A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan
Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determi...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Aslam, Bilal [verfasserIn] Ismail, Sharjeel [verfasserIn] Ali, Ibtisam [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Modeling earth systems and environment - Berlin : Springer, 2015, 6(2020), 2 vom: 11. März, Seite 995-1005 |
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| Übergeordnetes Werk: |
volume:6 ; year:2020 ; number:2 ; day:11 ; month:03 ; pages:995-1005 |
| Links: |
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| DOI / URN: |
10.1007/s40808-020-00735-8 |
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| Katalog-ID: |
SPR039392880 |
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| 245 | 1 | 2 | |a A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan |
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| 520 | |a Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. | ||
| 650 | 4 | |a Geographic information system (GIS) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Vulnerability |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a DRASTIC |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Ismail, Sharjeel |e verfasserin |4 aut | |
| 700 | 1 | |a Ali, Ibtisam |e verfasserin |4 aut | |
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10.1007/s40808-020-00735-8 doi (DE-627)SPR039392880 (SPR)s40808-020-00735-8-e DE-627 ger DE-627 rakwb eng 333.7 ASE 333.7 ASE Aslam, Bilal verfasserin aut A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. Geographic information system (GIS) (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 DRASTIC (dpeaa)DE-He213 Ismail, Sharjeel verfasserin aut Ali, Ibtisam verfasserin aut Enthalten in Modeling earth systems and environment Berlin : Springer, 2015 6(2020), 2 vom: 11. März, Seite 995-1005 (DE-627)825736587 (DE-600)2821317-8 2363-6211 nnns volume:6 year:2020 number:2 day:11 month:03 pages:995-1005 https://dx.doi.org/10.1007/s40808-020-00735-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 2 11 03 995-1005 |
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10.1007/s40808-020-00735-8 doi (DE-627)SPR039392880 (SPR)s40808-020-00735-8-e DE-627 ger DE-627 rakwb eng 333.7 ASE 333.7 ASE Aslam, Bilal verfasserin aut A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. Geographic information system (GIS) (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 DRASTIC (dpeaa)DE-He213 Ismail, Sharjeel verfasserin aut Ali, Ibtisam verfasserin aut Enthalten in Modeling earth systems and environment Berlin : Springer, 2015 6(2020), 2 vom: 11. März, Seite 995-1005 (DE-627)825736587 (DE-600)2821317-8 2363-6211 nnns volume:6 year:2020 number:2 day:11 month:03 pages:995-1005 https://dx.doi.org/10.1007/s40808-020-00735-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 2 11 03 995-1005 |
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10.1007/s40808-020-00735-8 doi (DE-627)SPR039392880 (SPR)s40808-020-00735-8-e DE-627 ger DE-627 rakwb eng 333.7 ASE 333.7 ASE Aslam, Bilal verfasserin aut A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. Geographic information system (GIS) (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 DRASTIC (dpeaa)DE-He213 Ismail, Sharjeel verfasserin aut Ali, Ibtisam verfasserin aut Enthalten in Modeling earth systems and environment Berlin : Springer, 2015 6(2020), 2 vom: 11. März, Seite 995-1005 (DE-627)825736587 (DE-600)2821317-8 2363-6211 nnns volume:6 year:2020 number:2 day:11 month:03 pages:995-1005 https://dx.doi.org/10.1007/s40808-020-00735-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 2 11 03 995-1005 |
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10.1007/s40808-020-00735-8 doi (DE-627)SPR039392880 (SPR)s40808-020-00735-8-e DE-627 ger DE-627 rakwb eng 333.7 ASE 333.7 ASE Aslam, Bilal verfasserin aut A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. Geographic information system (GIS) (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 DRASTIC (dpeaa)DE-He213 Ismail, Sharjeel verfasserin aut Ali, Ibtisam verfasserin aut Enthalten in Modeling earth systems and environment Berlin : Springer, 2015 6(2020), 2 vom: 11. März, Seite 995-1005 (DE-627)825736587 (DE-600)2821317-8 2363-6211 nnns volume:6 year:2020 number:2 day:11 month:03 pages:995-1005 https://dx.doi.org/10.1007/s40808-020-00735-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 2 11 03 995-1005 |
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10.1007/s40808-020-00735-8 doi (DE-627)SPR039392880 (SPR)s40808-020-00735-8-e DE-627 ger DE-627 rakwb eng 333.7 ASE 333.7 ASE Aslam, Bilal verfasserin aut A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. Geographic information system (GIS) (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 DRASTIC (dpeaa)DE-He213 Ismail, Sharjeel verfasserin aut Ali, Ibtisam verfasserin aut Enthalten in Modeling earth systems and environment Berlin : Springer, 2015 6(2020), 2 vom: 11. März, Seite 995-1005 (DE-627)825736587 (DE-600)2821317-8 2363-6211 nnns volume:6 year:2020 number:2 day:11 month:03 pages:995-1005 https://dx.doi.org/10.1007/s40808-020-00735-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2020 2 11 03 995-1005 |
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Aslam, Bilal |
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Aslam, Bilal ddc 333.7 misc Geographic information system (GIS) misc Vulnerability misc DRASTIC A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan |
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333.7 ASE A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan Geographic information system (GIS) (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 DRASTIC (dpeaa)DE-He213 |
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ddc 333.7 misc Geographic information system (GIS) misc Vulnerability misc DRASTIC |
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ddc 333.7 misc Geographic information system (GIS) misc Vulnerability misc DRASTIC |
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A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan |
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A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan |
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gis-based drastic model for assessing aquifer susceptibility of safdarabad tehsil, sheikhupura district, punjab province, pakistan |
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A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan |
| abstract |
Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. |
| abstractGer |
Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. |
| abstract_unstemmed |
Abstract Assessment of the vulnerability of groundwater can be defined as the area’s rate of incorporation capacity to the impurity from surface overlying the aquifer. This study is of profound importance with regard to natural resource management and land use planning. This study deals with determining shallow aquifer vulnerability by using a DRASTIC model based on GIS in Tehsil Safdarabad of District Sheikhupura in Punjab. Within a local watershed, the quality of groundwater deteriorates as a result of various physical and environmental activities. This research, therefore, uses a combination of GIS and DRASTIC to estimate groundwater assessment. Seven hydrogeological data layers are being utilized as input to the model. The layers comprise Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity. DRASTIC index results would assist in determining pollution vulnerable zones. Research indicates about 11.32% of the research area is highly exposed, 34.4% is at moderate risk and 54.2% is at low risk exposure. Northern, northwestern and middle sectors of the area under consideration exhibited low aquifer susceptibility, whereas some areas in the southern and northeastern parts were highly vulnerable. |
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A GIS-based DRASTIC model for assessing aquifer susceptibility of Safdarabad Tehsil, Sheikhupura District, Punjab Province, Pakistan |
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https://dx.doi.org/10.1007/s40808-020-00735-8 |
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Ismail, Sharjeel Ali, Ibtisam |
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| doi_str |
10.1007/s40808-020-00735-8 |
| up_date |
2024-07-03T23:42:35.359Z |
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