Space Technology in Assessment of Loss in Live Storage

Capacity of Reservoir

Karishma Bhatnagar Malhotra (Deputy Director), Rishi Srivastava (Director),

Amrendra Kumar Singh (Chief Engineer)

Central Water Commission, New Delhi-110066, India

Abstract

Reservoirs are created all over the world to store water for Irrigation, Hydro power etc. Storage in reservoirs is subject to silting which occurs not only in the dead storage but also in live storage zone. Any loss of storage in excess of the designed rate of loss is actually a matter of concern. Periodic capacity survey of reservoir is thus essential to ascertain the rate of sedimentation and reduction in storage capacity for efficient and productive management of water resources. Satellite Remote sensing (SRS) technique has emerged and established itself as a useful cost and time effective tool to estimate live storage capacity loss in reservoirs due to sedimentation. The added advantage of this technique is that the capacity of reservoir can be established for earlier years also. This paper describes the 128 assessment studies of loss in live storage capacity using SRS technique carried out by Central Water Commission for 121 important reservoirs distributed all across the country using optical/microwave remote sensing inputs. Of late, CWC has started using microwave data to assess sedimentation loss in reservoirs. Assessment of live storage loss using microwave inputs has advantages over optical inputs as the microwave based imageries are available at frequent time intervals regardless of weather and illumination conditions. India is divided into 7 Sedimentation zones based on factors such as hydrometeorology, physiography, climate etc. In each zone a number of reservoirs were studied and the zone-wise range of annual percentage loss in live storage capacity obtained is zone 1 (0.03%-1.074%), zone 2 (0.0045%-1.41%), zone 3 (0.031%-1.66%), zone 4 (0.05%-2.180%), zone 5 (0.09%-1.17%), zone 6 (0.19%-0.65%), zone 7 (0.006%-1.449%).

1. Introduction

Reservoirs, created by dams on rivers, lose their storage capacity due to sedimentation. Rivers in India carry only 5% of the global water runoff but they transport about 30% of the total sediment carried to the oceans (Jeyakanthan, V. S., & Sanjeevi, 2013). A large proportion of the transported silt eventually gets deposited at different levels of a reservoir and causes reduction not only in dead storage but also in live storage capacities. It is estimated that annual water storage capacity losses ranged from 2.3% in China to 0.5% in India, with a worldwide average of about 1% (Majumdar, P. K. 2015). The consequence of loss in storage due to sediment accumulation precludes the intended long term usages of reservoir such as irrigation, hydro-power generation, water supply, flood control, recreation etc and may even cause operational problems. Periodic capacity survey of reservoir is thus essential to ascertain the rate of sedimentation and reduction in storage capacity for efficient and productive management of water resources.

Space technologies, including satellite remote sensing technology in particular, have demonstrated proven capabilities in assessment and management of water resources. The Satellite Remote Sensing method has shown enormous promise for providing wealth of data and information that were deficient with the in-situ observations (P. S. Roy et.al, 2010). Multi temporal satellite data from have been used as an aid to capacity survey of many reservoirs in a cost and time effective manner in India. While this technique helps in revising capacity table between full reservoir level and minimum draw down level, loss of dead storage capacity can be obtained only through conventional hydrographic survey. The capacity surveys of reservoirs in India although dates back to as early as 1870, the systematic surveys started only in 1958 when it was established that the live storage of reservoir is getting reduced due to siltation. Since the silting of reservoirs is of vital concern to the functioning of projects systematic efforts have been made by Ministry of Jal Shakti, Government of India to evaluate capacity of reservoirs. The Working Group for National Action Plan for Reservoir Sedimentation Assessment using Satellite Remote Sensing (SRS) under the Chairmanship of Member (WP&P), Central Water Commission set up in the year 2001, recommended for laying emphasis and high importance to carrying out reservoir sedimentation surveys in the country. It recommended for need to adopt composite method coupling both the hydrographic technique (below MDDL) and SRS technique since the latter does not cover the area of reservoir below MDDL. The periodicity of the composite reservoir sedimentation survey could be set as 10 years. It has to be complemented by mid-term survey by SRS technique every 5 years. With the regular reservoir sedimentation surveys, a database could be created for the reservoirs located in various regions of the country, which can be utilized to derive the sediment yield from different types of catchment areas.

Remote sensing technique has an edge over conventional methods like hydrographic survey in assessment of present capacity of reservoir as surveys based on remote sensing data are faster and economical. The added advantage of this technique is the capacity of reservoir can be established for earlier years also. The conventional techniques are found time consuming, costly, laborious and require considerable manpower and sophisticated instruments.

