Articles | Volume 23, issue 2
https://doi.org/10.5194/hess-23-851-2019
© 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-23-851-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Feb 2019
Research article |
| 13 Feb 2019
| 13 Feb 2019
Linear Optimal Runoff Aggregate (LORA): a global gridded synthesis runoff product
Sanaa Hobeichi
CORRESPONDING AUTHOR
Climate Change Research Centre, University of New South Wales,
Sydney, NSW 2052, Australia
ARC Centre of Excellence for Climate System Science, University of New
South Wales, Sydney, NSW 2052, Australia
Gab Abramowitz
Climate Change Research Centre, University of New South Wales,
Sydney, NSW 2052, Australia
ARC Centre of Excellence for Climate Extremes, University of New South
Wales, Sydney, NSW 2052, Australia
Jason Evans
Climate Change Research Centre, University of New South Wales,
Sydney, NSW 2052, Australia
ARC Centre of Excellence for Climate Extremes, University of New South
Wales, Sydney, NSW 2052, Australia
Hylke E. Beck
Department of Civil and Environmental Engineering, Princeton
University, Princeton, NJ 08544, USA
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- Climate change rather than vegetation greening dominates runoff change in China Z. Song et al. https://doi.org/10.1016/j.jhydrol.2023.129519
42 citations as recorded by crossref.
- Can Hydrological Models Benefit From Using Global Soil Moisture, Evapotranspiration, and Runoff Products as Calibration Targets? Y. Mei et al. https://doi.org/10.1029/2022WR032064
- OpenBench: a land model evaluation system Z. Wei et al. https://doi.org/10.5194/gmd-18-6517-2025
- Leveraging global climate models to assess multi-year hydrologic drought M. Vieira & T. Stadnyk https://doi.org/10.1038/s41612-023-00496-y
- Investigating the spatial variability of water security risk and its driving mechanisms in China using machine learning Z. Xu et al. https://doi.org/10.1016/j.jclepro.2022.132303
- Robust historical evapotranspiration trends across climate regimes S. Hobeichi et al. https://doi.org/10.5194/hess-25-3855-2021
- Comparison and integration of hydrological models and machine learning models in global monthly streamflow simulation J. Zhang et al. https://doi.org/10.1016/j.jhydrol.2024.132549
- Hydrostreamer v1.0 – improved streamflow predictions for local applications from an ensemble of downscaled global runoff products M. Kallio et al. https://doi.org/10.5194/gmd-14-5155-2021
- Vegetation dynamics offset nearly 30% of precipitation’s impact on runoff and are amplified by aridity Y. Liu et al. https://doi.org/10.1016/j.oneear.2026.101612
- Assessment of Daily of Reference Evapotranspiration Using CLDAS Product in Different Climate Regions of China L. Wu et al. https://doi.org/10.3390/w14111744
- Pervasive alterations to snow-dominated ecosystem functions under climate change W. Wieder et al. https://doi.org/10.1073/pnas.2202393119
- Validation and Comparison of Seven Land Surface Evapotranspiration Products in the Haihe River Basin, China X. Guo et al. https://doi.org/10.3390/rs14174308
- Rapid Evaluation Framework for the CMIP7 Assessment Fast Track F. Hoffman et al. https://doi.org/10.5194/gmd-19-7415-2026
- Generation of High-Resolution Gridded Runoff Product for the Republic of Korea Sub-Basins from Seasonal Merging of Global Reanalysis Datasets W. Sunwoo et al. https://doi.org/10.3390/w15213741
- Temporally compounding energy droughts in European electricity systems with hydropower L. van der Most et al. https://doi.org/10.1038/s41560-024-01640-5
- Revisiting a Two‐Parameter Budyko Equation With the Complementary Evaporation Principle for Proper Consideration of Surface Energy Balance D. Kim & J. Chun https://doi.org/10.1029/2021WR030838
- Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region D. Xu et al. https://doi.org/10.5194/gmd-17-1197-2024
- Conserving Land–Atmosphere Synthesis Suite (CLASS) S. Hobeichi et al. https://doi.org/10.1175/JCLI-D-19-0036.1
