Articles | Volume 23, issue 3
https://doi.org/10.5194/hess-23-1779-2019
© Author(s) 2019. 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-23-1779-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Apr 2019
Research article |
| 02 Apr 2019
| 02 Apr 2019
The benefits of spatial resolution increase in global simulations of the hydrological cycle evaluated for the Rhine and Mississippi basins
Meteorology and Air Quality Group, Wageningen University, Droevendaalsesteeg 4, 6708 BP Wageningen, the Netherlands
Chiel C. van Heerwaarden
Meteorology and Air Quality Group, Wageningen University, Droevendaalsesteeg 4, 6708 BP Wageningen, the Netherlands
Albrecht H. Weerts
Hydrology and Quantitative Water Management Group, Wageningen University, Droevendaalsesteeg 4, 6708 BP Wageningen, the Netherlands
Deltares, P.O. Box 177, 2600 MH Delft, the Netherlands
Wilco Hazeleger
Meteorology and Air Quality Group, Wageningen University, Droevendaalsesteeg 4, 6708 BP Wageningen, the Netherlands
Netherlands eScience Center (NLeSC), Science Park 140, 1098 XG Amsterdam, the Netherlands
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Robin Stoffer, Caspar M. van Leeuwen, Damian Podareanu, Valeriu Codreanu, Menno A. Veerman, Martin Janssens, Oscar K. Hartogensis, and Chiel C. van Heerwaarden
Geosci. Model Dev., 14, 3769–3788, https://doi.org/10.5194/gmd-14-3769-2021, https://doi.org/10.5194/gmd-14-3769-2021, 2021
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Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
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Pleun N. J. Bonekamp, Chiel C. van Heerwaarden, Jakob F. Steiner, and Walter W. Immerzeel
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Hendrik Wouters, Irina Y. Petrova, Chiel C. van Heerwaarden, Jordi Vilà-Guerau de Arellano, Adriaan J. Teuling, Vicky Meulenberg, Joseph A. Santanello, and Diego G. Miralles
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Bart van Osnabrugge, Remko Uijlenhoet, and Albrecht Weerts
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Laurène Bouaziz, Albrecht Weerts, Jaap Schellekens, Eric Sprokkereef, Jasper Stam, Hubert Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 22, 6415–6434, https://doi.org/10.5194/hess-22-6415-2018, https://doi.org/10.5194/hess-22-6415-2018, 2018
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Albert I. J. M. van Dijk, Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts
Hydrol. Earth Syst. Sci., 22, 4959–4980, https://doi.org/10.5194/hess-22-4959-2018, https://doi.org/10.5194/hess-22-4959-2018, 2018
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Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.
David R. Casson, Micha Werner, Albrecht Weerts, and Dimitri Solomatine
Hydrol. Earth Syst. Sci., 22, 4685–4697, https://doi.org/10.5194/hess-22-4685-2018, https://doi.org/10.5194/hess-22-4685-2018, 2018
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In high-latitude (> 60° N) watersheds, measuring the snowpack and predicting of snowmelt runoff are uncertain due to the lack of data and complex physical processes. This provides challenges for hydrological assessment and operational water management. Global re-analysis datasets have great potential to aid in snowpack representation and snowmelt prediction when combined with a distributed hydrological model, though they still have clear limitations in remote boreal forest and tundra environments.
Anouk I. Gevaert, Luigi J. Renzullo, Albert I. J. M. van Dijk, Hans J. van der Woerd, Albrecht H. Weerts, and Richard A. M. de Jeu
Hydrol. Earth Syst. Sci., 22, 4605–4619, https://doi.org/10.5194/hess-22-4605-2018, https://doi.org/10.5194/hess-22-4605-2018, 2018
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We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294, https://doi.org/10.5194/hess-22-3275-2018, https://doi.org/10.5194/hess-22-3275-2018, 2018
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In North Africa rain storms can be as vital as they are devastating. The present study uses multi-year satellite data to better understand how and where soil moisture conditions affect development of rainfall in the area. Our results reveal two major regions in the southwest and southeast, where drier soils show higher potential to cause rainfall development. This knowledge is essential for the hydrological sector, and can be further used by models to improve prediction of rainfall and droughts.
Fabio Sai, Lydia Cumiskey, Albrecht Weerts, Biswa Bhattacharya, and Raihanul Haque Khan
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2018-26, https://doi.org/10.5194/nhess-2018-26, 2018
Revised manuscript not accepted
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The research tackled the challenge of flood impact-based forecasting and service for Bangladesh by proposing an approach based on colour coded as mean for linking forecasted water levels to possible impacts. This was tested at the local level and, although limited to the case study, the results encouraged us to share our outcomes for triggering interest in such approach and to foster further research aimed to move it forward.
Imme Benedict, Chiel C. van Heerwaarden, Albrecht H. Weerts, and Wilco Hazeleger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-473, https://doi.org/10.5194/hess-2017-473, 2017
Revised manuscript not accepted
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The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is increasing. This study examines the benefits of a very high resolution GCM and GHM on representing the hydrological cycle in the Rhine and Mississippi basin. We conclude that increasing the resolution of a GCM is the most straightforward route to better precipitation and thereby discharge results, although this is depending on the climatic drivers of the basin.
