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Hydrogeochemical characterization and quality assessment of groundwater using self-organizing maps in the Hangjinqi gasfield area,Ordos Basin,NW China
Authors:Chu Wu  Chen Fang  Xiong Wu  Ge Zhu  Yuzhe Zhang
Institution:Department of Water Resources,China Institute of Water Resources and Hydropower Research,Beijing 100083,China;School of Water Resources and Environment,China University of Geosciences (Beijing),Beijing 100083,China;Center for Advanced Technology and Education (CATE),Florida International University,Miami,FL 33174,USA;School of Water Resources and Environment,China University of Geosciences (Beijing),Beijing 100083,China
Abstract:Water resources are scarce in arid or semiarid areas, which not only limits economic development, but also threatens the survival of mankind. The local communities around the Hangjinqi gasfield depend on groundwater sources for water supply. A clear understanding of the groundwater hydrogeochemical characteristics and the groundwater quality and its seasonal cycle is invaluable and indispensable for groundwater protection and management. In this study, self- organizing maps were used in combination with the quantization and topographic errors and K-means clustering method to investigate groundwater chemistry datasets. The Piper and Gibbs diagrams and saturation index were systematically applied to investigate the hydrogeochemical characteristics of groundwater from both rainy and dry seasons. Further, the entropy-weighted theory was used to characterize groundwater quality and assess its seasonal variability and suitability for drinking purposes. Our hydrochemical groundwater dataset, consisting of 10 parameters measured during both dry and rainy seasons, was classified into 6 clusters, and the Piper diagram revealed three hydrochemical facies: Cl-Na type (clusters 1, 2 and 3), mixed type (clusters 4 and 5), and HCO3-Ca type (cluster 6). The Gibbs diagram and saturation index suggested that weathering of rock-forming minerals were the primary process controlling groundwater chemical composition and validated the credibility and practicality of the clustering results. Two-thirds of 45 groundwater samples were categorized as excellent- or good-quality and were suitable as drinking water. Cluster changes within the same and different clusters from the dry season to the rainy season were detected in approximately 78% of the collected samples. The main factors affecting the groundwater quality were hydrogeochemical characteristics, and dry season groundwater quality was better than rainy season groundwater quality. Based on this work, such results can be used to investigate the seasonal variation of hydrogeochemical characteristics and assess water quality accurately in the others similar area.
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