Skip to main navigation menu Skip to main content Skip to site footer
Plant Science Today (PST)

Review Articles

Vol. 12 No. sp4 (2025): Recent Advances in Agriculture by Young Minds - III

Water quality assessment a review in the era of smart technologies: Methods, indices, statistical and geospatial applications

DOI
https://doi.org/10.14719/pst.9247
Submitted
2 May 2025
Published
17-11-2025

Abstract

Water quality assessment is crucial for ensuring sustainable water resources management in the face of increasing pollution and climate change. This review examines how methods for evaluating water quality have changed over time, moving from traditional field-based methods to cutting-edge technology like artificial intelligence, remote sensing, and IoT (internet of things)- enabled devices. The evaluation of important physicochemical, bacteriological, and heavy metal factors that affect the safety and usability of water is emphasized. Both surface and groundwater quality are examined in relation to the use of tools like the water quality index (WQI), geographic information systems (GIS), multivariate statistical analysis (MSA), and regression-based machine learning models, such as artificial neural networks (ANN) and Hammerstein-Wiener (HW) models. Strong connections between geospatial analysis, water quality, pollution risk assessment, and statistical analysis are revealed by bibliometric analysis, which also identifies research hotspots and interdisciplinary trends in water quality studies. Through the integration of contemporary data analytics and geographical tools, this review advances the creation of sustainable and comprehensive water resource management.

