The Influence of Large Scale Phosphate Mining on the Water Quality of the Huangbaihe River Basin in China: Dominant Pollutants and Spatial Distributions

被引:6
|
作者
Reta, Gebrehiwet Legese [1 ,2 ]
Dong, Xiaohua [1 ,2 ]
Su, Bob [1 ,3 ]
Hu, Xiaonong [1 ,4 ]
Bo, Huijuan [1 ,2 ]
Wan, Hao [1 ,2 ]
Liu, Ji [1 ,2 ]
Li, Yinghai [1 ,2 ]
Peng, Tao [1 ,2 ]
Ma, Haibo [1 ,2 ]
Wang, Kai [5 ]
Xu, Shijin [5 ]
机构
[1] China Three Gorges Univ, Coll Hydraul & Environm Engn, Yichang 443002, Peoples R China
[2] Hubei Prov Collaborat Innovat Ctr Water Secur, Wuhan 430070, Hubei, Peoples R China
[3] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, NL-7500 AE Enschede, Netherlands
[4] Jinan Univ, Inst Groundwater & Earth Sci, Guangzhou 510632, Guangdong, Peoples R China
[5] Huaihe River Commiss, Hydrol Bur, Bengbu 233001, Peoples R China
基金
中国国家自然科学基金;
关键词
Chemometrics; Discriminant analysis; Principal component analysis; MULTIVARIATE STATISTICAL TECHNIQUES; POLLUTION; LAKE; APPORTIONMENT; RESERVOIR; IMPACT;
D O I
10.1007/s10230-019-00604-6
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Large scale phosphate mining in the Huangbaihe River Basin, China has reduced the self-purification capacity of the basin's fresh water. Three years (2014-2016) of monitoring data and chemometric analysis were used to identify the dominant pollutants and define their spatial distribution in the basin. Principal component analysis was applied to determine the contribution of the individual pollutants. Total phosphorus (TP) 53%, water temperature (TEMP) 27%, and total nitrogen (TN) 20% proved to be the dominant problems. A discriminant functions (DF) model was developed to classify the study area into high, moderate, and low pollution zones. The DF coefficients were applied to analyze the correlation between DF and the measured parameters and it was found that TP, TN, and TEMP were positively correlated with the DF, indicating that these parameters were the most important. Finally, the results were compared with the locations of the mining activities, which revealed that TP is higher in the upper sub-basins, Xuanmiaoguan and Tianfumiao, where most of the high pollution zones are located and more than 78% of the areas are affected by the phosphate mines. It is concluded that the phosphate mining is the major source of pollution and TP is the dominant pollutant responsible for the total water quality variation in the river basin. More effective management measures have to betaken to reduce phosphorus runoff into the reservoir watersheds. ZusammenfassungGro ss ma ss stablicher Phosphatbergbau im Huangbaihe Becken, China hat zur Herabsetzung des Selbstreinigungsvermogens des Frischwassers im Flusseinzugsgebiet gefuhrt. Zur Identifizierung der Hauptschadstoffe und deren raumlicher Verteilung im Flussgebiet wurde eine dreijahrige Zeitreihe (2014-2016) von Monitoringdaten in Kombination mit einer chemometrischen Analyse herangezogen. Mittels Hauptkomponentenanalyse wurde der Beitrag einzelner Schadstoffe bestimmt. Als vorherrschende Probleme erwiesen sich Gesamtphosphor (TP, 53%), Wassertemperatur (TEMP, 27%) und Gesamtstickstoff (TN, 20%). Zwecks Unterteilung des Untersuchungsgebiets in Zonen mit starker, ma ss iger und geringer Kontamination wurde ein Diskriminanzfunktions-(DF-)modell entwickelt. Der DF-Koeffizient wurde zur Untersuchung des Zusammenhangs von DF und den Messparametern verwendet, und es zeigte sich, dass TP, TN und TEMP positiv mit DF korreliert waren und diese Parameter somit als die dominierenden angesehen werden konnen. Schlie ss lich wurden die Ergebnisse mit der Lage der Bergbaustandorte abgeglichen, wobei sich zeigte, dass TP die hochsten Werte in den oberen Teileinzugsgebieten Xuanmiaoguan und Tianfumiao aufwies, wo sich auch die Zonen starker Belastung und mehr als 78 % der von Phosphatbergbau betroffenen Flachen befinden. Es wird geschlussfolgert, dass der Phosphatbergbau der hauptsachliche Kontaminationsverursacher ist und dass TP der fur die Schwankung der Wassergute im Flussgebiet wichtigste Schadstoff ist. Effektivere Steuerungsma ss nahmen sind notig zur Verringerung des Phosphoreintrags in die Gewasser. ResumenLa mineria de extraccion de fosfato a gran escala en la cuenca del rio Huangbaihe, China, ha