Articles | Volume 22, issue 9
https://doi.org/10.5194/hess-22-4815-2018
© Author(s) 2018. 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-22-4815-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Sep 2018
Research article |
| 18 Sep 2018
| 18 Sep 2018
Toward continental hydrologic–hydrodynamic modeling in South America
Vinícius A. Siqueira
CORRESPONDING AUTHOR
Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio
Grande do Sul (UFRGS), Porto Alegre, 91501-970, Brazil
Rodrigo C. D. Paiva
Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio
Grande do Sul (UFRGS), Porto Alegre, 91501-970, Brazil
Ayan S. Fleischmann
Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio
Grande do Sul (UFRGS), Porto Alegre, 91501-970, Brazil
Fernando M. Fan
Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio
Grande do Sul (UFRGS), Porto Alegre, 91501-970, Brazil
Anderson L. Ruhoff
Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio
Grande do Sul (UFRGS), Porto Alegre, 91501-970, Brazil
Paulo R. M. Pontes
Instituto Tecnológico Vale (ITV), Belém, 66055-090, Brazil
Adrien Paris
LEGOS, Université de Toulouse, CNRS, CNES, IRD, UPS, Toulouse,
France
GET, Université de Toulouse, UPS, CNRS, IRD, Toulouse, France
now at: Collecte Localisation Satellite (CLS), Ramonville-Saint-Agne,
31520, France
Stéphane Calmant
LEGOS, Université de Toulouse, CNRS, CNES, IRD, UPS, Toulouse,
France
Walter Collischonn
Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio
Grande do Sul (UFRGS), Porto Alegre, 91501-970, Brazil
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Subject: Global hydrology | Techniques and Approaches: Modelling approaches
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Juliette Godet, Eric Gaume, Pierre Javelle, Pierre Nicolle, and Olivier Payrastre
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Haiyang Shi, Geping Luo, Olaf Hellwich, Xiufeng He, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 27, 4551–4562, https://doi.org/10.5194/hess-27-4551-2023, https://doi.org/10.5194/hess-27-4551-2023, 2023
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En Ning Lai, Lan Wang-Erlandsson, Vili Virkki, Miina Porkka, and Ruud J. van der Ent
Hydrol. Earth Syst. Sci., 27, 3999–4018, https://doi.org/10.5194/hess-27-3999-2023, https://doi.org/10.5194/hess-27-3999-2023, 2023
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This research scrutinized predicted changes in root zone soil moisture dynamics across different climate scenarios and different climate regions globally between 2021 and 2100. The Mediterranean and most of South America stood out as regions that will likely experience permanently drier conditions, with greater severity observed in the no-climate-policy scenarios. These findings underscore the impact that possible future climates can have on green water resources.
Julia Pfeffer, Anny Cazenave, Alejandro Blazquez, Bertrand Decharme, Simon Munier, and Anne Barnoud
Hydrol. Earth Syst. Sci., 27, 3743–3768, https://doi.org/10.5194/hess-27-3743-2023, https://doi.org/10.5194/hess-27-3743-2023, 2023
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The GRACE (Gravity Recovery And Climate Experiment) satellite mission enabled the quantification of water mass redistributions from 2002 to 2017. The analysis of GRACE satellite data shows here that slow changes in terrestrial water storage occurring over a few years to a decade are severely underestimated by global hydrological models. Several sources of errors may explain such biases, likely including the inaccurate representation of groundwater storage changes.
Thedini Asali Peiris and Petra Döll
Hydrol. Earth Syst. Sci., 27, 3663–3686, https://doi.org/10.5194/hess-27-3663-2023, https://doi.org/10.5194/hess-27-3663-2023, 2023
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Hydrological models often overlook vegetation's response to CO2 and climate, impairing their ability to forecast impacts on evapotranspiration and water resources. To address this, we suggest involving two model variants: (1) the standard method and (2) a modified approach (proposed here) based on the Priestley–Taylor equation (PT-MA). While not universally applicable, a dual approach helps consider uncertainties related to vegetation responses to climate change, enhancing model representation.
Samah Larabi, Juliane Mai, Markus Schnorbus, Bryan A. Tolson, and Francis Zwiers
Hydrol. Earth Syst. Sci., 27, 3241–3263, https://doi.org/10.5194/hess-27-3241-2023, https://doi.org/10.5194/hess-27-3241-2023, 2023
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The computational cost of sensitivity analysis (SA) becomes prohibitive for large hydrologic modeling domains. Here, using a large-scale Variable Infiltration Capacity (VIC) deployment, we show that watershed classification helps identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. Findings reveal the opportunity to leverage climate and land cover attributes to reduce the cost of SA and facilitate more rapid deployment of large-scale land surface models.
Tanja Denager, Torben O. Sonnenborg, Majken C. Looms, Heye Bogena, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 27, 2827–2845, https://doi.org/10.5194/hess-27-2827-2023, https://doi.org/10.5194/hess-27-2827-2023, 2023
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This study contributes to improvements in the model characterization of water and energy fluxes. The results show that multi-objective autocalibration in combination with mathematical regularization is a powerful tool to improve land surface models. Using the direct measurement of turbulent fluxes as the target variable, parameter optimization matches simulations and observations of latent heat, whereas sensible heat is clearly biased.
Yuki Kimura, Yukiko Hirabayashi, Yuki Kita, Xudong Zhou, and Dai Yamazaki
Hydrol. Earth Syst. Sci., 27, 1627–1644, https://doi.org/10.5194/hess-27-1627-2023, https://doi.org/10.5194/hess-27-1627-2023, 2023
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Since both the frequency and magnitude of flood will increase by climate change, information on spatial distributions of potential inundation depths (i.e., flood-hazard map) is required. We developed a method for constructing realistic future flood-hazard maps which addresses issues due to biases in climate models. A larger population is estimated to face risk in the future flood-hazard map, suggesting that only focusing on flood-frequency change could cause underestimation of future risk.
Hoontaek Lee, Martin Jung, Nuno Carvalhais, Tina Trautmann, Basil Kraft, Markus Reichstein, Matthias Forkel, and Sujan Koirala
Hydrol. Earth Syst. Sci., 27, 1531–1563, https://doi.org/10.5194/hess-27-1531-2023, https://doi.org/10.5194/hess-27-1531-2023, 2023
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We spatially attribute the variance in global terrestrial water storage (TWS) interannual variability (IAV) and its modeling error with two data-driven hydrological models. We find error hotspot regions that show a disproportionately large significance in the global mismatch and the association of the error regions with a smaller-scale lateral convergence of water. Our findings imply that TWS IAV modeling can be efficiently improved by focusing on model representations for the error hotspots.
Jannis M. Hoch, Edwin H. Sutanudjaja, Niko Wanders, Rens L. P. H. van Beek, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 27, 1383–1401, https://doi.org/10.5194/hess-27-1383-2023, https://doi.org/10.5194/hess-27-1383-2023, 2023
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To facilitate locally relevant simulations over large areas, global hydrological models (GHMs) have moved towards ever finer spatial resolutions. After a decade-long quest for hyper-resolution (i.e. equal to or smaller than 1 km), the presented work is a first application of a GHM at 1 km resolution over Europe. This not only shows that hyper-resolution can be achieved but also allows for a thorough evaluation of model results at unprecedented detail and the formulation of future research.
Chinchu Mohan, Tom Gleeson, James S. Famiglietti, Vili Virkki, Matti Kummu, Miina Porkka, Lan Wang-Erlandsson, Xander Huggins, Dieter Gerten, and Sonja C. Jähnig
Hydrol. Earth Syst. Sci., 26, 6247–6262, https://doi.org/10.5194/hess-26-6247-2022, https://doi.org/10.5194/hess-26-6247-2022, 2022
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The relationship between environmental flow violations and freshwater biodiversity at a large scale is not well explored. This study intended to carry out an exploratory evaluation of this relationship at a large scale. While our results suggest that streamflow and EF may not be the only determinants of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods or with other biodiversity data or metrics.