References

  1. 1. Huchhe MR, Bandela N. Study of water quality parameter assessment using GIS and remote sensing in DR. BAM University, Aurangabad, MS. Int J Latest Technol Engin Manag Appl Sci. 2016;5(6):46–50.
  2. 2. Kc A, Chalise A, Parajuli D, Dhital N, Shrestha S, Kandel T. Surface water quality assessment using remote sensing, GIS and artificial intelligence. Technical J. 2019;1(1):113–22.
  3. 3. Singh P, Tiwari AK, Singh PK. Hydro chemical characteristic and quality assessment of groundwater of Ranchi township area, Jharkhand, India. Curr World Environ. 2014;9(3):804.
  4. 4. Chandra S, Singh PK, Tiwari AK, Panigrahy BP, Kumar A. Evaluation of hydrogeological factors and their relationship with seasonal water table fluctuation in Dhanbad district, Jharkhand, India. ISH J Hydraul Engin. 2015;21(2):193–206.
  5. 5. Tiwari AK, Singh PK, Singh AK, De Maio M. Estimation of heavy metal contamination in groundwater and development of a heavy metal pollution index by using GIS technique. Bulletin of Environmental Contamination and Toxicology. 2016;96:508–15.
  6. 6. Sanad H, Moussadek R, Dakak H, Zouahri A, Oueld Lhaj M, Mouhir L. Ecological and health risk assessment of heavy metals in groundwater within an agricultural ecosystem using GIS and multivariate statistical analysis (MSA): a case study of the Mnasra region, Gharb Plain, Morocco. Water. 2024;16(17):2417.
  7. 7. Japitana MV, Burce MEC. A satellite-based remote sensing technique for surface water quality estimation. Engineering, Technology & Applied Science Research. 2019;9(2):3965–70.
  8. 8. Al-Dahhan NAA, Al-Atwi AKH, Al-Zubaidi MGM. Water quality index for surface water assessment by using remote sensing and GIS techniques, Al-Najaf, Al-Manathera district, Iraq. Journal of Physics: Conference Series; IOP Publishing; 2019.
  9. 9. Badar MS, Ali S, Daniyal, Akram MW, Faheem K, Khan SU, et al. GIS-based assessment of groundwater vulnerability to heavy metal contamination via water quality pollution indices in urban Aligarh, India. Water Practice & Technology. 2024;19(2):419–34.
  10. 10. Adilakshmi A, Venkatesan V. Effective monitoring of Noyyal River surface water quality using remote sensing and machine learning and GIS techniques. Desalination and Water Treatment. 2024;320:100630.
  11. 11. Ramachandran R, Kannan B, Sivasubramanian K, Arunadevi K, Patil S. Spatio-temporal analysis of surface water quality on urban tanks in Coimbatore. Plant Sci Today. 2025;12:5919.
  12. 12. Ighalo JO, Adeniyi AG, Marques G. Internet of things for water quality monitoring and assessment: a comprehensive review. Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications. 2021:245–59.
  13. 13. Van Eck N, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010;84(2):523–38.
  14. 14. Singh MR, Gupta A. Water pollution-sources, effects and control. Centre for Biodiversity, Department of Botany, Nagaland University; 2016. p. 1–16.
  15. 15. Singh J, Yadav P, Pal AK, Mishra V. Water pollutants: origin and status. Sensors in water pollutants monitoring: role of material; 2020. p. 5–20.
  16. 16. Borrelli P, Robinson DA, Fleischer LR, Lugato E, Ballabio C, Alewell C, et al. An assessment of the global impact of 21st century land use change on soil erosion. Nature Communications. 2017;8(1):2013.
  17. 17. Pimentel D, Burgess M. Soil erosion threatens food production. Agriculture. 2013;3(3):443–63.
  18. 18. Vitousek PM, Chadwick OA. Pedogenic thresholds and soil process domains in basalt-derived soils. Ecosystems. 2013;16:1379–95.
  19. 19. Carpenter SR, Caraco NF, Correll DL, Howarth RW, Sharpley AN, Smith VH. Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecological Applications. 1998;8(3):559–68.
  20. 20. Allan JD, Castillo MM. Detrital energy sources. Stream ecology: structure and function of running waters; 2007. p. 135–61.
  21. 21. Legesse W, Kloos H. Water pollution from industrial and agricultural sources. Water resources management in Ethiopia: implications for the Nile Basin Cambria Press, Amherst, NY; 2010. p. 321–51.
  22. 22. Sharma A, Gupta R. Unmasking the silent threat: understanding and mitigating heavy metal contamination in aquatic ecosystems; 2024.
  23. 23. Tiwari K, Singh N, Patel M, Tiwari M, Rai U. Metal contamination of soil and translocation in vegetables growing under industrial wastewater irrigated agricultural field of Vadodara, Gujarat, India. Ecotoxicology and Environmental Safety. 2011;74(6):1670–7.
  24. 24. Bastida F, Moreno JL, Hernandez T, García C. Microbiological activity in a soil 15 years after its devegetation. Soil Biology and Biochemistry. 2006;38(8):2503–7.
  25. 25. Murtaza G, Ghafoor A, Qadir M, Owens G, Aziz M, Zia M. Disposal and use of sewage on agricultural lands in Pakistan: a review. Pedosphere. 2010;20(1):23–34.
  26. 26. Farooqi A, Farooqi A. Arsenic and fluoride pollution in water and soils. Arsenic and fluoride contamination: a Pakistan perspective; 2015. p. 1–20.
  27. 27. Schwarzenbach RP, Escher BI, Fenner K, Hofstetter TB, Johnson CA, Von Gunten U, et al. The challenge of micropollutants in aquatic systems. Science. 2006;313(5790):1072–7.
