2. 2
Indus River System

3. 3
Irrigation Scenario at the time of Partition
 The partition in 1947 brought only 20% of the canal
system of undivided Punjab to India’s share with 50%
population.
 The “Upper Bari Doab Canal” between the Ravi and
the Beas (1859) and the “Sirhind Canal” in southern
Punjab (1872) only came to India’s share.
 Construction of Bhakra-Nangal Project was started in
the year 1948.
History of Bhakra-Beas Projects

4. 4Bhakra Beas
Nation’s Pride

6. 6
Height of Dam : 225.55 m (740 feet )
Gross Storage capacity : 9621 million m3 (7.80 MAF)
Area of Reservoir : 168.35 Sq. km. (65 Sq. Miles)
Length of the Reservoir : 96.56 km. (60 Miles)
Installed capacity : 1050 MW (Uprated to 1325 MW)
Bhakra Dam
Bhakra Nangal Project

7. 7
Beas Project
Unit-II Beas Dam at Pong
Height of Dam : 132.59 m (435 feet)
Gross Storage Capacity of Reservoir : 8570 million cu m (6.95 MAF)
Area of Reservoir : 260 Sq. km (100 Sq. Miles)
Length of Reservoir : 41.8 km (26 Miles)
Installed capacity : 360 MW (Uprated to 390 MW)

8. 8
Satluj & Beas Basins
BHAKRA DAM
BEAS
DAM
Nangal
Manali
Mandi
Suni
Rampur
Sangla
Dehra
Pandoh
Slapper
Tabo
Kaza
Pooh
Sainj Khad
Kangra
Kullu
Bilaspu
r
TIBET
N
Satluj Catchment :
56980 Km2 (20000
Km2 in India)
Beas Catchment:
12560 Km2
Legend:
International Boundary
Catchment Boundary
Rivers/Khads
Gobind Sagar
Pong
Reservoi
r
Palampur
Sundernagar
Nauti Khad
Nogli Khad
Juni
Khad
Alsaid
Khad
8

9. 9
RAJASTHAN
CHANDIGAR
H
DELHI
Beas (Pong)
Dam
Pandoh Dam
Ranjit Sagar(Thein)
Dam
Bhakra
Dam
Nangal
Dam
Harike
H/W
Sutlej River
Ropar H/W
Madhopur
H/W
Sirhind
Canal
Anandpur Sahib
H/Channel
Nangal H/Channel
Tajewala H/W
Madhopur
Beas Link
BeasSutlej
Link
Sutlej, Beas, Ravi &
Main Canal Network
Ghaggar H/W
Bikaner
Jaisalmer
Manak Escape
International
Border
State
Boundary
River
Canal/Branch
Legend:
Dam/HW
N
Head
BML
Har. Con.
Pt. RD
1,60,000’
HR. Con.
Pt. RD
3,90,000’
UTTAR
PRADES
H
J & K
HARYANA
PUNJAB
HIMACHAL
PRADESH
Ferozepur
Feeder’
Wazirabad
Barrage
Okhla
Barrage

10. 10SATLUJ AND BEAS BASIN

11. PROPOSED
STATIONS 85
SATLUJ
58
GAUGING
24
RADAR 6
BUBBLER
AND
CABLEWAY 5
BBMB
UPGRAD. 13
HYDRO-
MET. 34
S.W.E. 9 A.R.G. 14
FULL
CLIMATE 6
SNOW
DEPTH ON
IMD 5
BEAS 27
GAUGING
18
RADAR
12
BUBBLER
AND
CABLEWAY 5
BBMB
UPGRAD.
1
HYDRO-MET.
9
S.W.E 0 A.R.G. 3
FULL
CLIMATE 5
SNOW
DEPTH ON
IMD 1
CLASSIFICATION OF BBMB DAS STATIONS

12. Telemetry Data – Snow Water Equivalent
Snow Pillow Installed at Chumar, Elevation 14668 ft
12

13. Telemetry Data – Snow Water Equivalent
Snow Pillow Installed at Tso-Morari, Elevation 14845 ft
13

14. Telemetry Network – Rainfall data
Automatic Precipitation Gauge Installed at Kalpa, Elevation 9050 ft
14

15. Telemetry Data – Full Climatic Stations
Full Climatic Station Installed at Pandoh Dam, Elevation 3000 ft
15

16. Telemetry Data – Water Level Recorder
Automatic Water Level Recorder
Installed at Olinda, downstream of
Bhakra Dam
Elevation : 1200 ft
16

17. BBMB RTDSS Integrates the Processing from Data to
Water Management Decisions
Data Processing
Data Storage
ModelingObserved
Data
Water Control
Management
Decisions
Instructions
SERVERS
Public and
CooperatorsField Office
Weather
Forecast

18. Modeling - Process
Weighted
Average
Precipitation
• IMD Rainfall
• Telemetry Precipitation
• Satellite Precipitation
• RIMES forecast
• Geographical shapes
Rainfall
Runoff Model
• Sub catchments Area
• Parameters
• Snow coverage and depth
• Temperatures
Hydrodynamic
Model
• Cross sections
• DEM
• Flow parameters
• Structures
Inflow and
water levels
forecasts
18

