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The AAPG/Datapages Combined Publications Database

Environmental Geosciences (DEG)


Environmental Geosciences, V. 17, No. 1 (March 2010), P. 3744.

Copyright copy2010. The American Association of Petroleum Geologists/Division of Environmental Geosciences. All rights reserved.


Derivations of simple site-specific recharge-precipitation relationships: A case study from the Cuddalore Basin, India

S. Mohan,1 Marykutty Abraham2

1Environmental and Water Resources Engineering, Department of Civil Engineering, IIT Madras, Chennai 600 036, India
2Center for Water Research, Sathyabama University, Chennai 600 119, India; [email protected]


S. Mohan is a professor in the Department of Civil Engineering at the Indian Institute of Technology Madras, India. His research interests include environmental system analysis, environmental impact assessment, water quality modeling, water and wastewater treatment, water resources system analysis, Geographic Information System and its applications, and evolutionary algorithms. He has published several articles in national and international journals, which are of high value.

Marykutty Abraham is a scientist in the Center for Water Research, Sathyabama University, Chennai, India. Her main areas of interest are groundwater hydrology-groundwater flow and contaminant transport modeling, water harvesting, irrigation engineering, water resources systems engineering, air and water quality modeling, and geographic information systems. She has also conducted many field experiments related to evapotraspiration.


Population growth and higher living standards have resulted in an ever-increasing demand for water. Quantifying the current rate of groundwater recharge is a prerequisite for efficient and sustainable groundwater resource management in dry areas. The normal practice of assuming natural recharge value as certain percentage of rainfall may be suitable for yearly estimation, but this method miserably fails if it is used for short-term estimation. Equations were developed for natural recharge estimation and applied to a case study for Cuddalore Basin, Tamilnadu, India. Natural recharge was estimated using water level fluctuation method, water balance method, Previous HitnonlinearNext Hit regression method, and artificial neural network (ANN) model. According to the water level fluctuation method, on an average, 18.74% of the rain got recharged to the ground. The average annual recharge to the groundwater reserve was 18.98, 16.81, and 18.48% of rainfall in the case of the water balance model, Previous HitnonlinearNext Hit regression model, and ANN model. The study shows that the framework adopted for the Previous HitnonlinearTop regression and ANN models can be locally used to predict natural recharge based on precipitation estimates.

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