摘要
基于花园口水文站以上区域的71个气象站1961—2005年逐日降水量、气温和花园口水文站1961—2005年逐日实测流量,利用人工神经网络模型建立月平均流量与降水、气温之间的关系,并设定不同气候变化条件,研究了花园口水文站年平均流量对不同气候条件的响应。结果表明:花园口水文站年平均流量在降水增加10%和20%、气温变化-2～2℃时均为增加趋势,在降水减小10%和20%、气温变化-2～2℃时均为减小趋势,且增大幅度大于减小的幅度。
Based on daily precipitation and daily temperature of 71 meteorological stations from 1961 to 2005 and daily discharge at Huayuankou Hydrological Station from 1961 to 2005 of the Yellow River basin, artificial neural networks were applied to simulate the relationships between monthly discharge and monthly precipitation and monthly temperature, then figured annual discharge at Huayuankou Hydrological Station by different climate conditions of the Yellow River basin whieb were analyzed by setting different climate change scenarios. The results show that the annual discharge at Huayuankou Hydrological Station tends to increase under the condition of annual precipitation increasing 10% or 20% while variation of annual temperature changing from -2 ℃ to 2 ℃, and annual discharge tends to decrease under the conditions of amlual precipitation decreasing 10% or 20% while variation of annual temperature changing from -2℃ to 2℃, and the increasing extent of annual discharge is bigger than that of the decreasing extent.
出处
《人民黄河》
CAS
北大核心
2012年第3期24-26,共3页
Yellow River
基金
中国气象局气候变化专项(CCSF-10-04)
关键词
水文效应
气候
人工神经网络
年平均流量
花园口
黄河
hydrological effect
climate
artificial neural networks
annual discharge
Huayuankou
Yellow River
