基于数据驱动模型的河流水温异变研究

Investigation of River Water Temperature Variation Based on Data-Driven Model

河流水温是重要的生态和环境评价因子,人类活动的干预(如大坝建设)会引起河流水温异常变化,对河流生态系统造成一定负面影响。有效的水温预测能够为河流的长期演变趋势提供良好指示,将一种新型的数据驱动水温预测模型——Air2stream模型,应用于长江三峡大坝上游寸滩站和下游宜昌站建坝前后的水温预测,模型的预测效果通过均方根误差和纳什效率系数两种指标衡量,并与其它经验回归模型进行对比分析。结果表明Air2stream模型相比经验回归模型具有精度高、稳定性好的优点,可用于判断影响河流水温变化的主要因子,检测河流水温的异变现象和幅度。该模型适用于反演自然演化条件下(即不考虑大型水利工程等强人类活动影响)河流水温的中长期变化,其中实测值和模拟值之差可作为大型水利工程等强人类活动的影响指标。可为河流生态系统监测及管理提供重要技术支撑。

River water temperature has been regarded as an important ecological and environmental assessment factor.Intervention of human activities(such as dam construction)often causes abnormal changes in river water temperature and significant effects on river ecosystem.The effective water temperature prediction can provide a good indication for the long-term evolution trend of the river thermal dynamics.In this paper,the Air2stream model,which is a newly data-driven water temperature prediction model,has been used in the Yangtze River to explore its temperature variation before and after the operation of Three Gorges Dam.The performance of the model is assessed by the root mean square error(RMSE)and the Nash efficiency coefficient(NSE),with a comparison with other empirical regression models.The results show that the Air2stream model has the advantages of higher accu-racy and better stability in the medium and long-term water temperature prediction for the river water temperature that would have occurred in absence of the large-scale engineering works or other intensive human interventions.In addition,the difference between observed and simulated values of river water temperature can be used as a useful indicator for assessing the impacts of hu-man interventions.The case study applied to the Yangtze River shows that Air2stream can be used to determine the extent of variation of water temperature and main controlled factors,as well as quantitatively analyzes the contributions of both human interventions and climate change to water temperature mutation.Therefore,it can provide an important technical support for monitoring and management of river ecosystem.