Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/86913 |
Resumo: | Groundwater is the main source to answer the irrigation supply in several arid and semi-arid areas. In the present work, groundwater quality for irrigation purposes in the arid region of Menzel Habib (Tunisia) for thirty-six groundwater samples is assessed considering the application of different conventional water quality indicators, particularly, electrical conductivity (EC), sodium absorption ratio (SAR), soluble sodium percentage (SSP), magnesium adsorption ratio (MAR), Kelly ratio (KR), and permeability index (PI). The results obtained indicate a variability for EC: 3.06 to 14.98 mS.cm-1; SAR: 4.08 to 19.30; SSP: 35.78 to 71.53%; MAR: 34.19 to 56.01; PI: 38.47 to 72.74; and KR: 0.56 to 2.47. These results suggest that groundwater from Menzel Habib aquifer system is classified between excellent to unsuitable according to the applied water quality indices. Furthermore, the groundwater samples are also plotted in the Richards diagram classification system, based on the relation between SAR and EC, suggesting that almost groundwater samples present a harmful quality. Moreover, fuzzy logic model has been proposed and created to assess groundwater quality for irrigation. The membership functions are constructed for six significant parameters such as EC, SAR, SSP, MAR, KR, and PI and the rules are, then, fired to get a simple Fuzzy Irrigation Water Quality Index (FIWQI). The obtained groundwater quality results suggest that 3% of the samples from Menzel Habib region are considered as "good" for irrigation, 3% are classified as "good to permissible", 33% with a "permissible" quality, 36% "permissible to unsuitable", while 25% of groundwater present an "unsuitable" quality. Thus, the use of fuzzy logic techniques has more reliable and robust results by overcoming the uncertainties in the decision-making attributed to the conventional methods by the creation of new classes (excellent to good, good to permissible, and permissible to unsuitable) in addition to the classes proposed by Richards diagram classification (excellent, good, permissible, and unsuitable) to assess the groundwater quality suitability for irrigation purposes. |
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Groundwater quality for irrigation in an arid region-application of fuzzy logic techniquesWater SupplyFuzzy LogicEnvironmental MonitoringWater QualitySodiumGroundwaterWater Pollutants, ChemicalMenzel HabibWater quality indicesAgricultural useTunisiaCiências Naturais::Ciências da Terra e do AmbienteScience & TechnologyÁgua potável e saneamentoGroundwater is the main source to answer the irrigation supply in several arid and semi-arid areas. In the present work, groundwater quality for irrigation purposes in the arid region of Menzel Habib (Tunisia) for thirty-six groundwater samples is assessed considering the application of different conventional water quality indicators, particularly, electrical conductivity (EC), sodium absorption ratio (SAR), soluble sodium percentage (SSP), magnesium adsorption ratio (MAR), Kelly ratio (KR), and permeability index (PI). The results obtained indicate a variability for EC: 3.06 to 14.98 mS.cm-1; SAR: 4.08 to 19.30; SSP: 35.78 to 71.53%; MAR: 34.19 to 56.01; PI: 38.47 to 72.74; and KR: 0.56 to 2.47. These results suggest that groundwater from Menzel Habib aquifer system is classified between excellent to unsuitable according to the applied water quality indices. Furthermore, the groundwater samples are also plotted in the Richards diagram classification system, based on the relation between SAR and EC, suggesting that almost groundwater samples present a harmful quality. Moreover, fuzzy logic model has been proposed and created to assess groundwater quality for irrigation. The membership functions are constructed for six significant parameters such as EC, SAR, SSP, MAR, KR, and PI and the rules are, then, fired to get a simple Fuzzy Irrigation Water Quality Index (FIWQI). The obtained groundwater quality results suggest that 3% of the samples from Menzel Habib region are considered as "good" for irrigation, 3% are classified as "good to permissible", 33% with a "permissible" quality, 36% "permissible to unsuitable", while 25% of groundwater present an "unsuitable" quality. Thus, the use of fuzzy logic techniques has more reliable and robust results by overcoming the uncertainties in the decision-making attributed to the conventional methods by the creation of new classes (excellent to good, good to permissible, and permissible to unsuitable) in addition to the classes proposed by Richards diagram classification (excellent, good, permissible, and unsuitable) to assess the groundwater quality suitability for irrigation purposes.The authors are grateful to the staff of Applied Hydrosciences Laboratory for their effort and support during laboratory analysis. This research was developed under the FCT-Fundacao para a Ciencia e a Tecnologia, I.P. program, through the project's reference UIDB/04683/2020 and UIDP/04683/2020.SpringerUniversidade do MinhoDhaoui, OussamaAgoubi, BelgacemAntunes, Isabel Margarida Horta RibeiroTlig, LotfiKharroubi, Adel20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/86913engDhaoui, O., Agoubi, B., Antunes, I. M., Tlig, L., & Kharroubi, A. (2022, November 23). Groundwater quality for irrigation in an arid region—application of fuzzy logic techniques. Environmental Science and Pollution Research. Springer Science and Business Media LLC. http://doi.org/10.1007/s11356-022-24334-50944-13441614-749910.1007/s11356-022-24334-53642278517https://link.springer.com/article/10.1007/s11356-022-24334-5info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-16T01:19:57Zoai:repositorium.sdum.uminho.pt:1822/86913Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:39:02.959104Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques |
