GIS USED FOR GROUND WATER LEVEL ANALYSIS & PREDICTION - PHAGI CASE STUDY

Ground water Level Scenario Analysis using GIS-Phagi Tehsil (2012-2024)

Erratic rainfall, squeezed rainy season, increase in impervious layer etc. have affected the demand and supply of water in the village/city/district/state. Therefore dependency on ground water is increase a lot for drinking, agriculture and other usage in day to day life. Due to this ground water is too much exploited and most of the area/locations in India as well as in Rajasthan became the dark zones. This ground water demand will increase in future as population is growing rapidly. This will affect the ground water quality and which leads to disease and health issues of human beings. Therefore authorities need to regularly monitor the ground water condition as well as plan accordingly to efficiently use of ground water.

GIS plays important role in database generation especially in the spatial format both raster and vector. If same monitoring and mapping of ground water performed using GIS will take less time and cost effective. It will also reduce the redundancy of data and data can be easily integrated with existing data or models. GIS can also be used to predict the future condition of water level in any specific area.

Therefore in this article, ground water level mapping using GIS is demonstrated based on case study of Phagi.

Pre-monsoon and post monsoon ground water level and ground water quality data of year 2012 to 2019 was collected from State Ground Water Department, Rajasthan for different sampling locations of Phagi tehsil.

The sampling locations were wells, bore wells and hand pumps. The spatial analyst tool of GIS was used for analyzing spatial and temporal trends of ground water level and ground water quality.



Ground Water Level Analysis

Ordinary kriging technique was applied to interpolate the eight years (2012 to 2019) ground water level data. Kriging is an unbiased point interpolation method, which requires a point map as input and returns a raster map with estimations. The advantage of Kriging above inverse distance weighted (IDW) method is that it provides a measure of the probable error associated with the estimates. The spatial and temporal variation in ground water level could be seen in figure given below.

By applying Zonal statistics tool of GIS, one can calculate the ground water level at panchayat or village level. Zonal analysis is an important raster based analysis tool of GIS which could be used for different GIS related studies viz. demographic studies, surface modelling, environmental monitoring, planning and design, land management etc. This tool creates an output raster or statistics table from the input value raster that intersect or fall within each zone of a specified input zone datasets.

 A single output value is computed for every zone in the input zone datasets. The comparative spatial and temporal analysis of Phagi tehsil at village level is shown in below figure. 

The ground water variations indicate that water level is directly affected by the rainfall as maximum water level depth decreased from 2016 (42.69 mbgl) to 2019 (27.92mbgl). However, the minimum depth of ground water is increasing from 2013 (5.95 mbgl) to 2019 (6.63 mbgl) and the deeper water level is observed in the northern part of Phagi tehsil such as Renwal, Harsooliya villages.



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