PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Fuzzy system modelling to assess water quality for irrigation purposes

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study attempts to find a fuzzy logic system for assessing the quality of water in water treatment plants (WTPs) providing water for irrigation purposes in the Basrah Governorate (South of Iraq). Each month, samples are taken in each of six major WTPs to measure electrical conductivity (EC), and the content of sodium, magnesium and calcium. The calculated value which is the sodium adsorption ratio (SAR) is plotted with EC on the Richard diagram. SAR and EC values are combined together in a fuzzy inference system (FIS) to find out a quality number called the fuzzy irrigation water quality index number (FIWQI) which ranges from zero to one. The higher the value of the index, the better water quality. The Richard diagram, which helps to classify irrigation water, is used to adjust FIS components. Results show that the FIWQI for all WTPs changes depending on location and season. It ranges between 0.114–0.170, 0.120–0.190, 0.114–0.170, 0.114–0.202, 0.118–0.500 and 0.46–0.500 for Al-Bradhaia 1, Al-Jubaila 1, Shatt Al-Arab, Garmmah 1, Al-Rebat, and Old Shauaibah WTPs, respectively. The results indicate that WTPs effluent drawn from the Shatt Al-Arab River has poor water quality for irrigation purposes, except for an Old Shauaibah which receives water from another source called a sweet water canal. FIS results are compared with values obtained from the Richard diagram and 96% degree of compatibility between the two methods is attained. This indicates that FIS is an acceptable method for water quality classification.
Wydawca
Rocznik
Tom
Strony
98--107
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
  • University of Basrah, Engineering College, Civil Engineering Department, Basrah 61004, Iraq
  • University of Basrah, Engineering College, Civil Engineering Department, Basrah 61004, Iraq
  • University of Basrah, Engineering College, Civil Engineering Department, Basrah 61004, Iraq
Bibliografia
  • ABDULLAH P., WASEEM S., BAI V R., IJAZ-UL-MOHSIN 2008. Development of new water quality model using fuzzy logic system for Malaysia. Open Environmental Sciences. Vol. 2. Iss. 1 p. 101–106.
  • AHMED A.N., DAWOOD A.S. 2016. Neural network modelling of TDS concentrations in Shatt Al-Arab River water. Engineering and Technology Journal. Vol. 34. Iss. 2. Part (A) Engineering p. 334– 345.
  • AL-MAMOORI S.K., AL-MALIKI L.A. 2016. Evaluation of suitability of drainage water of Al-Hussainia sector (KUT Iraq) to irrigate cotton crop. Kufa Journal of Engineering. Vol. 7. Iss. 1 p. 67–78.
  • ALMUKTAR S., HAMDAN A.N.A., SCHOLZ M. 2020. Assessment of the effluents of Basra City main water treatment plants for drinking and irrigation purposes. Water. Vol. 12. Iss. 12, 3334. DOI 10.3390/w12123334.
  • AL SAAD Z.A., HAMDAN A.N. 2020. Evaluation of water treatment plants quality in Basrah Province, by factor and cluster analysis. Journal of Water and Land Development. No. 46 (VII–IX) p. 10–19. DOI 10.24425/jwld.2020.134097.
  • AYERS R.S., WESTCOT D.W. 1985. Water quality for agriculture. Rome. Food and Agriculture Organization of the United Nations. FAO Irrigation and Drainage Paper 29. Rev. 1. ISBN 92-5-102263-1 pp. 97.
  • CLESCERI L.S., GREENBERG A.E., TRUSSELL R.R. (eds.) 1989. Standard methods for the examination of water and wastewater. 17th ed. American Public Health Association. ISBN 087553161X pp. 1624.
  • DAWOOD A.S., HAMDAN A., KHUDIER A.S. 2018. Assessment of water quality index with analysis of physico-clemical parameters. Case study: The Shatt Al-Arab River, Iraq. In: Progress in river engineering and hydraulic structures. Vol. 2. CreateSpace Independent Publishing Platform p. 93–106.
  • HAMDAN A.N. 2016a. Simulation of salinity intrusion from Arabian Gulf to Shatt Al-Arab River. Basrah Journal for Engineering Science. Vol. 16. Iss. 1 p. 28–32.
