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Analysis of AEM data density and its optimization for mapping the network of water potential fractures in crystalline hard rock

Authors

Choudhury,  Joy
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Chandra,  Subash
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Choudhury, J., Chandra, S. (2023): Analysis of AEM data density and its optimization for mapping the network of water potential fractures in crystalline hard rock, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-3908


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020639
Abstract
The weathered zone in granitic hard rock, that use to facilitate potential zone for groundwater occurrence, goes mostly dry due to lowering of water level and as a result presence of underlying fractures and its interconnectivity becomes vital for groundwater prospecting in hard rock terrains. The bedrock fractures are known for sporadic and random distribution. The generating knowledge on the distribution of bedrock fracture pattern with limited data sets usually faces either underestimation or overestimation due to interpolation, which leads to inaccurate assessment of the aquifer dynamics. This paper presents a comparative analysis on degree of lithological variability and role of data density with special reference to granitic hard rock terrain. An integrated hydrogeophysical study including airborne electromagnetic (AEM) that measures at every 2.5-3 m along the flight lines has been carried out in a 380 sq.km granitic terrain in Tumkur district, Karnataka state of India. Previous studies has shown that AEM Depth of Investigation is very effective parameter in mapping of fracture network due to associated weathering and presence of water. We extend the work to establish the optimal data density required for mapping the network of fracture. We also present an analysis demonstrating how the information is getting lost or superficial information generated by changing the data density. A demonstrative exercise has been carried out by gradually decreasing data density from 100% to 0.05% and compared with general practices for groundwater application. This is helpful for conceptualization and planning of the aquifer mapping in hard rock terrains.