2010
DOI: 10.1002/hyp.7914
|View full text |Cite
|
Sign up to set email alerts
|

Fluctuation of groundwater in an urban coastal city of India: a GIS‐based approach

Abstract: Abstract:Groundwater is the most important and valuable natural resources especially in coastal urban environment where surface water is insufficient to satisfy the water requirement. Puri city is located on the east coast of India where groundwater is the only source available to meet city water supply. As the city is situated on the sandy aquifer, quality of groundwater is deteriorating because of anthropogenic activities, lack of sewerage system, etc. The objective of the study was to assess the groundwater… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2015
2015
2020
2020

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(2 citation statements)
references
References 26 publications
0
2
0
Order By: Relevance
“…Few published studies are available that used GIS and RS technologies to quantitatively estimate groundwater levels with limited information, short of a hydrogeologic modeling study. Vijay et al (2011) used kriging to interpolate the water table surface from water elevations measured at 35 production wells north of the Bay of Bengal in India and used it to characterize seasonal water table fluctuations. Direct interpolation of water table measurements is ideal when data are sufficiently dense, but indirect methods must be used when monitoring data are sparse.…”
Section: Introductionmentioning
confidence: 99%
“…Few published studies are available that used GIS and RS technologies to quantitatively estimate groundwater levels with limited information, short of a hydrogeologic modeling study. Vijay et al (2011) used kriging to interpolate the water table surface from water elevations measured at 35 production wells north of the Bay of Bengal in India and used it to characterize seasonal water table fluctuations. Direct interpolation of water table measurements is ideal when data are sufficiently dense, but indirect methods must be used when monitoring data are sparse.…”
Section: Introductionmentioning
confidence: 99%
“…; Vijay et al . ; Berhane and Walraevens ), remote sensing and satellite imagery (e.g. Xu and Ji ) as well as model‐based approaches, such as digital elevation models – DEMs (e.g.…”
Section: Introductionmentioning
confidence: 99%