19. THE VIEW OF SATLUJ AND BEAS RIVER BASINS WITH SUB BASINS,
HYDROLOGICAL,HYDRODYNAMIC AND RESERVOIR SIMULATION
MODELS WERE DEVELOPED DURING HP-II

20. MIKE CUSTOMIZED - Interface
20

21. Data Management - Interface snapshot
21

22. THE DATA ACQUSITION AND VISULIZATION INTERFACE IN RTDSS AS
DATA RECEIVED FROM VARIOUS SOURCES LIKE BBMB TELEMETRY ,
IMD , TRMM , MODIS AND TRMM CAN BE SHOWN IN DIFFERENT LAYERS

23. THE DATA CAN BE VISULIZE IN GRAPHICAL AND TABULAR FORMAT AS
WELL AS THE QUALITY OF DATA RECEIVED CAN BE CHECKED WITH
QUALITY FLAGS

24. THE PHOTOS,REPORTS, WEBPAGES AND TIME SERIES DATA
CAN BE ASSOCIATED WITH DISPLAYED ICONS IN RTDSS

25. THE 500M RESOLUTION SNOW COVERED IMAGRIES FROM MODIS
AQUA AND TERRA RECEVIED DAILY FOR SNOW EXTENT IN VARIOUS
ELEVATION BANDS snow.wmv

26. Near Real time 3 Hours Precipitation Data
Obtained from Tropical Rainfall Measuring Mission
(TRMM) Available at 0.25 degree grid trmmm.wmv

27. THE 72 HOURS PRECIPITATION FORCAST DATA RECEIVED FROM
REGIONAL INTEGRATED MULTIHAZARD EARLY WARNING SYSTEMS FOR
ASIA AND AFRICA (RIMES) rimes.mp4

28. THE REAL TIME SIMULATION AND INFLOW FORCASTING BASED
ON RIMES FORCAST IS CARRIED OUT AUTOMATICALLY
IN RTDSS ,VARIOUS SCENARIOS CAN ALSO BE GENERATED

29. HD Modeling - Results
Simulation for 5 days before Time of Forecast (ToF) and 3 days after ToF
Actual Rainfall data till time of forecast
RIMES forecasted rainfall for 3 days
Simulation Period
Forecast Period
29

30. An Achievement
June to September Cummulative inflow
1988 – 12204 MCM
2013 – 12024 MCM
RELEASESE IN 1988 ARE
24SEPTEMBER=70767CUSEC 25SEPTEMBER=123767CUSEC
26SEPTEMBER=117170CUSEC 27SEPTEMBER=114156CUSEC
Flood Gates had to be opened in 1988 but better management could avoid
floods in 2013
Dams Levels on 20th - September
Bhakra – 1678.32 ft
Pong - 1390.01
Achieved first time in 25 Years after 1988
30

31. Flood Modeling
 Indian Satellite CartoSAT 30 m resolution DEM used
 1-D HD model run with 2-D mapping
 Model setup for Satluj River between Nangal and Ropar
 September 1988 (flood period) Data used as release from Nangal
 Time varying 2-D flood inundation map generated
 The results uploaded to Google earth for visualization
Data Acquisition
System
Telemetry Data
IMD Data
RIMES Forecast
Modis Snow Imageries
NASA Satellite Precipitation
Manual Observation Data
Data Storage and
Management
System Architecture
Data Flow
Backup and Security
Modelling Tools
Weighted Rainfall
Rainfall Runoff
Snow Melt
Hydrodynamic
Allocation Model
Flood Models
Results Visualization
and Dissemination
Realtime DSS Interface
Workstations
Remote Locations
Website – Dashboard
Daily Reports
Email and SMS Alerts
31

32. Flood Modeling
32

33. 33
Real Time DSS In BBMB
Envisaged . . .
A well structured, user friendly and
complete water resources management system
Provision of forecasting snowfall & rainfall
Estimation of corresponding discharges in rivers
Advanced Observation & communication System
To provide better means for organizing, accessing and
evaluating a wide range of data & alternatives to
establish sound resultant information

34. 34
RTDSS Benefits
Quicker & better
designed to understand, explore alternate course of actions,
predicting impacts and solving problems
Better access to information
Improved evaluation tools
Enhanced communication
Improve System Efficiency
Efficient data gathering, storage and processing
Facilitate communication in broader organizational context
Promote learning & Training
Reduce Flood Impacts & Improve Drought Preparedness
Operational Flexibility & Efficiency
Replace old traditional system with a modern system;

35. 35
Expected Benefits of RT-DSS

36. June 2013 Uttrakhand Disaster
Observed heavy Rainfall just below Satluj –
Gagna basin ridge divide
36

37. Run Video
Cummulative Rainfall – 15-20 June
2013uttrakhand trmm.mp4
Black Cells shows
heavily affected areas
37

38. THANK YOU
38