Articles | Volume 20, issue 6
https://doi.org/10.5194/hess-20-2453-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-2453-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
22 Jun 2016
Research article |
| 22 Jun 2016
An experimental seasonal hydrological forecasting system over the Yellow River basin – Part 2: The added value from climate forecast models
RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
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40 citations as recorded by crossref.
- Quantifying the spatiotemporal evolution and driving factors of soil erosion in the source region of the Yellow River using 137Cs and machine learning models J. Su et al. https://doi.org/10.1016/j.catena.2025.109296
- Large-Scale Linkages of Socioeconomic Drought with Climate Variability and Its Evolution Characteristics in Northwest China S. Liu et al. https://doi.org/10.1155/2020/2814539
- Understanding and seasonal forecasting of hydrological drought in the Anthropocene X. Yuan et al. https://doi.org/10.5194/hess-21-5477-2017
- Evaluation of summer drought ensemble prediction over the Yellow River basin M. YAO & X. YUAN https://doi.org/10.1080/16742834.2018.1484253
- Long-lead daily streamflow forecasting using Long Short-Term Memory model with different predictors J. Li et al. https://doi.org/10.1016/j.ejrh.2023.101471
- A probabilistic drought forecasting framework: A combined dynamical and statistical approach H. Yan et al. https://doi.org/10.1016/j.jhydrol.2017.03.004
- A comparison of large-scale climate signals and the North American Multi-Model Ensemble (NMME) for drought prediction in China L. Xu et al. https://doi.org/10.1016/j.jhydrol.2017.12.044
- Potential Threats from Variations of Hydrological Parameters to the Yellow River and Pearl River Basins in China over the Next 30 Years L. Liu et al. https://doi.org/10.3390/w10070883
- Reliable long-range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model J. Bennett et al. https://doi.org/10.1002/2016WR019193
- Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes Z. Huang & T. Zhao https://doi.org/10.1002/wat2.1580
- Seasonal streamflow forecasting by surrogate modeling in the Yarlung Zangbo River Basin, China H. Gu et al. https://doi.org/10.1016/j.ejrh.2024.101835
- Seasonal streamflow forecasting in South America’s largest rivers I. Petry et al. https://doi.org/10.1016/j.ejrh.2023.101487
- An Efficient Approach for Estimating Streamflow Forecast Skill Elasticity L. Arnal et al. https://doi.org/10.1175/JHM-D-16-0259.1
- Monthly and seasonal streamflow forecasting of large dryland catchments in Brazil A. Costa et al. https://doi.org/10.1007/s40333-021-0097-y
- Long-Term Runoff Prediction Using Large-Scale Climatic Indices and Machine Learning Model in Wudongde and Three Gorges Reservoirs F. Ma et al. https://doi.org/10.3390/w17202942
- Seasonal drought ensemble predictions based on multiple climate models in the upper Han River Basin, China F. Ma et al. https://doi.org/10.1007/s00382-017-3577-1
- Extended-Range Runoff Forecasting Using a One-Way Coupled Climate–Hydrological Model: Case Studies of the Yiluo and Beijiang Rivers in China L. Liu et al. https://doi.org/10.3390/w11061150
- Changes in climate and snow cover and their synergistic influence on spring runoff in the source region of the Yellow River Z. Li et al. https://doi.org/10.1016/j.scitotenv.2021.149503
- Assessment of an ensemble seasonal streamflow forecasting system for Australia J. Bennett et al. https://doi.org/10.5194/hess-21-6007-2017
- Seasonal streamflow forecasts for Europe – Part 2: Sources of skill W. Greuell et al. https://doi.org/10.5194/hess-23-371-2019
- Monthly and Seasonal Prediction of Precipitation and Air Temperature in the Amur River Basin V. Tishchenko et al. https://doi.org/10.3103/S1068373919030026
- Contribution of temperature and precipitation anomalies to the California drought during 2012–2015 L. Luo et al. https://doi.org/10.1002/2016GL072027
- Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in northwestern China F. Ma et al. https://doi.org/10.5194/hess-22-5697-2018
- Skill decreases in real-time seasonal climate prediction due to decadal variability C. Shao et al. https://doi.org/10.1007/s00382-023-06800-z
- Investigating the Role of Bias Correction Methods and Climate Models on Water Budget of Büyük Menderes Basin Z. ERKOL & İ. DALOGLU ÇETİNKAYA https://doi.org/10.16984/saufenbilder.1125240
- Adapting subseasonal-to-seasonal (S2S) precipitation forecast at watersheds for hydrologic ensemble streamflow forecasting with a machine learning-based post-processing approach L. Zhang et al. https://doi.org/10.1016/j.jhydrol.2024.130643
- An experimental seasonal hydrological forecasting system over the Yellow River basin – Part 1: Understanding the role of initial hydrological conditions X. Yuan et al. https://doi.org/10.5194/hess-20-2437-2016
- A multi-scale ensemble-based framework for forecasting compound coastal-riverine flooding: The Hackensack-Passaic watershed and Newark Bay F. Saleh et al. https://doi.org/10.1016/j.advwatres.2017.10.026
- Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency D. Lucatero et al. https://doi.org/10.5194/hess-22-3601-2018
- Daily Streamflow Forecasts Based on Cascade Long Short-Term Memory (LSTM) Model over the Yangtze River Basin J. Li & X. Yuan https://doi.org/10.3390/w15061019
- Unravelling the potential of global streamflow reanalysis in characterizing local flow regime T. Zhao et al. https://doi.org/10.1016/j.scitotenv.2022.156125
- Superensemble seasonal forecasting of soil moisture by NMME M. Yao & X. Yuan https://doi.org/10.1002/joc.5436
- Assessment of seasonal soil moisture forecasts over the Central Mediterranean L. Silvestri et al. https://doi.org/10.5194/hess-29-925-2025
- A five-parameter Gamma-Gaussian model to calibrate monthly and seasonal GCM precipitation forecasts Z. Huang et al. https://doi.org/10.1016/j.jhydrol.2021.126893
- The Potential of EO Data for Enhanced Flood Monitoring and Forecasting: A Consortium Assessment A. Tarpanelli et al. https://doi.org/10.1007/s10712-026-09935-w
- The development and evaluation of a hydrological seasonal forecast system prototype for predicting spring flood volumes in Swedish rivers K. Foster et al. https://doi.org/10.5194/hess-22-2953-2018
- Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas K. Lee et al. https://doi.org/10.1155/2017/8485130
- Seasonal Drought Prediction: Advances, Challenges, and Future Prospects Z. Hao et al. https://doi.org/10.1002/2016RG000549
- Relating Anomaly Correlation to Lead Time: Principal Component Analysis of NMME Forecasts of Summer Precipitation in China T. Zhao et al. https://doi.org/10.1029/2018JD028267
- How Suitable is Quantile Mapping For Postprocessing GCM Precipitation Forecasts? T. Zhao et al. https://doi.org/10.1175/JCLI-D-16-0652.1
Saved (final revised paper)
Latest update: 22 Sep 2026
Short summary
This paper evaluates the added value from climate forecast models over the Yellow River basin. Without considering the errors in hydrological models, the climate-model-based seasonal hydrological forecasts show higher skill than the climatological forecasts, especially during the rainy season. The improvement decreases especially at short leads when the post-processed forecasts are verified against observed streamflow, and the added value mainly exists in the transition from wet to dry seasons.
This paper evaluates the added value from climate forecast models over the Yellow River basin....
