Identification of Mine Water Sources Based on the Spatial and Chemical Characteristics of Bedrock Brines: A Case Study of the Xinli Gold Mine
Water inrush caused by mining below the seafloor is extremely harmful to mine production. Identifying the sources of mine water can help guide mine water management and sustainable mine development. Saline brines were known to be entering the Xinli Mine, a portion of which lies beneath Laizhou Bay,...
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description | Water inrush caused by mining below the seafloor is extremely harmful to mine production. Identifying the sources of mine water can help guide mine water management and sustainable mine development. Saline brines were known to be entering the Xinli Mine, a portion of which lies beneath Laizhou Bay, Shandong Province, China. Preliminary classification of the bedrock brines was determined using hydrochemical analysis and the spatial position of the brines. Four bedrock brine types were identified: shallow, middle, middle high-salinity, and deep. The study area was divided into three levels (shallow, middle, and deep) according to the spatial distribution of the brines. Hierarchical-multi-index analysis (HMIA) was used, along with five pairs of chemical indicators (Cl, δ
18
O, Mg, Ca, SO
4
, Na), to identify the mixing lines for each level. A ternary hybrid model was used to calculate the mixing ratio of mine water from different sources in the shallow sublevels. The bedrock brine classification and water source identification were evaluated by analysis of brine genesis and mixing ratio deviation, respectively. The mixed modes of mine water in the shallow and middle sublevels were seawater-saline water-shallow brine and seawater-saline water-middle brine, respectively. The mixed modes in the deep sublevels were seawater-saline water-deep brine and seawater-saline water-middle brine with a transition between these two modes. Previous studies classified bedrock brine as only one category, and using the mixing ratio greatly improved accuracy. The average proportion of seawater in the mine water has increased over time, but the rate of increased has slowed. In the shallow sublevels, the proportion of seawater in the − 105 m sublevel was higher than that in the − 135 m sublevel, but the difference has decreased every year, indicating that the seawater mainly infiltrates by vertical recharge. The mine water samples from the footwall and in the middle of the − 105 m sublevel were nearly 50% seawater, while the mine water sites on the hanging wall had a relatively low seawater proportion, indicating that the water-conducting fractures were mainly in the footwall. |
doi_str_mv | 10.1007/s10230-021-00810-1 |
format | Article |
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18
O, Mg, Ca, SO
4
, Na), to identify the mixing lines for each level. A ternary hybrid model was used to calculate the mixing ratio of mine water from different sources in the shallow sublevels. The bedrock brine classification and water source identification were evaluated by analysis of brine genesis and mixing ratio deviation, respectively. The mixed modes of mine water in the shallow and middle sublevels were seawater-saline water-shallow brine and seawater-saline water-middle brine, respectively. The mixed modes in the deep sublevels were seawater-saline water-deep brine and seawater-saline water-middle brine with a transition between these two modes. Previous studies classified bedrock brine as only one category, and using the mixing ratio greatly improved accuracy. The average proportion of seawater in the mine water has increased over time, but the rate of increased has slowed. In the shallow sublevels, the proportion of seawater in the − 105 m sublevel was higher than that in the − 135 m sublevel, but the difference has decreased every year, indicating that the seawater mainly infiltrates by vertical recharge. The mine water samples from the footwall and in the middle of the − 105 m sublevel were nearly 50% seawater, while the mine water sites on the hanging wall had a relatively low seawater proportion, indicating that the water-conducting fractures were mainly in the footwall.</description><identifier>ISSN: 1025-9112</identifier><identifier>EISSN: 1616-1068</identifier><identifier>DOI: 10.1007/s10230-021-00810-1</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aquifers ; Brines ; Calcium ; Chemical analysis ; Chemical indicators ; Classification ; Conduction ; Earth and Environmental Science ; Earth Sciences ; Ecotoxicology ; Fault lines ; Footwalls ; Fractures ; Geology ; Gold ; Groundwater ; Hanging walls ; Hydrogeology ; Identification ; Industrial Pollution Prevention ; Magnesium ; Maximum likelihood method ; Mine drainage ; Mine waters ; Mineral Resources ; Mixing ratio ; Modes ; Ocean floor ; Ratios ; Saline water ; Sea level ; Seawater ; Sediments ; Spatial analysis ; Spatial distribution ; Statistical analysis ; Sulphates ; Surface water ; Sustainable development ; Technical Article ; Water analysis ; Water inrush ; Water management ; Water Quality/Water Pollution ; Water resources ; Water resources