Approach/Methodology of Real Time Flood Forecasting-

Maharashtra state(World Bank Aided, India Hydrology Project Phase II)

Maharashtra (SW)Chief Engineer, Planning and Hydrology, Nashik

Krishna basin

Tapi basin

Godavari basin

West FlowingRivers Basin

Narmada basin

Flood Prone Areas in Maharashtra• About 7% area of Maharashtra state is flood prone:• 1. Mumbai (Mithi river) and 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)

• The Krishna and Bhima sub basins experience highly variable rainfall both in space and time ranging from 6000 mm in upper catchments to 400 mm in rain shadow areas (lower catchments).

• The state experiences flash floods particularly in Western

Ghats including Krishna and upper Bhima basins. For instance, Sangli, Kolhapur districts in Krishna basin and Pune, Solapur districts in Bhima basin experienced severe floods several times during recent decade (Year 2005 and 2006).

• Floods have caused heavy damages to the assets and loss of life.

Rainfall and Floods in Krishna basin

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

DistrictHuman 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)

Losses due to floods in Krishna River Basin

Human & Cattle losses in flood 2005 & 2006

Panchganga River Flood 2005

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.

• The Govt. of Maharashtra Vide Resolution dated 04/01/2007 constituted technical committee having main task of providing guidance for precise determination of reservoir releases during emergency situation in the state.

• The committee submitted the report in May 2007 by recommending Integrated Reservoir Operation, Basin Simulation and Real Time Flood Forecasting.

• To start with, for basin simulation study of Krishna sub basin, one division (Basin

Simulation Division, Pune) engaged and to supplement study with Real time data acquisition system, subject was included in the Mid Term Review of World Bank aided India Hydrology Project Phase-II, during October 1-14, 2009, (RTDSS: Maharashtra) as a new component.

• The RTDSS: Maharashtra includes both Krishna and Bhima sub basins in Maharashtra.

Recommendation of Technical Committee and RTDSS Maharashtra

Real time streamflow forecasting and reservoir operation system

14

INSAT Satellite

Internet

Decision Support Center

1. Real Time Data Acquisition System

The system would facilitate reservoir operators to act on time and prepare stakeholders for the floods.

The forecast of river flow and mapping of flood zone will help in taking the decisions such as evacuation of the areas likely to be affected well in advance.

In addition, the reservoir operation system would facilitate the optimization of the storages for ensuring flood cushion and improving agricultural productivity.

This system would revolutionize hydrologic monitoring system in the Krishna basin which will be extended to other basins later on.

Planned Benefits of the System

Planning and finalization of network:

1. Prepare inception proposal for each component with necessity of the work based on authentic information source defining problems in the area, objective of proposed work with scope, break up of activities into distinct groups with cost estimates. Two basic components will be i. Real time data acquisition system ii. Real time stream flow forecasting and integrated reservoir operation system.

2. Apart from this; provisions for River cross section survey works, site preparation and repairs to existing setups required for installation of RTDAS, Data collection and processing etc. may be done separately. Preparation of layout of the stations in line with the guide lines of IMD, WMO, CWC etc.

3. RTDAS Network Finalization: Finalization of category of stations, investigation, information collection, processing, sensor placements, communication mode finalization and arranging it in organized manner as a schedule of requirement.

• Station categories: Rainfall(ARS), River gauging (ARWL & RDS), Reservoir(ARWL & ODS), climate (AFCS), Canal gauging (ACWL& CDS)

• Check list prepared for information collection can be sent to different authorities(Divisions under regional CE’s in the basin) to collect data for each category of station and used in the finalization of schedule of requirements.

• Identify stations operated by co-operator agencies viz. IMD, CWC, ISRO, Agri. Dept etc. and are in operation.

a) Rain fall stations: Identify major and medium projects in the basin with compilation of their catchment area. Based on WMO, IMD, norms finalize required no. of stations. Finalize the locations to ensure that catchments are represented adequately facilitating drawing of Theissen polygon, avoiding too acute(<30 degree) and obtuse (>120 degree) angles.

i) Due consideration for local topography may be given. First priority must be up gradation of existing stations so that solution to land availability and security aspect is easier. Site selection shall follow IMD/WMO norms of exposure conditions.

ii)Network in free catchment may be finalized by integrating it with climate stations (Rainfall is one of parameter measured at AFCS).

iii)Existing civil works viz. available rooms, fencing, if are better can be utilized to reduce cost of civil work.

iv) Rainfall stations planned to be installed at dam sites can be combined either with reservoir stations or canal sites if distance is less than @ 300 m and line of sight is clear.

v) For area not represented by existing network new stations are to be proposed.

b)Reservoir station: Water level can be measured with Radar, Shaft Encoder or Bubbler type of sensors. Spillway discharge can be measured with provision of gate sensor for each gate (measures gate opening) and computation of discharge by formula.

