Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula
Chunnakam aquifer is the main limestone aquifer of Jaffna Peninsula. The population of the Jaffna Peninsula depends entirely on groundwater resources to meet all of their water requirements. Thus for protecting groundwater quality in Chunnakam aquifer, data on spatial and temporal distribution are i...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/111069 |
| _version_ | 1855532821567766528 |
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| author | Arasalingam, Sutharsiny Manthrithilake, Herath Pathmarajah, S. Mikunthan, T. Vithanage, Meththika |
| author_browse | Arasalingam, Sutharsiny Manthrithilake, Herath Mikunthan, T. Pathmarajah, S. Vithanage, Meththika |
| author_facet | Arasalingam, Sutharsiny Manthrithilake, Herath Pathmarajah, S. Mikunthan, T. Vithanage, Meththika |
| author_sort | Arasalingam, Sutharsiny |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Chunnakam aquifer is the main limestone aquifer of Jaffna Peninsula. The population of the Jaffna Peninsula depends entirely on groundwater resources to meet all of their water requirements. Thus for protecting groundwater quality in Chunnakam aquifer, data on spatial and temporal distribution are important. Geostatistics methods are one of the most advanced techniques for interpolation of groundwater quality. In this study, Ordinary Kriging and IDW methods were used for predicting spatial distribution of some groundwater characteristics such as: Electrical Conductivity (EC), pH, nitrate as nitrogen, chloride, calcium, carbonate, bicarbonate, sulfate and sodium concentration. Forty four wells were selected to represent the entire Chunnakam aquifer during January, March, April, July and October 2011 to represent wet and dry season within a year. After normalization of data, variogram was computed. Suitable model for fitness on experimental variogram was selected based on less Root Mean Square Error (RMSE) value. Then the best method for interpolation was selected, using cross validation and RMSE. Results showed that for all groundwater quality, Ordinary Kriging performed better than IDW method to simulate groundwater quality. Finally, using Ordinary Kriging method, maps of groundwater quality were prepared for studied groundwater quality in Chunnakam aquifer. The result of Ordinary Kriging interpolation showed that higher EC, chloride, sulphate and sodium concentrations are clearly shown to be more common closer to the coast, and decreasing inland due to intrusion of seawater into the Chunnakam aquifer. Also higher NO3 - - N are observed in intensified agricultural areas of Chunnakam aquifer in Jaffna Peninsula. |
| format | Journal Article |
| id | CGSpace111069 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| record_format | dspace |
| spelling | CGSpace1110692024-10-11T08:58:20Z Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula Arasalingam, Sutharsiny Manthrithilake, Herath Pathmarajah, S. Mikunthan, T. Vithanage, Meththika groundwater water quality aquifers spatial distribution forecasting water properties wells geostatistics models Chunnakam aquifer is the main limestone aquifer of Jaffna Peninsula. The population of the Jaffna Peninsula depends entirely on groundwater resources to meet all of their water requirements. Thus for protecting groundwater quality in Chunnakam aquifer, data on spatial and temporal distribution are important. Geostatistics methods are one of the most advanced techniques for interpolation of groundwater quality. In this study, Ordinary Kriging and IDW methods were used for predicting spatial distribution of some groundwater characteristics such as: Electrical Conductivity (EC), pH, nitrate as nitrogen, chloride, calcium, carbonate, bicarbonate, sulfate and sodium concentration. Forty four wells were selected to represent the entire Chunnakam aquifer during January, March, April, July and October 2011 to represent wet and dry season within a year. After normalization of data, variogram was computed. Suitable model for fitness on experimental variogram was selected based on less Root Mean Square Error (RMSE) value. Then the best method for interpolation was selected, using cross validation and RMSE. Results showed that for all groundwater quality, Ordinary Kriging performed better than IDW method to simulate groundwater quality. Finally, using Ordinary Kriging method, maps of groundwater quality were prepared for studied groundwater quality in Chunnakam aquifer. The result of Ordinary Kriging interpolation showed that higher EC, chloride, sulphate and sodium concentrations are clearly shown to be more common closer to the coast, and decreasing inland due to intrusion of seawater into the Chunnakam aquifer. Also higher NO3 - - N are observed in intensified agricultural areas of Chunnakam aquifer in Jaffna Peninsula. 2021-01-08 2021-01-31T13:09:45Z 2021-01-31T13:09:45Z Journal Article https://hdl.handle.net/10568/111069 en Open Access Arasalingam, Sutharsiny; Manthrithilake, Herath; Pathmarajah, S.; Mikunthan, T.; Vithanage, M. 2020. Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula. Journal of Jaffna Science Association, 2(1):12-24. |
| spellingShingle | groundwater water quality aquifers spatial distribution forecasting water properties wells geostatistics models Arasalingam, Sutharsiny Manthrithilake, Herath Pathmarajah, S. Mikunthan, T. Vithanage, Meththika Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula |
| title | Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula |
| title_full | Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula |
| title_fullStr | Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula |
| title_full_unstemmed | Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula |
| title_short | Geo-statistical approach for prediction of groundwater quality in Chunnakam Aquifer, Jaffna Peninsula |
| title_sort | geo statistical approach for prediction of groundwater quality in chunnakam aquifer jaffna peninsula |
| topic | groundwater water quality aquifers spatial distribution forecasting water properties wells geostatistics models |
| url | https://hdl.handle.net/10568/111069 |
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