management ; Water sampling</subject><ispartof>Mine water and the environment, 2022-03, Vol.41 (1), p.126-142</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-69f60c79f6b466f66926adfbd38e1607fa45fb5fc14ae66fcc6ae392df068e673</citedby><cites>FETCH-LOGICAL-c319t-69f60c79f6b466f66926adfbd38e1607fa45fb5fc14ae66fcc6ae392df068e673</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10230-021-00810-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10230-021-00810-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Duan, Xueliang</creatorcontrib><creatorcontrib>Ma, Fengshan</creatorcontrib><creatorcontrib>Gu, Hongyu</creatorcontrib><creatorcontrib>Guo, Jie</creatorcontrib><creatorcontrib>Zhao, Haijun</creatorcontrib><creatorcontrib>Liu, Guowei</creatorcontrib><creatorcontrib>Liu, Shuaiqi</creatorcontrib><title>Identification of Mine Water Sources Based on the Spatial and Chemical Characteristics of Bedrock Brines: A Case Study of the Xinli Gold Mine</title><title>Mine water and the environment</title><addtitle>Mine Water Environ</addtitle><description>Water inrush caused by mining below the seafloor is extremely harmful to mine production. Identifying the sources of mine water can help guide mine water management and sustainable mine development. Saline brines were known to be entering the Xinli Mine, a portion of which lies beneath Laizhou Bay, Shandong Province, China. Preliminary classification of the bedrock brines was determined using hydrochemical analysis and the spatial position of the brines. Four bedrock brine types were identified: shallow, middle, middle high-salinity, and deep. The study area was divided into three levels (shallow, middle, and deep) according to the spatial distribution of the brines. Hierarchical-multi-index analysis (HMIA) was used, along with five pairs of chemical indicators (Cl, δ
18
O, Mg, Ca, SO
4
, Na), to identify the mixing lines for each level. A ternary hybrid model was used to calculate the mixing ratio of mine water from different sources in the shallow sublevels. The bedrock brine classification and water source identification were evaluated by analysis of brine genesis and mixing ratio deviation, respectively. The mixed modes of mine water in the shallow and middle sublevels were seawater-saline water-shallow brine and seawater-saline water-middle brine, respectively. The mixed modes in the deep sublevels were seawater-saline water-deep brine and seawater-saline water-middle brine with a transition between these two modes. Previous studies classified bedrock brine as only one category, and using the mixing ratio greatly improved accuracy. The average proportion of seawater in the mine water has increased over time, but the rate of increased has slowed. In the shallow sublevels, the proportion of seawater in the − 105 m sublevel was higher than that in the − 135 m sublevel, but the difference has decreased every year, indicating that the seawater mainly infiltrates by vertical recharge. The mine water samples from the footwall and in the middle of the − 105 m sublevel were nearly 50% seawater, while the mine water sites on the hanging wall had a relatively low seawater proportion, indicating that the water-conducting fractures were mainly in the footwall.</description><subject>Aquifers</subject><subject>Brines</subject><subject>Calcium</subject><subject>Chemical analysis</subject><subject>Chemical indicators</subject><subject>Classification</subject><subject>Conduction</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Ecotoxicology</subject><subject>Fault lines</subject><subject>Footwalls</subject><subject>Fractures</subject><subject>Geology</subject><subject>Gold</subject><subject>Groundwater</subject><subject>Hanging walls</subject><subject>Hydrogeology</subject><subject>Identification</subject><subject>Industrial Pollution Prevention</subject><subject>Magnesium</subject><subject>Maximum likelihood method</subject><subject>Mine drainage</subject><subject>Mine waters</subject><subject>Mineral Resources</subject><subject>Mixing ratio</subject><subject>Modes</subject><subject>Ocean floor</subject><subject>Ratios</subject><subject>Saline water</subject><subject>Sea level</subject><subject>Seawater</subject><subject>Sediments</subject><subject>Spatial analysis</subject><subject>Spatial distribution</subject><subject>Statistical analysis</subject><subject>Sulphates</subject><subject>Surface water</subject><subject>Sustainable development</subject><subject>Technical Article</subject><subject>Water analysis</subject><subject>Water inrush</subject><subject>Water management</subject><subject>Water Quality/Water Pollution</subject><subject>Water resources</subject><subject>Water resources management</subject><subject>Water 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Characteristics of Bedrock Brines: A Case Study of the Xinli Gold Mine</title><author>Duan, Xueliang ; Ma, Fengshan ; Gu, Hongyu ; Guo, Jie ; Zhao, Haijun ; Liu, Guowei ; Liu, Shuaiqi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-69f60c79f6b466f66926adfbd38e1607fa45fb5fc14ae66fcc6ae392df068e673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aquifers</topic><topic>Brines</topic><topic>Calcium</topic><topic>Chemical