Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques

Detalhes bibliográficos
Autor(a) principal: Dhaoui, Oussama
Data de Publicação: 2022
Outros Autores: Agoubi, Belgacem, Antunes, Isabel Margarida Horta Ribeiro, Tlig, Lotfi, Kharroubi, Adel
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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spelling 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
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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