If well up to MDDL is available Shaft encoder is best, if masonry/concrete upright wall of dam near gorge portion is available Radar is good choice. However in case of earthen dam with saddle spillway and bed level at spillway portion is much above MDDL and no availability of well, Bubbler is an option (canal intake well from outside can be used, approach channel to canal intake are deeper portions). Intakes or well with gates and other moving parts inside it etc. are not useful for sensor installation. From emergency situations point of view more reliable and uninterrupted communication is necessary for dam sites. VSAT supports two way communication and if SCADA is on future agenda, VSAT is a good option for dams.

c)River gauging sites: The guidelines specified by CWC, manuals provided in HPI needs to be followed. i) identify critical flood pone area, important cities/towns in the basin and study the existing network. Ii) Reservoirs with gate sensor arrangement also acts as a gauging site. iii) However if rivers are too long, tributaries carrying large floods are joining the main river and important towns/localities needs early warning; river gauging sites can be proposed at u/s of city or on tributaries near confluence and on main river downstream.

iv) Important barrages along the rivers also can be provided with water level sensor. v) Existing forecast points finalized by Valley corporations/CWC may be included on priority. vi) Availability of stage discharge curves at river gauging sites is a important requirement.

vi)Communication: Mostly stations in the catchment do not have enough mobile signal strength and can be placed on VSAT/INSAT. For free catchment stations GSM can be used. Also in future if SCADA is to be implemented VSAT seems to be a good choice as it supports two way communication.

The planned network were discussed with River basin authority for its suitability for the purposes.

ABSTRACT of proposed RTDAS Network

Basin Name

Rain Gauge StationsRiver Water Level

(Stage) & River Discharge

Reservoir Water Level & Outflow

Discharges FCS Remark

Krishna

Within Catchment (37)

In free Catchment (30)

13 + 1 CWC   14 + 9 AWS  

Existing Proposed Existing Proposed Existing Proposed Proposed Existing Proposed  

25 12 26 4 10 3 19 7 7  

Bhima

Rain Gauge Stations River Water Level

(Stage) & River Discharge

Reservoir Water Level & Outflow

DischargesFCS  

Within Catchment In free Catchment 18 + 2 CWC   26 + 20 AWS  

Existing Proposed Existing Proposed Existing Proposed Proposed Existing Proposed  

22 35 19 6 14 4 27 12 14  

Total =67 + 82 = 149= (13 + 18) + (1 + 2) CWC = 31 + 3 CWC

= 19 + 27 = 46= (14 + 26) + (9 + 20) AWS = 40 + 29

AWS 

Final tally 149 31 + 3 CWC 46 40 + 29 AWS 298

RTDAS network Installed

Sr No Description

Proposed number of stations

Commissioned stations Balance stations

1 Automated Rainfall Stations 127 127 00

2 Automated Full Climate Stations 39 39 00

3 Automated River water Level and River Discharge Stations 31 31 00

4Automated River water Level and River Discharge Stations combined with Automated Rainfall Stations

03 03 00

5Automated River water Level and River Discharge Stations combined with Automated Full Climate Stations

03 03 00

6 Automated Reservoir water Level and outflow Discharge Stations 27 26 01

7Automated Reservoir water Level and outflow Discharge Stations combined with Automated Rainfall Stations

19 19 00

Total 249 248 01

Data AvailabilityHydro meteorological data:Rainfall data : SRG (twice daily)and ARG (hourly): Source- HP(SW), Reservoir

Management wing of WRD, IMD, ISRO.Climate data: Dry & wet bulb temp (to know RH), max and min temp, wind

speed(Average and instantaneous), wind direction, pan evaporation, rainfall, solar radiation: FCS (twice daily): Source- HP(SW), IMD,ISRO

River gauging data: stage (twice daily/hourly) and discharge (twice daily); stage discharge curves, zero gauge, HFL, type of station(bridge outfit/winch & cableway/wading). AWLR condition Source- HP(SW), CWC

Reservoir data: dam type, salient features, various control levels, area capacity elevation curves, time series data of inflow, spillway discharge, evaporation, releases for different uses (irrigation, hydropower, drinking/industrial demands) , guide rules, rule curves, spillway type, No. and types of spillway gates, discharge tables for spillway gates etc: Management wing of WRD.

