摘要
对流域径流的变化规律进行准确地分析及合理地预测对流域水资源的合理开发、水利工程的建设以及社会经济的发展具有重要的指导意义。利用Mann-Kendall秩次相关检验法和小波分析理论对秃尾河流域的径流变化规律进行分析研究,并建立BP神经网络模型对径流变化进行预测分析。结果表明:秃尾河流域年径流量变化总体上有明显的下降趋势;从小波系数图可以看出年径流过程主要存在2年、8年和19年左右的变化周期,其中19年左右时间尺度为第一主周期,同时发现目前年径流处在枯水期后期,水量有转向增加的趋势;采用BP神经网络法对秃尾河流域高家川站年径流量进行预测,预测结果相对误差仅为5.92%,说明所建立的BP神经网络模型用于该流域的年径流预测得精度较高,是一种有效地年径流预测方法。
The accurate analysis and reasonable prediction of rule of runoff variation have a great significance for reasonable development of water resources,construction of water conservancy project and development of social economy. Using Mann-Kendall method and wavelet analysis method,the paper analyzed and researched the variety regulation of runoff in Tuwei river basin,and established the neural network model to forecast the runoff variation. The results show that the runoff in Tuwei river basin has a obvious decreasing trend; from the wavelet coefficient chart we can know that the annual runoff process primarily have the period of 2 years,8 years and 19 years,of which about time scale of 19 years as the first cycle,also found that the current annual runoff is in the late dry season,the amount of water has trend of rising; by using the neural network model to forecast the annual runoff at Gaojiachuan station in Tuwei river basin,the relative error of prediction is only 5. 92%,which shows that the forecast precision of annual runoff in the basin by neural network model is higher and a very effective method of annual runoff forecast.
出处
《水资源与水工程学报》
2014年第2期153-157,共5页
Journal of Water Resources and Water Engineering
关键词
年径流
小波分析
BP神经网络
年径流预测
秃尾河
annual runoff
wavelet analysis
BP-neural network
forecast of annual runoff
Tuwei river