Ministry of Earth Science

Technology for Forecasting of Floods

Posted On: 15 MAR 2021 3:19PM by PIB Delhi

Forecasting and prevention of floods are the responsibilities of the Central Water Commission (CWC), Ministry of Water Resources. However, India Meteorological Department (IMD) supports flood warning services of Central Water Commission (CWC) by providing observed and predicted rainfall. In order to meet specific requirements of flood warnings by CWC, India Meteorological Department (IMD) operates Flood Meteorological Offices (FMOs) at 13 locations viz., Agra, Ahmedabad, Asansol, Bhubaneshwar, Guwahati, Hyderabad, Jalpaiguri, Lucknow, New Delhi, Patna, Srinagar, Bengaluru and Chennai. Apart from this, IMD also supports Damodar Valley Corporation (DVC) by providing Quantitative Precipitation Forecast (QPF) for Damodar river basin areas for their flood forecasting activities. Flood Meteorological Offices (FMO) provide meteorological support to the CWC for issuing flood warnings well in advance in respect of 153 river basins.

 

CWC issues flood forecasts as a non-structural measure of flood management, to concerned State Governments depending on the requisition from them at identified locations. CWC also issues inflow forecasts to identified reservoirs for proper reservoir regulation. Flood forecast formulation methodology used by CWC includes:

Conventional statistical correlation methodology: It includes gauge to gauge correlation between base station (upstream of forecasting station) and forecasting station. This method provides advance warning time from 6 to 24 hrs depending upon the terrain.  IMD provides 3 day Quantitative Precipitation Forecast (QPF) in ranges of 0, 0.1-10mm, 11-25 mm, 26-37mm, 38-50 mm, 51-75 mm, 76-100 mm and >100 mm for various  river sub-basins to the concerned Divisional Flood Control Room of CWC through their Flood Meteorological Offices spread all over the country.

Rainfall-Runoff mathematical modeling technology: It includes mathematical modeling of river basin based on rainfall runoff methodology. Input taken is rainfall provided by IMD through its Automatic Weather Station (AWS) & Automatic Rain Gauge (ARG) stations and CWC telemetry stations.  The three days advance forecast is generated using various available rainfall data products as a major input into the system like IMD Gridded Rainfall product and other global rainfall products such as GSMaP (Global Satellite Mapping of Precipitation), GPM (Global Precipitation Measurement) and the IMD forecasted rainfall data (WRF- Weather Research and Forecast, GFS- Global Forecast System). Numerical Weather Prediction (NWP) model products viz. Weather Research and Forecast (WRF) model which is given for 3 days and Global Forecasting System (GFS) model product which is given for 10 days are seamlessly shared by IMD for use in mathematical models by CWC. Mathematical model has been used for formulation of advisories and these advisories are shared with stake holders using dedicated website.

Besides this, CWC is also providing inundation forecast in the same platform using 2-dimensional models for main Brahmaputra and is also shared with beneficiaries through the same website.

Modernization of dissemination of flood forecasts: Dissemination of flood forecasts have been modernised by having a dedicated website. The flood information is also shared via various social media platforms of CWC Flood Forecast dissemination system. Daily Flood Situation Report cum Advisories are also shared with all stake holders as well as general public. CWC has signed an MOU with M/s Google Inc for using their vast repository of high resolution Digital Elevation Models and the power of dissemination to send alerts regarding inundation through Google Platform using the flood forecasts issued by CWC.

Flood Forecasting by CWC uses all the latest technology including remote-sensing, Geographical Information System (GIS), Internet, Artificial Intelligence and Machine Learning in development/ running/ formulation and calibration of Mathematical models and for providing Inundation Alerts which are closely at par with international standards.

At the end of flood season CWC prepares an Appraisal of flood forecasting activity in which the accuracy/performance of the forecasts are compiled.  In conventional methodology of forecast, a level forecast is deemed to be accurate if the forecasted level is within +/- 0.15 m from the actual river water level attained at the forecasted time.  Similarly, for inflow forecast, if the forecasted inflow is within +/- 20% from the actual inflow into the reservoir.  Statement showing the accuracy of the system for the period 2000-2020 is given in Annexure-I.

 

Annexure I

  FLOOD FORECASTING PERFORMANCE FROM 2000 TO 2020

(as provided by Central Water Commission)

Year

No.of Level Forecasts issued

No.of Inflow Forecasts issued

Total No.of Forecasts issued

Total

Within +/-15 cm of deviation from actual

Accuracy  (%)

Total

Within  +/-20% cumec of deviation from actual

Accuracy (%)

Total

Within  +/-15 cm or +/-20% cumec of deviation from actual

Accuracy  (%)

2000

5622

5504

97.90

821

747

90.99

6443

6251

97.02

2001

4606

4533

98.42

857

809

94.40

5463

5342

97.79

2002

3618

3549

98.09

623

602

96.63

4241

4151

97.88

2003

5989

5789

96.66

611

586

95.91

6600

6375

96.59

2004

4184

4042

96.61

705

654

92.77

4889

4696

96.05

2005

4323

4162

96.28

1295

1261

97.37

5618

5423

96.53

2006

5070

4827

95.21

1593

1550

97.30

6663

6377

95.71

2007

6516

6339

97.28

1707

1651

96.72

8223

7990

97.17

2008

5670

5551

97.90

1021

1003

98.24

6691

6554

97.95

2009

3343

3298

98.65

667

629

94.30

4010

3927

97.93

2010

6491

6390

98.44

1028

988

96.11

7519

7378

98.12

2011

4848

4795

98.91

1143

1109

97.03

5991

5904

98.55

2012

4200

4136

98.47

831

803

96.63

5031

4939

98.17

2013

5741

5471

95.30

1319

1289

97.73

7060

6760

95.75

2014

3884

3804

97.94

888

863

97.18

4772

4667

97.80

2015

3500

3429

97.97

572

562

98.25

4072

3991

98.01

2016

4969

4891

98.43

1270

1057

83.23

6239

5948

95.34

2017

5085

4975

97.84

1212

926

76.40

6297

5901

93.71

2018

4969

4871

98.03

1882

1624

86.29

6851

6495

94.80

2019

6004

5773

96.15

3750

2678

71.41

9754

8451

86.64

2020

8243

8133

98.67

3478

3065

88.13

11721

11198

95.54

Average

5089

4965

97.56

1299

1165

89.68

6388

6129

95.95

 

 

This information was given by Dr. Harsh Vardhan, Union Minister for Science & Technology,  Earth Sciences and Health & Family Welfare in a written reply in Lok Sabha on March 12, 2021.

                                                                                                          

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SS/KG/LS-15-03-2021                      



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