Zhaofei Liu
Hydrol. Earth Syst. Sci., 26, 6207–6226, https://doi.org/10.5194/hess-26-6207-2022, https://doi.org/10.5194/hess-26-6207-2022, 2022
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Ground heat flux (G) accounts for a significant fraction of the surface energy balance (SEB), but there is insufficient research on these models compared with other flux. The accuracy of G simulation methods in the SEB-based remote sensing evapotranspiration models is evaluated. Results show that the accuracy of each method varied significantly at different sites and at half-hour intervals. Further improvement of G simulations is recommended for the remote sensing evapotranspiration modelers.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022, https://doi.org/10.5194/hess-26-5971-2022, 2022
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We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
Feng Zhong, Shanhu Jiang, Albert I. J. M. van Dijk, Liliang Ren, Jaap Schellekens, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 26, 5647–5667, https://doi.org/10.5194/hess-26-5647-2022, https://doi.org/10.5194/hess-26-5647-2022, 2022
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A synthesis of rainfall interception data from past field campaigns is performed, including 166 forests and 17 agricultural plots distributed worldwide. These site data are used to constrain and validate an interception model that considers sub-grid heterogeneity and vegetation dynamics. A global, 40-year (1980–2019) interception dataset is generated at a daily temporal and 0.1° spatial resolution. This dataset will serve as a benchmark for future investigations of the global hydrological cycle.
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 5473–5491, https://doi.org/10.5194/hess-26-5473-2022, https://doi.org/10.5194/hess-26-5473-2022, 2022
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Sea level rise, storm surge and river discharge can cause coastal backwater effects in downstream sections of rivers, creating critical flood risks. This study simulates the backwater effects using a large-scale river model on a coastal-refined computational mesh. By decomposing the backwater drivers, we revealed their relative importance and long-term variations. Our analysis highlights the increasing strength of backwater effects due to sea level rise and more frequent storm surge.
Kieran M. R. Hunt, Gwyneth R. Matthews, Florian Pappenberger, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 5449–5472, https://doi.org/10.5194/hess-26-5449-2022, https://doi.org/10.5194/hess-26-5449-2022, 2022
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In this study, we use three models to forecast river streamflow operationally for 13 months (September 2020 to October 2021) at 10 gauges in the western US. The first model is a state-of-the-art physics-based streamflow model (GloFAS). The second applies a bias-correction technique to GloFAS. The third is a type of neural network (an LSTM). We find that all three are capable of producing skilful forecasts but that the LSTM performs the best, with skilful 5 d forecasts at nine stations.
Tongtiegang Zhao, Haoling Chen, Yu Tian, Denghua Yan, Weixin Xu, Huayang Cai, Jiabiao Wang, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 26, 4233–4249, https://doi.org/10.5194/hess-26-4233-2022, https://doi.org/10.5194/hess-26-4233-2022, 2022
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This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts).
Vili Virkki, Elina Alanärä, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu
Hydrol. Earth Syst. Sci., 26, 3315–3336, https://doi.org/10.5194/hess-26-3315-2022, https://doi.org/10.5194/hess-26-3315-2022, 2022
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Direct and indirect human actions have altered streamflow across the world since pre-industrial times. Here, we apply a method of environmental flow envelopes (EFEs) that develops the existing global environmental flow assessments by methodological advances and better consideration of uncertainty. By assessing the violations of the EFE, we comprehensively quantify the frequency, severity, and trends of flow alteration during the past decades, illustrating anthropogenic effects on streamflow.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
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Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Jawairia A. Ahmad, Barton A. Forman, and Sujay V. Kumar
Hydrol. Earth Syst. Sci., 26, 2221–2243, https://doi.org/10.5194/hess-26-2221-2022, https://doi.org/10.5194/hess-26-2221-2022, 2022
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Assimilation of remotely sensed data into a land surface model to improve the spatiotemporal estimation of soil moisture across South Asia exhibits potential. Satellite retrieval assimilation corrects biases that are generated due to an unmodeled hydrologic phenomenon, i.e., irrigation. The improvements in fine-scale, modeled soil moisture estimates by assimilating coarse-scale retrievals indicates the utility of the described methodology for data-scarce regions.
Naota Hanasaki, Hikari Matsuda, Masashi Fujiwara, Yukiko Hirabayashi, Shinta Seto, Shinjiro Kanae, and Taikan Oki
Hydrol. Earth Syst. Sci., 26, 1953–1975, https://doi.org/10.5194/hess-26-1953-2022, https://doi.org/10.5194/hess-26-1953-2022, 2022
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Global hydrological models (GHMs) are usually applied with a spatial resolution of about 50 km, but this time we applied the H08 model, one of the most advanced GHMs, with a high resolution of 2 km to Kyushu island, Japan. Since the model was not accurate as it was, we incorporated local information and improved the model, which revealed detailed water stress in subregions that were not visible with the previous resolution.
Basil Kraft, Martin Jung, Marco Körner, Sujan Koirala, and Markus Reichstein
Hydrol. Earth Syst. Sci., 26, 1579–1614, https://doi.org/10.5194/hess-26-1579-2022, https://doi.org/10.5194/hess-26-1579-2022, 2022
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We present a physics-aware machine learning model of the global hydrological cycle. As the model uses neural networks under the hood, the simulations of the water cycle are learned from data, and yet they are informed and constrained by physical knowledge. The simulated patterns lie within the range of existing hydrological models and are plausible. The hybrid modeling approach has the potential to tackle key environmental questions from a novel perspective.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung
Hydrol. Earth Syst. Sci., 26, 1089–1109, https://doi.org/10.5194/hess-26-1089-2022, https://doi.org/10.5194/hess-26-1089-2022, 2022
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We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare two experiments, one with globally uniform and one with vegetation parameters that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting the important role of the interaction between groundwater–soil moisture–vegetation in understanding TWS variations.
Marc F. P. Bierkens, Edwin H. Sutanudjaja, and Niko Wanders
Hydrol. Earth Syst. Sci., 25, 5859–5878, https://doi.org/10.5194/hess-25-5859-2021, https://doi.org/10.5194/hess-25-5859-2021, 2021
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We introduce a simple analytical framework that allows us to estimate to what extent large-scale groundwater withdrawal affects groundwater levels and streamflow. It also calculates which part of the groundwater withdrawal comes out of groundwater storage and which part from a reduction in streamflow. Global depletion rates obtained with the framework are compared with estimates from satellites, from global- and continental-scale groundwater models, and from in situ datasets.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, https://doi.org/10.5194/hess-25-5287-2021, 2021
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Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
Jérôme Kopp, Pauline Rivoire, S. Mubashshir Ali, Yannick Barton, and Olivia Martius
Hydrol. Earth Syst. Sci., 25, 5153–5174, https://doi.org/10.5194/hess-25-5153-2021, https://doi.org/10.5194/hess-25-5153-2021, 2021
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Episodes of extreme rainfall events happening in close temporal succession can lead to floods with dramatic impacts. We developed a novel method to individually identify those episodes and deduced the regions where they occur frequently and where their impact is substantial. Those regions are the east and northeast of the Asian continent, central Canada and the south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and north of Argentina and south of Bolivia.
Alyssa J. DeVincentis, Hervé Guillon, Romina Díaz Gómez, Noelle K. Patterson, Francine van den Brandeler, Arthur Koehl, J. Pablo Ortiz-Partida, Laura E. Garza-Díaz, Jennifer Gamez-Rodríguez, Erfan Goharian, and Samuel Sandoval Solis
Hydrol. Earth Syst. Sci., 25, 4631–4650, https://doi.org/10.5194/hess-25-4631-2021, https://doi.org/10.5194/hess-25-4631-2021, 2021
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Latin America and the Caribbean face many water-related stresses which are expected to worsen with climate change. To assess the vulnerability, we reviewed over 20 000 multilingual research articles using machine learning and an understanding of the regional landscape. Results reveal that the region’s inherent vulnerability is compounded by research blind spots in niche topics (reservoirs and risk assessment) and subregions (Caribbean nations), as well as by its reliance on one country (Brazil).
Michiel Maertens, Gabriëlle J. M. De Lannoy, Sebastian Apers, Sujay V. Kumar, and Sarith P. P. Mahanama
Hydrol. Earth Syst. Sci., 25, 4099–4125, https://doi.org/10.5194/hess-25-4099-2021, https://doi.org/10.5194/hess-25-4099-2021, 2021
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In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.
Louise J. Slater, Bailey Anderson, Marcus Buechel, Simon Dadson, Shasha Han, Shaun Harrigan, Timo Kelder, Katie Kowal, Thomas Lees, Tom Matthews, Conor Murphy, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 3897–3935, https://doi.org/10.5194/hess-25-3897-2021, https://doi.org/10.5194/hess-25-3897-2021, 2021
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Weather and water extremes have devastating effects each year. One of the principal challenges for society is understanding how extremes are likely to evolve under the influence of changes in climate, land cover, and other human impacts. This paper provides a review of the methods and challenges associated with the detection, attribution, management, and projection of nonstationary weather and water extremes.
