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Development of irrigation water quality index incorporating information entropy

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Abstract

The present study demonstrates the efficacy of information entropy for the development of water quality index (WQI) for irrigation purpose and its application on Bharalu River. Water quality for irrigation suitability was assessed by using derived parameters such as permeability index (PI), Kelly’s ratio (KR), magnesium adsorption ratio (MgR), sodium adsorption ratio (SAR), soluble sodium percentage (SSP), and residual sodium carbonate (RSC) using annual data from April’2008 to April’2013 and April’2016, April’2017 over a period of 8 years. Values obtained in the study varied from 1.85 to 39.35% for SSP, 0.08 to 1.37 for SAR, 31.7–60.0% for MgR, 0.0–5.45 for RSC, 0.33–2.36% for PI, an 0.01–0.52 for KR. The derived parameters values indicate that water of Bharalu River is suitable for irrigation except April’2008 and April’2011. United States Salinity Laboratory (USSL) and Wilcox diagrams were used for categorizing of water quality. USSL and Wilcox diagrams categorized the water samples as S1-C2 and S1-C3, and ‘Excellent to Good’ and ‘Good to Permissible’ respectively, which suggest River Bharalu’s irrigation suitability. Entropy weighted irrigation water quality index (EIWQI) has been proposed and applied on Bharalu River data for assessing its suitability and variability for irrigation. EIWQI was found to be less than 1 for all the years except April’2011, which showed its appropriateness for irrigation. This study can be of great help for policymakers and researchers to effectively manage water resources.

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Acknowledgements

Authors appreciatively accept the support from Pollution Control Board, Guwahati (Assam). Board has provided the previous year’s data (April’2008–April’2013) for the study.

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  1. Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, India

    Kunwar Raghvendra Singh, Ankit Pratim Goswami, Ajay S. Kalamdhad & Bimlesh Kumar

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  1. Kunwar Raghvendra Singh
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  2. Ankit Pratim Goswami
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  3. Ajay S. Kalamdhad
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  4. Bimlesh Kumar
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Correspondence to Kunwar Raghvendra Singh.

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Singh, K.R., Goswami, A.P., Kalamdhad, A.S. et al. Development of irrigation water quality index incorporating information entropy. Environ Dev Sustain 22, 3119–3132 (2020). https://doi.org/10.1007/s10668-019-00338-z

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