Abstract
Agriculture is a major sector in India which contributes around 14% of country’s gross domestic product (GDP). Being an agriculture-based country, good quality of water for irrigation has been a prime requisite. Highly growing population and accelerated industrial development are causing anthropogenic pollution to both surface and groundwater on one side and geogenic contamination like arsenic, fluoride, high dissolved solids, sodicity, and iron in groundwater on other side. As a result, ensuring safe water quality for the irrigation has become a major challenge to both the central and state governments. The present irrigation water quality standards being followed in India have been set by the Central Pollution Control Board (CPCB) and Central Ground Water Board (CGWB) in the year 2000. These standards are solely based on four parameters, namely electrical conductivity, sodium percentage, sodium absorption ratio, and residual sodium carbonate, which are quite subjective and many times are not capable to exactly decide the quality of irrigation water particularly when there are large variations in the source water quality. Therefore, in the present paper, an indices-based approach is presented for categorization of irrigation water quality. These indices are mathematical equations that transform water quality data into a numeric value, which describes the quality of irrigation water. The proposed irrigation water quality index (IWQI), which is based on 12 parameters, classifies the water into five categories, viz. excellent, good, medium, bad, and very bad in the same manner as given by the CPCB and CGWB. In order to give proper rating to various parameters of the index, weights are computed using Saaty’s analytic hierarchy process (AHP)-based multiple criteria decision analysis (MCDA) approach. This approach minimizes the subjectivity in assessment of weights and improves understanding of water quality issues by generating an overall index to describe the status of water quality. The proposed index will be beneficial for the water management authorities in ensuring safe water to the stakeholders.
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References
Balasundar, N. K. (1968). Tertiary deposits of Neyveli Lignite field. Geological Society of India, Mem. No. 2, 256–262.
Brown, R. M., McClelland, N. I., Deininger, R. A., & Tozer, R. G. (1970). A water quality index: do we dare? Water & Sewage Works, 117(10), 339–343.
Bureau of Indian Standards. (1991). Specifications for drinking water, IS:10500: 1991. New Delhi: Bureau of Indian Standards.
CPCB and CGWB. (2000). Status of ground water quality and pollution aspects in NCT-Delhi, India. Prepared by Central Pollution Control Board and Central Ground Water Board, India.
Dee, N., Baker, J., Drobny, N., Duke, K. M., Whitman, I., & Fahringer, D. (1973). An environmental evaluation system for water resource planning. Water Resources Research, 9(3), 523–535. https://doi.org/10.1029/WR009i003p00523.
Deininger, R., & Landwehr, J. M. (1971). A water quality index for public water supplies. In School of Public Health. Ann Arbor: Univ. of Michigan.
Dinius, S. H. (1972). Social accounting system for evaluating water. Water Resources Research, 8(5), 1159–1177. https://doi.org/10.1029/WR008i005p01159.
FAO. (1985). Water quality for agriculture. Irrigation and drainage paper, 29. Rev. 1. Rome: FAO 174 p.
Horton, R. K. (1965). An index number system for rating water quality. Journal of Water Pollution Control Administration, 37(3), 300.
Javanbarg, M. B., Scawthorn, C., Junji, K., & Shahbodghkhan, B. (2012). Fuzzy AHP-based multicriteria decision making systems using particle swarm optimization. Expert Systems with Applications, 39(1), 960–966. https://doi.org/10.1016/j.eswa.2011.07.095.
Landwehr, J. M. (1976). A statistical view of a class of water quality indices. Water Resources Research, 15(2), 460–468.
Lee, A. H. I., Chen, W. C., & Changm, C. J. (2008). A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Systems with Applications, 34(1), 96–107. https://doi.org/10.1016/j.eswa.2006.08.022.
Majumdar, A., Sarkar, B., & Majumdar, P. K. (2004). Application of analytic hierarchy process for the selection of cotton fibers. Fibers and Polymers, 5(4), 297–302. https://doi.org/10.1007/BF02875528.
Mc Duffie, B., & Haney, J. T. (1973). A proposed river pollution index. New York: American Chemical Society, Division of Water, Air and Waste Chemistry.
Mostafaei, A. (2014). Application of multivariate statistical methods and water-quality index to evaluation of water quality in the Kashkan River. Environmental Management, 53(4), 865–881. https://doi.org/10.1007/s00267-014-0238-6.
Nemerow, N. L., & Sumitomo, H. (1970). Benefits of water quality enhancement. Syracuse: Syracuse. University Report No. 16110 DAJ.
O’Cornor, F. M. (1972). The application of multi-attribute scaling procedures to the development of indices of water quality. Ph.D Dissertation, University of Michigan.
Orozco, C. D. L. M., Lopez, H. F., Arias, H. R., Duran, A. C., & Rivero, O. J. (2017). Developing a water quality index (WQI) for an irrigation dam. International Journal of Environmental Research and Public Health, 14(5), 439. https://doi.org/10.3390/ijerph14050439.
Parti, L., Pavanello, R., & Pesarin, F. (1971). Assessment of surface water quality by single index of pollution. Water Research, 5(9), 741–751. https://doi.org/10.1016/0043-1354(71)90097-2.
Paul, R., Das, S., Nag, S. K., & Singh, M. K. (2016). Deciphering groundwater quality for drinking and irrigation purposes—a study in Lefunga Block of West Tripura District, Tripura, India. Journal of Earth Science and Climatic Change, 7, 378.
Saaty, T. L. (1980). Fundamentals of decision making and priority theory with analytical hierarchical process (Vol. VI, pp. 3–95). Pittusburgh: RWS Publications, University of Pittsburgh.
Selvaraj, K., & Ramasamy, S. (1998). Depositional environment of Cuddalore sandstone formation, Tamil Nadu. Journal Geological Society of India, 51, 803–812.
Shankar, K., Aravindan, S., & Rajendran, S. (2011). Assessment of ground water quality in Paravanar River Sub-Basin, Cuddalore district, Tamil Nadu, India. Advances in Applied Science Research, 2(5), 92–103.
Singh, S., Ghosh, N. C., Krishan, G., Galkate, R., Thomas, T., & Jaiswal, R. K. (2015). Development of an overall water quality index (OWQI) for surface water in Indian context. Current World Environment, 10(3), 813–822. https://doi.org/10.12944/CWE.10.3.12.
Stoner, J. D. (1978). Water quality indices for specific water use (pp. 140–770). Reston. Circular: U.S. Geological Survey.
Sutadian, A. D., Muttil, N., Yilmaz, A. G., & Perera, B. J. (2016). Development of river water quality indices-a review. Environmental Monitoring and Assessment, 188(1), 58. https://doi.org/10.1007/s10661-015-5050-0.
Walski, T. M., & Parker, F. L. (1974). Consumers water quality index. Journal of Environmental Engineering, ASCE, 100, 593–611.
Wu, H., Qian, H., Chen, J., & Huo, C. (2017). Assessment of agricultural drought vulnerability in the Guanzhong Plain, China. Water Resources Management, 31(5), 1557–1574. https://doi.org/10.1007/s11269-017-1594-9.
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Singh, S., Ghosh, N.C., Gurjar, S. et al. Index-based assessment of suitability of water quality for irrigation purpose under Indian conditions. Environ Monit Assess 190, 29 (2018). https://doi.org/10.1007/s10661-017-6407-3
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DOI: https://doi.org/10.1007/s10661-017-6407-3