Application of Xin'an River model based on PSO algorithm in flood forecasting of Yongning River
According to the climatic characteristics of Yongning River basin,a first-class tributary of Jialing River,u-sing the day-by-day hydro-logical observation data of Yongning Town Hydro-logical Station for 20 consecutive years from 2002 to 2021,the parameter rates of Xin'an River model were determined based on Particle Swarm Algorithm(PSO),based on which the daily flow rate of Yongning Town Hydro-logical Station was simulated,to explore the application of the model in the flood forecasting of Yongning Town Hydro-logical Station.The results show:The results of Xin'an River model in the runoff simulation of Yongning Town Hydro-logical Station are good,the average value of the coefficient of certainty in the rate period is 0.53,with a qualification rate of 71%,and the average value of the coefficient of certainty in the validation period is 0.59,with a qualification rate of 100%,and the qualification rate of the simulation results has reached Grade B,and the co-efficient of certainty has reached Grade C forecasting accuracy,which is in line with the specification,and it can be used for the flood forecast of the station,and it has put forward a new direction for the flood forecast of the station.It can be used for flood forecasting in this station,which proposes a new direction for flood forecasting in this station and accumulates experience for the application of Xin'an River model in the upper reaches of Jialing River.
Xin'anjiang modelflood forecastingYong ning riverparticle swarm algorithm
NETL
NSTL
万方数据
