Influence of climate change on hydrological process in the upper reaches of Shiyang River:A case study of the Xiying River,China

Climate change is the dominant factor affecting the hydrological process, it is of great significance to simulate and predict its influence on water resources management, socio-economic activities, and sustainable development in the future. In this paper, the Xiying River Basin was taken as the study area, China Atmospheric Assimilation Driven Data Set(CMADS) and observation data from the Jiutiaoling station were used to simulate runoff of the SWAT model and calibrate and verify model parameters. On this basis, runoff change of the basin under the future climate scenario of CMIP6 was predicted. Our research shows that:(1) The contribution rates of climate change and human activities to runoff increase of the Xiying River are 89.17% and 10.83%, respectively. Climate change is the most important factor affecting runoff change of the Xiying River.(2) In these three different emission scenarios of SSP1-2.6, SSP2-4.5 and SSP5-8.5 in CMIP6 climate model, the average temperature increased by0.61, 1.09 and 1.74 C, respectively, in the Xiying River Basin from 2017 to 2050. Average precipitation increased by 14.36, 66.88, and 142.73 mm, respectively, and runoff increased by 15, 24, and 35 million m3, respectively.The effect of climate change on runoff will continue to deepen in the future.

Particulate matter assessment of a wetland in Beijing

To increase the knowledge on the particulate matter of a wetland in Beijing, an experimental study on the concentration and composition of PM10 and PM2.5was implemented in Beijing Olympic Forest Park from 2013 to 2014. This study analyzed the meteorological factors and deposition fluxes at different heights and in different periods in the wetlands. The results showed that the mean mass concentrations of PM10 and PM2.5were the highest at 06：00–09：00 and the lowest at 15：00–18：00. And the annual concentration of PM10 and PM2.5in the wetland followed the order of dry period（winter） 〉 normal water period（spring and autumn） 〉 wet period（summer）, with the concentration in the dry period significantly higher than that in the normal water and wet periods. The chemical composition of PM2.5in the wetlands included NH4^＋, K^＋, Na^＋, Mg^2＋, SO4^2-, NO3^-, and Cl^-, which respectively accounted for 12.7%, 1.0%, 0.8%, 0.7%, 46.6%, 33.2%, and 5.1% of the average annual composition. The concentration of PM10 and PM2.5in the wetlands had a significant positive correlation with relative humidity, a negative correlation with wind speed, and an insignificant negative correlation with temperature and radiation. The daily average dry deposition amount of PM10 in the different periods followed the order of dry period 〉normal water period 〉 wet period, and the daily average dry deposition amount of PM2.5in the different periods was dry period 〉 wet period 〉 normal water period.