Spatial and temporal variations of sediment flux entering into the South China Sea from 2001 to 2020
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摘要: 在人类活动和快速气候变化的影响下,南海周边河流入海沉积物通量发生巨大变化。本文基于2001−2020年间南海周边河流数据及海表悬浮沉积物浓度数据,探究南海周边河流入海沉积物通量的时空变化特征。研究结果表明:2001−2020年南海周边河流入海沉积物通量超过345 Mt/a,人类活动导致珠江、红河、湄公河入海沉积物通量减少约300 Mt/a。南海周边河流入海沉积物通量还受台风和气候变化的影响:台风是影响南海周边河流入海沉积物通量的重要因素,尤其是台风期间台湾地区的高屏溪入海沉积物通量可达全年总量的89%。在东亚季风系统影响下,南海周边河流入海沉积物通量表现出雨季高、旱季低的变化特征,雨季期间入海沉积物通量占全年总量的80%以上,相应地,河流表层羽流在雨季具有浓度高和扩散范围大的典型特征。受厄尔尼诺−南方涛动的影响,南海周边河流流量和入海沉积物通量也存在不同周期变化,南海周边大型河流入海沉积物通量表现出2.5~3.0 a的变化周期,并与NIÑO3.4指数存在相关性。本文利用20 年的河流数据系统论证了台风、气候变化和大坝建设对21世纪以来南海周边河流入海沉积物通量的影响,在源汇过程研究及流域治理方面具有重要意义。Abstract: Under the influence of human activities and rapid climate change, the fluvial sediments flux entering into the South China Sea (SCS) has changed greatly. Based on the hydrological data of rivers around the SCS and sea surface Suspended Sediment Concentration data from 2001 to 2020, this study investigated spatial and temporal variation of sediment flux entering into the SCS. The results show that the sediment flux entering into the SCS exceeds 345 Mt/a during 2001−2020. Human activities result in a reduction of 300 Mt/a in sediment flux from the Zhujiang River, Red River and Mekong River. The sediment flux is also affected by typhoons and climate change: typhoons are the most important factor affecting the sediment flux of small rivers, and the sediment flux of the Gaoping River during the typhoon can reach 89% of total. Under the influence of the East Asian monsoon system, the sediment flux entering into the SCS characterized by significant seasonal variations, the sediment flux is high in wet season and low in dry season. During the wet season, the sediment flux entering into the SCS accounted for more than 80% of total, accordingly, the river plume has the typical characteristics of high concentration and large diffusion range in the wet season. Under the influence of El Niño-Southern Oscillation, the discharge and sediment flux into the sea around the South China Sea also have different periodic changes. The river discharge and sediment flux of large rivers around the South China Sea show a 2.5−3.0 a period, and are correlated with the NIÑO3.4 index, while the sediment flux Taiwan rivers has no obvious period on the interannual scale. Based on data of the 20 a, this study systematically demonstrates the influences of extreme weather, climate change and dam construction on the sediment flux entering into SCS since the 21st century, which is of great significance in the study of source-to-sink processes and watershed management.
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Key words:
- South China Sea /
- fluvial sediment flux into the sea /
- dam construction /
- climate change
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图 1 南海周边主要河流系统及其入海沉积物通量(单位:Mt/a)(a)和本文统计结果与Liu等[8]历史沉积物通量差值(单位:Mt/a)(b)
a. 红色数字为本文统计的各区域河流编号,黑色数字为本文计算的南海各区域河流入海沉积物通量,括号内紫色数字为Liu等[8]提出的河流入海沉积物通量;b.2001−2020年南海周边河流入海沉积物通量平均下降量,红白色圆点为大坝位置(
2087 个,截至2020年),Liu等[8]提出的加里曼丹岛和苏门答腊岛河流沉积物通量数值为模型得出,未统计其下降量Fig. 1 Fluvial drainage systems and their annual sediment flux entering into the SCS (Unit: Mt/a) (a) and reduced sediment flux results of this paper compared to Liu et al.[8] (Unit: Mt/a) (b)
a.The red numbers are the riversinvestigated in this study. The black arrows withn umbers are the sediment flux calculated in this study. The purple numbers in the bracket are the sediment flux proposed by Liu et al.[8]; b. Decrease of sediment flux entering into the SCS from 2001 to 2020. The red and white circles show the location of dams (2087 dams, by 2020). The sediment flux of Kalimantan and Sumatra proposed by Liu et al.[8] are modal data and the decrease of these two regions is not calculated
