{"title":"基于gis的喀拉拉邦坎努尔地下水质量和重金属公共健康风险评估","authors":"Thangavelu Arumugam , Sapna Kinattinkara , Karpagamani Vellingiri , Anjana C","doi":"10.1016/j.clwat.2025.100113","DOIUrl":null,"url":null,"abstract":"<div><div>This study was conducted on groundwater quality in the Kannur region and surrounding areas using multivariate statistical techniques combined with Geographic Information Systems (GIS). We have collected and analysed 37 groundwater samples from different locations for physicochemical and heavy metal properties between January and May 2023. These properties were assessed according to WHO (2016) standards. GIS was employed to analyze spatial patterns and relationships among geographic features, supported by multivariate statistical methods for interpretation. The water quality index (WQI) and heavy metal pollution index (HMPI) were used to combine multiple water quality parameters into single scores for easier assessment. The main findings are as follows: (1) WQI results showed that most sampling sites had water suitable for drinking, except Anthoor and Ulikkal, where water quality was relatively poor; (2) HMPI results indicated that Edat, Peravoor, and Ramanthali had the highest levels of lead; and (3) combining GIS with multivariate statistics proved effective in identifying spatial patterns and pollution hotspots. The study highlights the importance of ongoing monitoring, site-specific actions, and preventive measures to ensure safe drinking water and safeguard public health.</div></div>","PeriodicalId":100257,"journal":{"name":"Cleaner Water","volume":"4 ","pages":"Article 100113"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A GIS-based assessment of groundwater quality and public health risks of heavy metals in Kannur, Kerala\",\"authors\":\"Thangavelu Arumugam , Sapna Kinattinkara , Karpagamani Vellingiri , Anjana C\",\"doi\":\"10.1016/j.clwat.2025.100113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study was conducted on groundwater quality in the Kannur region and surrounding areas using multivariate statistical techniques combined with Geographic Information Systems (GIS). We have collected and analysed 37 groundwater samples from different locations for physicochemical and heavy metal properties between January and May 2023. These properties were assessed according to WHO (2016) standards. GIS was employed to analyze spatial patterns and relationships among geographic features, supported by multivariate statistical methods for interpretation. The water quality index (WQI) and heavy metal pollution index (HMPI) were used to combine multiple water quality parameters into single scores for easier assessment. The main findings are as follows: (1) WQI results showed that most sampling sites had water suitable for drinking, except Anthoor and Ulikkal, where water quality was relatively poor; (2) HMPI results indicated that Edat, Peravoor, and Ramanthali had the highest levels of lead; and (3) combining GIS with multivariate statistics proved effective in identifying spatial patterns and pollution hotspots. The study highlights the importance of ongoing monitoring, site-specific actions, and preventive measures to ensure safe drinking water and safeguard public health.</div></div>\",\"PeriodicalId\":100257,\"journal\":{\"name\":\"Cleaner Water\",\"volume\":\"4 \",\"pages\":\"Article 100113\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cleaner Water\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2950263225000511\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cleaner Water","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950263225000511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A GIS-based assessment of groundwater quality and public health risks of heavy metals in Kannur, Kerala
This study was conducted on groundwater quality in the Kannur region and surrounding areas using multivariate statistical techniques combined with Geographic Information Systems (GIS). We have collected and analysed 37 groundwater samples from different locations for physicochemical and heavy metal properties between January and May 2023. These properties were assessed according to WHO (2016) standards. GIS was employed to analyze spatial patterns and relationships among geographic features, supported by multivariate statistical methods for interpretation. The water quality index (WQI) and heavy metal pollution index (HMPI) were used to combine multiple water quality parameters into single scores for easier assessment. The main findings are as follows: (1) WQI results showed that most sampling sites had water suitable for drinking, except Anthoor and Ulikkal, where water quality was relatively poor; (2) HMPI results indicated that Edat, Peravoor, and Ramanthali had the highest levels of lead; and (3) combining GIS with multivariate statistics proved effective in identifying spatial patterns and pollution hotspots. The study highlights the importance of ongoing monitoring, site-specific actions, and preventive measures to ensure safe drinking water and safeguard public health.