ABSTRACT
Groundwater, an important constituent of the hydrological cycle and a major source of water supply, is causing concern due to over-exploitation caused by population growth and extensive agricultural use. Pollution is also increasing and is threatening our ecosystems and even the life of future generations. Groundwater needs to be managed to maintain sustainability. Monitoring is essential of management but needs to be cost-effective. The selection of optimal groundwater monitoring network to observe the quality and quantity of the groundwater depends on several criteria. In the present study, two different geostatistical approaches were used on two monitoring variables to develop a monitoring network, which provides sufficient and useful information of these variables to delineate their spatial distribution. The study was carried out in a hard-rock aquifer. Optimisation of the water-level monitoring network was carried out using a geostatistical estimation variance reduction method (EVRM) in an unbiased way with a preset degree of accuracy. The monitoring network of 57 boreholes was reduced to 40 wells, in such a way that the variance of the estimation error does not exceed the pre-set limit. A simple method was then developed with the cross-validation technique of geostatistical estimation to analyse and optimise an existing network for monitoring fluoride. The fluoride values from the existing monitoring network of 60 boreholes was geostatistically analysed and the priority and/or redundancy of each measurement point was determined to provide an optimal monitoring network of only 30 wells. It was observed that the optimised monitoring network provided the same variability as that attained by the original monitoring network in both the cases.
