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Environmental Earth Sciences

, 77:788 | Cite as

Assessment of surface water potential and groundwater recharge in ungauged watersheds: a case study in Tamil Nadu, India

  • K. Santhanam
  • Marykutty Abraham
Original Article
  • 51 Downloads

Abstract

Many of the states in India have been facing water scarcity for more than 2 decades due to increased demand, because of the increase in population and higher living standards. Consequently, many states have almost fully utilized the available surface water resources and are exploiting groundwater to augment water supplies. Investigations were carried out in the upper Thurinjalar watershed of Ponnaiyar basin in Tamil Nadu to determine the availability of surface water and to investigate the potential for enhancing groundwater recharge to support the water demand in the watershed. Increasing the water availability would also enable the community to convert the 46% of the land area in the watershed that is currently underutilised into productive uses. The surface water potential for the upper Thurinjalar watershed was assessed by applying the USDA–NRCS model with daily time steps. This modelling exercise indicated that the annual runoff from the 323 km2 area of the watershed is 61 million m3. Groundwater recharge in the watershed was assessed by carrying out daily water balance method and indicated that about 43 million m3 of water from recharge is available on an annual basis or about 14% of annual rainfall. A simple regression model was developed to compute groundwater recharge from rainfall based on water balance computations and this was statistically verified. The modelling indicated that there is sufficient water available in the watershed to support current land uses and to increase the productivity of underutilised land in the area. The study also demonstrates that simple regression models can be used as an effective tool to compute groundwater recharge for ungauged basins with proper calibration.

Keywords

Groundwater NRCS model Recharge Water balance model Regression model 

Notes

Acknowledgements

The authors wish to acknowledge Dr. S. Mohan, Professor, Department of Civil Engineering, IIT Madras, Dr. R. Jaganathan, Head, Department of Geography, Madras University and Mr. K. S. Kathiravan, Deputy Director, PWD—Groundwater, Chennai and T. German Amali Jacintha, Scientist, Sathyabama University for the support rendered for the successful completion of the work.

Funding

This research did not receive any funding or financial support or specific grant from funding agencies or government or non-government or non-profit organizations.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Centre for Remote Sensing and GeoinformaticsSathyabama Institute of Science and TechnologyChennaiIndia

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