摘要
为提高城市降水径流短期预测和长期预测的精度,降低预测结果的绝对误差和相对误差,引入单位线法,开展对其预测方法的设计研究。为提供更可靠的预测依据,对城市流域河网水系信息进行提取,确定影响城市降水径流的各个因素;利用单位线法对城市降水径流过程进行数学描述,并完成对城市降水量的计算;引入GA-BP神经网络模型实现对城市年降水径流的预测。通过对比实验的方式,将新的预测方法与基于SCS-CN模型的预测方法应用到相同实验环境中,对同一城市降水径流进行预测。从实验结果得出,新的预测方法无论是短期预测还是长期预测,其预测精度均高于基于SCS-CN模型的预测方法,具有更高的应用价值。
In order to improve the accuracy of short-term and long-term forecast of urban precipitation runoff and reduce the absolute and relative errors of forecast results,unit hydrograph method is introduced to carry out design and research on its prediction method.In order to provide more reliable forecasting basis,river network information of urban watershed is extracted to determine various factors affecting urban precipitation and runoff.Unit hydrograph method is used to describe the process of urban precipitation runoff mathematically and to complete the calculation of urban precipitation.GA-BP neural network model is introduced to forecast urban annual precipitation runoff.By means of contrast experiments,the new forecasting method and the forecasting method based on SCS-CN model are applied in the same experimental environment to forecast the precipitation runoff of the same city.The experimental results show that the forecast accuracy of the new forecasting methods,whether short-term or long-term,is higher than that of SCS-CN model,which has higher application value.
作者
唐小婧
TANG Xiao-jing(Shenyang Hydraulic Architecture Survey and Design Institute Co.,Ltd.,Shenyang 110000,China)
出处
《云南水力发电》
2023年第4期36-39,共4页
Yunnan Water Power
关键词
单位线法
降水
方法
预测
径流
城市
unit hydrograph method
precipitation
method
forecast
runoff
city