Sanaa Hobeichi, Gab Abramowitz, and Jason P. Evans
Hydrol. Earth Syst. Sci., 25, 3855–3874, https://doi.org/10.5194/hess-25-3855-2021, https://doi.org/10.5194/hess-25-3855-2021, 2021
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Evapotranspiration (ET) links the water, energy and carbon cycle on land. Reliable ET estimates are key to understand droughts and flooding. We develop a new ET dataset, DOLCE V3, by merging multiple global ET datasets, and we show that it matches ET observations better and hence is more reliable than its parent datasets. Next, we use DOLCE V3 to examine recent changes in ET and find that ET has increased over most of the land, decreased in some regions, and has not changed in some other regions
Frederik Kratzert, Daniel Klotz, Sepp Hochreiter, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 25, 2685–2703, https://doi.org/10.5194/hess-25-2685-2021, https://doi.org/10.5194/hess-25-2685-2021, 2021
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We investigate how deep learning models use different meteorological data sets in the task of (regional) rainfall–runoff modeling. We show that performance can be significantly improved when using different data products as input and further show how the model learns to combine those meteorological input differently across time and space. The results are carefully benchmarked against classical approaches, showing the supremacy of the presented approach.
Fabian Stenzel, Dieter Gerten, and Naota Hanasaki
Hydrol. Earth Syst. Sci., 25, 1711–1726, https://doi.org/10.5194/hess-25-1711-2021, https://doi.org/10.5194/hess-25-1711-2021, 2021
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Ideas to mitigate climate change include the large-scale cultivation of fast-growing plants to capture atmospheric CO2 in biomass. To maximize the productivity of these plants, they will likely be irrigated. However, there is strong disagreement in the literature on how much irrigation water is needed globally, potentially inducing water stress. We provide a comprehensive overview of global irrigation demand studies for biomass production and discuss the diverse underlying study assumptions.
Charles Rougé, Patrick M. Reed, Danielle S. Grogan, Shan Zuidema, Alexander Prusevich, Stanley Glidden, Jonathan R. Lamontagne, and Richard B. Lammers
Hydrol. Earth Syst. Sci., 25, 1365–1388, https://doi.org/10.5194/hess-25-1365-2021, https://doi.org/10.5194/hess-25-1365-2021, 2021
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Amid growing interest in using large-scale hydrological models for flood and drought monitoring and forecasting, it is important to evaluate common assumptions these models make. We investigated the representation of reservoirs as separate (non-coordinated) infrastructure. We found that not appropriately representing coordination and control processes can lead a hydrological model to simulate flood and drought events that would not occur given the coordinated emergency response in the basin.
Robert Reinecke, Hannes Müller Schmied, Tim Trautmann, Lauren Seaby Andersen, Peter Burek, Martina Flörke, Simon N. Gosling, Manolis Grillakis, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Wim Thiery, Yoshihide Wada, Satoh Yusuke, and Petra Döll
Hydrol. Earth Syst. Sci., 25, 787–810, https://doi.org/10.5194/hess-25-787-2021, https://doi.org/10.5194/hess-25-787-2021, 2021
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Billions of people rely on groundwater as an accessible source of drinking water and for irrigation, especially in times of drought. Groundwater recharge is the primary process of regenerating groundwater resources. We find that groundwater recharge will increase in northern Europe by about 19 % and decrease by 10 % in the Amazon with 3 °C global warming. In the Mediterranean, a 2 °C warming has already lead to a reduction in recharge by 38 %. However, these model predictions are uncertain.
Laura E. Queen, Philip W. Mote, David E. Rupp, Oriana Chegwidden, and Bart Nijssen
Hydrol. Earth Syst. Sci., 25, 257–272, https://doi.org/10.5194/hess-25-257-2021, https://doi.org/10.5194/hess-25-257-2021, 2021
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Using a large ensemble of simulated flows throughout the northwestern USA, we compare daily flood statistics in the past (1950–1999) and future (2050–1999) periods and find that nearly all locations will experience an increase in flood magnitudes. The flood season expands significantly in many currently snow-dominant rivers, moving from only spring to both winter and spring. These results, properly extended, may help inform flood risk management and negotiations of the Columbia River Treaty.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Yared Abayneh Abebe, Amineh Ghorbani, Igor Nikolic, Natasa Manojlovic, Angelika Gruhn, and Zoran Vojinovic
Hydrol. Earth Syst. Sci., 24, 5329–5354, https://doi.org/10.5194/hess-24-5329-2020, https://doi.org/10.5194/hess-24-5329-2020, 2020
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The paper presents a coupled agent-based and flood model for Hamburg, Germany. It explores residents’ adaptation behaviour in relation to flood event scenarios, economic incentives and shared and individual strategies. We found that unique trajectories of adaptation behaviour emerge from different flood event series. Providing subsidies improves adaptation behaviour in the long run. The coupled modelling technique allows the role of individual measures in flood risk management to be examined.
Denise Cáceres, Ben Marzeion, Jan Hendrik Malles, Benjamin Daniel Gutknecht, Hannes Müller Schmied, and Petra Döll
Hydrol. Earth Syst. Sci., 24, 4831–4851, https://doi.org/10.5194/hess-24-4831-2020, https://doi.org/10.5194/hess-24-4831-2020, 2020
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We analysed how and to which extent changes in water storage on continents had an effect on global ocean mass over the period 1948–2016. Continents lost water to oceans at an accelerated rate, inducing sea level rise. Shrinking glaciers explain 81 % of the long-term continental water mass loss, while declining groundwater levels, mainly due to sustained groundwater pumping for irrigation, is the second major driver. This long-term decline was partly offset by the impoundment of water in dams.
Salma Tafasca, Agnès Ducharne, and Christian Valentin
Hydrol. Earth Syst. Sci., 24, 3753–3774, https://doi.org/10.5194/hess-24-3753-2020, https://doi.org/10.5194/hess-24-3753-2020, 2020
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In land surface models (LSMs), soil properties are inferred from soil texture. In this study, we use different input global soil texture maps from the literature to investigate the impact of soil texture on the simulated water budget in an LSM. The medium loamy textures give the highest evapotranspiration and lowest total runoff rates. However, the different soil texture maps result in similar water budgets because of their inherent similarities, especially when upscaled at the 0.5° resolution.
Xinxuan Zhang, Viviana Maggioni, Azbina Rahman, Paul Houser, Yuan Xue, Timothy Sauer, Sujay Kumar, and David Mocko
Hydrol. Earth Syst. Sci., 24, 3775–3788, https://doi.org/10.5194/hess-24-3775-2020, https://doi.org/10.5194/hess-24-3775-2020, 2020
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This study assesses the extent to which a land surface model can be optimized via the assimilation of leaf area index (LAI) observations at the global scale. The model performance is evaluated by the model-estimated LAI and five water flux/storage variables. Results show the LAI assimilation reduces errors in the model-estimated LAI. The LAI assimilation also improves the five water variables under wet conditions, but some of the model-estimated variables tend to be worse under dry conditions.
Cited articles
Abbaspour, K. C., Rouholahnejad, E., Vaghefi, S., Srinivasan, R., Yang, H., and Kløve, B.: A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model, J. Hydrol., 524, 733–752, https://doi.org/10.1016/j.jhydrol.2015.03.027, 2015.
Alkama, R., Decharme, B., Douville, H., Becker, M., Cazenave, A., Sheffield, J., Voldoire, A., Tyteca, S., and Le Moigne, P.: Global evaluation of the ISBA-TRIP continental hydrological system. Part I: Comparison to GRACE terrestrial water storage estimates and in situ river discharges, J. Hydrometeorol., 11, 583–600, https://doi.org/10.1175/2010JHM1211.1, 2010.
Allasia, D. G., Da Silva, B. C., Collischonn, W., and Tucci, C. E. M.: Large basin simulation experience in South America, IAHS-AISH Publication, 360–370, 2006.
Alsdorf, D., Bates, P., Melack, J., Wilson, M., and Dunne, T.: Spatial and temporal complexity of the Amazon flood measured from space, Geophys. Res. Lett., 34, L08402, https://doi.org/10.1029/2007GL029447, 2007.
