BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh
Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEsho...
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| Autor*in: |
Islam, Md. Muhyminul [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Environmental monitoring and assessment - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981, 195(2023), 2 vom: 09. Jan. |
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| Übergeordnetes Werk: |
volume:195 ; year:2023 ; number:2 ; day:09 ; month:01 |
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| DOI / URN: |
10.1007/s10661-022-10854-7 |
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SPR049021109 |
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| 520 | |a Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. | ||
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10.1007/s10661-022-10854-7 doi (DE-627)SPR049021109 (SPR)s10661-022-10854-7-e DE-627 ger DE-627 rakwb eng Islam, Md. Muhyminul verfasserin (orcid)0000-0002-1591-1398 aut BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. Natural background level (dpeaa)DE-He213 Threshold value (dpeaa)DE-He213 Groundwater (dpeaa)DE-He213 Chemical status assessment (dpeaa)DE-He213 Sustainable management (dpeaa)DE-He213 Bengal Basin (dpeaa)DE-He213 Marandi, Andres aut Zahid, Anwar aut Rabeya, Israth aut Fatema, Suraiya aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 2 vom: 09. Jan. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:2 day:09 month:01 https://dx.doi.org/10.1007/s10661-022-10854-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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 195 2023 2 09 01 |
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10.1007/s10661-022-10854-7 doi (DE-627)SPR049021109 (SPR)s10661-022-10854-7-e DE-627 ger DE-627 rakwb eng Islam, Md. Muhyminul verfasserin (orcid)0000-0002-1591-1398 aut BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. Natural background level (dpeaa)DE-He213 Threshold value (dpeaa)DE-He213 Groundwater (dpeaa)DE-He213 Chemical status assessment (dpeaa)DE-He213 Sustainable management (dpeaa)DE-He213 Bengal Basin (dpeaa)DE-He213 Marandi, Andres aut Zahid, Anwar aut Rabeya, Israth aut Fatema, Suraiya aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 2 vom: 09. Jan. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:2 day:09 month:01 https://dx.doi.org/10.1007/s10661-022-10854-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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 195 2023 2 09 01 |
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10.1007/s10661-022-10854-7 doi (DE-627)SPR049021109 (SPR)s10661-022-10854-7-e DE-627 ger DE-627 rakwb eng Islam, Md. Muhyminul verfasserin (orcid)0000-0002-1591-1398 aut BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. Natural background level (dpeaa)DE-He213 Threshold value (dpeaa)DE-He213 Groundwater (dpeaa)DE-He213 Chemical status assessment (dpeaa)DE-He213 Sustainable management (dpeaa)DE-He213 Bengal Basin (dpeaa)DE-He213 Marandi, Andres aut Zahid, Anwar aut Rabeya, Israth aut Fatema, Suraiya aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 2 vom: 09. Jan. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:2 day:09 month:01 https://dx.doi.org/10.1007/s10661-022-10854-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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 195 2023 2 09 01 |
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10.1007/s10661-022-10854-7 doi (DE-627)SPR049021109 (SPR)s10661-022-10854-7-e DE-627 ger DE-627 rakwb eng Islam, Md. Muhyminul verfasserin (orcid)0000-0002-1591-1398 aut BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. Natural background level (dpeaa)DE-He213 Threshold value (dpeaa)DE-He213 Groundwater (dpeaa)DE-He213 Chemical status assessment (dpeaa)DE-He213 Sustainable management (dpeaa)DE-He213 Bengal Basin (dpeaa)DE-He213 Marandi, Andres aut Zahid, Anwar aut Rabeya, Israth aut Fatema, Suraiya aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 2 vom: 09. Jan. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:2 day:09 month:01 https://dx.doi.org/10.1007/s10661-022-10854-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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 195 2023 2 09 01 |
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10.1007/s10661-022-10854-7 doi (DE-627)SPR049021109 (SPR)s10661-022-10854-7-e DE-627 ger DE-627 rakwb eng Islam, Md. Muhyminul verfasserin (orcid)0000-0002-1591-1398 aut BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. Natural background level (dpeaa)DE-He213 Threshold value (dpeaa)DE-He213 Groundwater (dpeaa)DE-He213 Chemical status assessment (dpeaa)DE-He213 Sustainable management (dpeaa)DE-He213 Bengal Basin (dpeaa)DE-He213 Marandi, Andres aut Zahid, Anwar aut Rabeya, Israth aut Fatema, Suraiya aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 2 vom: 09. Jan. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:2 day:09 month:01 https://dx.doi.org/10.1007/s10661-022-10854-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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 195 2023 2 09 01 |
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Muhyminul</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-1591-1398</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</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="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Natural background level</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Threshold value</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Groundwater</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Chemical status assessment</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Sustainable management</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bengal Basin</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Marandi, Andres</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zahid, Anwar</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rabeya, Israth</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Fatema, Suraiya</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Environmental monitoring and assessment</subfield><subfield code="d">Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981</subfield><subfield code="g">195(2023), 2 vom: 09. 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Islam, Md. Muhyminul |
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Islam, Md. Muhyminul misc Natural background level misc Threshold value misc Groundwater misc Chemical status assessment misc Sustainable management misc Bengal Basin BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh |
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BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh Natural background level (dpeaa)DE-He213 Threshold value (dpeaa)DE-He213 Groundwater (dpeaa)DE-He213 Chemical status assessment (dpeaa)DE-He213 Sustainable management (dpeaa)DE-He213 Bengal Basin (dpeaa)DE-He213 |
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misc Natural background level misc Threshold value misc Groundwater misc Chemical status assessment misc Sustainable management misc Bengal Basin |
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BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh |
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BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh |
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Islam, Md. Muhyminul |
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Islam, Md. Muhyminul Marandi, Andres Zahid, Anwar Rabeya, Israth Fatema, Suraiya |
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bridge methodology–based quality standards to assess aquifer chemical status in the southwest bengal basin, bangladesh |
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BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh |
| abstract |
Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, $ Ca^{2+} $, $ Mg^{2+} $, $ Na^{+} $, $ K^{+} $, $ Cl^{−} $, $ NO_{3} $−, $ SO_{4} $2−, $ PO_{4} $3−, $ Mn^{2+} $, and $ Fe^{2+} $). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the “poor” chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited “good” chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| title_short |
BRIDGE methodology–based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh |
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https://dx.doi.org/10.1007/s10661-022-10854-7 |
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Marandi, Andres Zahid, Anwar Rabeya, Israth Fatema, Suraiya |
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Marandi, Andres Zahid, Anwar Rabeya, Israth Fatema, Suraiya |
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10.1007/s10661-022-10854-7 |
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2024-07-03T22:52:00.879Z |
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|
| score |
7.40018 |