Chiel C. van Heerwaarden, Bart J. H. van Stratum, Thijs Heus, Jeremy A. Gibbs, Evgeni Fedorovich, and Juan Pedro Mellado
Geosci. Model Dev., 10, 3145–3165, https://doi.org/10.5194/gmd-10-3145-2017, https://doi.org/10.5194/gmd-10-3145-2017, 2017
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MicroHH (www.microhh.org) is a new and open-source computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is made to simulate atmospheric flows up to the finest detail levels at very high resolution. It has been designed from scratch in C++ in order to use a modern design that allows the code to run on more than 10 000 cores, as well as on a graphical processing unit.
Naze Candogan Yossef, Rens van Beek, Albrecht Weerts, Hessel Winsemius, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 21, 4103–4114, https://doi.org/10.5194/hess-21-4103-2017, https://doi.org/10.5194/hess-21-4103-2017, 2017
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Omar Wani, Joost V. L. Beckers, Albrecht H. Weerts, and Dimitri P. Solomatine
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We generate uncertainty intervals for hydrologic model predictions using a simple instance-based learning scheme. Errors made by the model in some specific hydrometeorological conditions in the past are used to predict the probability distribution of its errors during forecasting. We test it for two different case studies in England. We find that this technique, even though conceptually simple and easy to implement, performs as well as some other sophisticated uncertainty estimation methods.
Joost V. L. Beckers, Albrecht H. Weerts, Erik Tijdeman, and Edwin Welles
Hydrol. Earth Syst. Sci., 20, 3277–3287, https://doi.org/10.5194/hess-20-3277-2016, https://doi.org/10.5194/hess-20-3277-2016, 2016
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Oceanic–atmospheric climate modes, such as El Niño–Southern Oscillation (ENSO), are known to affect the streamflow regime in many rivers around the world. A new method is presented for ENSO conditioning of the ensemble streamflow prediction (ESP) method, which is often used for seasonal streamflow forecasting. The method was tested on three tributaries of the Columbia River, OR. Results show an improvement in forecast skill compared to the standard ESP.
N. Dogulu, P. López López, D. P. Solomatine, A. H. Weerts, and D. L. Shrestha
Hydrol. Earth Syst. Sci., 19, 3181–3201, https://doi.org/10.5194/hess-19-3181-2015, https://doi.org/10.5194/hess-19-3181-2015, 2015
O. Rakovec, A. H. Weerts, J. Sumihar, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 19, 2911–2924, https://doi.org/10.5194/hess-19-2911-2015, https://doi.org/10.5194/hess-19-2911-2015, 2015
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This is the first analysis of the asynchronous ensemble Kalman filter in hydrological forecasting. The results of discharge assimilation into a hydrological model for the catchment show that including past predictions and observations in the filter improves model forecasts. Additionally, we show that elimination of the strongly non-linear relation between soil moisture and assimilated discharge observations from the model update becomes beneficial for improved operational forecasting.
N. Tangdamrongsub, S. C. Steele-Dunne, B. C. Gunter, P. G. Ditmar, and A. H. Weerts
Hydrol. Earth Syst. Sci., 19, 2079–2100, https://doi.org/10.5194/hess-19-2079-2015, https://doi.org/10.5194/hess-19-2079-2015, 2015
A. Hally, O. Caumont, L. Garrote, E. Richard, A. Weerts, F. Delogu, E. Fiori, N. Rebora, A. Parodi, A. Mihalović, M. Ivković, L. Dekić, W. van Verseveld, O. Nuissier, V. Ducrocq, D. D'Agostino, A. Galizia, E. Danovaro, and A. Clematis
Nat. Hazards Earth Syst. Sci., 15, 537–555, https://doi.org/10.5194/nhess-15-537-2015, https://doi.org/10.5194/nhess-15-537-2015, 2015
P. López López, J. S. Verkade, A. H. Weerts, and D. P. Solomatine
Hydrol. Earth Syst. Sci., 18, 3411–3428, https://doi.org/10.5194/hess-18-3411-2014, https://doi.org/10.5194/hess-18-3411-2014, 2014
D. Leedal, A. H. Weerts, P. J. Smith, and K. J. Beven
Hydrol. Earth Syst. Sci., 17, 177–185, https://doi.org/10.5194/hess-17-177-2013, https://doi.org/10.5194/hess-17-177-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
Elevational control of isotopic composition and application in understanding hydrologic processes in the mid Merced River catchment, Sierra Nevada, California, USA
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Broadleaf afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
HESS Opinions: A few camels or a whole caravan?
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability has minor effects on the hydrological response in the Neckar basin, Germany
Toward interpretable LSTM-based modeling of hydrological systems
Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model
What controls the tail behaviour of flood series: rainfall or runoff generation?
Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California
Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
HESS Opinions: Never train an LSTM on a single basin
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
Simulation-Based Inference for Parameter Estimation of Complex Watershed Simulators
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Projected future changes in cryosphere and hydrology of a mountainous catchment in the Upper Heihe River, China
Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes
Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling
Modelling flood frequency and magnitude in a glacially conditioned, heterogeneous landscape: testing the importance of land cover and land use
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach
To what extent does river routing matter in hydrological modeling?
Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins
An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
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By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
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Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
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Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
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Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
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Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
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Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
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Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
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We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
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In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
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Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
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We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Franziska Maria Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
EGUsphere, https://doi.org/10.5194/egusphere-2024-864, https://doi.org/10.5194/egusphere-2024-864, 2024
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We compare the catchment forcing data provided in large-sample datasets, namely the Caravan dataset and three of the original CAMELS datasets (US, BR, GB). We show that the differences affect hydrological model performance and that the data quality in the Caravan dataset is lower than the one in the CAMELS datasets, both for precipitation and potential evapotranspiration. We want to raise awareness of the lower data quality in Caravan and we suggest possible improvements for the Caravan dataset.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
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This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
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To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
EGUsphere, https://doi.org/10.5194/egusphere-2024-629, https://doi.org/10.5194/egusphere-2024-629, 2024
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Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
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Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-62, https://doi.org/10.5194/hess-2024-62, 2024
Revised manuscript accepted for HESS
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Root zone storage capacity (Sumax) significantly changes over multiple decades reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
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Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
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Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
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In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
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In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
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This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
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Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
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We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
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Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-275, https://doi.org/10.5194/hess-2023-275, 2024
Revised manuscript accepted for HESS
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Recently, a special type of neural network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models require the use of large-sample hydrology datasets.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
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How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-264, https://doi.org/10.5194/hess-2023-264, 2024
Revised manuscript accepted for HESS
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Large-scale hydrologic a needed tool to explore complex watershed processes and how they may evolve under a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration with a set of experiments in the Upper Colorado River Basin.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
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Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
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We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
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Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
EGUsphere, https://doi.org/10.5194/egusphere-2023-3043, https://doi.org/10.5194/egusphere-2023-3043, 2023
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An integrated cryospheric-hydrologic model, FLEX-Cryo, was developed, considered glaciers, snow cover, frozen soil, and their dynamic impacts on hydrology. We utilized the model to simulate the future changes in cryosphere and hydrology in Hulu catchment. Our projections showed that the two glaciers will melt out around 2050; snow cover will reduce; and permafrost will degrade. For hydrology, runoff will decrease after glacier melt out; and permafrost degradation will increase baseflow.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
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Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
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Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Pamela E. Tetford and Joseph R. Desloges
Hydrol. Earth Syst. Sci., 27, 3977–3998, https://doi.org/10.5194/hess-27-3977-2023, https://doi.org/10.5194/hess-27-3977-2023, 2023
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An efficient regional flood frequency model relates drainage area to discharge, with a major assumption of similar basin conditions. In a landscape with variable glacial deposits and land use, we characterize varying hydrological function using 28 explanatory variables. We demonstrate that (1) a heterogeneous landscape requires objective model selection criteria to optimize the fit of flow data, and (2) incorporating land use as a predictor variable improves the drainage area to discharge model.
Ana Ramos Oliveira, Tiago Brito Ramos, Lígia Pinto, and Ramiro Neves
Hydrol. Earth Syst. Sci., 27, 3875–3893, https://doi.org/10.5194/hess-27-3875-2023, https://doi.org/10.5194/hess-27-3875-2023, 2023
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This paper intends to demonstrate the adequacy of a hybrid solution to overcome the difficulties related to the incorporation of human behavior when modeling hydrological processes. Two models were implemented, one to estimate the outflow of a reservoir and the other to simulate the hydrological processes of the watershed. With both models feeding each other, results show that the proposed approach significantly improved the streamflow estimation downstream of the reservoir.
Zhihua He, Kevin Shook, Christopher Spence, John W. Pomeroy, and Colin Whitfield
Hydrol. Earth Syst. Sci., 27, 3525–3546, https://doi.org/10.5194/hess-27-3525-2023, https://doi.org/10.5194/hess-27-3525-2023, 2023
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This study evaluated the impacts of climate change on snowmelt, soil moisture, and streamflow over the Canadian Prairies. The entire prairie region was divided into seven basin types. We found strong variations of hydrological sensitivity to precipitation and temperature changes in different land covers and basins, which suggests that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the prairies.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, https://doi.org/10.5194/hess-27-3505-2023, 2023
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This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
Dung Trung Vu, Thanh Duc Dang, Francesca Pianosi, and Stefano Galelli
Hydrol. Earth Syst. Sci., 27, 3485–3504, https://doi.org/10.5194/hess-27-3485-2023, https://doi.org/10.5194/hess-27-3485-2023, 2023
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The calibration of hydrological models over extensive spatial domains is often challenged by the lack of data on river discharge and the operations of hydraulic infrastructures. Here, we use satellite data to address the lack of data that could unintentionally bias the calibration process. Our study is underpinned by a computational framework that quantifies this bias and provides a safe approach to the calibration of models in poorly gauged and heavily regulated basins.
Francesco Fatone, Bartosz Szeląg, Przemysław Kowal, Arthur McGarity, Adam Kiczko, Grzegorz Wałek, Ewa Wojciechowska, Michał Stachura, and Nicolas Caradot
Hydrol. Earth Syst. Sci., 27, 3329–3349, https://doi.org/10.5194/hess-27-3329-2023, https://doi.org/10.5194/hess-27-3329-2023, 2023
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A novel methodology for the development of a stormwater network performance simulator including advanced risk assessment was proposed. The applied tool enables the analysis of the influence of spatial variability in catchment and stormwater network characteristics on the relation between (SWMM) model parameters and specific flood volume, as an alternative approach to mechanistic models. The proposed method can be used at the stage of catchment model development and spatial planning management.
