Real time decision support system krishna and upper bhima river basin system in maharashtra

1. Presentation by: D.A.Bagade
Ex. Engr, Basin Simulation Division Pune
HP(SW), WRD, Maharashtra

3. Krishna basin
Tapi basin
Godavari basin
West Flowing
Rivers Basin
Narmada basin

4. Flood Prone Areas in Maharashtra
About 7% area of Maharashtra state is flood prone:
1. Mumbai (Mithi river) & Thane Metropolitan cities (July 2005)
2.Konkan Region - Vashisthi river (Chiplun), Savitri river (Mahad
1923,1976,1989,1994)), Amba river (Nagothane, Pen), Ulhas river
3. Krishna basin- Krishna, Panchganga, Warna (Sangli and Kolhapur
2005, 2006), Mula, Mutha (Pune), Bhima (Pandharpur 2006).
4. Godavari Basin- Godavari river (Nanded 1962, 1969, 1973, 1975,
2005), Wainganga (Bhandara district 2006 and Brahmapuri taluka
(Chandrapur ), Conflulence of Wardha and Penganga (Chandrapur
proper) (August 1979).
5. Tapi basin- Tapi (Jalgaon district)

5. District
 
Crops &
Infrastructure Land/
Structure
Damages
Horticulture
Total
Farmers SAU's Crops
Govt.
Nursery
Satara 329.3 2.3 63.7 152.9 0.5 548.7
Sangli 744.4 3.5 148.2 98.6 0.4 995.1
Kolhapur 2080.5 26.8 125.7 152.0 1.3 2386.3
District
Human Losses Cattle Losses
2005 2006 2005 2006
Satara 11 23 156 239
Sangli 13 19 224 23
Kolhapur 26 26 236 80
Losses in flood 2005 (Rs.in Million)
Human & Cattle losses in flood 2005 & 2006

7. RESERVOIR OPERATION IN MAHARASHTRA
The reservoirs in Maharashtra are multipurpose including hydropower,
irrigation, domestic and industrial uses.
Though these reservoirs are not specifically provided with flood cushion,
they have moderated flood peaks to considerable extent by proper reservoir
operations.
Reservoirs are operated with rigid schedules as single entities based on the
historical hydro-meteorological data and experience gained.
These methods are often not adequate for establishing optimal operational
decisions, especially where integrated operation of multiple reservoirs for
flood management is contemplated.
In addition, manual data observation and transmission results in a
considerable time lag, between data observed in field and its
communication to decision making level which sometime leaves little time,
for flood forecasts.
Therefore WRD Maharashtra has installed the RTDAS and developed the RTSF
and ROS model for Krishna and Bhima basins of Maharashtra under World Bank
aided HPII project.

10. Sr
No
Item Model Make
1
Data Collection Platform H5000-S
Design Analysis
Associates Inc., USA
2
VSAT Radio & Antenna
Sky Edge Pro
(XC Band)
Gillat through Nelco
3
GSM/GPRS Modem & Antenna
Daul Band EGSM
TMA-M37i and TMN-51t
TCAM
4
Shaft Encoder SE-1
Microcom Design Inc.,
USA
5
Radar Sensor
FMR 240
(40 & 70 m range)
E+H
6 Bubbler Sensor H3553 DAA
7
Full Climate Station Sensors Xport ET
Microcom Design Inc.,
USA
8 Precipitation/Rainfall Sensor TB4 Hydrological Services
9 Gate Sensor MECH_GMS Mechatronics
10 Solar Power & Battery MECH_OBCS Mechatronics
11
VSAT Master Station
Sky Edge Pro (XC Band)
Gillat through Nelco
12 Servers X3100 M4 /Higher IBM
13
Acoustic Doppler Current Profiler
(ADCP)
M9 Sontek

11. Sr
No
Description
Proposed
number of
stations
Commission
ed stations
Balance
stations
1 Automated Rainfall Stations 125 118 07
2 Automated Full Climate Stations 40 38 02
3
Automated River water Level and River
Discharge Stations
33 29 04
4
Automated River water Level and River
Discharge Stations combined with
Automated Rainfall Stations
04 04 00
5
Automated River water Level and River
Discharge Stations combined with
Automated Full Climate Stations
02 02 00
6
Automated Reservoir water Level and
outflow Discharge Stations
29 25 04
7
Automated Reservoir water Level and
outflow Discharge Stations combined
with Automated Rainfall Stations
16 16 00
Total 249 232 17

18. ADCP Measurement : Pimple Gurav river gauging site

20. Pimpale Gurav_GD1.pdf

22. Ichalkaranji : River Water Level Comparison (Manual & Sensor)

23. Daily Rainfall Comparison (Sensor and Manual) July Month:
Khamgaon
Date

R
a
i
n
f
a
l
l

i
n

m
m

25. 485
486
487
488
489
490
491
492
493
494
495
496
13579111315171921232527293133
RTDAS Lake Level in m
Flood Control Cell, Pune Lake
Level in m
W
L

(
m
)
Date

26. Date
W
L

(
m
)

28. 1.The QPF, weighted QPF over the catchment, Real time Rainfall,
Climate, River water level and discharge and Reservoir Water level and
discharge data were disseminated twice/thrice daily basis to the Regional
Chief Engineers and Superintending Engineers in the Krishna & Bhima
basins to support the decision making.
2.Acess to the RTSF and ROS forecast is given to the authorities
(Regional Chief Engineers) of the basin.
3: The field organization was supported by providing Real Time data &
Forecasted results as per demand.
4. Awareness raising activity regarding use of model is initiated with
demonstration of system at WALMI, META, MKVDC, YASHADA, HP.
Now Field organizations are actively involved in use of the system.
5. Real time web application for RTDAS is developed. (live demo..)

29. 29

31. Comparison of Simulated and Observed Discharges for Koyna Catchment
(R2=0.95, Wbl=0.00% (Obs=5660mm/y, Sim=5660mm/y))

32. Hydrodynamic
model calibration

34. Model Outputs (Flood maps)
Simulated flood map of Pandarpur for a high discharge of 325,000
cusecs)

35. Comparision of RTSF Prediction of Releases from Reservoir And
Actual Releases (Outflow) by Dam Authority: Krishna Reservoirs

36. Comparison of Forecasted Water Level and Water Level by
Sensor for Reservoir (One Day Forecast)

37. 37