Andreadis, K. M., Schumann, G. J. P., and Pavelsky, T.: A simple global river bankfull width and depth database, Water Resour. Res., 49, 7164–7168, https://doi.org/10.1002/wrcr.20440, 2013.
Angarita, H., Wickel, A. J., Sieber, J., Chavarro, J., Maldonado-Ocampo, J. A., Herrera-R., G. A., Delgado, J., and Purkey, D.: Basin-scale impacts of hydropower development on the Mompós Depression wetlands, Colombia, Hydrol. Earth Syst. Sci., 22, 2839–2865, https://doi.org/10.5194/hess-22-2839-2018, 2018.
Archfield, S. A., Clark, M., Arheimer, B., Hay, L. E., McMillan, H., Kiang, J. E., Seibert, J., Hakala, K., Bock, A., Wagener, T., Farmer, W. H., Andréassian, V., Attinger, S., Viglione, A., Knight, R., Markstrom, S., and Over, T.: Accelerating advances in continental domain hydrologic modeling, Water Resour. Res., 51, 10078–10091, https://doi.org/10.1002/2015wr017498, 2015.
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. 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.
Barros, V., Clarke, R., and Dias, P. S.: Climate change in the La Plata basin, Publication of the Inter-American Institute for Global Change Research (IAI), São José dos Campos, Brazil, 2006.
Bates, P. D., Horritt, M. S., and Fewtrell, T. J.: A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling, J. Hydrol., 387, 33–45, https://doi.org/10.1016/j.jhydrol.2010.03.027, 2010.
Baugh, C. A., Bates, P. D., Schumann, G., and Trigg, M. A.: SRTM vegetation removal and hydrodynamic modeling accuracy, Water Resour. Res., 49, 5276–5289, https://doi.org/10.1002/wrcr.20412, 2013.
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, 2017a.
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, 2017b.
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, 2017c.
Beighley, R. E. and Gummadi, V.: Developing channel and floodplain dimensions with limited data: A case study in the Amazon Basin, Earth Surf. Proc. Land., 36, 1059–1071, https://doi.org/10.1002/esp.2132, 2011.
Berbery, E. H. and Barros, V. R.: The hydrologic cycle of the La Plata basin in South America, J. Hydrometeorol., 3, 630–645, https://doi.org/10.1175/1525-7541(2002)003<0630:THCOTL>2.0.CO;2, 2002.
Berry, P. A. M., Garlick, J. D., and Smith, R. G.: Near-global validation of the SRTM DEM using satellite radar altimetry, Remote Sens. Environ., 106, 17–27, https://doi.org/10.1016/j.rse.2006.07.011, 2007.
Bierkens, M. F. P.: Global hydrology 2015: State, trends, and directions, Water Resour. Res., 51, 4923–4947, https://doi.org/10.1002/2015wr017173, 2015.
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?, Hydrol. Process., 29, 310–320, https://doi.org/10.1002/hyp.10391, 2015.
Bravo, J. M., Allasia, D., Paz, A. R., Collischonn, W., and Tucci, C. E. M.: Coupled Hydrologic-Hydraulic Modeling of the Upper Paraguay River Basin, J. Hydrol. Eng., 17, 635–646, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000494, 2012.
Carabajal, C. C. and Harding, D. J.: ICESat validation of SRTM C-band digital elevation models, Geophys. Res. Lett., 32, L22S01, https://doi.org/10.1029/2005gl023957, 2005.
Chen, J. L., Wilson, C. R., Tapley, B. D., Blankenship, D. D., and Ivins, E. R.: Patagonia icefield melting observed by gravity recovery and climate experiment (GRACE), Geophys. Res. Lett., 34, L22501, https://doi.org/10.1029/2007gl031871, 2007.
Christoffersen, B. O., Restrepo-Coupe, N., Arain, M. A., Baker, I. T., Cestaro, B. P., Ciais, P., Fisher, J. B., Galbraith, D., Guan, X. D., Gulden, L., van den Hurk, B., Ichii, K., Imbuzeiro, H., Jain, A., Levine, N., Miguez-Machor, G., Poulter, B., Roberti, D. R., Sakaguchi, K., Sahoo, A., Schaefer, K., Shi, M. J., Verbeeck, H., Yang, Z. L., Araujo, A. C., Kruijt, B., Manzi, A. O., da Rocha, H. R., von Randow, C., Muza, M. N., Borak, J., Costa, M. H., de Gonçalves, L. G. G., Zeng, X. B., and Saleska, S. R.: Mechanisms of water supply and vegetation demand govern the seasonality and magnitude of evapotranspiration in Amazonia and Cerrado, Agr. Forest Meteorol., 191, 33–50, https://doi.org/10.1016/j.agrformet.2014.02.008, 2014.
Clark, E. A., Sheffield, J., van Vliet, M. T. H., Nijssen, B., and Lettenmaier, D. P.: Continental Runoff into the Oceans (1950–2008), J. Hydrometeorol., 16, 1502–1520, https://doi.org/10.1175/jhm-d-14-0183.1, 2015.
Collischonn, W.: Simulação Hidrológica de Grandes Bacias, Phd Dissertation, Doutorado em Recursos Hídricos e Saneamento Ambiental, Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, 270 pp., 2001 (in Portuguese).
Collischonn, W., Haas, R., Andreolli, I., and Tucci, C. E. M.: Forecasting River Uruguay flow using rainfall forecasts from a regional weather-prediction model, J. Hydrol., 305, 87–98, https://doi.org/10.1016/j.jhydrol.2004.08.028, 2005.
Collischonn, W., Allasia, D., Da Silva, B. C., and Tucci, C. E. M.: The MGB-IPH model for large-scale rainfall-runoff modelling, Hydrolog. Sci. J.-Journal Des Sciences Hydrologiques, 52, 878–895, https://doi.org/10.1623/hysj.52.5.878, 2007.
Costa, A. C., Bronstert, A., and de Araújo, J. C.: A channel transmission losses model for different dryland rivers, Hydrol. Earth Syst. Sci., 16, 1111–1135, https://doi.org/10.5194/hess-16-1111-2012, 2012.
Costa, A. C., Foerster, S., de Araújo, J. C., and Bronstert, A.: Analysis of channel transmission losses in a dryland river reach in north-eastern Brazil using streamflow series, groundwater level series and multi-temporal satellite data, Hydrol. Process., 27, 1046–1060, https://doi.org/10.1002/hyp.9243, 2013.
Crooks, S. M., Kay, A. L., Davies, H. N., and Bell, V. A.: From Catchment to National Scale Rainfall-Runoff Modelling: Demonstration of a Hydrological Modelling Framework, Hydrology, 1, 63–88, https://doi.org/10.3390/hydrology1010063, 2014.
Decharme, B., Douville, H., Prigent, C., Papa, F., and Aires, F.: A new river flooding scheme for global climate applications: Off-line evaluation over South America, J. Geophys. Res.-Atmos., 113, D11110, https://doi.org/10.1029/2007jd009376, 2008.
Dinku, T., Ceccato, P., Cressman, K., and Connor, S. J.: Evaluating detection skills of satellite rainfall estimates over desert locust recession regions, J. Appl. Meteorol. Clim., 49, 1322–1332, https://doi.org/10.1175/2010JAMC2281.1, 2010.
Döll, P., Fiedler, K., and Zhang, J.: Global-scale analysis of river flow alterations due to water withdrawals and reservoirs, Hydrol. Earth Syst. Sci., 13, 2413–2432, https://doi.org/10.5194/hess-13-2413-2009, 2009.
Donnelly, C., Andersson, J. C. M., and Arheimer, B.: Using flow signatures and catchment similarities to evaluate the E-HYPE multi-basin model across Europe, Hydrolog. Sci. J.-Journal Des Sciences Hydrologiques, 61, 255–273, https://doi.org/10.1080/02626667.2015.1027710, 2016.
Durr, H. H., Meybeck, M., and Durr, S. H.: Lithologic composition of the Earth's continental surfaces derived from a new digital map emphasizing riverine material transfer, Global Biogeochem. Cy., 19, GB4S10, https://doi.org/10.1029/2005gb002515, 2005.
Dutra, E., Balsamo, G., Calvet, J.-C., Munier, S., Burke, S., Fink, G., van Dijk, A., Martinez-de la Torre, A., van Beek, R., de Roo, A., and Polcher, J.: Report on the improved Water Resources Reanalysis. EartH2Observe, Report No.: 5.2., 94 pp., https://doi.org/10.13140/RG.2.2.14523.67369, 2017.
