4.7 Article

Identifying influencing groundwater parameter on human health associate with irrigation indices using the Automatic Linear Model (ALM) in a semi-arid region in India

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ENVIRONMENTAL RESEARCH
卷 202, 期 -, 页码 -

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ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2021.111778

关键词

Irrigation water quality; Automatic Linear Modelling (ALM); Irrigation indices; Integrated method; Groundwater contamination

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The study evaluated groundwater suitability for irrigation using various indices, finding that over half of the samples exceeded permissible levels, while some were suitable for irrigation but needed treatment. Automatic Linear Modelling predicted key influencing parameters, with findings showing magnesium concentration and salinity as primary factors affecting water suitability.
Quality of water for the purposes of irrigation is a serious threat to the sustainable development of the agriculture sector. The main objective of this study is to evaluate the suitability of groundwater for irrigation purposes using various irrigation indices such as: Sodium Absorption Ratio (SAR), Residual Sodium Carbonate (RSC), Percentage Sodium (%Na), Magnesium Hazards (MH), Permeability Index (PI), Potential Salinity (PS), Residual Sodium Bicarbonate (RBSC), Kelly's Ratio (KR), Synthetic Harmful Coefficient (K), and Exchangeable Sodium Percentage (ESP). A total of 30 samples were collected from the bore well of agricultural farmland and analysed for cations and anions. MH reveal that 53.33 % of samples exceed the permissible level. PS shows that 43.33 % of samples are marginally affected and 33.33 % of samples are unsuitable for use in irrigation. About 76 % of the groundwater samples were suitable for irrigation and the remainder require treatment before use. Automatic Linear Modelling (ALM) is used to predict the major influence parameter for MH and PS are RBSC, RSC and K value of groundwater. ALM shows that excess magnesium concentration and salinity are the primary factors that affect the suitability of groundwater for irrigation use. This integrated technique showed that water from approximately 25 % of the sample locations would require treatment before use. This study will improve the pattern of irrigation, identify sources of contamination and highlight the importance of organic fertilizers to develop and enhance the sustainable practices in the study region.

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