Reservoir sedimentation process is a universal phenomenon, which has been considered
as a most critical environmental hazard of modern time (Jain and Kothyari, 2000). The
range of problems caused by reservoir sedimentation is varied and wide. Apart from loss
of capacity, increased flood risks, interruption in hydropower generation and downstream
river bed degradation; other problems such as degradation of water quality, increased complexity in reservoir operation and maintenance led to increase in their associated
cost (Kothiyari et al., 2002). A broad estimate of soil erosion in India showed that about
5,334 million tons of soil is being lost every year, which means, soil erosion is taking place
at the rate of 16.35 tons/ha/year (Narayana and Ram Babu, 1983), which is more than
the permissible soil loss tolerance value of 4.5-11.2 tons/ha/year (Singh et al., 1981). As a
result, it is widely viewed that nearly 20% of the live storage capacity of our major and
medium-sized reservoirs was silted up by the end of the year 2000, which means a loss of
irrigation potential of about 60,000 ha every year due to silting. An analysis of
sedimentation survey in respect of 43 major, medium and minor reservoirs in India
indicated the variation of sedimentation rate between 0.003 and 0.28 million cu m/
100 sq km/year for major reservoirs, 0.002-0.11 million cu m/100 sq km year for medium
and 0.01-0.02 million cu m/100 sq km/year for minor reservoirs (Shangle, 1991).
With the introduction of remote sensing techniques in the recent past, it has become
convenient and far less expensive to quantify sedimentation in reservoirs and to assess
its distribution and deposition pattern. Advantages of using remote sensing data are: it is
highly cost-effective, easy to use and requires lesser time in analysis as compared to
conventional methods. Spatial, spectral and temporal attributes of remote sensing provide
invaluable synoptic and timely information regarding the revised area after the occurrence
of sedimentation and sediment distribution pattern in the reservoir. The ability to map
and estimate water spread from satellite data is well understood, and different techniques
such as visual interpretation of satellite imagery, density slicing, and digital classification
of water bodies have been employed for the delineation of water bodies (Work and Gilmer,
1976; Thiruvengadachari et al., 1980; Thiruvengadachari and Manavalan, 1983; Goel
and Jain, 1996; NIH, 2003-04; NIH, 2004-05; Jaiswal et al., 2008; and Thomas et al., 2009).
In this paper, an attempt has been made to compare the revised capacities of Rajaval and
Kharo reservoirs of southern Gujarat (India). The image analysis technique of remote
sensing data was used to estimate the revised capacity of these reservoirs. Seven Linear
Image Self Scanning (LISS III) digital data of IRS 1D/P6 were used in the analysis. |
