Perspective, B. Am. Meteorol. Soc., 99, 1253–1272, 2018.
Schellekens, J., Dutra, E., Martinez-de la Torre, A., Balsamo, G., van Dijk,
A., Weiland, F. S., Minvielle, M., Calvet, J. C., Decharme, B., Eisner, S.,
Fink, G., Florke, M., Pessenteiner, S., van Beek, R., Polcher, J., Beck, H.,
Orth, R., Calton, B., Burke, S., Dorigo, W., and Weedon, G. P.: A global
water resources ensemble of hydrological models: the eartH2Observe Tier-1
dataset, Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, 2017.
Schewe, J., Heinke, J., Gerten, D., Haddeland, I., Arnell, N. W., Clark, D. B., Dankers, R., Eisner, S., Fekete, B. M., Colon-Gonzalez, F. J., Gosling, S. N., Kim, H., Liu, X. C., Masaki, Y., Portmann, F. T., Satoh, Y., Stacke,
T., Tang, Q. H., Wada, Y., Wisser, D., Albrecht, T., Frieler, K., Piontek,
F., Warszawski, L., and Kabat, P.: Multimodel assessment of water scarcity
under climate change, P. Natl. Acad. Sci. USA, 111, 3245–3250,
https://doi.org/10.1073/pnas.1222460110, 2014.
Schneider, C., Florke, M., Eisner, S., and Voss, F.: Large scale modelling
of bankfull flow: An example for Europe, J. Hydrol., 408, 235–245,
https://doi.org/10.1016/j.jhydrol.2011.08.004, 2011.
Taylor, C. M., de Jeu, R. A., Guichard, F., Harris, P. P., and Dorigo, W. A.: Afternoon rain more likely over drier soils, Nature, 489, 423–426,
https://doi.org/10.1038/nature11377, 2012.
Tian, Y. D., Peters-Lidard, C. D., Adler, R. F., Kubota, T., and Ushio, T.:
Evaluation of GSMaP Precipitation Estimates over the Contiguous United
States, J. Hydrometeorol., 11, 566–574, https://doi.org/10.1175/2009JHM1190.1, 2010.
Trenberth, K. E., Fasullo, J. T., and Shepherd, T. G.: Attribution of
climate extreme events, Nat. Clim. Change, 5, 725–730, https://doi.org/10.1038/nclimate2657, 2015.
Ukkola, A. M., De Kauwe, M. G., Pitman, A. J., Best, M. J., Abramowitz, G.,
Haverd, V., Decker, M., and Haughton, N.: Land surface models systematically
overestimate the intensity, duration and magnitude of seasonal-scale
evaporative droughts, Environ. Res. Lett., 11, 104012,
https://doi.org/10.1088/1748-9326/11/10/104012, 2016.
Van Loon, A. F.: Hydrological drought explained, Wires Water, 2, 359–392,
https://doi.org/10.1002/wat2.1085, 2015.
Veldkamp, T. I. E. and Ward, P.: Report on global scale assessment of physical and social water scarcity, available at: http://earth2observe.eu/files/Public Deliverables/D2.6_Report_global assessment of water scarcity.pdf (last access: 7 January 2020), 2015.
Veldkamp, T. I. E., Zhao, F., Ward, P. J., de Moel, H., Aerts, J. C. J. H.,
Schmied, H. M., Portmann, F. T., Masaki, Y., Pokhrel, Y., Liu, X., Satoh, Y., Gerten, D., Gosling, S. N., Zaherpour, J., and Wada, Y.: Human impact
parameterizations in global hydrological models improve estimates of monthly
discharges and hydrological extremes: a multi-model validation study, Environ. Res. Lett., 13, 055008, https://doi.org/10.1088/1748-9326/aab96f, 2018.
Verzano, K., Barlund, I., Florke, M., Lehner, B., Kynast, E., Voss, F., and
Alcamo, J.: Modeling variable river flow velocity on continental scale: Current situation and climate change impacts in Europe, J. Hydrol., 424, 238–251, https://doi.org/10.1016/j.jhydrol.2012.01.005, 2012.
Wartenburger, R., Seneviratne, S. I., Hirschi, M., Chang, J. F., Ciais, P.,
Deryng, D., Elliott, J., Folberth, C., Gosling, S. N., Gudmundsson, L., Henrot, A. J., Hickler, T., Ito, A., Khabarov, N., Kim, H., Leng, G. Y.,
Liu, J. G., Liu, X. C., Masaki, Y., Morfopoulos, C., Muller, C., Schmied, H.
M., Nishina, K., Orth, R., Pokhrel, Y., Pugh, T. A. M., Satoh, Y., Schaphoff, S., Schmid, E., Sheffield, J., Stacke, T., Steinkamp, J., Tang, Q. H., Thiery, W., Wada, Y., Wang, X. H., Weedon, G. P., Yang, H., and Zhou, T.: Evapotranspiration simulations in ISIMIP2a-Evaluation of spatio-temporal
characteristics with a comprehensive ensemble of independent datasets,
Environ. Res. Lett., 13, 075001, https://doi.org/10.1088/1748-9326/aac4bb, 2018.
Yi, C., Pendall, E., and Ciais, P.: Focus on extreme events and the carbon
cycle, Environ. Res. Lett., 10, 070201, https://doi.org/10.1088/1748-9326/10/7/070201, 2015.
Yin, H., Donat, M. G., Alexander, L. V., and Sun, Y.: Multi-dataset comparison of gridded observed temperature and precipitation extremes over
China, Int. J. Climatol., 35, 2809–2827, https://doi.org/10.1002/joc.4174, 2015.
Short summary
Climate change impact modellers can only act on predictions of the occurrence of an extreme event in the Earth system if they know the uncertainty in that prediction and how uncertainty is attributable to different model components. Using eartH2Observe data, we quantify the balance between different sources of uncertainty in global evapotranspiration and runoff, making a crucial contribution to understanding the spatial distribution of water resources allocation deficiencies.
Climate change impact modellers can only act on predictions of the occurrence of an extreme...