Availability of cloud free data throughout reservoir operations poses limitation in Remote sensing analysis using optical images. This is overcome by using microwave data to assess sedimentation loss in reservoirs. Of late Remote Sensing Dte. of Central Water Commission has started assessment of live storage loss using microwave inputs that has advantages over optical inputs as the microwave based imageries are available at frequent time intervals regardless of weather and illumination conditions.

In this paper data on capacity survey of 121 reservoirs distributed all over the country have been considered. The whole country is subdivided into 7 sedimentation zones namely (1) Himalayan Region (Indus, Ganga and Brahmaputra basins) (2) Indo Gangetic Plains (3) East flowing rivers upto Godavari (Excluding Ganga) (4) Deccan Peninsular east flowing rivers including Godavari and south Indian rivers (5) West flowing rivers upto Narmada (6) Narmada and Tapi Basins and (7) West flowing rivers beyond Tapi and south Indian rivers. The paper describes remote sensing approach for estimation of live storage capacity and the outcome of the studies carried out in CWC using optical and microwave imageries.

2. Methodology

Multi date satellite remote sensing imageries provide information on water spread of the reservoir at different elevations between Full Reservoir Level (FRL) and Minimum Draw Down Level (MDDL). An example of False colour composite (FCC) prepared from multi date SRS imageries obtained at different elevations for Kharkhara reservoir in Chhattisgarh is shown in figure 1. The basic principle of revised capacity estimation using remote sensing is that when the sedimentation occurs in a reservoir its water spread reduces with respect to its original area before impoundment (Thomas et.al. 2009). Water spread area of the reservoir is easily delineated using remote sensing technique due to high contrast with surrounding land features in the near-infrared (approximately 0.75 – 1.0 m) of the electromagnetic wavelength as shown in figure 2 (Compendium on Silting of Reservoirs in India, 2015). By taking a series of satellite data, water spread contours are obtained for corresponding elevations and present area-elevation curve is prepared.

Figure1: Multidate False Color Composite Images of Landsat8 for Matatila Reservoir

17-May-17 (301.29m) 01-May-17 (303.79m) 30-Mar-17 (304.71m) 25-Jan-17 (305.53m)

09-Nov-2017(306.35m) 24-Oct-2017(307.03m) 11-Oct-2018(308.46m)

Figure 2: Multidate Microwave Imageries of Sentinel 1A/1B for Idamalayar Reservoir

23-June-2019 (124.078 m) 18-May-2019 (130.019 m) 29-July-2019 (133.618 m)

12-April-2019 (138.937 m) 19-Mar-2019 (144.259 m) 23-Feb-2019 (148.748 m)

12-Jan-2019 (154.320 m) 15-Sept-2019 (158.868 m) 26-Sept-2018 (160.840 m)

14-Sept-2018 (162.501 m) 09-Aug-2018 (169.950 m)

2.1 Water Spread Area Estimation

Reduction in capacity of reservoir at different levels is depicted by reduction in water-spread area (WSA)

at different water levels. Estimation of water-spread area is done using various digital image processing

(DIP) techniques. The technique adopted for water-spread area estimation are as follows:

Generation of False Color Composite (FCC) and analysis of histogram in case of optical images

SAR data Pre-processing using Sentinel Application Platform (SNAP) for Microwave images

Thresholding using ARC-GIS

The digitally processed images of Idamalayar Reservoir showing its water spread area for eleven

overpass dates are shown in fig. 3.

Figure 3. Superimposed water spread area of Idamalayar reservoir

The actual reservoir storage between the observed water levels is computed using trapezoidal formula. This helps in generating present elevation-area-capacity curves and comparison of this curve with the original curve prepared before reservoir impoundment or the ones obtained from subsequent sedimentation surveys provides a realistic picture of change between two periods and enables computation of loss in capacity due to sedimentation. The detailed methodology explained in the form of flowchart is given below.

Figure 4. Flowchart for Methodology of SRS technique

3. Results and Discussion

The loss in live storage capacity of 121 reservoirs scattered all across the country have been estimated using SRS technique. For the analysis the whole country was classified into 7 zones and in each zone a number of reservoirs were studied. The different zones and list of reservoirs studied is shown in map in figure 4. These zones were created based on several factors which affect the rate of sedimentation such as hydrometeorology, physiography, climate etc. The analysis of capacity survey of the reservoirs distributed in different zones show a wide variation in the annual percentage loss in live capacity. Zone-wise distribution of reservoirs with respect to annual percentage loss in live capacity is shown in table 1. It was observed that for maximum reservoirs the annual percentage loss in live capacity was in the range 0.1-0.5%. The zone-wise annual percentage loss in live storage (minimum & maximum) is given in table 2.