Eisner, S., Florke, M., Chamorro, A., Daggupati, P., Donnelly, C., Huang, J., Hundecha, Y., Koch, H., Kalugin, A., Krylenko, I., Mishra, V., Piniewski, M., Samaniego, L., Seidou, O., Wallner, M., and Krysanova, V.: An ensemble analysis of climate change impacts on streamflow seasonality across 11 large river basins, Climatic Change, 141, 401–417, https://doi.org/10.1007/s10584-016-1844-5, 2017.
Erfanian, A., Wang, G., and Fomenko, L.: Unprecedented drought over tropical South America in 2016: Significantly under-predicted by tropical SST, Sci. Rep., 7, 5811, https://doi.org/10.1038/s41598-017-05373-2, 2017.
Fan, F. M., Buarque, D. C., Pontes, P. R. M., and Collischonn, W.: Um mapa de unidades de resposta hidrológica para a América do Sul, XXI Simpósio Brasileiro de Recursos Hídricos, Brasilia, PAP019919, 2015.
Fan, F. M., Collischonn, W., Quiroz, K. J., Sorribas, M. V., Buarque, D. C., and Siqueira, V. A.: Flood forecasting on the Tocantins River using ensemble rainfall forecasts and real-time satellite rainfall estimates, J. Flood Risk Manag., 9, 278–288, https://doi.org/10.1111/jfr3.12177, 2016.
Fleischmann, A. S., Siqueira, V. A., Paris, A., Collischonn, W., Paiva, R. C. D., Pontes, P. R. M., Crétaux, J.-F., Bergé-Nguyen, M., Biancamaria, S., Gosset, M., Calmant, S., and Tanimoun, B. A.: Modeling hydrologic and hydrodynamic processes in basins with semi-arid wetlands, J. Hydrol., 561, 943–959, 2018.
Frappart, F., Papa, F., Malbeteau, Y., León, J., Ramillien, G., Prigent, C., Seoane, L., Seyler, F., and Calmant, S.: Surface Freshwater Storage Variations in the Orinoco Floodplains Using Multi-Satellite Observations, Remote Sensing, 7, 89–110, https://doi.org/10.3390/rs70100089, 2014.
Garcia, N. O. and Mechoso, C. R.: Variability in the discharge of South American rivers and in climate, Hydrolog. Sci. J.-Journal Des Sciences Hydrologiques, 50, 459–478, https://doi.org/10.1623/hysj.50.3.459.65030, 2005.
Garreaud, R. D., Vuille, M., Compagnucci, R., and Marengo, J.: Present-day South American climate, Palaeogeogr. Palaeocl., 281, 180–195, https://doi.org/10.1016/j.palaeo.2007.10.032, 2009.
Getirana, A. C. V.: Integrating spatial altimetry data into the automatic calibration of hydrological models, J. Hydrol., 387, 244–255, https://doi.org/10.1016/j.jhydrol.2010.04.013, 2010.
Getirana, A. C. V., Boone, A., Yamazaki, D., Decharme, B., Papa, F., and Mognard, N.: The Hydrological Modeling and Analysis Platform (HyMAP): Evaluation in the Amazon Basin, J. Hydrometeorol., 13, 1641–1665, https://doi.org/10.1175/jhm-d-12-021.1, 2012.
Getirana, A. C. V., Boone, A., Yamazaki, D., and Mognard, N.: Automatic parameterization of a flow routing scheme driven by radar altimetry data: Evaluation in the Amazon basin, Water Resour. Res., 49, 614–629, https://doi.org/10.1002/wrcr.20077, 2013.
Getirana, A. C. V. and Paiva, R. C. D.: Mapping large-scale river flow hydraulics in the Amazon Basin, Water Resour. Res., 49, 2437–2445, https://doi.org/10.1002/wrcr.20212, 2013.
Getirana, A., Kumar, S., Girotto, M., and Rodell, M.: Rivers and Floodplains as Key Components of Global Terrestrial Water Storage Variability, Geophys. Res. Lett., 44, 10359–310368, https://doi.org/10.1002/2017GL074684, 2017a.
Getirana, A., Peters-Lidard, C., Rodell, M., and Bates, P. D.: Trade-off between cost and accuracy in large-scale surface water dynamic modeling, Water Resour. Res., 53, 4942–4955, https://doi.org/10.1002/2017wr020519, 2017b.
Gonçalves, H. C., Mercante, M. A., and Santos, E. T.: Hydrological cycle, Brazilian Journal of Biology, 71, 241–253, https://doi.org/10.1590/s1519-69842011000200003, 2011.
Gosling, S. N., Taylor, R. G., Arnell, N. W., and Todd, M. C.: A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models, Hydrol. Earth Syst. Sci., 15, 279–294, https://doi.org/10.5194/hess-15-279-2011, 2011.
Gudmundsson, L., Tallaksen, L. M., Stahl, K., Clark, D. B., Dumont, E., Hagemann, S., Bertrand, N., Gerten, D., Heinke, J., Hanasaki, N., Voss, F., and Koirala, S.: Comparing Large-Scale Hydrological Model Simulations to Observed Runoff Percentiles in Europe, J. Hydrometeorol., 13, 604–620, https://doi.org/10.1175/jhm-d-11-083.1, 2012.
Güntner, A. and Bronstert, A.: Representation of landscape variability and lateral redistribution processes for large-scale hydrological modelling in semi-arid areas, J. Hydrol., 297, 136–161, https://doi.org/10.1016/j.jhydrol.2004.04.008, 2004.
Guswa, A. J., Celia, M. A., and Rodriguez-Iturbe, I.: Models of soil moisture dynamics in ecohydrology: A comparative study, Water Resour. Res., 38, 1166, https://doi.org/10.1029/2001wr000826, 2002.
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.
Hamilton, S. K., Sippel, S. J., and Melack, J. M.: Comparison of inundation patterns among major South American floodplains, J. Geophys. Res.-Atmos., 107, 8038, https://doi.org/10.1029/2000jd000306, 2002.
Hanasaki, N., Yoshikawa, S., Pokhrel, Y., and Kanae, S.: A global hydrological simulation to specify the sources of water used by humans, Hydrol. Earth Syst. Sci., 22, 789–817, https://doi.org/10.5194/hess-22-789-2018, 2018.
Hattermann, F. F., Vetter, T., Breuer, L., Su, B. D., Daggupati, P., Donnelly, C., Fekete, B., Florke, F., Gosling, S. N., Hoffmann, P., Liersch, S., Masaki, Y., Motovilov, Y., Muller, C., Samaniego, L., Stacke, T., Wada, Y., Yang, T., and Krysnaova, V.: Sources of uncertainty in hydrological climate impact assessment: a cross-scale study, Environ. Res. Lett., 13, 015006, https://doi.org/10.1088/1748-9326/aa9938, 2018.
Hodges, B. R.: Challenges in Continental River Dynamics, Environ. Modell. Soft., 50, 16–20, https://doi.org/10.1016/j.envsoft.2013.08.010, 2013.
Hoyos, N., Escobar, J., Restrepo, J. C., Arango, A. M., and Ortiz, J. C.: Impact of the 2010-2011 La Nina phenomenon in Colombia, South America: The human toll of an extreme weather event, Appl. Geogr., 39, 16–25, https://doi.org/10.1016/j.apgeog.2012.11.018, 2013.
Huang, S., Kumar, R., Flörke, M., Yang, T., Hundecha, Y., Kraft, P., Gao, C., Gelfan, A., Liersch, S., Lobanova, A., Strauch, M., van Ogtrop, F., Reinhardt, J., Haberlandt, U., and Krysanova, V.: Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide, Climatic Change, 141, 381–397, https://doi.org/10.1007/s10584-016-1841-8, 2016.
Humphrey, V., Gudmundsson, L., and Seneviratne, S. I.: Assessing Global Water Storage Variability from GRACE: Trends, Seasonal Cycle, Subseasonal Anomalies and Extremes, Surv. Geophys., 37, 357–395, https://doi.org/10.1007/s10712-016-9367-1, 2016.
Jarihani, A. A., Larsen, J. R., Callow, J. N., McVicar, T. R., and Johansen, K.: Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing, J. Hydrol., 529, 1511–1529, https://doi.org/10.1016/j.jhydrol.2015.08.030, 2015.