  • HAMDAN A.N.A. 2016b. The assessment of the quality of water treatment plants effluent of Basrah City for irrigation. Wasit Journal of Engineering Sciences. Vol. 4. Iss. 2 p. 36–52.
  • HAMDAN A.N.A., ABBAS A.A., NAJM A.T. 2019. Flood hazard analysis of proposed regulator on Shatt Al-Arab River. Hydrology. Vol. 6. Iss. 3, 80. DOI 10.3390/hydrology6030080.
  • HAMDAN A.N.A., AL-MAHDI A.A.J., MAHMOOD A.B. 2020. Modeling the effect of sea water intrusion into Shatt Al-Arab River (Iraq). Journal of University of Babylon for Engineering Sciences. Vol. 28. Iss. 2 p. 210–224.
  • HAMDAN A., DAWOOD A., NAEEM D. 2018. Assessment study of water quality index (WQI) for Shatt Al-arab River and its branches, Iraq. In: MATEC Web of Conferences. The 3rd International Conference on Buildings, Construction and Environmental Engineering, BCEE3-2017. Vol. 162, 05005. EDP Sciences. DOI 10.1051/matecconf/201816205005.
  • ICS: 13.060.20, IQS: 417. Iraqi criteria and standards for drinking water, chemical limits. 2nd update 2009 for chemical and physical limits p. 1–6.
  • JEON C., RAZA M., LEE J.Y., KIM H., KIM C.S., KIM B., LEE S.W. 2020. Countrywide groundwater quality trend and suitability for use in key sectors of Korea. Water. Vol. 12. Iss. 4, 1193. DOI 10.3390/ w12041193.
  • LAZE P., RIZANI S., IBRALIU A. 2016. Assessment of irrigation water quality of Dukagjin basin in Kosovo. Journal of International Scientific Publications. Vol. 4 p. 544–551.
  • MIRABBASI R., MAZLOUMZADEH S., RAHNAMA M. 2008. Evaluation of irrigation water quality using fuzzy logic. Research Journal of Environmental Sciences. Vol. 2. Iss. 5 p. 340–352. DOI 10.3923/ RJES.2008.340.352.
  • NISHANTHINY S.C., THUSHYANTHY M., BARATHITHASAN T., SARAVANAN S. 2010. Irrigation water quality based on hydro chemical analysis, Jaffna, Sri Lanka. American-Eurasian Journal of Agricultural and Environmental Science. Vol. 7. Iss. 1 p. 100–102.
  • OSTOVARI Y., BEIGI-HARCHEGANI H., ASGARI K. 2015. A fuzzy logic approach for assessment and mapping of groundwater irrigation quality: A case study of Marvdasht aquifer, Iran. Archives of Agronomy and Soil Science. Vol. 61. Iss. 5 p. 711–723. DOI 10.1080/03650340.2014.946020.
  • PRIYA K. 2013. A fuzzy logic approach for irrigation water quality assessment: A case study of Karunya Watershed, India. Journal of Hydrogeology and Hydrologic Engineering. Vol. 2. Iss. 1 p. 2. DOI 10.4172/2325-9647.1000104.
  • RICHARDS L.A. (ed.) 1954. Diagnosis and improvement of saline and alkali soils. Agriculture Handbook. No. 60. Washington, DC. USSLS pp. 159.
  • VADIATI M., NALLEY D., ADAMOWSKI J., NAKHAEI M., ASGHARI-MOGHADDAM A. 2019. A comparative study of fuzzy logic-based models for groundwater quality evaluation based on irrigation indices. Journal of Water and Land Development. No. 43 p. 158–170. DOI 10.2478/jwld-2019-007.
  • YASEEN D.A., ABU-ALHAIL S., KHANFAR H.A. 2019. Assessment of water quality of Garmat Ali River for irrigation purposes, E3S Web of Conferences. EDP Sciences, 03054. 4th International Conference on Advances in Energy and Environment Research (ICAEER 2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-47fb371e-a23a-4f4d-a757-e1e9238d615b
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.