Cited articles
Balsamo, G., Albergel, C., Beljaars, A., Boussetta, S., Brun, E., Cloke, H.,
Dee, D., Dutra, E., Muñoz-Sabater, J., Pappenberger, F., de Rosnay, P.,
Stockdale, T., and Vitart, F.: ERA-Interim/Land: a global land surface reanalysis
data set, Hydrol. Earth Syst. Sci., 19, 389–407, https://doi.org/10.5194/hess-19-389-2015, 2015. a
Beck, H. E., van Dijk, A. I. J. M., de Roo, A., Miralles, D. G., McVicar, T.
R., Schellekens, J., and Bruijnzeel, L. A.: Global-scale regionalization of
hydrologic model parameters, Water Resour. Res., 52, 3599–3622,
https://doi.org/10.1002/2015WR018247, 2016. a
Beck, H. E., van Dijk, A. I. J. M., de Roo, A., Dutra, E., Fink, G., Orth, R.,
and Schellekens, J.: Global evaluation of runoff from 10 state-of-the-art
hydrological models, Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, 2017. a, b
Benedict, I.: README file related to datasets of hydrological simulations of the
Rhine and Mississippi basin, 4TU, Centre of Research Data, https://doi.org/10.4121/uuid:c3b6e367-8215-4640-81d2-9f74994e65f4, 2018. a
Berghuijs, W. R., Woods, R. A., Hutton, C. J., and Sivapalan, M.: Dominant
flood generating mechanisms across the United States, Geophys. Res. Lett., 43,
4382–4390, https://doi.org/10.1002/2016GL068070, 2016. a, b
Betts, A. K., Köhler, M., and Zhang, Y.: Comparison of river basin
hydrometeorology in ERA-Interim and ERA-40 reanalyses with observations, J.
Geophys. Res.-Atmos., 114, D02101, https://doi.org/10.1029/2008JD010761, 2009. a
Biemans, H., Hutjes, R., Kabat, P., Strengers, B., Gerten, D., and Rost, S.:
Effects of precipitation uncertainty on discharge calculations for main river
basins, J. Hydrometeorol., 10, 1011–1025, 2009. a
Bierkens, M. F. P., Bell, V. A., Burek, P., Chaney, N., Condon, L. E., David,
C. H., de Roo, A., Döll, P., Drost, N., Famiglietti, J. S., Flörke, M.,
Gochis, D. J., Houser, P., Hut, R., Keune, J., Kollet, S., Maxwell, R. M.,
Reager, J. T., Samaniego, L., Sudicky, E., Sutanudjaja, E. H., van de Giesen,
N., Winsemius, H., and Wood, E. F.: Hyper-resolution global hydrological
modelling: what is next?: “Everywhere and locally relevant”, Hydrol. Process.,
29, 310–320, https://doi.org/10.1002/hyp.10391, 2015. a, b
Chang, E. K. M., Guo, Y., and Xia, X.: CMIP5 multimodel ensemble projection of
storm track change under global warming: CMIP5 model-projected storm track
change, J. Geophys. Res.-Atmos., 117, D23118, https://doi.org/10.1029/2012JD018578, 2012. a
Davini, P., Corti, S., D'Andrea, F., Rivière, G., and von Hardenberg, J.:
Improved Winter European Atmospheric Blocking Frequencies in High-Resolution
Global Climate Simulations, J. Adv. Model. Earth Syst., 9, 2615–2634, 2017a. a
Davini, P., von Hardenburg, J., Corti, S., Christensen, H. M., Juricke, S.,
Subramanian, A., Watson, P. A., Weisheimer, A., and Palmer, T. N.: Climate
SPHINX: evaluating the impact of resolution and stochastic physics parameterisations
in the EC-Earth global climate model, Geosci. Model Dev., 10, 1383–1402,
https://doi.org/10.5194/gmd-10-1383-2017, 2017b. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars,
A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R.,
Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm,
E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally,
A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay,
P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis:
configuration and performance of the data assimilation system, Q. J. Roy.
Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Delworth, T. L., Rosati, A., Anderson, W., Adcroft, A. J., Balaji, V., Benson,
R., Dixon, K., Griffies, S. M., Lee, H.-C., Pacanowski, R. C., Vecchi, G. A.,
Wittenberg, A. T., Zeng, F., and Zhang, R.: Simulated climate and climate change
in the GFDL CM2.5 high-resolution coupled climate model, J. Climate, 25, 2755–2781, 2012. a
Demory, M.-E., Vidale, P. L., Roberts, M. J., Berrisford, P., Strachan, J.,
Schiemann, R., and Mizielinski, M. S.: The role of horizontal resolution in
simulating drivers of the global hydrological cycle, Clim. Dynam., 42, 2201–2225,
https://doi.org/10.1007/s00382-013-1924-4, 2014. a
Disse, M. and Engel, H.: Flood events in the Rhine basin: genesis, influences
and mitigation, Nat. Hazards, 23, 271–290, 2001. a
Efron, B. and Tibshirani, R. J.: An introduction to the bootstrap, CRC Press, USA, 1994. a
Fekete, B. M., Vörösmarty, C. J., Roads, J. O., and Willmott, C. J.:
Uncertainties in precipitation and their impacts on runoff estimates, J. Climate,
17, 294–304, 2004. a
Fowler, H. J., Blenkinsop, S., and Tebaldi, C.: Linking climate change modelling
to impacts studies: recent advances in downscaling techniques for hydrological
modelling, Int. J. Climatol., 27, 1547–1578, https://doi.org/10.1002/joc.1556, 2007. a
Gao, H., Hrachowitz, M., Fenicia, F., Gharari, S., and Savenije, H. H. G.:
Testing the realism of a topography-driven model (FLEX-Topo) in the nested
catchments of the Upper Heihe, China, Hydrol. Earth Syst. Sci., 18, 1895–1915,
https://doi.org/10.5194/hess-18-1895-2014, 2014a. a
Gao, H., Hrachowitz, M., Schymanski, S., Fenicia, F., Sriwongsitanon, N., and
Savenije, H.: Climate controls how ecosystems size the root zone storage
capacity at catchment scale, Geophys. Res. Lett., 41, 7916–7923, 2014b. a
Gao, H., Hrachowitz, M., Sriwongsitanon, N., Fenicia, F., Gharari, S., and
Savenije, H. H.: Accounting for the influence of vegetation and landscape
improves model transferability in a tropical savannah region, Water Resour. Res.,
52, 7999–8022, 2016. a
GRDC: GRDC in the Bundesanstalt fuer Gewaesserkunde, Tech. rep., Koblenz,
Germany, available at: http://grdc.bafg.de (last access: 12 March 2019), 2007. a
Haarsma, R. J., Hazeleger, W., Severijns, C., de Vries, H., Sterl, A., Bintanja,
R., van Oldenborgh, G. J., and van den Brink, H. W.: More hurricanes to hit
western Europe due to global warming, Geophys. Res. Lett., 40, 1783–1788,
https://doi.org/10.1002/grl.50360, 2013. a, b, c
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao,
Q., Chang, P., Corti, S., Fuckar, N. S., Guemas, V., von Hardenberg, J.,
Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao,
J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E.,
Semmler, T., Small, J., and von Storch, J.-S.: High Resolution Model
Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9,
4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016. a, b, c
Haddeland, I., Clark, D. B., Franssen, W., Ludwig, F., Voß, F., Arnell, N.
W., Bertrand, N., Best, M., Folwell, S., Gerten, D., Gomes, S., Gosling, S. N.,
Hagemann, S., Hanasaki, N., Harding, R., Heinke, J., Kabat, P., Koirala, S.,
Oki, T., Polcher, J., Stacke, T., Viterbo, P., Weedon, G. P., and Yeh, P.:
Multimodel Estimate of the Global Terrestrial Water Balance: Setup and First
Results, J. Hydrometeorol., 12, 869–884, https://doi.org/10.1175/2011JHM1324.1, 2011. a
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D.,
and New, M.: A European daily high-resolution gridded data set of surface
temperature and precipitation for 1950–2006, J. Geophys. Res., 113, D20119,
https://doi.org/10.1029/2008JD010201, 2008. a
Hazeleger, W., Severijns, C., Semmler, T., Stefanescu, S., Yang, S., Wang, X.,
Wyser, K., Dutra, E., Baldasano, J. M., Bintanja, R., Bougeault, P., Caballero,
R., Ekman, A. M. L., Christensen, J. H., van den Hurk, B., Jimenez, P., Jones,
C., Kållberg, P., Koenigk, T., McGrath, R., Miranda, P., Van Noije, T.,
Palmer, T., Parodi, J. A., Schmith, T., Selten, F., Storelvmo, T., Sterl, A.,
Tapamo, H., Vancoppenolle, M., Viterbo, P., and Willén, U.: EC-Earth: A
Seamless Earth-System Prediction Approach in Action, B. Am. Meteorol. Soc., 91,
1357–1363, https://doi.org/10.1175/2010BAMS2877.1, 2010. a
Hazeleger, W., Wang, X., Severijns, C., Ştefănescu, S., Bintanja, R.,
Sterl, A., Wyser, K., Semmler, T., Yang, S., Van den Hurk, B., van Noije, T.,
van der Linden, E., and van der Wiel, K.: EC-Earth V2.2: description and
validation of a new seamless earth system prediction model, Clim. Dynam.,
39, 2611–2629, 2012. a
Hazeleger, W., van den Hurk, B., Min, E., van Oldenborgh, G., Petersen, A.,
Stainforth, D., Vasileiadou, E., and Smith, L.: Tales of future weather, Nat.
