Articles | Volume 20, issue 7
https://doi.org/10.5194/hess-20-2573-2016
https://doi.org/10.5194/hess-20-2573-2016
Research article
 | 
04 Jul 2016
Research article |  | 04 Jul 2016

Dominant climatic factors driving annual runoff changes at the catchment scale across China

Zhongwei Huang, Hanbo Yang, and Dawen Yang

Related authors

The general formulation for runoff components estimation and attribution at mean annual time scale
Yufen He, Changming Li, and Hanbo Yang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-349,https://doi.org/10.5194/hess-2024-349, 2024
Preprint under review for HESS
Short summary
Estimating the sensitivity of the Priestley–Taylor coefficient to air temperature and humidity
Ziwei Liu, Hanbo Yang, Changming Li, and Taihua Wang
Hydrol. Earth Syst. Sci., 28, 4349–4360, https://doi.org/10.5194/hess-28-4349-2024,https://doi.org/10.5194/hess-28-4349-2024, 2024
Short summary
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data
Changming Li, Ziwei Liu, Wencong Yang, Zhuoyi Tu, Juntai Han, Sien Li, and Hanbo Yang
Earth Syst. Sci. Data, 16, 1811–1846, https://doi.org/10.5194/essd-16-1811-2024,https://doi.org/10.5194/essd-16-1811-2024, 2024
Short summary
Long-term reconstruction of satellite-based precipitation, soil moisture, and snow water equivalent in China
Wencong Yang, Hanbo Yang, Changming Li, Taihua Wang, Ziwei Liu, Qingfang Hu, and Dawen Yang
Hydrol. Earth Syst. Sci., 26, 6427–6441, https://doi.org/10.5194/hess-26-6427-2022,https://doi.org/10.5194/hess-26-6427-2022, 2022
Short summary
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data
Changming Li, Hanbo Yang, Wencong Yang, Ziwei Liu, Yao Jia, Sien Li, and Dawen Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-456,https://doi.org/10.5194/essd-2021-456, 2022
Revised manuscript not accepted
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Mathematical applications
Processes and controls of regional floods over eastern China
Yixin Yang, Long Yang, Jinghan Zhang, and Qiang Wang
Hydrol. Earth Syst. Sci., 28, 4883–4902, https://doi.org/10.5194/hess-28-4883-2024,https://doi.org/10.5194/hess-28-4883-2024, 2024
Short summary
A national-scale hybrid model for enhanced streamflow estimation – consolidating a physically based hydrological model with long short-term memory (LSTM) networks
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, and Raphael J. M. Schneider
Hydrol. Earth Syst. Sci., 28, 2871–2893, https://doi.org/10.5194/hess-28-2871-2024,https://doi.org/10.5194/hess-28-2871-2024, 2024
Short summary
Inferring heavy tails of flood distributions through hydrograph recession analysis
Hsing-Jui Wang, Ralf Merz, Soohyun Yang, and Stefano Basso
Hydrol. Earth Syst. Sci., 27, 4369–4384, https://doi.org/10.5194/hess-27-4369-2023,https://doi.org/10.5194/hess-27-4369-2023, 2023
Short summary
Landscape structures regulate the contrasting response of recession along rainfall amounts
Jun-Yi Lee, Ci-Jian Yang, Tsung-Ren Peng, Tsung-Yu Lee, and Jr-Chuan Huang
Hydrol. Earth Syst. Sci., 27, 4279–4294, https://doi.org/10.5194/hess-27-4279-2023,https://doi.org/10.5194/hess-27-4279-2023, 2023
Short summary
Hydrological objective functions and ensemble averaging with the Wasserstein distance
Jared C. Magyar and Malcolm Sambridge
Hydrol. Earth Syst. Sci., 27, 991–1010, https://doi.org/10.5194/hess-27-991-2023,https://doi.org/10.5194/hess-27-991-2023, 2023
Short summary

Cited articles

Allen, R., Pereira, L., Raes, D., and Smith, M.: Crop evapotranspiration: guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56, FAO, Rome, 300, D05109, 1998.
Angström, A.: Solar and terrestrial radiation, Q. J. Roy. Meteorol. Soc., 50, 121–126, 1924.
Arnold, J. G. and Fohrer, N.: SWAT2000: current capabilities and research opportunities in applied watershed modelling, Hydrol. Process., 19, 563–572, https://doi.org/10.1002/hyp.5611, 2005.
Arnold, J. G., Srinivasan, R., Muttiah, R. R., and Williams, J. R.: Large hydrologic modeling and assessment Part 1: Model development, J. Am. Water Resour. Assoc, 34, 73–89, https://doi.org/10.1111/j.1752-1688.1998.tb05961.x, 1998.
Arora, V. K.: The use of the aridity index to assess climate change effect on annual runoff, J. Hydrol., 265, 164–177, https://doi.org/10.1007/BF02873094, 2002.
Download
Short summary
The hydrologic processes have been influenced by different climatic factors. However, the dominant climatic factor driving annual runoff change is still unknown in many catchments in China. By using the climate elasticity method proposed by Yang and Yang (2011), the elasticity of runoff to climatic factors was estimated, and the dominant climatic factors driving annual runoff change were detected at catchment scale over China.