Spatial variability of ground water quality: a case study of Udupi district, Karnataka State, India

被引:14
|
作者
Deepika, B., V [1 ,2 ]
Ramakrishnaiah, C. R. [2 ]
Naganna, Sujay Raghavendra [3 ]
机构
[1] Shri Madhwa Vadiraja Inst Technol & Management, Dept Civil Engn, Bantakal 574115, Udupi, India
[2] BMS Coll Engn, Dept Civil Engn, Bangalore 560019, Karnataka, India
[3] Siddaganga Inst Technol, Dept Civil Engn, Tumkur 572103, Karnataka, India
关键词
Groundwater quality analysis; water quality index; water quality mapping; geostatistics; kriging; INTERPOLATION; INDEX; CONTAMINATION; GIS;
D O I
10.1007/s12040-020-01471-4
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Groundwater is a reliable source of fresh water for domestic and agricultural water users. It supports subsurface ecosystem by balancing the geo-biological and bio-geochemical processes at micro- and macro-scales of the ecosystem. Overexploitation, anthropogenic activities and improper agricultural practices have contributed to the pollution of groundwater sources all around the globe. The water quality index (WQI) is the most extensively used indicator which transforms the water quality information derived from several parameters into a single value/rating to categorize and provide a general perception of water quality standard. Groundwater quality analysis and mapping via geographical information system (GIS) proves to be beneficial in identifying the locations where the groundwater quality is deteriorating. In the current study, the WQI of groundwater was determined for the samples collected from open and tube wells located within the Udupi district of Karnataka state, India. The groundwater quality parameters such as pH, hardness, calcium, chlorides, nitrates, iron, fluoride, sulfates, manganese, sodium, magnesium, potassium, turbidity, and phosphate were analyzed for water samples collected from 112 randomly chosen open/tube wells in order to determine the WQI. Interpolation approaches such as inverse distance weighting (IDW) and kriging were adopted in the GIS environment to quantify the spatial variability of groundwater quality over the entire geographical area. The groundwater quality maps were generated using the best fit models. The results portray that, the accuracy of interpolation using IDW and kriging methods was dependent on the measures of central tendency and variability of water quality data of different parameters. The kriging interpolation was much accurate for most of the groundwater quality parameters compared to IDW maps. The WQI maps, perhaps signposted the poor quality of groundwater quality in about 1.88% of the geographical area of Udupi district. Further, about 21.69% of the area was affected by poor quality of groundwater where suitable strategies for replenishment of groundwater resources should be taken up by the concerned authorities. The spatial distribution maps of groundwater quality aid to locate vulnerable places where immediate action is required.
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页数:20
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