Clim. Change, 5, 107–113, https://doi.org/10.1038/nclimate2450, 2015. a, b
Hegnauer, M., Beersma, J. J., van den Boogaard, H. F. P., Buishand, T. A., and
Passchier, R. H.: Publications, presentations and other activities Generator
of Rainfall and Discharge Extremes (GRADE) for the Rhine and Meuse basins, Final
report of GRADE 2.0 2014, 1209424-004, Deltares, Delft, 2014. a
Henn, B., Newman, A. J., Livneh, B., Daly, C., and Lundquist, J. D.: An
assessment of differences in gridded precipitation datasets in complex terrain,
J. Hydrol., 556, 1205–1219, https://doi.org/10.1016/j.jhydrol.2017.03.008, 2017. a
Higgins, R. W., Shi, W., Yarosh, E., and Joyce, R.: Improved United States
Precipitation Quality Control System and Analysis, ATLAS No. 7, NCEP/Climate
Prediction Center, Camp Springs, USA, 40 pp., 2000. a
Hodges, K. I., Lee, R. W., and Bengtsson, L.: A comparison of extratropical
cyclones in recent reanalyses ERA-Interim, NASA MERRA, NCEP CFSR, and JRA-25,
J. Climate, 24, 4888–4906, 2011. a
Hofstra, N., Haylock, M., New, M., and Jones, P. D.: Testing E-OBS European
high-resolution gridded data set of daily precipitation and surface temperature,
J. Geophys. Res., 114, D21101, https://doi.org/10.1029/2009JD011799, 2009. a
Hohenegger, C., Brockhaus, P., Bretherton, C. S., and Schär, C.: The soil
moisture–precipitation feedback in simulations with explicit and parameterized
convection, J. Climate, 22, 5003–5020, 2009. a
Hrachowitz, M., Savenije, H., Blöschl, G., McDonnell, J., Sivapalan, M.,
Pomeroy, J., Arheimer, B., Blume, T., Clark, M., Ehret, U., Fenicia, F., Freer,
J. E., Gelfan, A., Gupta, H. V., Hughes, D. A., Hut, R. W., Montanari, A., Pande,
S., Tetzlaff, D., Troch, P. A., Uhlenbrook, S., Wagener, T., Winsemius, H. C.,
Woods, R. A., Zehe, E., and Cudennec, C.: A decade of Predictions in Ungauged
Basins (PUB) – a review, Hydrolog. Sci. J., 58, 1198–1255, 2013. a
Iorio, J. P., Duffy, P., Govindasamy, B., Thompson, S. L., Khairoutdinov, M.,
and Randall, D.: Effects of model resolution and subgrid-scale physics on the
simulation of precipitation in the continental United States, Clim. Dynam.,
23, 243–258, https://doi.org/10.1007/s00382-004-0440-y, 2004. a, b, c
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L.
M., Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou,
E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C.,
Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin,
E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher,
C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana,
J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.:
EURO-CORDEX: new high-resolution climate change projections for European impact
research, Reg. Environ. Change, 14, 563–578, 2014. a
Jung, T., Miller, M., Palmer, T., Towers, P., Wedi, N., Achuthavarier, D.,
Adams, J., Altshuler, E., Cash, B., Kinter III, J., Marx, L., Stan, C., and
Hodges, K. I.: High-resolution global climate simulations with the ECMWF model
in Project Athena: Experimental design, model climate, and seasonal forecast
skill, J. Climate, 25, 3155–3172, 2012. a
Kew, S. F., Selten, F. M., Lenderink, G., and Hazeleger, W.: Robust assessment
of future changes in extreme precipitation over the Rhine basin using a GCM,
Hydrol. Earth Syst. Sci., 15, 1157–1166, https://doi.org/10.5194/hess-15-1157-2011, 2011. a
Liu, C., Ikeda, K., Rasmussen, R., Barlage, M., Newman, A. J., Prein, A. F.,
Chen, F., Chen, L., Clark, M., Dai, A., Dudhia, J., Eidhammer, T., Gochis, D.,
Gutmann, E., Kurkute, S., Li, Y., Thompson, G., and Yates, D.: Continental-scale
convection-permitting modeling of the current and future climate of North America,
Clim. Dynam., 49, 71–95, 2017. a, b
Lundquist, J. D., Hughes, M., Henn, B., Gutmann, E. D., Livneh, B., Dozier, J.,
and Neiman, P.: High-Elevation Precipitation Patterns: Using Snow Measurements
to Assess Daily Gridded Datasets across the Sierra Nevada, California, J.
Hydrometeorol., 16, 1773–1792, https://doi.org/10.1175/JHM-D-15-0019.1, 2015. a
Manganello, J. V., Hodges, K. I., Kinter III, J. L., Cash, B. A., Marx, L.,
Jung, T., Achuthavarier, D., Adams, J. M., Altshuler, E., Huang, B., Jin, E. K.,
Stan, C., Towers, P., and Wedi, N.: Tropical cyclone climatology in a 10-km
global atmospheric GCM: toward weather-resolving climate modeling, J. Climate,
25, 3867–3893, 2012. a
Maraun, D., Shepherd, T. G., Widmann, M., Zappa, G., Walton, D., Gutiérrez,
J. M., Hagemann, S., Richter, I., Soares, P. M., Hall, A., and Mearns, L. O.:
Towards process-informed bias correction of climate change simulations, Nat.