Kauffeldt, A., Wetterhall, F., Pappenberger, F., Salamon, P., and Thielen, J.: Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level, Environ. Modell. Soft., 75, 68–76, https://doi.org/10.1016/j.envsoft.2015.09.009, 2016.
Kerr, Y. H., Waldteufel, P., Richaume, P., Wigneron, J. P., Ferrazzoli, P., Mahmoodi, A., Al Bitar, A., Cabot, F., Gruhier, C., Juglea, S. E., Leroux, D., Mialon, A., and Delwart, S.: The SMOS soil moisture retrieval algorithm, IEEE T. Geosci. Remote, 50, 1384–1403, https://doi.org/10.1109/TGRS.2012.2184548, 2012.
Kirchner, J. W.: Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology, Water Resour. Res., 42, W03S04, https://doi.org/10.1029/2005wr004362, 2006.
Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios, J. Hydrol., 424–425, 264–277, https://doi.org/10.1016/j.jhydrol.2012.01.011, 2012.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World map of the Köppen-Geiger climate classification updated, Meteorol. Z., 15, 259–263, https://doi.org/10.1127/0941-2948/2006/0130, 2006.
Krysanova, V., Vetter, T., Eisner, S., Huang, S., Pechlivanidis, I., Strauch, M., Gelfan, A., Kumar, R., Aich, V., Arheimer, B., Chamorro, A., Van Griensven, A., Kundu, D., Lobanova, A., Mishra, V., Plötner, S., Reinhardt, J., Seidou, O., Wang, X., Wortmann, M., Zeng, X., and Hattermann, F. F.: Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide – A synthesis, Environ. Res. Lett., 12, 105002, https://doi.org/10.1088/1748-9326/aa8359, 2017.
Kuppel, S., Houspanossian, J., Nosetto, M. D., and Jobbagy, E. G.: What does it take to flood the Pampas?: Lessons from a decade of strong hydrological fluctuations, Water Resour. Res., 51, 2937–2950, https://doi.org/10.1002/2015wr016966, 2015.
Landerer, F. W. and Swenson, S. C.: Accuracy of scaled GRACE terrestrial water storage estimates, Water Resour. Res., 48, W04531, https://doi.org/10.1029/2011wr011453, 2012.
Latrubesse, E. M., Stevaux, J. C., and Sinha, R.: Tropical rivers, Geomorphology, 70, 187–206, https://doi.org/10.1016/j.geomorph.2005.02.005, 2005.
Latrubesse, E. M.: Large rivers, megafans and other Quaternary avulsive fluvial systems: A potential “who's who” in the geological record, Earth-Sci. Rev., 146, 1–30, https://doi.org/10.1016/j.earscirev.2015.03.004, 2015.
Lehner, B. and Döll, P.: Development and validation of a global database of lakes, reservoirs and wetlands, J. Hydrol., 296, 1–22, https://doi.org/10.1016/j.jhydrol.2004.03.028, 2004.
Lehner, B., Verdin, K., and Jarvis, A.: New global hydrography derived from spaceborne elevation data, EOS, 89, 93–94, https://doi.org/10.1029/2008EO100001, 2008.
Leopold, L. B. and Maddock, T. J.: The hydraulic geometry of stream channels and some physiographic implications, U.S. Geological Survey Professional Paper, 252, 56 pp., 1953.
Lininger, K. B. and Latrubesse, E. M.: Flooding hydrology and peak discharge attenuation along the middle Araguaia River in central Brazil, Catena, 143, 90–101, https://doi.org/10.1016/j.catena.2016.03.043, 2016.
López López, P., Sutanudjaja, E. H., Schellekens, J., Sterk, G., and Bierkens, M. F. P.: Calibration of a large-scale hydrological model using satellite-based soil moisture and evapotranspiration products, Hydrol. Earth Syst. Sci., 21, 3125–3144, https://doi.org/10.5194/hess-21-3125-2017, 2017.
Luo, X., Li, H.-Y., Leung, L. R., Tesfa, T. K., Getirana, A., Papa, F., and Hess, L. L.: Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: impacts of geomorphological parameters and river flow representation, Geosci. Model Dev., 10, 1233–1259, https://doi.org/10.5194/gmd-10-1233-2017, 2017.
Maeda, E. E., Ma, X., Wagner, F. H., Kim, H., Oki, T., Eamus, D., and Huete, A.: Evapotranspiration seasonality across the Amazon Basin, Earth Syst. Dynam., 8, 439–454, https://doi.org/10.5194/esd-8-439-2017, 2017.
Marengo, J. A., Jones, R., Alves, L. M., and Valverde, M. C.: Future change of temperature and precipitation extremes in south america as derived from the precis regional climate modeling system, Int. J. Climatol., 29, 2241–2255, https://doi.org/10.1002/joc.1863, 2009.
Marengo, J. A., Tomasella, J., Soares, W. R., Alves, L. M., and Nobre, C. A.: Extreme climatic events in the Amazon basin, Theor. Appl. Climatol., 107, 73–85, https://doi.org/10.1007/s00704-011-0465-1, 2012.
Mateo, C. M. R., Yamazaki, D., Kim, H., Champathong, A., Vaze, J., and Oki, T.: Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods, Hydrol. Earth Syst. Sci., 21, 5143–5163, https://doi.org/10.5194/hess-21-5143-2017, 2017.
Meade, R. H., Rayol, J. M., Daconceicao, S. C., and Natividade, J. R. G.: Backwater effects in the Amazon river basin of Brazil, Environ. Geol. Water S., 18, 105–114, https://doi.org/10.1007/bf01704664, 1991.
Melo, D. D. C. D., Scanlon, B. R., Zhang, Z., Wendland, E., and Yin, L.: Reservoir storage and hydrologic responses to droughts in the Paraná River basin, south-eastern Brazil, Hydrol. Earth Syst. Sci., 20, 4673–4688, https://doi.org/10.5194/hess-20-4673-2016, 2016.
Miralles, D. G., De Jeu, R. A. M., Gash, J. H., Holmes, T. R. H., and Dolman, A. J.: Magnitude and variability of land evaporation and its components at the global scale, Hydrol. Earth Syst. Sci., 15, 967–981, https://doi.org/10.5194/hess-15-967-2011, 2011.
Mizukami, N., Clark, M. P., Newman, A. J., Wood, A. W., Gutmann, E. D., Nijssen, B., Rakovec, O., and Samaniego, L.: Towards seamless large-domain parameter estimation for hydrologic models, Water Resour. Res., 53, 8020–8040, https://doi.org/10.1002/2017WR020401, 2017.
Müller Schmied, H., Eisner, S., Franz, D., Wattenbach, M., Portmann, F. T., Flörke, M., and Döll, P.: Sensitivity of simulated global-scale freshwater fluxes and storages to input data, hydrological model structure, human water use and calibration, Hydrol. Earth Syst. Sci., 18, 3511–3538, https://doi.org/10.5194/hess-18-3511-2014, 2014.
New, M., Lister, D., Hulme, M., and Makin, I.: A high-resolution data set of surface climate over global land areas, Clim. Res., 21, 1–25, 2002.
O'Loughlin, F. E., Paiva, R. C. D., Durand, M., Alsdorf, D. E., and Bates, P. D.: A multi-sensor approach towards a global vegetation corrected SRTM DEM product, Remote Sens. Environ., 182, 49–59, https://doi.org/10.1016/j.rse.2016.04.018, 2016.
Ovando, A., Tomasella, J., Rodriguez, D. A., Martinez, J. M., Siqueira-Junior, J. L., Pinto, G. L. N., Passy, P., Vauchel, P., Noriega, L., and von Randow, C.: Extreme flood events in the Bolivian Amazon wetlands, J. Hydrol.-Regional Studies, 5, 293–308, https://doi.org/10.1016/j.ejrh.2015.11.004, 2016.
Paiva, R. C. D., Collischonn, W., and Tucci, C. E. M.: Large scale hydrologic and hydrodynamic modeling using limited data and a GIS based approach, J. Hydrol., 406, 170–181, https://doi.org/10.1016/j.jhydrol.2011.06.007, 2011.
Paiva, R. C. D., Buarque, D. C., Collischonn, W., Bonnet, M. P., Frappart, F., Calmant, S., and Bulhões Mendes, C. A.: Large-scale hydrologic and hydrodynamic modeling of the Amazon River basin, Water Resour. Res., 49, 1226–1243, https://doi.org/10.1002/wrcr.20067, 2013.
