入海河流水质分析对广东省治理近岸海域水质,实现经济社会与生态环境协调发展有重要意义。本研究选取广东省27个入海河流监测断面,基于2016~2020年水质监测数据,分析了该地区入海河流水质演变特征和影响因素。结果表明,5年间广东省入海河流水质呈现先恶化后改善的趋势,多数水质指标的超标断面主要集中在4~6月和10~12月。练江在广东省入海河流中污染最严重,深圳河、淡澳河和寨头河污染较严重,污染物以NH3-N、TP为主。自然因素中的降水、气温是影响河流水质的间接因素,社会经济因素中的第一产业占比、工业废水及生活污水排放量、化肥农药施用量、城镇污水处理率与河流水质呈显著的相关关系。研究结果可为揭示广东省海岸带环境治理成果及指导后续治理举措提供参考。The analysis of water quality in seaward rivers holds significant implications for Guangdong Province in managing coastal marine water quality and achieving coordinated socio-economic and ecological development. This study examined 27 monitoring sections along coastal rivers in Guangdong, utilizing water quality monitoring data spanning 2016~2020 to investigate temporal variations and driving factors of fluvial water quality dynamics. The results revealed that water quality in Guangdong Province’s coastal rivers exhibited a trend of initial deterioration followed by improvement over the five-year study period. Notably, the majority of non-compliant sections for key water quality parameters were concentrated during the months of April-June and October-December. Among the coastal rivers in Guangdong, the Lianjiang River was identified as the most severely polluted, with the Shenzhen River, Dan’ao River, and Zhaigang River also showing significant pollution levels. The primary pollutants in these rivers were NH3-N and TP. The analysis identified precipitation and temperature as indirect drivers of river water quality within nat
以中山大学珠海校区滨海水循环综合试验基地2006年12月到2007年3月地下水排泄区井群井水和海水温度、电导数据为基础,计算井水和海水温度平均值及变差系数,发现研究区域地下20m处存在含水层与海洋联通现象。使用混合比（End member mixing analysis,EMMA）、Mallet小波分解重构、互相关计算以及频谱分析等方法,对D5井水中混合海水含量以及海水对D5井作用机制进行研究,结果表明：D5井水中海水所占比例为9%~16%,海水对D5井能量贡献比为31%（其中12%通过海水-井水混合实现,19%通过介质传导实现）;D5中海水混合比的变动相对潮汐站水位变化存在5.5h相位延迟,其变化趋势及显著周期大致与潮汐站水位变化情况一致。