  28. 28. Foster S, Chilton PJ. Groundwater: the processes and global significance of aquifer degradation. Philosophical Transactions of the Royal Society of London Series B: Biological Sciences. 2003;358(1440):1957–72.
  29. 29. Rengasamy P. World salinization with emphasis on Australia. J Exp Bot. 2006;57(5):1017–23.
  30. 30. Gholizadeh MH, Melesse AM, Reddi L. A comprehensive review on water quality parameters estimation using remote sensing techniques. Sensors. 2016;16(8):1298.
  31. 31. Ahmed U, Mumtaz R, Anwar H, Mumtaz S, Qamar AM. Water quality monitoring: from conventional to emerging technologies. Water Supply. 2020;20(1):28–45.
  32. 32. Babatunde A. A study on traditional water quality assessment methods. Risk Assessment and Management Decisions. 2024;1(1):41–52.
  33. 33. Amrita CM, Babiyola D. Analysing the water quality parameters from traditional to modern methods in aquaculture. International Journal of Science, Environment and Technology. 2018;7(6):1954–61.
  34. 34. Jan F, Min-Allah N, Düştegör D. Iot based smart water quality monitoring: recent techniques, trends and challenges for domestic applications. Water. 2021;13(13):1729.
  35. 35. Lowe M, Qin R, Mao X. A review on machine learning, artificial intelligence, and smart technology in water treatment and monitoring. Water. 2022;14(9):1384.
  36. 36. Lim BJ, Hong EY, Kim HO, Jeong ES, Heo WM, Kim YH. Establishment of alarm criteria for automatic water quality
  37. monitoring system in Korea. Korean Journal of Ecology and Environment. 2008;41(4):423–30.
  38. 37. Aljanabi ZZ, Al-Obaidy AHMJ, Hassan FM. A brief review of water quality indices and their applications. IOP conference series: earth and environmental science: IOP Publishing; 2021.
  39. 38. Sutadian AD, Muttil N, Yilmaz AG, Perera B. Development of river water quality indices-a review. Environmental Monitoring and Assessment. 2016;188:1–29.
  40. 39. Kannel PR, Lee S, Lee YS, Kanel SR, Khan SP. Application of water quality indices and dissolved oxygen as indicators for river water classification and urban impact assessment. Environmental Monitoring and Assessment. 2007;132:93–110.
  41. 40. Howladar MF, Al Numanbakth MA, Faruque MO. An application of water quality index (WQI) and multivariate statistics to evaluate the water quality around Maddhapara Granite Mining Industrial Area, Dinajpur, Bangladesh. Environmental Systems Research. 2018;6:1–18.
  42. 41. Lumb A, Halliwell D, Sharma T. Application of CCME water quality index to monitor water quality: a case study of the Mackenzie River basin, Canada. Environmental Monitoring and assessment. 2006;113:411–29.
  43. 42. Alam MJ, Islam MR, Muyen Z, Mamun M, Islam S. Water quality parameters along rivers. International Journal of Environmental Science & Technology. 2007;4:159–67.
  44. 43. Ugbaja A, Ephraim B. Physicochemical and bacteriological parameters of surface water quality in part of Oban Massif, Nigeria. Global Journal of Geological Sciences. 2019;17:13–24.
  45. 44. Dey S, Uddin MS, Manchur MA. Physicochemical and bacteriological assessment of surface water quality of the Karnaphuli River in Bangladesh. Journal of Pure and Applied Microbiology. 2017;11(4):1721–8.
  46. 45. Albaggar AKA. Investigation of some physical, chemical, and bacteriological parameters of water quality in some dams in Albaha region, Saudi Arabia. Saudi Journal of Biological Sciences. 2021;28(8):4605–12.
  47. 46. Mallika S, Umamaheswari R, Krishnamoorthy S. Physico-chemical parameters and bacteriological study of Vaigai river water Madurai district, Tamilnadu, India. International Journal of Fisheries and Aquatic Studies. 2017;5(1):42–5.
  48. 47. Anyanwu C, Okoli E. Evaluation of the bacteriological and physicochemical quality of water supplies in Nsukka, Southeast, Nigeria. African Journal of Biotechnology. 2012;11(48):10868–73.
  49. 48. Adesakin TA, Oyewale AT, Bayero U, Mohammed AN, Aduwo IA, Ahmed PZ, et al. Assessment of bacteriological quality and physico-chemical parameters of domestic water sources in Samaru community, Zaria, Northwest Nigeria. Heliyon. 2020;6(8).
  50. 49. Kassegne AB, Leta S. Assessment of physicochemical and bacteriological water quality of drinking water in Ankober district, Amhara region, Ethiopia. Cogent Environmental Science. 2020;6(1):1791461.
  51. 50. Adeniji OO, Sibanda T, Okoh AI. Recreational water quality status of the Kidd's Beach as determined by its physicochemical and bacteriological quality parameters. Heliyon. 2019;5(6).
  52. 51. Kothari V, Vij S, Sharma S, Gupta N. Correlation of various water quality parameters and water quality index of districts of Uttarakhand. Environmental and Sustainability Indicators. 2021;9:100093.
  53. 52. Gorde S, Jadhav M. Assessment of water quality parameters: a review. J Eng Res Appl. 2013;3(6):2029–35.
  54. 53. Dohare D, Deshpande S, Kotiya A. Analysis of ground water quality parameters: a review. Research Journal of Engineering Sciences ISSN. 2014;2278:9472.
