Articles | Volume 23, issue 6
https://doi.org/10.5194/hess-23-2647-2019
© 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-23-2647-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sensitivity of hydrological models to temporal and spatial resolutions of rainfall data
Yingchun Huang
CORRESPONDING AUTHOR
College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
András Bárdossy
Institute for Modelling Hydraulic and Environmental Engineering, University of Stuttgart, 70596 Stuttgart, Germany
College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
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- Improving the flood prediction capability of the Xin’anjiang model by formulating a new physics-based routing framework and a key routing parameter estimation method S. Zang et al. 10.1016/j.jhydrol.2021.126867
- Quantitative assessment of the scale conversion from instantaneous to daily GPP under various sky conditions based on MODIS local overpassing time J. Lee & J. Im 10.1080/15481603.2024.2319372
Latest update: 02 Nov 2024
Short summary
This study investigates whether higher temporal and spatial resolution of rainfall can lead to improved model performance. Four rainfall datasets were used to drive lumped and distributed HBV models to simulate daily discharges. Results show that a higher temporal resolution of rainfall improves the model performance if the station density is high. A combination of observed high temporal resolution observations with disaggregated daily rainfall leads to further improvement of the tested models.
This study investigates whether higher temporal and spatial resolution of rainfall can lead to...