中文摘要：

采用流溪河模型构建乐昌峡水库入库洪水预报模型,通过＂粒子群（PSO）＂算法优选模型参数,并对实测洪水过程进行了模拟,对比模型性能。研究发现,采用流溪河模型的乐昌峡水库入库洪水预报性能优良,可满足乐昌峡水库入库洪水预报对精度的要求;模型参数优选可明显提高乐昌峡水库入库洪水预报流溪河模型的洪水模拟精度;＂粒子群＂算法具有很强的全局优化能力,快速的计算收敛能力,参数优选中种群进化次数在30次以内;乐昌峡水库的建成运行产生了一定的水库洪水效应,10场洪水平均峰现时间提前1.3 h,次洪径流系数增加1.596%,洪峰流量增加0.207%。该模型可用于同类水库入库洪水预报。

英文摘要：

The inflow flood forecasting model of Lechangxia Reservoir is established herein with Liuxihe Model, for which the model parameters are optimized throughPSO algorithm, and then the measured flood hydrographsare simulated, while the model performances are compared as well. The study find out that the performance of the inflow flood forecasting of Lechangxia Reservoir carried out with Liuxihe Model is perfect and can meet the requirement of the accuracy of the inflow flood forecasting for the reser- voir. The optimization of the model parameters can obviously enhance the flood simulation accuracy of Liuxihe Model used for the inflow flood forecasting of Lechangxia Reservoir. The PSO algorithm has strong global optimization capability, rapid convergence capacity with the swarm evolution number within 30 times. The complete and operation of Lechangxia Reservoir create a certain reservoir flood effect, i.e. the average peak occurrence time of 10 flood events is advanced by 1.3 hour, the runoff coefficient of the half-hourly flood is increased by 1.59% and the flood peak discharge is increased by 0. 207%. The model can be applied to the inflow flood forecasting of the similar reservoir.