  55. 54. Latif M, Nasim I, Ahmad M, Nawaz R, Tahir A, Irshad MA, et al. Human health risk assessment of drinking water using heavy metal pollution index: a GIS-based investigation in mega city. Applied Water Science. 2025;15(1):12.
  56. 55. Fallahzadeh RA, Ghaneian MT, Miri M, Dashti MM. Spatial analysis and health risk assessment of heavy metals concentration in drinking water resources. Environmental Science and Pollution Research. 2017;24:24790–802.
  57. 56. Yoshida T, Yamauchi H, Sun GF. Chronic health effects in people exposed to arsenic via the drinking water: dose–response relationships in review. Toxicology and Applied Pharmacology. 2004;198(3):243–52.
  58. 57. Shirkhanloo H, Mirzahosseini SAH, Shirkhanloo N, Moussavi-Najarkola SA, Farahani H. The evaluation and determination of heavy metals pollution in edible vegetables, water and soil in the south of Tehran province by GIS. Archives of Environmental Protection. 2015;41(2).
  59. 58. Bux RK, Haider SI, Mallah A, Shah Z-u-H, Solangi AR, Moradi O, et al. Spatial analysis and human health risk assessment of elements in ground water of District Hyderabad, Pakistan using ArcGIS and multivariate statistical analysis. Environmental Research. 2022;210:112915.
  60. 59. Stern BR, Solioz M, Krewski D, Aggett P, Aw TC, Baker S, et al. Copper and human health: biochemistry, genetics, and strategies for modeling dose-response relationships. Journal of Toxicology and Environmental Health, Part B. 2007;10(3):157–222.
  61. 60. Arnous MO, Hassan MA. Heavy metals risk assessment in water and bottom sediments of the eastern part of Lake Manzala, Egypt, based on remote sensing and GIS. Arabian Journal of Geosciences. 2015;8:7899–918.
  62. 61. Sazakli E, Villanueva CM, Kogevinas M, Maltezis K, Mouzaki A, Leotsinidis M. Chromium in drinking water: association with biomarkers of exposure and effect. International Journal of Environmental Research and Public Health. 2014;11(10):10125–45.
  63. 62. Şener Ş, Şener E, Davraz A. Assessment of groundwater quality and health risk in drinking water basin using GIS. Journal of Water and Health. 2017;15(1):112–32.
  64. 63. Woolf A, Wright R, Amarasiriwardena C, Bellinger D. A child with chronic manganese exposure from drinking water. Environmental Health Perspectives. 2002;110(6):613–6.
  65. 64. Tiwari AK, De Maio M, Singh PK, Mahato MK. Evaluation of surface water quality by using GIS and a heavy metal pollution index (HPI) model in a coal mining area, India. Bulletin of Environmental Contamination and Toxicology. 2015;95:304–10.
  66. 65. Chain EPoCitF, Schrenk D, Bignami M, Bodin L, Chipman JK, Del Mazo J, et al. Update of the risk assessment of nickel in food and drinking water. EFSA Journal. 2020;18(11):e06268.
  67. 66. Cüce H, Kalıpcı E, Ustaoğlu F, Kaynar I, Baser V, Türkmen M. Multivariate statistical methods and GIS based evaluation of the health risk potential and water quality due to arsenic pollution in the Kızılırmak River. International Journal of Sediment Research. 2022;37(6):754–65.
  68. 67. Mohseni U, Patidar N, Pathan AI, Agnihotri P, Patel D. An innovative approach for groundwater quality assessment with the integration of various water quality indexes with GIS and multivariate statistical analysis—a case of Ujjain city, India. Water Conservation Science and Engineering. 2022;7(3):327–49.
  69. 68. Uslu A, Dugan ST, El Hmaidi A, Muhammetoglu A. Comparative evaluation of spatiotemporal variations of surface water quality using water quality indices and GIS. Earth Science Informatics. 2024;17(5):4197–212.
  70. 69.Gadelha AJF, da Rocha CO, Neto JGV, Gomes MA. Multivariate statistical analysis of physicochemical parameters of groundwater quality using PCA and HCA techniques. Eclética Química. 2023;48(4):37–47.
  71. 70.Azhari HE, Cherif EK, Sarti O, Azzirgue EM, Dakak H, Yachou H, et al. Assessment of surface water quality using the water quality index (IWQ), multivariate statistical analysis (MSA) and geographic information system (GIS) in Oued Laou Mediterranean Watershed, Morocco. Water. 2022;15(1):130.
  72. 71. Bekele E, Page D, Vanderzalm J, Kaksonen A, Gonzalez D. Water recycling via aquifers for sustainable urban water quality management: current status, challenges and opportunities. Water. 2018;10(4):457.
  73. 72. Grady CA, Weng SC, Blatchley ER. Global potable water: current status, critical problems, and future perspectives. Potable water: emerging global problems and solutions; 2014. p. 37–59.
  74. 73. Dalu T, Froneman PW. Diatom-based water quality monitoring in southern Africa: challenges and future prospects. Water SA. 2016;42(4):551–9.
  75. 74. Parris K. Impact of agriculture on water pollution in OECD countries: recent trends and future prospects. Water Quality Management. 2014:33–52.
  76. 75. Chen J, Chen S, Fu R, Li D, Jiang H, Wang C, et al. Remote sensing big data for water environment monitoring: current status, challenges, and future prospects. Earth's Future. 2022;10(2):e2021EF002289.
  77. 76. Araújo SO, Peres RS, Ramalho JC, Lidon F, Barata J. Machine learning applications in agriculture: current trends, challenges, and future perspectives. Agronomy. 2023;13(12):2976.

Downloads

Download data is not yet available.