Arid Zone Research ›› 2024, Vol. 41 ›› Issue (10): 1685-1698.doi: 10.13866/j.azr.2024.10.07

• Land and Water Resources • Previous Articles     Next Articles

Simulation of rainfall and snowmelt runoff on the daily scale of the Kuwei Station in the Irtysh River

ZHAO Wenlong1,2(), LYU Haishen1,2(), ZHU Yonghua1,2, LIU Han1,2, WU Zhuojun1,2   

  1. 1. National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing 210098, Jiangsu, China
    2. College of Hydrology and Water Resources, Hohai University, Nanjing 210098, Jiangsu, China
  • Received:2024-03-29 Revised:2024-06-27 Online:2024-10-15 Published:2024-10-14
  • Contact: LYU Haishen E-mail:221301010052@hhu.edu.cn;lvhaishen@hhu.edu.cn

Abstract:

Due to geographical conditions, there are limited hydrometeorological stations and a lack of basic data in the Irtysh River Basin, and the snowmelt flood exerts a considerable effect on the flood season and water resources management in the basin. In this study, precipitation and temperature reanalysis products and AVHRR snow cover data were applied, the K-means clustering method was used to divide the characteristics of different runoff periods, the corresponding SRM+LSTM model in different periods was constructed, and the runoff data observed in the field in 2023 were used. Results showed that the reanalysis product CMFD can be well applied to the Irtysh River Basin according to precipitation and temperature. The relationship between snow cover and runoff was divided into different runoff periods, as follows: December 11th to April 10th of the following year was the snow retreat period, April 11th to August 10th was the snowmelt precipitation runoff period, and August 11th was the precipitation runoff period. The simulation effect of the SRM model was poor, and the Nash efficiency coefficient of most runoff was<0. The SRM+LSTM model could better simulate the runoff in different periods of the basin, the deterministic coefficient could reach>0.5, and the Nash efficiency coefficient NSE could also reach>0.5, which confirms that the SRM+LSTM model can be better applied to the area with high accuracy.

Key words: K-means clustering method, SRM model, LSTM model, runoff simulation, Irtysh River