• River Cross section data: Spatial interval @ 500 m to 1 km: Only @ 5 % of cross sections required were available. Source- Management wing of WRD. Physical survey was carried out in two working season.

• Latitude, longitude of all stations planned are verified with hand held GPS. Check list for all category of stations were prepared and was circulated for field offices to know site situation and were analyzed and organized for bidding document.

• Computerized and well organized data of rainfall, climate station was available. Computerized Reservoir/Tank data was made available by SE, KWDT Office at Pune. However few reservoirs data manuscript were available and needed computerization. Fitting Rating curves for river gauging sites was imp. Task. Spillway rating curves, area elevation capacity curve, Rule curves, spillway gate discharge table needed computerization.

• DEM, Satellite imageries, GIS layers were used by Consultants.

Installations under RTDASAutomated Rainfall Stations :1) Thoseghar 2) Pabal

Automated River Water Level (Stage) and Discharge Stations: 1) Kalyani Nagar bridge 2) Pimple Gurav

Automated Full Climate Stations : 1)Bhima nagar 2) Rosa

Automated Reservoir Water Level and Outflow discharge stations: 1)Kadvi 2) Radhanagari

Automated Reservoir Water Level and Outflow discharge station :1)Dhom Balkawadi (Bubbler) 2) Urmodi (Shaft Encoder)

ADCP Measurement : Pimple Gurav river gauging site

Pimpale Gurav_GD1.pdf

Discharge Measurement using ADCP in Krishna & Bhima Basin

Cost of Main component of RTDSS

• Administrative approval cost: Rs. 3033 lakhs; Expenditure: @ 2900 lakhs• Technical consultancy for Implementation of RTSF and ROS for Krishna

and Bhima basins• Consultants: DHI(India), Water and Environment Pvt. Ltd, India• ICB Tender Cost: Rs. 762.39 Lakhs (Note: Service tax @12.36% to be

added separately, Payments are based on Euro exchange rates which varied from 62 to 84 during contract operation period); Contract Period: 42 months (18 months for main task and 24 months support period).

• Supply, Installation, Testing, Commissioning and Maintenance of RTDAS for Krishna Bhima basins of Maharashtra

• Contractor: Mechatronis Systems Pvt.Ltd., Pune• ICB Tender Cost: Rs. 1790.07 Lakhs (One year warranty period cost

included; VAT @ 8% and Service Taxes 12.36% extra); Contract Period: 18 months; One year warranty Period, 4 year Post warranty period.

• River cross section survey work: @ Rs. 68 lakhs• Electrification , Environmental control of data center, furniture etc: 12

lakhs• WSR repairs for installation of Shaft encoders: @ 7 lakhs

Important Issues

• Sufficient and qualified, trained staff not available

• Liability of HPII- 1.60 Crore• Four year Operation and Maintenance

contract- budget availability• Support of DHI is necessary even after support

period (ending by FEB 2015)

Modelling the hydrological system(Rainfall Runoff Model)

Time Delay

Time Delay

Time Delay

Time Delay

NOW!

Future!

