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Real time decision support system sutlej and beas river basin system

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Page 1: Real time decision support system sutlej and beas river basin system
Page 2: Real time decision support system sutlej and beas river basin system

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Indus River System

Page 3: Real time decision support system sutlej and beas river basin system

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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

Page 4: Real time decision support system sutlej and beas river basin system

4Bhakra BeasNation’s Pride

Page 5: Real time decision support system sutlej and beas river basin system
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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

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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)

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8

Satluj & Beas Basins

BHAKRA DAM

BEAS DAM

BEAS RIVER

SATLUJ

RIVER

Nangal

Manali

Mandi

Suni

RampurSangla

Dehra

Pandoh

Slapper

Tabo

Kaza

Pooh

PARVATI RIVER

Sainj Khad

Kangra

BASPA RIVER

SPITI RIVER

Kullu

Bilaspur

TIBET

N

Satluj Catchment : 56980 Km2

(20000 Km2 in India)

Beas Catchment: 12560 Km2

Legend:International BoundaryCatchment BoundaryRivers/Khads

SATLUJ

RIVERGobind Sagar

Pong Reservoi

rPalampur

BE

AS

RIV

ER

BSL

Sundernagar

Suke

ti K

had

Bharari Khad

Nauti KhadNogli Khad

Bha

ba K

had

Solding Nala

Tidong Nala

Ban

er K

hadGaj

Kha

d

Neo

gal K

had

Bin

wa

Kha

d

Uhl

Riv

er

Hurla Nala

Sal

asi K

had

Juni

Kha

d Bakhli Khad

Tirthan

River

Beh

ana

Kha

d

Gambar Khad

Als

aid

Kha

d

Kansa

Khad

Gha

nvi

Kha

d

Sho

rang

Kha

d

Mehbor K

hadTaiti K

had

Ropa Khad

Tiang Nala

Rong Tong

Nala

Ligt

i Kha

d

Page 9: Real time decision support system sutlej and beas river basin system

9

RAJASTHAN

CHANDIGARH

DELHI

Beas (Pong) Dam

Pandoh Dam

Ranjit Sagar(Thein) Dam

Bhakra Dam

Nangal Dam

Harike H/W

Feroze

pur

H/W

Sutlej R

iver

Indu

s R

iver

Ravi R

iver

Yam

un

a R

iver

Sutlej River

Beas River

Ropar H/W

Madhopur H/W

UB

DC

Indira

Bikaner C

analEas

tern

Can

al Sirhind Canal

B h

a k

r a M

a i n

L i n

e`

Sirh

ind

Fee

der

Raj

asth

an F

eede

r

BDCAnandpur Sahib H/Channel

Nangal H/Channel

SY

L

Tajewala H/W

Ghaggar River

W.Y

amuna

Canal

Madhopur Beas Link

Bea

s S

utl

ej

Lin

k

Sutlej, Beas, Ravi & Main Canal Network

I

N

D

I

A

Beas

River

GandhiCanal

Ghaggar H/W

Bhakra Main Br.

Fatehabad Br.

Del

hi

Br.

Sirsa Br.

Narw

ana Br.

Bikaner

Jaisalmer

KashmirCanal

Manak Escape

International BorderState Boundary

RiverCanal/Branch

Legend:

Dam/HW

N

P A

K

I

S

T

A

N

Head BML

Har. Con. Pt. RD 1,60,000’

Karni Singh Br.

Sadul Br.

Baruwali

Disty

Kishangarh Link

Jandwala

Disty

HR. Con. Pt. RD 3,90,000’

S G Canal

Barwala

Link

UTTAR PRADES

H

J & K

HARYANA

PUNJAB

HIMACHAL PRADESH

Ferozepur Feeder’

Shah

Nehar

Wazirabad Barrage

Okhla Barrage

M H

C

Rori

Feeder

Page 10: Real time decision support system sutlej and beas river basin system

10SATLUJ AND BEAS BASIN

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PROPOSED STATIONS 85

SATLUJ 58

GAUGING 24

BEAS 27

CLASSIFICATION OF BBMB DAS STATIONS

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

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

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14Telemetry Network – Rainfall dataAutomatic Precipitation Gauge Installed at Kalpa, Elevation 9050 ft

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

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16Telemetry Data – Water Level Recorder

Automatic Water Level Recorder Installed at Olinda, downstream of Bhakra Dam

Elevation : 1200 ft

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BBMB RTDSS Integrates the Processing from Data to Water Management Decisions

Data ProcessingData Storage

ModelingObserved Data

Water Control Management Decisions

Instructions

SERVERS

Public and CooperatorsField Office

WeatherForecast

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18Modeling - 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

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

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20MIKE CUSTOMIZED - Interface

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21Data Management - Interface snapshot

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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

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

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

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

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Near Real time 3 Hours Precipitation Data

Obtained from Tropical Rainfall Measuring Mission (TRMM) Available at 0.25 degree grid trmmm.wmv

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

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

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29HD 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 PeriodForecast Period

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30An 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 - SeptemberBhakra – 1678.32 ftPong - 1390.01

Achieved first time in 25 Years after 1988

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31Flood 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

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32Flood Modeling

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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 riversAdvanced Observation & communication SystemTo provide better means for organizing, accessing and

evaluating a wide range of data & alternatives to establish sound resultant information

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RTDSS Benefits

Quicker & betterdesigned to understand, explore alternate course of actions,

predicting impacts and solving problems Better access to information Improved evaluation toolsEnhanced communication Improve System EfficiencyEfficient data gathering, storage and processing Facilitate communication in broader organizational contextPromote learning & TrainingReduce Flood Impacts & Improve Drought PreparednessOperational Flexibility & EfficiencyReplace old traditional system with a modern system;

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Expected Benefits of RT-DSS

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36June 2013 Uttrakhand Disaster

Observed heavy Rainfall just below Satluj – Gagna basin ridge divide

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Run Video

Cummulative Rainfall – 15-20 June 2013uttrakhand trmm.mp4

Black Cells shows heavily affected areas

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38THANK YOU