摘要
径流量预测的常用方法具有不确定性大、未考虑大气变化及人类活动等因素影响的缺点,因此提出人工神经网络结合SWAT模型的预测方法来对其进行优化。应用该方法对辽宁省哈巴气水文站的降雨量及径流量进行模拟,预测结果与实测值吻合度较高,证明了该方法的合理性。此外,应用该方法对该站未来15年的径流量变化情况进行了预测,为该地区的水资源规划提供基础资料。
Common methods of runoff volume prediction has defects of large uncertainty, none consideration of climate change and influence of human activities and similar factors. Therefore, the method is optimized through the prediction method of artificial neural network combined with SWAT model. The method is applied to stimulating the precipitation and runoff volume in Liaoning Habaqi Hydrological Station. The prediction results are highly fit with measured value. The rationality of the method is proved. In addition, the method is applied for predicting the runoff volume change condition of the station within 15 years in the future, thereby providing basic information for water resources planning in the area.
出处
《水资源开发与管理》
2017年第8期67-70,共4页
Water Resources Development and Management
关键词
人工神经网络
SWAT模型
径流量
预测
artificial neural network
SWAT model
runoff volume
prediction
