Assessment of sedimentation in kharkhara reservoir using digital image processing techniques

Kumar Jaiswal, Anoop Kumar Rai, Ravi Galkate, T. R. Nayak
  • Email
1National Institute of Hydrology, Roorkee
  • Submitted02-05-2019|

  • Accepted22-05-2019|

  • First Online 12-10-2019|

  • doi 10.18805/BKAP166

Cite article:- Jaiswal Kumar, Rai Kumar Anoop, Galkate Ravi, Nayak R. T. (2019). Assessment of sedimentation in kharkhara reservoir using digital image processing techniques. Bhartiya Krishi Anusandhan Patrika. 34(2): 118-123. doi: 10.18805/BKAP166.
Dams or reservoirs have proven to be very beneficial for the sustained development of human beings since its evolution. The usefulness of dam depends upon its capacity to store water. Sedimentation is a process which involves deposition of silt carried by flowing water from erosion of soil of upstream catchment area. Sedimentation has proven to be very detrimental for the capacity of dams or reservoirs. Sedimentation results in huge loss of storage capacity of dams or reservoirs thus reducing its life. Many methods have developed to measure the reservoir sedimentation like hydrographic survey, inflow-outflow approaches, remote sensing method etc. Out of these, remote sensing method is widely used as it is very simple and involves very less human survey thus reducing the chances of error. In remote sensing method, revised water spread area at different levels of reservoir is calculated and used for computation of loss of capacities between these levels. The present study has been carried out on Kharkhara reservoirs situated in Chhattisgarh state. Multi–date satellite data of IRS-P6, LISS-III is used for Kharkhara dam to estimate revised capacity. The normalized difference water index (NDWI), band ratioing technique (BRT) and false color composite (FCC) along with field truth verification were used to differentiate water pixels from rest of image. As the revised water spread at dead storage and full reservoir levels were not available, best –fit curve has been used to get revised spreads on these levels. From the analysis, it has been observed that Kharkhara reservoir has lost 8.41 MCM of gross storage against its total capacity of 169.54 MCM during 50 years(1967-2017). The average rate of sedimentation in Kharkhara reservoir is 16.82 Ha-m per year.
  1. Goel, M.K. and Jain, S. K., 1996. Evaluation of Reservoir Sedimentation Using Multi-    Temporal IRS-1A LISS-II data. Asian-Pacific Rem. Sens. GIS J. 8(2), 39-43.
  2. Goel M.K., Jain, S.K. and Agrawal. P.K., (2002) Assessment of sediment deposition rate in Bargi Reservoir using digital image processing, Hydrological Sci. J., 47(S): S81-S92
  3. Jain and Goel., (1993). Reservoir Sedimentation Using Digital Image Processing of IRS-I, LISS-I Data, Proc. Nat. Symp. Remote Sens. Appl. Resour. Manage. with Special Emphasis on N.E. Region, Guwahati (India), 504 – 510.
  4. Jaiswal, R.K., Thomas, T., Singh, S. and Galkate, R.V., (2008). Assessment of Revised Capacity of Kharo Reservoir Using Remote Sensing and GIS, Proc. Nat. Seminar Conserv. Restoration Lakes (CAROL-2008),Nagpur (India), 551-562.
  5. Jaiswal, R.K., Thomas, T., Galkate, R.V. and Jain, S.K. (2009). Assessment of Sedimentation in Ravishankar Sagar Reservoir using Digital Image Processing Techniques, J. Environ. Res. Develop. 3(4): 1238-245.
  6. Mukherjee, S., Veer, V., Tyagi, S.K. and Sharma, V., (2007). Sedimentation Study of Hirakud Reservoir using Remote Sensing Technique. J. Spatial Hydrol. 7(1).
  7. Thomas, T., Jaiswal, R.K., Galkate, R.V. and Singh, S., (2009). Estimation of Revised Capacity in Shetrunji Reservoir Using Remote Sensing and GIS, J. Indian Water. Resour. Soc. 29 (3): 8-14. 

Editorial Board

View all (0)