Clim. Change, 7, 764–773, 2017. a
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. a
McCabe, G. J., Hay, L. E., and Clark, M. P.: Rain-on-snow events in the western
United States, B. Am. Meteorol. Soc., 88, 319–328, 2007. a
Meehl, G. A., Moss, R., Taylor, K. E., Eyring, V., Stouffer, R. J., Bony, S.,
and Stevens, B.: Climate model intercomparisons: preparing for the next phase,
Eos Trans. Am. Geophys. Un., 95, 77–78, 2014. a
Melsen, L., Teuling, A., Torfs, P., Zappa, M., Mizukami, N., Clark, M., and
Uijlenhoet, R.: Representation of spatial and temporal variability in
large-domain hydrological models: case study for a mesoscale pre-Alpine basin,
Hydrol. Earth Syst. Sci., 20, 2207–2226, https://doi.org/10.5194/hess-20-2207-2016, 2016. a, b
Moezzi, M., Janda, K. B., and Rotmann, S.: Using stories, narratives, and
storytelling in energy and climate change research, Energy Res. Social Sci.,
31, 1–10, 2017. a
Monteith, J. L.: Evaporation and environment, in the state and movement of water
in living organisms, in: Symp. Soc. Exp. Biol., Academic Press, 205–234, 1965. a
Photiadou, C. S., Weerts, A. H., and van den Hurk, B. J. J. M.: Evaluation of
two precipitation data sets for the Rhine River using streamflow simulations,
Hydrol. Earth Syst. Sci., 15, 3355–3366, https://doi.org/10.5194/hess-15-3355-2011, 2011. a
Poli, P., Hersbach, H., Dee, D. P., Berrisford, P., Simmons, A. J., Vitart, F.,
Laloyaux, P., Tan, D. G., Peubey, C., Thépaut, J.-N., Trémolet, Y.,
Hólm, E. V., Bonavita, M., Isaksen, L., and Fisher, M.: ERA-20C: An
atmospheric reanalysis of the twentieth century, J. Climate, 29, 4083–4097, 2016. a
Prein, A. F. and Gobiet, A.: Impacts of uncertainties in European gridded
precipitation observations on regional climate analysis, Int. J. Climatol.,
37, 305–327, 2017. a
Prein, A. F., Liu, C., Ikeda, K., Bullock, R., Rasmussen, R. M., Holland, G.
J., and Clark, M.: Simulating North American mesoscale convective systems with
a convection-permitting climate model, Clim. Dynam., 1–16, https://doi.org/10.1007/s00382-017-3993-2, 2017. a, b
Priestley, C. and Taylor, R.: On the assessment of surface heat flux and
evaporation using large-scale parameters, Mon. Weather Rev., 100, 81–92, 1972. a
Samaniego, L., Kumar, R., and Attinger, S.: Multiscale parameter regionalization
of a grid-based hydrologic model at the mesoscale, Water Resour. Res., 46,
W05523, https://doi.org/10.1029/2008WR007327, 2010. a
Scaife, A. A., Copsey, D., Gordon, C., Harris, C., Hinton, T., Keeley, S.,
O'Neill, A., Roberts, M., and Williams, K.: Improved Atlantic winter blocking
in a climate model, Geophys. Res. Lett., 38, L23703, https://doi.org/10.1029/2011GL049573, 2011. a
Schellekens, J.: OpenStreams Wflow Documentation, available at: http://wflow.readthedocs.io
(last access: 12 March 2019), 2016. a
Schellekens, J., Dutra, E., Martínez-de la Torre, A., Balsamo, G., van Dijk,
A., Sperna Weiland, F., Minvielle, M., Calvet, J.-C., Decharme, B., Eisner, S.,
Fink, G., Flörke, 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. a
Schiemann, R., Vidale, P. L., Shaffrey, L. C., Johnson, S. J., Roberts, M. J.,
Demory, M.-E., Mizielinski, M. S., and Strachan, J.: Mean and extreme
precipitation over European river basins better simulated in a 25 km AGCM,
Hydrol. Earth Syst. Sci., 22, 3933–3950, https://doi.org/10.5194/hess-22-3933-2018, 2018. a, b
Shabalova, M. V., v. Deursen, W. P. A., and Buishand, T. A.: Assessing future
discharge of the river Rhine using regional climate model integrations and a
hydrological model, Clim. Res., 23, 233–246, https://doi.org/10.3354/cr023233, 2003. a
Stott, P. A., Allen, M., Christidis, N., Dole, R. M., Hoerling, M., Huntingford,
C., Pall, P., Perlwitz, J., and Stone, D.: Attribution of weather and
climate-related events, in: Climate Science for Serving Society, Springer,
Dordrecht, 307–337, 2013. a
Strachan, J., Vidale, P. L., Hodges, K., Roberts, M., and Demory, M.-E.:
Investigating global tropical cyclone activity with a hierarchy of AGCMs: The
role of model resolution, J. Climate, 26, 133–152, 2013. a
Sutanudjaja, E. H., van Beek, R., Wanders, N., Wada, Y., Bosmans, J. H. C.,
Drost, N., van der Ent, R. J., de Graaf, I. E. M., Hoch, J. M., de Jong, K.,
Karssenberg, D., López López, P., Peßenteiner, S., Schmitz, O.,
Straatsma, M. W., Vannametee, E., Wisser, D., and Bierkens, M. F. P.:
PCR-GLOBWB 2: a 5?arcmin global hydrological and water resources model, Geosci.