title |
Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques |
spellingShingle |
Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques Dhaoui, Oussama Water Supply Fuzzy Logic Environmental Monitoring Water Quality Sodium Groundwater Water Pollutants, Chemical Menzel Habib Water quality indices Agricultural use Tunisia Ciências Naturais::Ciências da Terra e do Ambiente Science & Technology Água potável e saneamento |
title_short |
Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques |
title_full |
Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques |
title_fullStr |
Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques |
title_full_unstemmed |
Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques |
title_sort |
Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques |
author |
Dhaoui, Oussama |
author_facet |
Dhaoui, Oussama Agoubi, Belgacem Antunes, Isabel Margarida Horta Ribeiro Tlig, Lotfi Kharroubi, Adel |
author_role |
author |
author2 |
Agoubi, Belgacem Antunes, Isabel Margarida Horta Ribeiro Tlig, Lotfi Kharroubi, Adel |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Dhaoui, Oussama Agoubi, Belgacem Antunes, Isabel Margarida Horta Ribeiro Tlig, Lotfi Kharroubi, Adel |
dc.subject.por.fl_str_mv |
Water Supply Fuzzy Logic Environmental Monitoring Water Quality Sodium Groundwater Water Pollutants, Chemical Menzel Habib Water quality indices Agricultural use Tunisia Ciências Naturais::Ciências da Terra e do Ambiente Science & Technology Água potável e saneamento |
topic |
Water Supply Fuzzy Logic Environmental Monitoring Water Quality Sodium Groundwater Water Pollutants, Chemical Menzel Habib Water quality indices Agricultural use Tunisia Ciências Naturais::Ciências da Terra e do Ambiente Science & Technology Água potável e saneamento |
description |
Groundwater is the main source to answer the irrigation supply in several arid and semi-arid areas. In the present work, groundwater quality for irrigation purposes in the arid region of Menzel Habib (Tunisia) for thirty-six groundwater samples is assessed considering the application of different conventional water quality indicators, particularly, electrical conductivity (EC), sodium absorption ratio (SAR), soluble sodium percentage (SSP), magnesium adsorption ratio (MAR), Kelly ratio (KR), and permeability index (PI). The results obtained indicate a variability for EC: 3.06 to 14.98 mS.cm-1; SAR: 4.08 to 19.30; SSP: 35.78 to 71.53%; MAR: 34.19 to 56.01; PI: 38.47 to 72.74; and KR: 0.56 to 2.47. These results suggest that groundwater from Menzel Habib aquifer system is classified between excellent to unsuitable according to the applied water quality indices. Furthermore, the groundwater samples are also plotted in the Richards diagram classification system, based on the relation between SAR and EC, suggesting that almost groundwater samples present a harmful quality. Moreover, fuzzy logic model has been proposed and created to assess groundwater quality for irrigation. The membership functions are constructed for six significant parameters such as EC, SAR, SSP, MAR, KR, and PI and the rules are, then, fired to get a simple Fuzzy Irrigation Water Quality Index (FIWQI). The obtained groundwater quality results suggest that 3% of the samples from Menzel Habib region are considered as "good" for irrigation, 3% are classified as "good to permissible", 33% with a "permissible" quality, 36% "permissible to unsuitable", while 25% of groundwater present an "unsuitable" quality. Thus, the use of fuzzy logic techniques has more reliable and robust results by overcoming the uncertainties in the decision-making attributed to the conventional methods by the creation of new classes (excellent to good, good to permissible, and permissible to unsuitable) in addition to the classes proposed by Richards diagram classification (excellent, good, permissible, and unsuitable) to assess the groundwater quality suitability for irrigation purposes. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/86913 |
url |
https://hdl.handle.net/1822/86913 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Dhaoui, O., Agoubi, B., Antunes, I. M., Tlig, L., & Kharroubi, A. (2022, November 23). Groundwater quality for irrigation in an arid region—application of fuzzy logic techniques. Environmental Science and Pollution Research. Springer Science and Business Media LLC. http://doi.org/10.1007/s11356-022-24334-5 0944-1344 1614-7499 10.1007/s11356-022-24334-5 36422785 17 https://link.springer.com/article/10.1007/s11356-022-24334-5 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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