Monitoring and statistical analysis of mine subsidence at three metal mines in China
Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Min...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hui, Xin [verfasserIn] Ma, Fengshan [verfasserIn] Zhao, Haijun [verfasserIn] Xu, Jiamo [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Bulletin of engineering geology and the environment - Berlin : Springer, 1970, 78(2018), 6 vom: 03. Sept., Seite 3983-4001 |
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| Übergeordnetes Werk: |
volume:78 ; year:2018 ; number:6 ; day:03 ; month:09 ; pages:3983-4001 |
| Links: |
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| DOI / URN: |
10.1007/s10064-018-1367-6 |
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| Katalog-ID: |
SPR008477957 |
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| 520 | |a Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. | ||
| 650 | 4 | |a Mine subsidence |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Power law |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Scale invariance |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Geological hazard |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Event prediction |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Ma, Fengshan |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Haijun |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Jiamo |e verfasserin |4 aut | |
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10.1007/s10064-018-1367-6 doi (DE-627)SPR008477957 (SPR)s10064-018-1367-6-e DE-627 ger DE-627 rakwb eng 550 600 ASE 38.58 bkl 56.00 bkl 56.20 bkl Hui, Xin verfasserin aut Monitoring and statistical analysis of mine subsidence at three metal mines in China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. Mine subsidence (dpeaa)DE-He213 Power law (dpeaa)DE-He213 Scale invariance (dpeaa)DE-He213 Geological hazard (dpeaa)DE-He213 Event prediction (dpeaa)DE-He213 Ma, Fengshan verfasserin aut Zhao, Haijun verfasserin aut Xu, Jiamo verfasserin aut Enthalten in Bulletin of engineering geology and the environment Berlin : Springer, 1970 78(2018), 6 vom: 03. Sept., Seite 3983-4001 (DE-627)271597011 (DE-600)1480689-7 1435-9537 nnns volume:78 year:2018 number:6 day:03 month:09 pages:3983-4001 https://dx.doi.org/10.1007/s10064-018-1367-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.58 ASE 56.00 ASE 56.20 ASE AR 78 2018 6 03 09 3983-4001 |
| spelling |
10.1007/s10064-018-1367-6 doi (DE-627)SPR008477957 (SPR)s10064-018-1367-6-e DE-627 ger DE-627 rakwb eng 550 600 ASE 38.58 bkl 56.00 bkl 56.20 bkl Hui, Xin verfasserin aut Monitoring and statistical analysis of mine subsidence at three metal mines in China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. Mine subsidence (dpeaa)DE-He213 Power law (dpeaa)DE-He213 Scale invariance (dpeaa)DE-He213 Geological hazard (dpeaa)DE-He213 Event prediction (dpeaa)DE-He213 Ma, Fengshan verfasserin aut Zhao, Haijun verfasserin aut Xu, Jiamo verfasserin aut Enthalten in Bulletin of engineering geology and the environment Berlin : Springer, 1970 78(2018), 6 vom: 03. Sept., Seite 3983-4001 (DE-627)271597011 (DE-600)1480689-7 1435-9537 nnns volume:78 year:2018 number:6 day:03 month:09 pages:3983-4001 https://dx.doi.org/10.1007/s10064-018-1367-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.58 ASE 56.00 ASE 56.20 ASE AR 78 2018 6 03 09 3983-4001 |
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10.1007/s10064-018-1367-6 doi (DE-627)SPR008477957 (SPR)s10064-018-1367-6-e DE-627 ger DE-627 rakwb eng 550 600 ASE 38.58 bkl 56.00 bkl 56.20 bkl Hui, Xin verfasserin aut Monitoring and statistical analysis of mine subsidence at three metal mines in China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. Mine subsidence (dpeaa)DE-He213 Power law (dpeaa)DE-He213 Scale invariance (dpeaa)DE-He213 Geological hazard (dpeaa)DE-He213 Event prediction (dpeaa)DE-He213 Ma, Fengshan verfasserin aut Zhao, Haijun verfasserin aut Xu, Jiamo verfasserin aut Enthalten in Bulletin of engineering geology and the environment Berlin : Springer, 1970 78(2018), 6 vom: 03. Sept., Seite 3983-4001 (DE-627)271597011 (DE-600)1480689-7 1435-9537 nnns volume:78 year:2018 number:6 day:03 month:09 pages:3983-4001 https://dx.doi.org/10.1007/s10064-018-1367-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.58 ASE 56.00 ASE 56.20 ASE AR 78 2018 6 03 09 3983-4001 |