Table 1. Distribution of reservoirs with respect to annual percentage loss in live cacpacity

S.No. Zone

Number of Reservoirs having annual % loss

in live capacity No. of

reservoirs

considered <0.1% 0.1%-0.5% 0.5%-1.0% >1.0%

1 Himalayan Region (Indus,

Ganga and Brahmaputra basins) 1 3 3 1 8

2 Indo Gangetic Plains 1 10 6 3 20

3 East flowing rivers upto

Godavari (Excluding Ganga) 3 9 1 1 14

4 Deccan Peninsular east flowing

rivers including Godavari and

south Indian rivers 7 21 7 4 39

5 West flowing rivers upto

Narmada 1 8 1 - 10

6 Narmada and Tapi Basins - 3 1 - 4

7 West flowing rivers beyond Tapi

and south Indian rivers. 4 5 1 2 12

Total no. of reservoirs 17 59 20 11 107*

*For remaining 14 reservoirs out of 121 either error in original survey has been recorded or hydrographic survey

has been recommended.

Table 2. Zone-wise annual percentage loss in live storage capacity

Zone Annual % loss in live capacity

Minimum Maximum

1 0.0300 1.074

2 0.0045 1.410

3 0.0310 1.660

4 0.0500 2.180

5 0.0900 1.170

6 0.1900 0.650

7 0.0060 1.449

Figure 5: Reservoirs studied for assessment of loss in live storage

4. Conclusions

Remote sensing technique has an edge over conventional methods like hydrographic survey in assessment of present capacity of reservoir as surveys based on remote sensing data are faster and economical. The added advantage of this technique is the capacity of reservoir can be established for earlier years also. The conventional techniques are found time consuming, costly, laborious and require considerable manpower and sophisticated instruments (Thomas et. al. 2009). One of the limitations of remote sensing technique is that sedimentation taking place below MDDL cannot be measured. Thus, changes can be estimated only in live capacity of reservoir. Considering these limitations, it has been recommended by the working group for national action plan for reservoir, both the techniques of reservoir capacity survey i.e. Hydrographic and Satellite remote sensing should be used complementary to each other. It would be appropriate if hydrographic surveys are conducted at longer intervals and remote sensing based sedimentation surveys are carried out at shorter intervals. Availability of cloud free data throughout reservoir operations also poses limitation in the analysis. This is overcome by using Microwave remote sensing inputs that has the advantage that cloud-free imageries are available throughout the year at frequent interval as they are not affected by weather or illumination conditions.

REFERENCES

1. Compendium on Silting of Reservoirs in India (2015), WS&RS Directorate, CWC, New Delhi.

(Publication no. 113/2001).

2. Jeyakanthan, V. S., & Sanjeevi, S. (2013). Capacity survey of Nagarjuna Sagar reservoir, India using

Linear Mixture Model (LMM) approach. International Journal of Geomatics and Geosciences, 4(1),

186.

3. Majumdar, P. K. (2015). New dimensions of reservoir sedimentation: a case study of Khodiyar

Reservoir, India. Lakes & Reservoirs: Research & Management, 20(1), 42-53.

4. Narasayya, K. (2013). Assessment of reservoir sedimentation using remote sensing satellite

imageries. Asian Journal of Geoinformatics, 12(4).

5. P.S. Roy, R.S. Dwivedi & D. Vijayan (2010), Remote Sensing Applications, NRSC/ISRO, ISBN 978-

81-909460-0-1, Hyderabad, India.

6. Sanjay k Jain (2000), Assessment of Sedimentation in Bhakra Reservoir Using Remote Sensing,

Hydrology Journal 23.

7. Thomas, T., Jaiswal, R. K., Galkate, R. V., & Singh, S. (2009). Estimation of revised capacity in

shetrunji reservoir using remote sensing and GIS. J. Indian Water Resour. Soc. Vol, 29(3).

8. W.M. Tembhurney , Yogesh Paithankar & Prashant Kumar Gupta (2012), Compendium on Siltation in

selected Reservoirs in India using Remote Sensing Techniques, Remote Sensing Directorate, CWC,

New Delhi

9. Report of working group for National Action Plan for reservoir sedimentation assessment using

satellite remote sensing (2002), CWC, New Delhi.

10. Technical report on Sedimentation Assessment of Matatila Reservoir, Uttar Pradesh on through

Satellite Remote Sensing, Remote Sensing Dte, CWC, May 2019, pp 1-32.

11. Technical report on Sedimentation Assessment of Idamalayar Reservoir, Kerala on Idamalayar river

through Satellite Remote Sensing, Remote Sensing Dte, CWC, January 2020, pp 1-30.