In order to reveal the trend of water chemistry change in the Yarlung Tsangpo River (Yajiang River) under the background of climate change and provide scientific and technological support for water resources and water environment management in the basin, based on the study of hydrochemical characteristics of the Yajiang River in 2016, 2017 and 2018, combined with the research results of existing research teams on hydrochemistry, this paper studies the trend of 11 hydrochemical components change of the upper, middle and lower reaches of the Yajiang River over the past 60 years by comprehensive use of linear tendency estimation, climate change model output and BP neural network model. The results show that the annual average temperature in the upper, middle and lower reaches of the Yajiang River Basin has been increasing obviously in the past 60 years. The average temperature warming rate was 0.38°C/10a. The precipitation in the Yajiang River Basin fluctuated obviously and showed an overall rising trend, with a rising rate of 7.34 mm/10a. pH value of the water in Yajiang River was weakly alkaline and showd an upward trend. TDS was higher than the average level of the world river (120 mg/L) and showed a trend of gradual increase. Based on the climate change model RCP4.5 scenario, the artificial neural network prediction shows that the TDS flux in the upper, middle and lower reaches of the Yajiang River Basin presents a gradually increasing trend, and the downstream will have a certain impact on the production and life of the downstream residents. 

为探究雅鲁藏布江(简称雅江)河流水化学组分的历史变化趋势及未来气候变化的影响, 将2016, 2017和2018年雅江实测数据与文献数据相结合, 采用线性倾向性估计方法, 分析雅江上、中、下游近60年来气象及11种水化学组分的变化, 采用气候变化模式和BP神经网络模型预测未来气候情景下总溶解固体(TDS)的浓度, 以期为资料缺失的雅江流域水资源管理和水环境治理提供科学支撑。研究结果表明, 近60年来, 雅江流域年均气温上升趋势显著, 升温速率为0.38°C/10a; 年降雨量总体上呈上升趋势, 速率为7.34 mm/10a; 河流水化学组分存在一定程度的波动, 其中TDS远高于全球河流平均水平(120 mg/L), 并存在上升趋势, pH为弱碱性并存在上升趋势。在未来气候变化模式(RCP4.5)下, BP神经网络模型预测结果显示雅江流域上、中、下游TDS浓度将显著增加, 下游最为显著, 河流水质存在恶化的风险, 将对流域居民生产生活产生不利影响。