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10.1007/s10064-018-1367-6 doi (DE-627)SPR008477957 (SPR)s10064-018-1367-6-e DE-627 ger DE-627 rakwb eng 550 600 ASE 38.58 bkl 56.00 bkl 56.20 bkl Hui, Xin verfasserin aut Monitoring and statistical analysis of mine subsidence at three metal mines in China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. Mine subsidence (dpeaa)DE-He213 Power law (dpeaa)DE-He213 Scale invariance (dpeaa)DE-He213 Geological hazard (dpeaa)DE-He213 Event prediction (dpeaa)DE-He213 Ma, Fengshan verfasserin aut Zhao, Haijun verfasserin aut Xu, Jiamo verfasserin aut Enthalten in Bulletin of engineering geology and the environment Berlin : Springer, 1970 78(2018), 6 vom: 03. Sept., Seite 3983-4001 (DE-627)271597011 (DE-600)1480689-7 1435-9537 nnns volume:78 year:2018 number:6 day:03 month:09 pages:3983-4001 https://dx.doi.org/10.1007/s10064-018-1367-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.58 ASE 56.00 ASE 56.20 ASE AR 78 2018 6 03 09 3983-4001 |
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10.1007/s10064-018-1367-6 doi (DE-627)SPR008477957 (SPR)s10064-018-1367-6-e DE-627 ger DE-627 rakwb eng 550 600 ASE 38.58 bkl 56.00 bkl 56.20 bkl Hui, Xin verfasserin aut Monitoring and statistical analysis of mine subsidence at three metal mines in China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. Mine subsidence (dpeaa)DE-He213 Power law (dpeaa)DE-He213 Scale invariance (dpeaa)DE-He213 Geological hazard (dpeaa)DE-He213 Event prediction (dpeaa)DE-He213 Ma, Fengshan verfasserin aut Zhao, Haijun verfasserin aut Xu, Jiamo verfasserin aut Enthalten in Bulletin of engineering geology and the environment Berlin : Springer, 1970 78(2018), 6 vom: 03. Sept., Seite 3983-4001 (DE-627)271597011 (DE-600)1480689-7 1435-9537 nnns volume:78 year:2018 number:6 day:03 month:09 pages:3983-4001 https://dx.doi.org/10.1007/s10064-018-1367-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.58 ASE 56.00 ASE 56.20 ASE AR 78 2018 6 03 09 3983-4001 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR008477957</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220110203423.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10064-018-1367-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR008477957</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10064-018-1367-6-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">550</subfield><subfield code="a">600</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">38.58</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">56.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">56.20</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hui, Xin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Monitoring and statistical analysis of mine subsidence at three metal mines in China</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. 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Hui, Xin |
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Hui, Xin ddc 550 bkl 38.58 bkl 56.00 bkl 56.20 misc Mine subsidence misc Power law misc Scale invariance misc Geological hazard misc Event prediction Monitoring and statistical analysis of mine subsidence at three metal mines in China |
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550 600 ASE 38.58 bkl 56.00 bkl 56.20 bkl Monitoring and statistical analysis of mine subsidence at three metal mines in China Mine subsidence (dpeaa)DE-He213 Power law (dpeaa)DE-He213 Scale invariance (dpeaa)DE-He213 Geological hazard (dpeaa)DE-He213 Event prediction (dpeaa)DE-He213 |
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ddc 550 bkl 38.58 bkl 56.00 bkl 56.20 misc Mine subsidence misc Power law misc Scale invariance misc Geological hazard misc Event prediction |
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monitoring and statistical analysis of mine subsidence at three metal mines in china |
| title_auth |
Monitoring and statistical analysis of mine subsidence at three metal mines in China |
| abstract |
Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. |
| abstractGer |
Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. |
| abstract_unstemmed |
Abstract Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency–size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency–size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency–size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency–size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction. |
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Monitoring and statistical analysis of mine subsidence at three metal mines in China |
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| score |
7.3974905 |