Spatial Flood Early Warning

nrsc

Disaster Management Support Group
National Remote Sensing Centre
Indian Space Research Organisation,Hyderabad, India

Presented byAmanpreet Singh
Scientist ‘SE’
NRSC/ISRODrainage Basin Hydrological Cycle“Flood is an overflow of water onto land thatis normally dry”
Source: https://www.zurich.com/en/knowledge/topics/flood-and-water-damage/three-common-types-of-floodnrsc

River Flooding (Fluvial Flooding)nrsc•A fluvial or river flood, occurs when the water level in a river, lake or stream rises andoverflows onto the surrounding banks, shores and neighboring land.

•The water level rise could be due to excessive rain or snowmelt.

Flooded Ganga RiverUrban Flooding (Pluvial Flooding)As
perFederalEmergency
Management
Agency(FEMA),
Urban Flooding is the inundationof property in a built environment,
particularly in more densely
populated areas, caused by rain
falling on increased amounts ofimpervious
surfaces
andinsufficient capacity of drainage
systems.

nrsc

Coastal Flood• Storm surge is anabnormal rise of water
generated by a storm,
over and above thenormal tides.
• This rise in water level
cancause
extremeflooding in coastal areasnrsc

Flood Problem (India)

Geographical Area

329 mhaTotal Flood Prone Area

40 mhaMajor Flood Prone States

Assam, Bihar, West Bengal,UP, Orissa and A.P

Major Flood Prone Basins

Ganga, Brahmaputra,
Mahanadi and GodavariRivernrsc

Early Warning System•nrsc

UNDRR, 2009 defines EWS as “the set of capacities needed to generate anddisseminate timely and meaningful warning information to enable individuals,
communities and organizations threatened by a hazard to prepare and to act
appropriately and in sufficient time to reduce the possibility of harm or loss.”

Flood Early Warning System•••••

Flood Early Warning System is a system by which flood induced hazards can be minimized and prevented.
In a flood early warning system the most important input is real time hydro-meteorological observations such as
rainfall, water level or discharge etc. Weather forecasts (Numerical Weather Prediction-NWP) are also playing animportant role in providing input for hydrological models.
LULC, Soil and DEM are important inputs for hydrological model and spatial flood inundation model.
Besides having forecasts of the most important input (precipitation), a model needs to be selected that characterizes
and simulates the catchment responses for flood early warning.

Flood early warning system can provide essential help for the risk and disaster management by helping to identify
possible affected areas as well as the potential impact and therefore giving more time to prepare disaster relief efforts
and to allocate resources.

Flood Early Warning Models mainly consist ofnrsc

 Development of medium-range flood early warning models using space based
inputs through hydrological modelling approach.
 Development of spatial flood inundation simulation models using highresolution DTM in the major floodplains of the rivers
 Development of web-enabled real-time spatial flood early warning system.

Categories of Flood Forecasting Techniques•

Short Range Forecast
This method can give advance warning of 12-40 hrs for flood•

Medium Range Forecast
This method can give advance warning of 2-5 days for flood•

Long Range Forecast
This method can give advance warning of more than 5 daysnrsc

Digital Elevation Models at National Level forSpatial Hydrological ModellingCourse Resolution DEMs
•Global DEM (1 km resolution)•SRTM DEM (90 m resolution,Vertical Accuracy: < 16 m)

Medium Resolution
DEMs•CARTO DEM (30m resolution,Vertical Accuracy: < 8 m)
•ASTER DEM (30m resolution)

Fine Resolution DEMs

Very Fine Resolution•CARTO DEM (10m resolution,Vertical Accuracy: < 8 m)
•ALOS (Advanced Land
Observing Satellite, 5mresolution)•LiDAR DEM (1m resolution,Vertical Accuracy: ~50 cm)•SAR DEM (<5m)

nrscSatellite Remote Sensing Based Flood MappingvsFlood Inundation Simulation Based Flood Mapping
Satellite Remote Sensing

nrsc

Flood inundation simulation

During or within a short time after a flood event

Before the event

Provides only Spatial Flood extent

Flood extent, water depth and velocity and otherparameter
Time series of images are discontinuous

Time series of images are continuous

Represents actual observed flooded areas, therefore

Results based upon the accuracy of input parametermore realistic than inundation simulation
The time of acquisition of satellite data may not

It covers entire range of flood progression, peak andcoincide with the time of flood peakrecession

Study Area
Godavari Basin•

Length of the Godavari river isapproximately around 1,465 km. BasinArea is 312,812 km2. It drains through sixstates.

•2006, 2010, 2013, 2016, and 2020 are
major floods year in the Godavari basin.

•Reservoirs: Jayakwadi, SRS, Gosi Kurd,Bailmela, Isapur etc

The Godavari Basin
Year
1981
1983
1986
1990
1994
1995
2000
2006
2010
2013
2019
2020

Discharge(cumec)
51496
43879
62889
62800
41042
40205
40942
51916
44200
57244
38070
44988

Major floods (discharge at Perur, CWC)

Tapi Basin•

Length of the Tapi river is approximatelyaround 724 km. It drains through threestates.

