EGU21-1933
https://doi.org/10.5194/egusphere-egu21-1933
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Application of Xin'anjiang Model and Wetspa Model in the Inflow Forecasting of Shiquan Reservoir

Siyu Cai1,2, Ruifang Yuan3, Weihong Liao2, and Liang Wu4
Siyu Cai et al.
  • 1Department of Hydraulic Engineer, Tsinghua University, Beijing, China
  • 2China Institute of Water Resource and Hydropower Research, Beijing, China
  • 3College of Water Resources and Environment, China University of Geosciences, Beijing, China
  • 4Qinghai Provincial Geological Environment Monitoring Station , Qinghai, China

In order to improve the accuracy of the inflow forecasting of Shiquan Reservoir in the Han River Basin, this paper compared the application effects of Xin'anjing model and Wetspa model. The study collected the rainfall and runoff data from 2009 to 2015, as well as the DEM, land use and soil data with 1000´1000m grid size. The model calibration and verification periods were from 2009 to 2012 and from 2013 to 2015, respectively. In addition to using the runoff depth and the determination coefficient to evaluate the accuracy of the two models, the flow relative error CR1, model confidence coefficient CR2, Nash-Sutcliffe efficiency CR3, logarithmic version of Nash-Sutcliffe efficiency CR4 for low flow, improved Nash-Sutcliffe efficiency CR5 for high flow were adopted to analyze the simulation results of the two models. The results showed that the simulation results of the Wetspa model could be used as a supplement to the simulation results of the Xin'anjiang model, providing high-precision flood forecasting results for the scheduling decisions of Shiquan Reservoir in terms of time and space.

How to cite: Cai, S., Yuan, R., Liao, W., and Wu, L.: Application of Xin'anjiang Model and Wetspa Model in the Inflow Forecasting of Shiquan Reservoir, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1933, https://doi.org/10.5194/egusphere-egu21-1933, 2021.