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

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

  • Presentation by: D.A.Bagade Ex. Engr, Basin Simulation Division Pune HP(SW), WRD, Maharashtra
  • Krishna basin Tapi basin Godavari basin West Flowing Rivers Basin Narmada basin
  • 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)
  • 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
  • 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.
  • 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
  • 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
  • ADCP Measurement : Pimple Gurav river gaug
  • Pimpale Gurav_GD1.pdf
  • Ichalkaranji : River Water Level Comparison (Manual & Sensor)
  • Daily Rainfall Comparison (Sensor and Manual) July Month: Khamgaon Date Rainfallinmm
  • 485 486 487 488 489 490 491 492 493 494 495 496 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 RTDAS Lake Levelin m Flood Control Cell, Pune Lake Level in m WL(m) Date
  • Date WL(m)
  • 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..)
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  • Comparison of Simulated and Observed Discharges for Koyna Catchment (R2=0.95, Wbl=0.00% (Obs=5660mm/y, Sim=5660mm/y))
  • Hydrodynamic model calibration
  • Model Outputs (Flood maps) Simulated flood map of Pandarpur for a high discharge of 325,000 cusecs)
  • Comparision of RTSF Prediction of Releases from Reservoir And Actual Releases (Outflow) by Dam Authority: Krishna Reservoirs
  • Comparison of Forecasted Water Level and Water Level by Sensor for Reservoir (One Day Forecast)
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