Pappenberger, F., Cloke, H. L., Balsamo, G., Ngo-Duc, T., and Oki, T.: Global runoff routing with the hydrological component of the ECMWF NWP system, Int. J. Climatol., 30, 2155–2174, https://doi.org/10.1002/joc.2028, 2010.
Paris, A., Dias de Paiva, R., Santos da Silva, J., Medeiros Moreira, D., Calmant, S., Garambois, P. A., Collischonn, W., Bonnet, M. P., and Seyler, F.: Stage-discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin, Water Resour. Res., 52, 3787–3814, https://doi.org/10.1002/2014WR016618, 2016.
Pasquini, A. I. and Depetris, P. J.: Discharge trends and flow dynamics of South American rivers draining the southern Atlantic seaboard: An overview, J. Hydrol., 333, 385–399, https://doi.org/10.1016/j.jhydrol.2006.09.005, 2007.
Paz, A. R., Collischonn, W., Tucci, C. E. M., and Padovani, C. R.: Large-scale modelling of channel flow and floodplain inundation dynamics and its application to the Pantanal (Brazil), Hydrol. Process., 25, 1498–1516, https://doi.org/10.1002/hyp.7926, 2011.
Paz, A. R., Collischonn, W., Bravo, J. M., Bates, P. D., and Baugh, C.: The influence of vertical water balance on modelling Pantanal (Brazil) spatio-temporal inundation dynamics, Hydrol. Process., 28, 3539–3553, https://doi.org/10.1002/hyp.9897, 2014.
Pechlivanidis, I. G. and Arheimer, B.: Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case, Hydrol. Earth Syst. Sci., 19, 4559–4579, https://doi.org/10.5194/hess-19-4559-2015, 2015.
Pedinotti, V., Boone, A., Decharme, B., Crétaux, J. F., Mognard, N., Panthou, G., Papa, F., and Tanimoun, B. A.: Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets, Hydrol. Earth Syst. Sci., 16, 1745–1773, https://doi.org/10.5194/hess-16-1745-2012, 2012.
Pontes, P. R. M.: Modelagem hidrológica e hidrodinâmica integrada da bacia do Prata, Phd Dissertation, Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, 194 pp., 2016 (in Portuguese).
Pontes, P. R. M., Fan, F. M., Fleischmann, A. S., de Paiva, R. C. D., Buarque, D. C., Siqueira, V. A., Jardim, P. F., Sorribas, M. V., and Collischonn, W.: MGB-IPH model for hydrological and hydraulic simulation of large floodplain river systems coupled with open source GIS, Environ. Modell. Softw., 94, 1–20, https://doi.org/10.1016/j.envsoft.2017.03.029, 2017.
Rahman, S., Bagtzoglou, A. C., Hossain, F., Tang, L., Yarbrough, L. D., and Easson, G.: Investigating Spatial Downscaling of Satellite Rainfall Data for Streamflow Simulation in a Medium-Sized Basin, J. Hydrometeorol., 10, 1063–1079, https://doi.org/10.1175/2009JHM1072.1, 2009.
Ramillien, G., Cazenave, A., and Brunau, O.: Global time variations of hydrological signals from GRACE satellite gravimetry, Geophys. J. Int., 158, 813–826, https://doi.org/10.1111/j.1365-246X.2004.02328.x, 2004.
Rennó, C. D., Nobre, A. D., Cuartas, L. A., Soares, J. V., Hodnett, M. G., Tomasella, J., and Waterloo, M. J.: HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia, Remote Sens. Environ., 112, 3469–3481, https://doi.org/10.1016/j.rse.2008.03.018, 2008.
Restrepo-Coupe, N., da Rocha, H. R., Hutyra, L. R., da Araujo, A. C., Borma, L. S., Christoffersen, B., Cabral, O. M. R., de Camargo, P. B., Cardoso, F. L., da Costa, A. C. L., Fitzjarrald, D. R., Goulden, M. L., Kruijt, B., Maia, J. M. F., Malhi, Y. S., Manzi, A. O., Miller, S. D., Nobre, A. D., von Randow, C., Sa, L. D. A., Sakai, R. K., Tota, J., Wofsy, S. C., Zanchi, F. B., and Saleska, S. R.: What drives the seasonality of photosynthesis across the Amazon basin? A cross-site analysis of eddy flux tower measurements from the Brasil flux network, Agr. Forest Meteorol., 182, 128–144, https://doi.org/10.1016/j.agrformet.2013.04.031, 2013.
Revilla-Romero, B., Beck, H. E., Burek, P., Salamon, P., de Roo, A., and Thielen, J.: Filling the gaps: Calibrating a rainfall-runoff model using satellite-derived surface water extent, Remote Sens. Environ., 171, 118–131, https://doi.org/10.1016/j.rse.2015.10.022, 2015.
Richey, J. E., Mertes, L. A. K., Dunne, T., Victoria, R. L., Forsberg, B. R., Tancredi, A., and Oliveira, E.: Sources and routing of the Amazon River flood wave, Global Biogeochem. Cy., 3, 191–204, https://doi.org/10.1029/GB003i003p00191, 1989.
Rivera, J. A., Penalba, O. C., Villalba, R., and Araneo, D. C.: Spatio-temporal patterns of the 2010–2015 extreme hydrological drought across the Central Andes, Argentina, Water, 9, 652, https://doi.org/10.3390/w9090652, 2017.
Rivera, J. A., Araneo, D. C., Penalba, O. C., and Villalba, R.: Regional aspects of streamflow droughts in the Andean rivers of Patagonia, Argentina. Links with large-scale climatic oscillations, Hydrol. Res., 49, 134–149, https://doi.org/10.2166/nh.2017.207, 2018.
Rodriguez, E., Morris, C. S. and Belz, J. E.: A global assessment of the SRTM performance, Photogramm. Eng. Rem. S., 72, 249–260, https://doi.org/10.14358/pers.72.3.249, 2006.
Rosales, J., Vispo, C., Dezzeo, N., Blanco-Belmonte, L., Knab-Vispo, C., González, N., Daza, F., Bradley, C., Gilvear, D., and Escalante, G.: Ecohydrology of riparian forests in the Orinoco River Basin, The ecohydrology of South American rivers and wetlands, Special Publication No. 6, IAHS Press, Wallingford, UK, 93–110, 2002.
Samaniego, L., Kumar, R., Thober, S., Rakovec, O., Zink, M., Wanders, N., Eisner, S., Müller Schmied, H., Sutanudjaja, E. H., Warrach-Sagi, K., and Attinger, S.: Toward seamless hydrologic predictions across spatial scales, Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, 2017.
Santos da Silva, J., Calmant, S., Seyler, F., Rotunno Filho, O. C., Cochonneau, G., and Mansur, W. J.: Water levels in the Amazon basin derived from the ERS 2 and ENVISAT radar altimetry missions, Remote Sens. Environ., 114, 2160–2181, https://doi.org/10.1016/j.rse.2010.04.020, 2010.
Scanlon, B. R., Zhang, Z., Save, H., Wiese, D. N., Landerer, F. W., Long, D., Longuevergne, L., and Chen, J.: Global evaluation of new GRACE mascon products for hydrologic applications, Water Resour. Res., 52, 9412–9429, https://doi.org/10.1002/2016wr019494, 2016.
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.
Schmidt, R., Flechtner, F., Meyer, U., Neumayer, K. H., Dahle, C., Konig, R., and Kusche, J.: Hydrological Signals Observed by the GRACE Satellites, Surv. Geophys., 29, 319–334, https://doi.org/10.1007/s10712-008-9033-3, 2008.
Siqueira, V. A., Collischonn, W., Fan, F. M., and Chou, S. C.: Ensemble flood forecasting based on operational forecasts of the regional Eta EPS in the Taquari-Antas basin, RBRH, 21, 587–602, https://doi.org/10.1590/2318-0331.011616004, 2016a.
Siqueira, V. A., Fleischmann, A., Jardim, P. F., Fan, F. M., and Collischonn, W.: IPH-Hydro Tools: A GIS coupled tool for watershed topology acquisition in an open-source environment, RBRH, 21, 274–287, https://doi.org/10.21168/rbrh.v21n1.p274-287, 2016b.
