Articles | Volume 25, issue 12
https://doi.org/10.5194/hess-25-6151-2021
© Author(s) 2021. 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-25-6151-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Dec 2021
Research article |
| 03 Dec 2021
| 03 Dec 2021
Can we use precipitation isotope outputs of isotopic general circulation models to improve hydrological modeling in large mountainous catchments on the Tibetan Plateau?
Department of Hydraulic Engineering, State Key Laboratory of
Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Zhihua He
Centre for Hydrology, University of Saskatchewan, Saskatchewan, Canada
Department of Hydraulic Engineering, State Key Laboratory of
Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Zhongwang Wei
Guangdong Province Key Laboratory for Climate Change and Natural
Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University,
Guangzhou, Guangdong, China
Lide Tian
Institute of International Rivers and Eco-security, Yunnan
University, Kunming, China
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Cited
16 citations as recorded by crossref.
- Corrected ERA5 Precipitation by Machine Learning Significantly Improved Flow Simulations for the Third Pole Basins H. Sun et al. 10.1175/JHM-D-22-0015.1
- Impact of Snowmelt Conditions on the Isotopic Composition of the Surface Waters of the Upper Ob River during the Flood Period T. Papina et al. 10.3390/w15112096
- Altitude Correction of GCM-Simulated Precipitation Isotopes in a Valley Topography of the Chinese Loess Plateau Y. Xiao et al. 10.3390/su151713126
- Isotope data-constrained hydrological model improves soil moisture simulation and runoff source apportionment Y. Nan & F. Tian 10.1016/j.jhydrol.2024.131006
- Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau Y. Nan & F. Tian 10.5194/hess-28-669-2024
- Evaluating input data sources for isotope‐enabled rainfall‐runoff models A. Watson et al. 10.1002/hyp.15276
- Diagnosis of atmospheric circulation shifts in the central Tibetan Plateau: Evidence from stable isotopes Y. Li et al. 10.1016/j.atmosres.2022.106536
- imc-precip-iso: open monthly stable isotope data of precipitation over the Indonesian Maritime Continent R. Suwarman et al. 10.1007/s42488-024-00116-1
- Longer simulation time step of the tracer-aided hydrological model estimates lower contribution of slow runoff components Y. Nan et al. 10.1016/j.jhydrol.2023.129889
- Hybrid hydrological modeling for large alpine basins: a semi-distributed approach B. Li et al. 10.5194/hess-28-4521-2024
- Large scale hydrologic and tracer aided modelling: A review T. Stadnyk & T. Holmes 10.1016/j.jhydrol.2023.129177
- Validation and Bias Correction of Monthly δ18O Precipitation Time Series from ECHAM5-Wiso Model in Central Europe V. Salamalikis & A. Argiriou 10.3390/oxygen2020010
- Regional contributions of climate change and human activities to altered flow of the Lancang-mekong river K. Zhang et al. 10.1016/j.ejrh.2023.101535
- Influence of seasonal sea-ice loss on Arctic precipitation δ18O: a GCM-based analysis of monthly data W. Song et al. 10.33265/polar.v42.9751
- Assessing the influence of water sampling strategy on the performance of tracer-aided hydrological modeling in a mountainous basin on the Tibetan Plateau Y. Nan et al. 10.5194/hess-26-4147-2022
- Improving LSTM hydrological modeling with spatiotemporal deep learning and multi-task learning: A case study of three mountainous areas on the Tibetan Plateau B. Li et al. 10.1016/j.jhydrol.2023.129401
16 citations as recorded by crossref.
- Corrected ERA5 Precipitation by Machine Learning Significantly Improved Flow Simulations for the Third Pole Basins H. Sun et al. 10.1175/JHM-D-22-0015.1
- Impact of Snowmelt Conditions on the Isotopic Composition of the Surface Waters of the Upper Ob River during the Flood Period T. Papina et al. 10.3390/w15112096
- Altitude Correction of GCM-Simulated Precipitation Isotopes in a Valley Topography of the Chinese Loess Plateau Y. Xiao et al. 10.3390/su151713126
- Isotope data-constrained hydrological model improves soil moisture simulation and runoff source apportionment Y. Nan & F. Tian 10.1016/j.jhydrol.2024.131006
- Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau Y. Nan & F. Tian 10.5194/hess-28-669-2024
- Evaluating input data sources for isotope‐enabled rainfall‐runoff models A. Watson et al. 10.1002/hyp.15276
- Diagnosis of atmospheric circulation shifts in the central Tibetan Plateau: Evidence from stable isotopes Y. Li et al. 10.1016/j.atmosres.2022.106536
- imc-precip-iso: open monthly stable isotope data of precipitation over the Indonesian Maritime Continent R. Suwarman et al. 10.1007/s42488-024-00116-1
- Longer simulation time step of the tracer-aided hydrological model estimates lower contribution of slow runoff components Y. Nan et al. 10.1016/j.jhydrol.2023.129889
- Hybrid hydrological modeling for large alpine basins: a semi-distributed approach B. Li et al. 10.5194/hess-28-4521-2024
- Large scale hydrologic and tracer aided modelling: A review T. Stadnyk & T. Holmes 10.1016/j.jhydrol.2023.129177
- Validation and Bias Correction of Monthly δ18O Precipitation Time Series from ECHAM5-Wiso Model in Central Europe V. Salamalikis & A. Argiriou 10.3390/oxygen2020010
- Regional contributions of climate change and human activities to altered flow of the Lancang-mekong river K. Zhang et al. 10.1016/j.ejrh.2023.101535
- Influence of seasonal sea-ice loss on Arctic precipitation δ18O: a GCM-based analysis of monthly data W. Song et al. 10.33265/polar.v42.9751
- Assessing the influence of water sampling strategy on the performance of tracer-aided hydrological modeling in a mountainous basin on the Tibetan Plateau Y. Nan et al. 10.5194/hess-26-4147-2022
- Improving LSTM hydrological modeling with spatiotemporal deep learning and multi-task learning: A case study of three mountainous areas on the Tibetan Plateau B. Li et al. 10.1016/j.jhydrol.2023.129401
Latest update: 16 Nov 2024
Short summary
Hydrological modeling has large problems of uncertainty in cold regions. Tracer-aided hydrological models are increasingly used to reduce uncertainty and refine the parameterizations of hydrological processes, with limited application in large basins due to the unavailability of spatially distributed precipitation isotopes. This study explored the utility of isotopic general circulation models in driving a tracer-aided hydrological model in a large basin on the Tibetan Plateau.
Hydrological modeling has large problems of uncertainty in cold regions. Tracer-aided...