•2006, 2012, 2013 are major floods year in
the Tapi basin.

•Reservoirs: Hathnur, Ukai etc

Year

Hydrological setting of Godavari basin

Discharge(cumec)

1944
33527
1945
28996
1949
23843
1959
36642
1968
44174
1998
19057
2006
25768
2012
9508
2013
12146
Major floods at Surat (CWC)

The Tapi Basin

Gauge stations
RiverSubbasin

Hydrological setting of Tapi basinnrsc

Hydrological Model and Hydrodynamic Model

Evaporation

Precipitation

HydrologicalModel

Hydrodynamic Model
Evaporation

Surface runoff

CoastGroundwater

Estuary

Source: https://publicwiki.deltares.nl/download/attachments/13402418/Flood%20forecasting%20using%20MIKE11.ppt?api=v2

Hydrological Model Classification

nrsc

The Broad Methodology

nrsc
Hydrological Model (NAM)

Model Parameter:

Input Data:•••

Data Requirement
Meteorological data (rainfall and potential evaporation)
Hydrological data (discharge at the outlet of the catchments formodel calibration and validation)
Model parameters (time constants and threshold values for routing
surface storage, rootzone storage and groundwater storage)

Parameter
Umax (mm)Lmax (mm)CQOF
CKIF (h)TOF
CK1,2 (h)TIFTG
CKBF (h)DescriptionMaximum water content in surface storage
Maximum water content in root zone storage
Overland flow runoff coefficientTime constant for interflow
Root zone threshold value for overland flow
Time constant for routing overland flow
Root zone threshold value for interflow
Root zone threshold value for groundwater recharge
Time constant for routing base flow

Unitmmmm
hHh

DSM and DTM
Digital Surface Model (DSM)
represents the earth's surface andincludes all objects on it.
Building,Treenrsc

Digital Terrain Model(DTM)
represents the bare ground surface
without any objects like trees andbuildings

Bare earthParameter Extraction and 1D-2D model
coupling for flood inundation

Mesh

Bathymetry

Bed resistance

Boundary Conditions

Model Calibration & Validation- Godavari Basin
2006(C)Perur
R2=0.915

R2=0.943

2012(V)

Tekra
2007(C)

2013(V)

R2=0.909

R2=0.920
Simulated Discharge
Observed Discharge

Konta
2008(C)

R2=0.9182012(V)

R2=0.938

Calibration:(2006-2010)
Validation:(2011-2013)

Spatial Flood Inundation Simulations (Observed Vs Simulated)(Godavari Floodplains)

Simulated flood inundation during 2006 flood at Sabari confluence (calibrated)

Simulated flood inundation during 2020 flood at Sabari confluencenrsc

Advantages of Flood Inundation Simulation•

Flood inundation simulation helps in many of these, such as Planning Rescue and Relief
 Damage Assessment

 Flood Risk Assessment
 Design of structure Zoning the floodplain to guide appropriate development
 Flood mapping to raise community awareness Assess benefits of natural flood management options

nrsc

Real time point rainfall and WRF meteorological data

nrsc

Rainfall Stations

Topographic data
(600 – 3000 mm)
Mean: 1090 mm

Digital Elevation ModelRainfall

Dominant LULC: Kharif Crop,Dominant Soil: Clayey,Deciduous Forest, Double/Triple CropLoamy

Landuse/Landcover

Soil Texture (NBSS & LUP)

Spatial Flood Early Warning Systems- Godavari and Tapi Rivers (2022)

Godavari Flood Early Warning-2022

nrscSpatial Flood Early Warning Systems- Godavari and Tapi Rivers (2022)

Inundation July 2022 flood event in Godavari Rivernrsc

Spatial Flood Early Warning Systems- Godavari and Tapi Rivers (2022)

Village Affectednrsc

Spatial Flood Early Warning Systems- Godavari and Tapi Rivers (2023)

Flood Hydrograph at Bhadrachalam in Godavari River

Spatial flood inundation simulation (29 Jul 2023)

nrsc

Flood Hydrograph at Sarangkheda in Tapi River

Spatial flood early warning and villages affected (29 Jul 2023)

Flood Inundation Simulations forGodavari Basin - 2022

PAN INDIA RUNOFF (14 July 2022)

nrsc

PAN INDIA RUNOFF (15 July 2022)

nrsc

PAN INDIA RUNOFF (16 July 2022)

nrsc

Major Highlights & End use

Accuracy

Flood discharge computation accuracy is > 85 % with Improved
Forecast lead time (36 to 50 hours) at multiple locations.

Application

End useSpatial flood advisories on flood extent & depth to all the stakeholders through automated sms services.

Vital input in relief & rescue operations, and in preparing Basin level DMplans for DRR.
Scientific assessment of flood-prone area in the Basins

For details, please contact at
durgarao_khv@nrsc.gov.in