图 6 2001−2020年高屏溪里岭大桥测站处日平均气压(a),降水量(b),流量和入海沉积物通量(c)时间序列
绿色虚线代表台风,粉色虚线代表浊流
Fig. 6 Time series for daily average pressure (a), precipitation (b), discharge and sediment flux (c) at Liling-Bridge Station for Gaoping River from 2001 to 2020
Green dashed lines indicate the typhoons and pink dashed lines indicate turbidity currents
图 14 泰国湾雨季(a)、旱季(b)海表悬浮体浓度以及雨季和旱季的差值(c)
a中标号1−4分别为:美功河、他钦河、湄南河及邦巴功河
Fig. 14 Distribution of seasurface SSC in wet season (a), dry season (b) and difference between wet season and dry season of Gulf of Thailand (c)
Numbers 1−4 in figure a represent: Mae Klong River, Tha Chin River, Chao Phraya River and Bangpakhlong River
图 15 2001−2020年珠江月平均流量(a)和入海沉积物通量(b)序列小波功率谱;流量(c)和入海沉积物通量(d)低通滤波序列小波功率谱;流量(e)和入海沉积物通量(f)与NIÑO3.4指数的交叉小波谱
Fig. 15 The wavelet power spectra for monthly average discharge (a) and sediment flux (b); the low pass filtered seriesfor discharge (c) and sediment flux (d); cross wavelet spectra for discharge (e) and sediment flux (f) between the NIÑO3.4 Index hydrological series of the Zhujiang River
表 1 南海周边河流沉积物通量数据
Tab. 1 Sediment flux of rivers around the SCS
地区 河流 流域面积/
(103 km2)Liu等[8]发布
入海通量/(Mt·a−1)2001−2020平均
入海通量/(Mt·a−1)数据源 时间分辨率 台湾地区 浊水溪 3 54.1 72.69 台湾水文年报 每月30 ± 2个 北港溪 0.6 2.2 2.91 台湾水文年报 朴子溪 0.3 2.1 0.80 台湾水文年报 八掌溪 0.4 6.3 3.10 台湾水文年报 急水溪 0.2 1.8 1.44 台湾水文年报 曾文溪 1.2 25.1 5.24 台湾水文年报 盐水溪 0.1 1.1 0.24 台湾水文年报 二仁溪 0.2 30.2 4.61 台湾水文年报 高屏溪 3 49 30.37 台湾水文年报 东港溪 0.2 0.4 0.34 台湾水文年报 林边溪 0.3 3.3 1.76 台湾水文年报 华南地区 九龙江 15 3.1 2.46 Alain Isabwe[18] 公报数据为每月平均
文献数据为每年平均韩江 30 10 1.70 王宇飞[19] 榕江 4.4 0.28 敖亮挺[20] 珠江 450 84.3 28.98 中国河流泥沙公报 漠阳江 6.1 0.8 1.26 蔡绪军[21] 鉴江 9.5 1.5 1.20 张义宇[22] 南流江 6.6 1.1 0.66 珠江片河流泥沙公报 大风江 1.9 0.36 罗亚飞等[23] 钦江 2.5 0.26 欧芳兰等[24] 茅岭江 2.9 0.32 亢振军等[25] 南渡江 6.6 1.1 0.29 珠江片河流泥沙公报 昌化江 5.1 0.08 0.59 珠江片河流泥沙公报 万泉河 3.7 0.16 珠江片河流泥沙公报 中南半岛 Thai Binh(太平江) 15 1 Milliman和Farnsworth[1] Red River(红河) 120 130 23.39 Dethier等[6] 每年平均 Ma(马江) 28 3 Milliman和Farnsworth[1] Ca(蓝江) 27 4 3.70 Phuong等[26] 多年平均 Thu-bon(秋盆河) 10 2 Milliman和Farnsworth[1] SaiGon(西贡河) 44 3 0.43 Dethier等[6] 每年平均 Mekong(湄公河) 790 160 34.40 Chua和Lu[29] 每年平均 泰国中部 Petch(碧武里河) 6 Milliman和Farnsworth[1] Mae Klong(美功河) 31 8.1 0.80 Dethier等[6] 每年平均 Chao Phraya(湄南河) 160 11 6.96 Dethier等[6] 每年平均 Tha Chin(塔他河) 3 0.12 Milliman和Farnsworth[1] Bangpakhlong(邦巴功河) 10 Milliman和Farnsworth[1] 马来半岛 Pattani(北大年河) 4 0.35 Milliman和Farnsworth[1] Kelantan(吉兰丹河) 12 13.9 Milliman和Farnsworth[1] Terengganu(登嘉楼河) 3.3 0.8 Milliman和Farnsworth[1] Pahang(彭亨河) 19 20.4 12.11 Dethier等[6] 每年平均 Johor(柔佛河) 2.6 0.07 Latif等[27] 多年平均 苏门答腊岛 Rokan(罗坎河) 19 0.98 Dethier等[6] 每年平均 Siak(夏克河) 16 Milliman和Farnsworth[1] Kampar(甘巴河) 36 0.65 Dethier等[6] 每年平均 Inderagiri(因德拉吉里河) 22 Milliman和Farnsworth[1] Hari(哈里河) 50 5.90 Dethier等[6] 每年平均 Musi(穆西河) 61 Milliman和Farnsworth[1] 加里曼丹岛 Segama(昔加末河) 6 Milliman和Farnsworth[1] Padas(巴达斯河) 5 Milliman和Farnsworth[1] Baram(巴拉姆河) 22.8 12 24.00 Prabakaran等[28] 多年平均 Kidurong(都东河) 5.4 Milliman和Farnsworth[1] Rajang(拉让江) 51 30 53.86 Dethier等[6] Lupar(卢帕河) 7 Milliman和Farnsworth[1] 每年平均 吕宋岛 Cagayan(卡加延河) 30.4 1.53 Dethier等[6] 每年平均 Agno(阿格诺河) 6.3 4.7 Liu等[8] Pampanga(邦板牙河) 8.6 3.6 Liu等[8] Angat(安加特河) 0.6 4.6 Liu等[8] 表 2 卫星观测数据标准误差(由流量和沉积物浓度数据误差计算得出,Dethier等[6]研究)
Tab. 2 Standard error of satellite observation data (calculated from discharge and sediment concentration data, data from Dethier[6])
中南半岛 泰国中部 马来半岛 苏门答腊岛 加里曼丹岛 吕宋岛 红河 西贡河 美功河 湄南河 彭亨河 罗坎河 甘巴河 哈里河 拉让江 卡加延河 误差 0.15 0.20 0.17 0.23 0.15 0.18 0.17 0.13 0.14 0.18 表 3 南海周边部分河流水沙关系曲线参数(log10(a)、b)及决定系数(r2)
Tab. 3 Sediment rating parameters (log10(a) and b) and determination (r2) in part of rivers around the SCS
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