SOIL MOISTURE PROFILE

Depth

L

Lmax

GWL

Sy

GWL

GROUNDWATER STORAGE

Root Zone

GWPump

BF

BaseFlow

GWLBFo

CKBF

LOVER ZONE STORAGELmax

L

BFu

DL

CAFlux

SURFACE STORAGE UUmax

OF

IF

G

RAIN

SNOW

SNOW STORAGE

PPs

QIF

InterFlow

Pn

CK1

CK2

QOF

Overland Flow

Ep

Ea

Owp Ofc Osat

SOIL MOISTURE PROFILE

Depth

L

Lmax

GWL

Sy

GWL

GROUNDWATER STORAGE

Root Zone

GWPump

BF

BaseFlow

GWLBFo

CKBF

LOVER ZONE STORAGELmax

L

BFu

DL

CAFlux

SURFACE STORAGE UUmax

OF

IF

G

RAIN

SNOW

SNOW STORAGE

PPs

QIF

InterFlow

Pn

CK1

CK2

QOF

Overland Flow

Ep

Ea

Owp Ofc Osat

The Hydrological Model(Conceptual catchment Model)

• Coutinuous Moisture Accounting model such as NAM holds a memory of the catchment history

Memory of past days of rainfall in the Soil Storages, distributed over the basin

Memory of past monsoon rainfall in the groundwater storage, distributed over the Basin

Rainfall – runoff model

A Basin is divided into a large number of sub-catchment and Computed Catchment runoff are routed through the

river network

Example of perfect calibration (Koyna)

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

Simple Inflow forecasting (CWC)

With knowledge on conditions upstream, downstream flows can be estimated

U/S Station

D/S Station

Hydrological Modelling, How does it help in Inflow forecasting?

Hydrological modelling helps quantifying the reservoir inflows

Rainfall(current and future – QPF)

Basin wise water resources simulation model

MIKE BASIN MODEL (applied in the DSS- Planning Project, HP-II)

Krishna-Bhima MIKEBASIN Model

Hydrodynamic model for flood forecast :Introduction to MIKE 11

MIKE 11 is a world standard in 1D river modelling for simulating flow and water level, water quality and sediment transport in rivers, floodplains, irrigation canals, reservoirs and other inland water bodies.

PHYSICAL SYSTEMRiver Network

FloodplainsStructures

PHYSICAL LAWSConservation of Mass

Conservation of Momentum

SCHEMATISERepresent by a simple

Equivalent System

DISCRETISEExpress as a Finite Difference Relation

NUMERICAL MODEL

Modelling of unsteady flow is based on three fundamental elements:

• A differential relationship expressing the physical laws

• A finite difference scheme producing a system of algebraic equations

• A mathematical algorithm to solve these equations

HYDRODYNAMICS

The MIKE 11 Hydrodynamic Module

Saint Venant Equations

6 Point Abbott-Ionescu Finite Difference Schemedynamic/diffusive/kinematic

Looped Network

Q

x

h

t

Q

t

QA

x

h

x + b = 0, + + gA = 0

2

Databases

•Topographical Data

•Time Series DataWater Quality

Sediment Transport

Hydrodynamics

Rainfall-Runoff

Advection-Dispersion

Flood Forecasting

Modules and Databases that Interact Dynamically

ArcGIS

Pre- and Post- Processing

MIKE11 STRUCTURE

Reservoirs & Hydraulic StructuresWide Range of Structures Requested – and Available in MIKE 11

The Bhima-Krishna Network

Hydrodynamic model calibration

Sequence of Steps in Forecasting System1.Import data from RTDAS

2.Import data from Pune Flood Control www.punefloodcontrol.com

3.Import QPF – Quantitative Precipitation Forecast

4.Mike 11 Simulation

5.Results in .dfs0 files

6.Prepare Results for WEB Page

7.Archival of Results

8.Uploading Forecast to Web Saving Forecast in KBS

http://www.rtsfros.com/mahakrishna

(Real time data and forecast of water level and discharge can be viewed on this website)

WEB Portal of RTSF&ROS

Model Outputs (Flood maps)

Simulated flood map of Pandarpur for a high discharge of 325,000 cusecs)

Scenario - Reservoirs

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STATISTICAL ANALYSIS OF RESERVOIR WATER LEVEL

Comparision of Model Predicted Releases from Reservoir and Actual Releases (Outflow) : Krishna Reservoirs

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

Comparison of Forecasted Water Level and Water Level by Sensor for Reservoirs (One Day Forecast)-July 2013

Reservoir Water Level Comparison ( Sensor & RTSF Model): July 2014

River Discharge Comparison ( RTDAS level and derived from G-D curve & RTSF Model)

River Water Level Comparison ( Sensor & RTSF Model): July 2014

Travel time computation

75

Indicative Area For LiDAR Survey for Sangli

THANK YOU