2011～2050年松花江流域径流预估

Future Projections of Runoff in the Songhuajiang River Basin

针对全球气候变暖难以利用水文模型评估大尺度流域径流对气候变化的响应,以松花江流域为例,基于人工神经网络模型,根据全球气候模式ECHAM5/MPI-OM在三种排放情景下对该流域2011～2050年的气候做了预估,并计算了佳木斯站流量变化。结果表明,该站在三种排放情景下年平均流量的年际、年代际变化不明显、周期特征不相同、季节平均流量变化不一致。该法模拟可靠,预报精度高,可用于大流域气候变化影响评估。

It is difficult to evaluate impacts of climate change under global climate warming on runoff in large scale basin by applying physical hydrological models.To solve the problem,Taking the Songhuajiang River basin for an example,runoff in Jiamusi hydrological station under three emission scenarios from 2011 to 2050 years are projected by applying artificial neural networks in this research,based on climate projection by global climate model ECHAM5/MPI-OM.The results show that interannual and decadal changes of annual runoff are not obvious,and annual runoff has different periods and seasonal runoffs show different trends under three emission scenarios.The methodology has reliable prediction with high precision and is applicable for climate change impact assessment in large basin.