analysis</topic><topic>Chemical indicators</topic><topic>Classification</topic><topic>Conduction</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Ecotoxicology</topic><topic>Fault lines</topic><topic>Footwalls</topic><topic>Fractures</topic><topic>Geology</topic><topic>Gold</topic><topic>Groundwater</topic><topic>Hanging walls</topic><topic>Hydrogeology</topic><topic>Identification</topic><topic>Industrial Pollution Prevention</topic><topic>Magnesium</topic><topic>Maximum likelihood method</topic><topic>Mine drainage</topic><topic>Mine waters</topic><topic>Mineral Resources</topic><topic>Mixing ratio</topic><topic>Modes</topic><topic>Ocean floor</topic><topic>Ratios</topic><topic>Saline water</topic><topic>Sea level</topic><topic>Seawater</topic><topic>Sediments</topic><topic>Spatial analysis</topic><topic>Spatial distribution</topic><topic>Statistical analysis</topic><topic>Sulphates</topic><topic>Surface water</topic><topic>Sustainable development</topic><topic>Technical Article</topic><topic>Water analysis</topic><topic>Water inrush</topic><topic>Water management</topic><topic>Water Quality/Water Pollution</topic><topic>Water resources</topic><topic>Water resources management</topic><topic>Water sampling</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Duan, Xueliang</creatorcontrib><creatorcontrib>Ma, 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Shuaiqi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of Mine Water Sources Based on the Spatial and Chemical Characteristics of Bedrock Brines: A Case Study of the Xinli Gold Mine</atitle><jtitle>Mine water and the environment</jtitle><stitle>Mine Water Environ</stitle><date>2022-03-01</date><risdate>2022</risdate><volume>41</volume><issue>1</issue><spage>126</spage><epage>142</epage><pages>126-142</pages><issn>1025-9112</issn><eissn>1616-1068</eissn><abstract>Water inrush caused by mining below the seafloor is extremely harmful to mine production. Identifying the sources of mine water can help guide mine water management and sustainable mine development. Saline brines were known to be entering the Xinli Mine, a portion of which lies beneath Laizhou Bay, Shandong Province, China. Preliminary classification of the bedrock brines was determined using hydrochemical analysis and the spatial position of the brines. Four bedrock brine types were identified: shallow, middle, middle high-salinity, and deep. The study area was divided into three levels (shallow, middle, and deep) according to the spatial distribution of the brines. Hierarchical-multi-index analysis (HMIA) was used, along with five pairs of chemical indicators (Cl, δ
18
O, Mg, Ca, SO
4
, Na), to identify the mixing lines for each level. A ternary hybrid model was used to calculate the mixing ratio of mine water from different sources in the shallow sublevels. The bedrock brine classification and water source identification were evaluated by analysis of brine genesis and mixing ratio deviation, respectively. The mixed modes of mine water in the shallow and middle sublevels were seawater-saline water-shallow brine and seawater-saline water-middle brine, respectively. The mixed modes in the deep sublevels were seawater-saline water-deep brine and seawater-saline water-middle brine with a transition between these two modes. Previous studies classified bedrock brine as only one category, and using the mixing ratio greatly improved accuracy. The average proportion of seawater in the mine water has increased over time, but the rate of increased has slowed. In the shallow sublevels, the proportion of seawater in the − 105 m sublevel was higher than that in the − 135 m sublevel, but the difference has decreased every year, indicating that the seawater mainly infiltrates by vertical recharge. The mine water samples from the footwall and in the middle of the − 105 m sublevel were nearly 50% seawater, while the mine water sites on the hanging wall had a relatively low seawater proportion, indicating that the water-conducting fractures were mainly in the footwall.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s10230-021-00810-1</doi><tpages>17</tpages></addata></record> |
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subjects | Aquifers Brines Calcium Chemical analysis Chemical indicators Classification Conduction Earth and Environmental Science Earth Sciences Ecotoxicology Fault lines Footwalls Fractures Geology Gold Groundwater Hanging walls Hydrogeology Identification Industrial Pollution Prevention Magnesium Maximum likelihood method Mine drainage Mine waters Mineral Resources Mixing ratio Modes Ocean floor Ratios Saline water Sea level Seawater Sediments Spatial analysis Spatial distribution Statistical analysis Sulphates Surface water Sustainable development Technical Article Water analysis Water inrush Water management Water Quality/Water Pollution Water resources Water resources management Water sampling |
title | Identification of Mine Water Sources Based on the Spatial and Chemical Characteristics of Bedrock Brines: A Case Study of the Xinli Gold Mine |
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