Model Dev., 11, 2429–2453, https://doi.org/10.5194/gmd-11-2429-2018, 2018. a
Szczypta, C., Decharme, B., Carrer, D., Calvet, J.-C., Lafont, S., Somot, S.,
Faroux, S., and Martin, E.: Impact of precipitation and land biophysical
variables on the simulated discharge of European and Mediterranean rivers,
Hydrol. Earth Syst. Sci., 16, 3351–3370, https://doi.org/10.5194/hess-16-3351-2012, 2012. a
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, 2012. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the
experiment design, B. Am. Meteorol. Soc., 93, 485–498, 2012. a
Turco, M., Zollo, A. L., Ronchi, C., De Luigi, C., and Mercogliano, P.:
Assessing gridded observations for daily precipitation extremes in the Alps
with a focus on northwest Italy, Nat. Hazards Earth Syst. Sci., 13, 1457–1468,
https://doi.org/10.5194/nhess-13-1457-2013, 2013. a
Ulbrich, U. and Fink, A.: The January 1995 flood in Germany: meteorological
versus hydrological causes, Phys. Chem. Earth, 20, 439–444, 1995. a
Van den Hurk, B. J., Viterbo, P., Beljaars, A., and Betts, A.: O ine validation of
the ERA40 surface scheme, ECMWF Tech. Mem. 295, ECMWF, Reading, 1–42, 2000. a
van den Hurk, B. J., Viterbo, P., and Los, S. O.: Impact of leaf area index
seasonality on the annual land surface evaporation in a global circulation
model, J. Geophys. Res.-Atmos., 108, 4191, https://doi.org/10.1029/2002JD002846, 2003. a
van der Wiel, K., Kapnick, S. B., Vecchi, G. A., Cooke, W. F., Delworth, T. L.,
Jia, L., Murakami, H., Underwood, S., and Zeng, F.: The Resolution Dependence
of Contiguous U.S. Precipitation Extremes in Response to CO2 Forcing,
J. Climate, 29, 7991–8012, https://doi.org/10.1175/JCLI-D-16-0307.1, 2016. a, b
Van der Wiel, K., Kapnick, S. B., Vecchi, G. A., Smith, J. A., Milly, P. C.,
and Jia, L.: 100-Year Lower Mississippi Floods in a Global Climate Model:
Characteristics and Future Changes, J. Hydrometeorol., 19, 1547–1563, 2018. a
van Dijk, A. I. J. M.: Climate and terrain factors explaining streamflow response
and recession in Australian catchments, Hydrol. Earth Syst. Sci., 14, 159-169,
https://doi.org/10.5194/hess-14-159-2010, 2010b. a
van Dijk, A. I. J. M. and Renzullo, L. J.: Water resource monitoring systems
and the role of satellite observations, Hydrol. Earth Syst. Sci., 15, 39–55,
https://doi.org/10.5194/hess-15-39-2011, 2011. a
Van Dijk, A. I. J. M. and Warren, G.: The Australian Water Resources Assessment
System, Technical Report 4, Landscape Model (version 0.5) Evaluation Against
Observations, CSIRO: Water for a Healthy Country National Research Flagship, Sydney, 2010. a
van Dijk, A. I. J. M., Peña-Arancibia, J. L., Wood, E. F., Sheffield, J.,
and Beck, H. E.: Global analysis of seasonal streamflow predictability using
an ensemble prediction system and observations from 6192 small catchments
worldwide: Global Analysis of Seasonal Streamflow Predictability, Water Resour.
Res., 49, 2729–2746, https://doi.org/10.1002/wrcr.20251, 2013. a, b
van Haren, R., van Oldenborgh, G. J., Lenderink, G., and Hazeleger, W.:
Evaluation of modeled changes in extreme precipitation in Europe and the Rhine
basin, Environ. Res. Lett., 8, 014053, https://doi.org/10.1088/1748-9326/8/1/014053, 2013. a
Viterbo, P. and Beljaars, A. C. M.: An Improved Land Surface Parameterization
Scheme in the ECMWF Model and Its Validation, J. Climate, 8, 2716–2748, 1995. a
Wang-Erlandsson, L., Bastiaanssen, W. G. M., Gao, H., Jägermeyr, J., Senay,
G. B., van Dijk, A. I. J. M., Guerschman, J. P., Keys, P. W., Gordon, L. J.,
and Savenije, H. H. G.: Global root zone storage capacity from satellite-based
evaporation, Hydrol. Earth Syst. Sci., 20, 1459–1481, https://doi.org/10.5194/hess-20-1459-2016, 2016. a
Wehner, M. F., Smith, R. L., Bala, G., and Duffy, P.: The effect of horizontal
resolution on simulation of very extreme US precipitation events in a global
atmosphere model, Clim. Dynam., 34, 241–247, https://doi.org/10.1007/s00382-009-0656-y, 2010. a, b
Wood, A. W., Leung, L. R., Sridhar, V., and Lettenmaier, D.: Hydrologic
implications of dynamical and statistical approaches to downscaling climate
model outputs, Climatic change, 62, 189–216, 2004. a
Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, L. P. H., Bierkens, M. F. P.,
Blyth, E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis, D., van de
Giesen, N., Houser, P., Jaffé, P. R., Kollet, S., Lehner, B., Lettenmaier,
D. P., Peters-Lidard, C., Sivapalan, M., Sheffield, J., Wade, A., and Whitehead,
P.: Hyperresolution global land surface modeling: Meeting a grand challenge for
monitoring Earth's terrestrial water, Water Resour. Res., 47, W05301,
https://doi.org/10.1029/2010WR010090, 2011. a, b, c
Zappa, G. and Shepherd, T. G.: Storylines of atmospheric circulation change for
European regional climate impact assessment, J. Climate, 30, 6561–6577, 2017. a
Short summary
The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is increasing. This model study examines the benefits of a very high-resolution GCM and GHM in representing the hydrological cycle in the Rhine and Mississippi basins. We find that a higher-resolution GCM results in an improved precipitation budget, and therefore an improved hydrological cycle for the Rhine. For the Mississippi, no substantial improvements are found with increased resolution.
The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is...