Sood, A. and Smakhtin, V.: Global hydrological models: a review, Hydrol. Sci. J., 60, 549–565, https://doi.org/10.1080/02626667.2014.950580, 2015.
Sperna Weiland, F. C., Vrugt, J. A., van Beek, R. P. H., Weerts, A. H., and Bierkens, M. F. P.: Significant uncertainty in global scale hydrological modeling from precipitation data errors, J. Hydrol., 529, 1095–1115, https://doi.org/10.1016/j.jhydrol.2015.08.061, 2015.
Su, F. G. and Lettenmaier, D. P.: Estimation of the Surface Water Budget of the La Plata Basin, J. Hydrometeorol., 10, 981–998, https://doi.org/10.1175/2009jhm1100.1, 2009.
Sunilkumar, K., Narayana Rao, T., Saikranthi, K., and Purnachandra Rao, M.: Comprehensive evaluation of multisatellite precipitation estimates over India using gridded rainfall data, J. Geophys. Res., 120, 8987–9005, https://doi.org/10.1002/2015JD023437, 2015.
Tapley, B. D., Bettadpur, S., Watkins, M., and Reigber, C.: The gravity recovery and climate experiment: Mission overview and early results, Geophys. Res. Lett., 31, L09607, https://doi.org/10.1029/2004gl019920, 2004.
Tian, Y. and Peters-Lidard, C. D.: A global map of uncertainties in satellite-based precipitation measurements, Geophys. Res. Lett., 37, L24407, https://doi.org/10.1029/2010GL046008, 2010.
Todini, E.: The ARNO rainfall-runoff model, J. Hydrol., 175, 339–382, 1996.
Trigg, M. A., Wilson, M. D., Bates, P. D., Horritt, M. S., Alsdorf, D. E., Forsberg, B. R., and Vega, M. C.: Amazon flood wave hydraulics, J. Hydrol., 374, 92–105, https://doi.org/10.1016/j.jhydrol.2009.06.004, 2009.
Tucci, C. E. M. and Clarke, R. T.: Environmental issues in the la Plata Basin, Int. J. Water Resour. D., 14, 157–173, https://doi.org/10.1080/07900629849376, 1998.
Vera, C., Baez, J., Douglas, M., Emmanuel, C. B., Marengo, J., Meitin, J., Nicolini, M., Nogues-Paegle, J., Paegle, J., Penalba, O., Salio, P., Saulo, C., Dias, M. A. S., Dias, P. S., and Zipser, E.: The South American low-level jet experiment, B. Am. Meteorol. Soc., 87, 63–77, https://doi.org/10.1175/bams-87-1-63, 2006.
Vinukollu, R. K., Meynadier, R., Sheffield, J., and Wood, E. F.: Multi-model, multi-sensor estimates of global evapotranspiration: climatology, uncertainties and trends, Hydrol. Process., 25, 3993–4010, https://doi.org/10.1002/hyp.8393, 2011.
Wada, Y., van Beek, L. P. H., and Bierkens, M. F. P.: Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability, Hydrol. Earth Syst. Sci., 15, 3785–3808, https://doi.org/10.5194/hess-15-3785-2011, 2011.
Wahr, J., Molenaar, M., and Bryan, F.: Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE, J. Geophys. Res.-Sol. Ea., 103, 30205–30229, 1998.
Wang, A., Zeng, X., Shen, S. S. P., Zeng, Q. C., and Dickinson, R. E.: Time scales of land surface hydrology, J. Hydrometeorol., 7, 868–879, https://doi.org/10.1175/JHM527.1, 2006.
Watkins, M. M., Wiese, D. N., Yuan, D. N., Boening, C., and Landerer, F. W.: Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons, J. Geophys. Res.-Sol. Ea., 120, 2648–2671, https://doi.org/10.1002/2014JB011547, 2015.
Werth, D. and Avissar, R.: The local and global effects of Amazon deforestation, J. Geophys. Res.-Atmos., 107, 8087, https://doi.org/10.1029/2001jd000717, 2002.
Werth, S. and Güntner, A.: Calibration analysis for water storage variability of the global hydrological model WGHM, Hydrol. Earth Syst. Sci., 14, 59–78, https://doi.org/10.5194/hess-14-59-2010, 2010.
Wiese, D. N., Landerer, F. W., and Watkins, M. M.: Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution, Water Resour. Res., 52, 7490–7502, https://doi.org/10.1002/2016wr019344, 2016.
Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, L. P. H., Bierkens, M. F. P., Blyth, E., de Roo, A., Doll, P., Ek, M., Famiglietti, J., Gochis, D., van de Giesen, N., Houser, P., Jaffe, 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.
Wu, H., Adler, R. F., Tian, Y. D., Huffman, G. J., Li, H. Y., and Wang, J. J.: Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model, Water Resour. Res., 50, 2693–2717, https://doi.org/10.1002/2013wr014710, 2014.
Yamazaki, D., Kanae, S., Kim, H., and Oki, T.: A physically based description of floodplain inundation dynamics in a global river routing model, Water Resour. Res., 47, W04501, https://doi.org/10.1029/2010WR009726, 2011.
Yamazaki, D., De Almeida, G. A. M., and Bates, P. D.: Improving computational efficiency in global river models by implementing the local inertial flow equation and a vector-based river network map, Water Resour. Res., 49, 7221–7235, https://doi.org/10.1002/wrcr.20552, 2013.
Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O'Loughlin, F., Neal, J. C., Sampson, C. C., Kanae, S., and Bates, P. D.: A high-accuracy map of global terrain elevations, Geophys. Res. Lett., 44, 5844–5853, https://doi.org/10.1002/2017GL072874, 2017.
Zaitchik, B. F., Rodell, M., and Olivera, F.: Evaluation of the Global Land Data Assimilation System using global river discharge data and a source-to-sink routing scheme, Water Resour. Res., 46, W06507, https://doi.org/10.1029/2009wr007811, 2010.
Zajac, Z., Revilla-Romero, B., Salamon, P., Burek, P., Hirpa, F., and Beck, H.: The impact of lake and reservoir parameterization on global streamflow simulation, J. Hydrol., 548, 552–568, https://doi.org/10.1016/j.jhydrol.2017.03.022, 2017.
Zhang, Y., Zheng, H., Chiew, F. H. S., Arancibia, J. P., and Zhou, X.: Evaluating Regional and Global Hydrological Models against Streamflow and Evapotranspiration Measurements, J. Hydrometeorol., 17, 995–1010, https://doi.org/10.1175/jhm-d-15-0107.1, 2016.
Zhang, Y., Pan, M., Sheffield, J., Siemann, A. L., Fisher, C. K., Liang, M., Beck, H. E., Wanders, N., MacCracken, R. F., Houser, P. R., Zhou, T., Lettenmaier, D. P., Pinker, R. T., Bytheway, J., Kummerow, C. D., and Wood, E. F.: A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010, Hydrol. Earth Syst. Sci., 22, 241–263, https://doi.org/10.5194/hess-22-241-2018, 2018.
Zhao, F., Veldkamp, T. I. E., Frieler, K., Schewe, J., Ostberg, S., Willner, S., Schauberger, B., Gosling, S. N., Schmied, H. M., Portmann, F. T., Leng, G., Huang, M., Liu, X., Tang, Q., Hanasaki, N., Biemans, H., Gerten, D., Satoh, Y., Pokhrel, Y., Stacke, T., Ciais, P., Chang, J., Ducharne, A., Guimberteau, M., Wada, Y., Kim, H., and Yamazaki, D.: The critical role of the routing scheme in simulating peak river discharge in global hydrological models, Environ. Res. Lett., 12, W06507, https://doi.org/10.1088/1748-9326/aa7250, 2017.
Zhou, X., Zhang, Y., Wang, Y., Zhang, H., Vaze, J., Zhang, L., Yang, Y., and Zhou, Y.: Benchmarking global land surface models against the observed mean annual runoff from 150 large basins, J. Hydrol., 470–471, 269–279, https://doi.org/10.1016/j.jhydrol.2012.09.002, 2012.
Short summary
Providing reliable estimates of water fluxes at the continental scale is challenging. We extended a regional hydrological model to the entirety of South America and assessed its performance using multiple observations. After a comparison with global models, we show the extent to which estimates of daily river discharge can be improved, even by using global forcing data. Issues of global-/continental-scale modeling and future directions for simulating discharge in this continent are discussed.
Providing reliable estimates of water fluxes at the continental scale is challenging. We...
