Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method
Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to buil...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yang, Haitao [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental science and pollution research - Berlin : Springer, 1994, 29(2022), 44 vom: 02. Mai, Seite 66160-66176 |
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| Übergeordnetes Werk: |
volume:29 ; year:2022 ; number:44 ; day:02 ; month:05 ; pages:66160-66176 |
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| DOI / URN: |
10.1007/s11356-022-19871-y |
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SPR048164747 |
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| 245 | 1 | 0 | |a Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method |
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| 520 | |a Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. | ||
| 650 | 4 | |a Seawater intrusion |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fuzzy analytic hierarchy process |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Exponential smoothing |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Water quality prediction |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Jia, Chao |0 (orcid)0000-0002-2448-894X |4 aut | |
| 700 | 1 | |a Li, Xin |4 aut | |
| 700 | 1 | |a Yang, Fan |4 aut | |
| 700 | 1 | |a Wang, Cong |4 aut | |
| 700 | 1 | |a Yang, Xiao |4 aut | |
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10.1007/s11356-022-19871-y doi (DE-627)SPR048164747 (SPR)s11356-022-19871-y-e DE-627 ger DE-627 rakwb eng Yang, Haitao verfasserin aut Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. Seawater intrusion (dpeaa)DE-He213 Fuzzy analytic hierarchy process (dpeaa)DE-He213 Exponential smoothing (dpeaa)DE-He213 Water quality prediction (dpeaa)DE-He213 Jia, Chao (orcid)0000-0002-2448-894X aut Li, Xin aut Yang, Fan aut Wang, Cong aut Yang, Xiao aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 29(2022), 44 vom: 02. Mai, Seite 66160-66176 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:29 year:2022 number:44 day:02 month:05 pages:66160-66176 https://dx.doi.org/10.1007/s11356-022-19871-y 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_381 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_2360 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 29 2022 44 02 05 66160-66176 |
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10.1007/s11356-022-19871-y doi (DE-627)SPR048164747 (SPR)s11356-022-19871-y-e DE-627 ger DE-627 rakwb eng Yang, Haitao verfasserin aut Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. Seawater intrusion (dpeaa)DE-He213 Fuzzy analytic hierarchy process (dpeaa)DE-He213 Exponential smoothing (dpeaa)DE-He213 Water quality prediction (dpeaa)DE-He213 Jia, Chao (orcid)0000-0002-2448-894X aut Li, Xin aut Yang, Fan aut Wang, Cong aut Yang, Xiao aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 29(2022), 44 vom: 02. Mai, Seite 66160-66176 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:29 year:2022 number:44 day:02 month:05 pages:66160-66176 https://dx.doi.org/10.1007/s11356-022-19871-y 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_381 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_2360 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 29 2022 44 02 05 66160-66176 |
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10.1007/s11356-022-19871-y doi (DE-627)SPR048164747 (SPR)s11356-022-19871-y-e DE-627 ger DE-627 rakwb eng Yang, Haitao verfasserin aut Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. Seawater intrusion (dpeaa)DE-He213 Fuzzy analytic hierarchy process (dpeaa)DE-He213 Exponential smoothing (dpeaa)DE-He213 Water quality prediction (dpeaa)DE-He213 Jia, Chao (orcid)0000-0002-2448-894X aut Li, Xin aut Yang, Fan aut Wang, Cong aut Yang, Xiao aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 29(2022), 44 vom: 02. Mai, Seite 66160-66176 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:29 year:2022 number:44 day:02 month:05 pages:66160-66176 https://dx.doi.org/10.1007/s11356-022-19871-y 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_381 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_2360 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 29 2022 44 02 05 66160-66176 |
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10.1007/s11356-022-19871-y doi (DE-627)SPR048164747 (SPR)s11356-022-19871-y-e DE-627 ger DE-627 rakwb eng Yang, Haitao verfasserin aut Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. Seawater intrusion (dpeaa)DE-He213 Fuzzy analytic hierarchy process (dpeaa)DE-He213 Exponential smoothing (dpeaa)DE-He213 Water quality prediction (dpeaa)DE-He213 Jia, Chao (orcid)0000-0002-2448-894X aut Li, Xin aut Yang, Fan aut Wang, Cong aut Yang, Xiao aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 29(2022), 44 vom: 02. Mai, Seite 66160-66176 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:29 year:2022 number:44 day:02 month:05 pages:66160-66176 https://dx.doi.org/10.1007/s11356-022-19871-y 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_381 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_2360 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 29 2022 44 02 05 66160-66176 |
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10.1007/s11356-022-19871-y doi (DE-627)SPR048164747 (SPR)s11356-022-19871-y-e DE-627 ger DE-627 rakwb eng Yang, Haitao verfasserin aut Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. Seawater intrusion (dpeaa)DE-He213 Fuzzy analytic hierarchy process (dpeaa)DE-He213 Exponential smoothing (dpeaa)DE-He213 Water quality prediction (dpeaa)DE-He213 Jia, Chao (orcid)0000-0002-2448-894X aut Li, Xin aut Yang, Fan aut Wang, Cong aut Yang, Xiao aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 29(2022), 44 vom: 02. Mai, Seite 66160-66176 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:29 year:2022 number:44 day:02 month:05 pages:66160-66176 https://dx.doi.org/10.1007/s11356-022-19871-y 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_381 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_2360 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 29 2022 44 02 05 66160-66176 |
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This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Seawater intrusion</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fuzzy analytic hierarchy process</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Exponential smoothing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Water quality prediction</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jia, Chao</subfield><subfield code="0">(orcid)0000-0002-2448-894X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Xin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yang, Fan</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Cong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yang, Xiao</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Environmental science and pollution research</subfield><subfield code="d">Berlin : Springer, 1994</subfield><subfield code="g">29(2022), 44 vom: 02. 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Yang, Haitao |
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Yang, Haitao misc Seawater intrusion misc Fuzzy analytic hierarchy process misc Exponential smoothing misc Water quality prediction Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method |
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Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method Seawater intrusion (dpeaa)DE-He213 Fuzzy analytic hierarchy process (dpeaa)DE-He213 Exponential smoothing (dpeaa)DE-He213 Water quality prediction (dpeaa)DE-He213 |
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Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method |
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Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method |
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evaluation of seawater intrusion and water quality prediction in dagu river of north china based on fuzzy analytic hierarchy process exponential smoothing method |
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Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method |
| abstract |
Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
| abstractGer |
Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
| abstract_unstemmed |
Abstract It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as $ Cl^{−} $, $ SO_{4} $2−, $ NO_{3} $−, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars’ research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process. The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method |
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Jia, Chao Li, Xin Yang, Fan Wang, Cong Yang, Xiao |
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| score |
7.3975677 |