reducido la capacidad de autolimpieza del agua dulce de la cuenca. Se monitoreo durante tres anos (2014-2016) los datos y analisis quimiometricos para identificar los contaminantes predominantes y definir su distribucion espacial en la cuenca. El analisis de componentes principales se aplico para determinar la contribucion de los contaminantes individuales. El fosforo total (TP) 53%, la temperatura del agua (TEMP) 27% y el nitrogeno total (TN) 20% resultaron ser los problemas mas importantes. Se desarrollo un modelo de funciones discriminantes (FD) para clasificar el area de estudio en zonas de alta, moderada y baja contaminacion. Los coeficientes del DF se aplicaron para analizar la correlacion entre el DF y los parametros medidos y se encontro que TP, TN y TEMP correlacionaron positivamente con el DF, lo que indica que estos parametros eran efectivamente los mas importantes. Finalmente, los resultados se compararon con la ubicacion de las actividades mineras, que revelaron que el TP es mayor en las subcuencas superiores, Xuanmiaoguan y Tianfumiao, donde se localizan la mayoria de las zonas de alta contaminacion y mas del 78% de las areas afectadas por las minas de fosfato. Se concluye que la extraccion de fosfato es la principal fuente de contaminacion y TP es el contaminante predominante responsable de la variacion total de la calidad del agua en la cuenca del rio. Se deben tomar medidas de manejo mas efectivas para reducir la escorrentia de fosforo en las cuencas hidrograficas del embalse.
引用
收藏
页码:366 / 377
页数:12
相关论文
共 50 条
  • [41] Temporal and spatial variations in water quality of Changjiang River Basin in Luzhou, China based on multivariate statistical techniques
    Xiao, Kaihuang
    Yang, Jia
    Li, Yunxiang
    Quan, Qiumei
    DESALINATION AND WATER TREATMENT, 2019, 145 : 151 - 159
  • [42] Influence of landscape structures on river water quality at multiple spatial scales: A case study of the Yuan river watershed, China
    Xu, Qiyu
    Wang, Peng
    Shu, Wang
    Ding, Mingjun
    Zhang, Hua
    ECOLOGICAL INDICATORS, 2021, 121
  • [43] Assessment of Spatial Variation in River Water Quality of the Baiyangdian Basin (China) during Environmental Water Release Period of Upstream Reservoirs
    Zhou, Ling
    Sun, Wenchao
    Han, Quan
    Chen, Haiyang
    Chen, He
    Ji, Yongliang
    Tong, Runze
    Tian, Zaifeng
    WATER, 2020, 12 (03)
  • [44] Spatial scale effect of irrigation efficiency paradox based on water accounting framework in Heihe River Basin, Northwest China
    Cai, Wenjuan
    Jiang, Xiaohui
    Sun, Haotian
    Lei, Yuxin
    Nie, Tong
    Li, Lichan
    AGRICULTURAL WATER MANAGEMENT, 2023, 277
  • [45] Occurrence, spatial distribution and risk and hazard assessments of antibiotics in drinking water sources of a polluted large river basin in China
    Ju, H.
    Zhang, J.
    Sun, C.
    AQUATIC ECOSYSTEM HEALTH & MANAGEMENT, 2018, 21 (01) : 107 - 117
  • [46] Influence of Precipitation Effects Induced by Large-Scale Irrigation in Northwest China on Soil Erosion in the Yellow River Basin
    Huang, Ya
    Zhao, Yong
    Li, Guiping
    Yang, Jing
    Li, Yanping
    REMOTE SENSING, 2023, 15 (07)
  • [47] Precipitation in the Pearl River basin, South China: scaling, regional patterns, and influence of large-scale climate anomalies
    Jun Niu
    Stochastic Environmental Research and Risk Assessment, 2013, 27 : 1253 - 1268
  • [48] Precipitation in the Pearl River basin, South China: scaling, regional patterns, and influence of large-scale climate anomalies
    Niu, Jun
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2013, 27 (05) : 1253 - 1268
  • [49] Assessment the impact of drought on vegetation carbon source/sink at a spatial scale and identify the dominant factors in the Middle Reaches of the Yellow River Basin, China
    Shi, Xiaoliang
    Wang, Li
    Ding, Hao
    Liu, Siqi
    Lv, Wenyu
    HUMAN AND ECOLOGICAL RISK ASSESSMENT, 2024, 30 (5-6): : 546 - 569
  • [50] Evaluating Economic Growth, Industrial Structure, and Water Quality of the Xiangjiang River Basin in China Based on a Spatial Econometric Approach
    Chen, Xiaohong
    Yi, Guodong
    Liu, Jia
    Liu, Xiang
    Chen, Yang
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2018, 15 (10)