- Reconciling historical changes in the hydrological cycle over land S. Hobeichi et al. https://doi.org/10.1038/s41612-022-00240-y
- A hydrological knowledge-informed LSTM model for monthly streamflow reconstruction using distributed data: Application to typical rivers across the Tibetan plateau S. Hou et al. https://doi.org/10.1016/j.jhydrol.2024.132409
- Reanalysis in Earth System Science: Toward Terrestrial Ecosystem Reanalysis R. Baatz et al. https://doi.org/10.1029/2020RG000715
- Evaluating Precipitation Datasets Using Surface Water and Energy Budget Closure S. Hobeichi et al. https://doi.org/10.1175/JHM-D-19-0255.1
- Power‐Function Expansion of the Polynomial Complementary Relationship of Evaporation J. Szilagyi et al. https://doi.org/10.1029/2022WR033095
- Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate V. Levizzani & E. Cattani https://doi.org/10.3390/rs11192301
- WATcycle: A software for terrestrial water cycle and budget analysis with case studies on the Amazon and Mississippi Basins R. Anjaneyulu et al. https://doi.org/10.1016/j.envsoft.2025.106656
- G‐RUN ENSEMBLE: A Multi‐Forcing Observation‐Based Global Runoff Reanalysis G. Ghiggi et al. https://doi.org/10.1029/2020WR028787
- Exploring the Influences of Stream Network Structure and Connectivity on Water Environment Risk in China M. Chen et al. https://doi.org/10.3390/w14244007
- Effects of Soil Texture Datasets on FGOALS-g3 Global Long-Term Simulations K. Xia et al. https://doi.org/10.2151/sola.2024-047
- Development of observation-based global multilayer soil moisture products for 1970 to 2016 Y. Wang et al. https://doi.org/10.5194/essd-13-4385-2021
- Enhancing dynamic flood risk assessment and zoning using a coupled hydrological-hydrodynamic model and spatiotemporal information weighting method L. Zhou & L. Liu https://doi.org/10.1016/j.jenvman.2024.121831
- Long‐Term Experimental Evaluation of a High‐Resolution Atmospheric General Circulation Model From a Hydrological Perspective Y. Miura & T. Nakaegawa https://doi.org/10.1029/2023JD038786
- Identification of spatially distributed parameters of hydrological models using the dimension-adaptive key grid calibration strategy K. Xie et al. https://doi.org/10.1016/j.jhydrol.2020.125772
- Multifaceted characteristics of dryland aridity changes in a warming world X. Lian et al. https://doi.org/10.1038/s43017-021-00144-0
- New Forest Aboveground Biomass Maps of China Integrating Multiple Datasets Z. Chang et al. https://doi.org/10.3390/rs13152892
- Regionalization of hydrological model parameters using gradient boosting machine Z. Song et al. https://doi.org/10.5194/hess-26-505-2022
- Evaluation of CMIP6 Global Climate Models for Simulating Land Surface Energy and Water Fluxes During 1979–2014 J. Li et al. https://doi.org/10.1029/2021MS002515
- Revisiting the global distribution of the exponent of the power-function complementary relationship of terrestrial evaporation: Insights from an isenthalpic index J. Szilagyi et al. https://doi.org/10.1016/j.jhydrol.2024.131864
- Hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data F. Yang et al. https://doi.org/10.1007/s11629-021-6727-1
- Finer resolutions and targeted process representations in earth system models improve hydrologic projections and hydroclimate impacts P. Das & A. Ganguly https://doi.org/10.1038/s41612-025-01134-5
- Hydrological magnitude discrepancy between the Amazon and the La Plata watersheds P. Zanin https://doi.org/10.15406/ijh.2020.04.00236
- ET-WB: water-balance-based estimations of terrestrial evaporation over global land and major global basins J. Xiong et al. https://doi.org/10.5194/essd-15-4571-2023
- Evaluation and comparison of CMIP6 and CMIP5 model performance in simulating the runoff H. Guo et al. https://doi.org/10.1007/s00704-022-04118-0
- Climate change rather than vegetation greening dominates runoff change in China Z. Song et al. https://doi.org/10.1016/j.jhydrol.2023.129519
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