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Flood Mapping Services and Development of
Flood Forecasting Tool (Gash Catchment, Sudan)
Giriraj Amarnath1, Niranga Alahacoon1, Bharat Sharma2, Gijs
Simons3, Younis Gismalla4, Yasir Mohammed4, Vladimir Smakhtin1
1International Water Management Institute (IWMI), Sri Lanka;
2IWMI, India; 3eLEAF Competence Center, The Netherlands
4Hydraulic Research Station (HRS) Sudan

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WORK PACKAGE: FLOOD COMPONENT
• To provide flood inundation mapping services for the 2
flood seasons (i.e. 2012 & 2013)
• To develop operational flood forecasting tool using
hydrological modeling system for the upstream Gash
catchment
• To provide detail training on the use of satellite data and
modeling system on studies related to flood irrigation.

FLOOD INUNDATION MAPPING
ALGORITHM
• MODIS surface reflectance
• Temporal resolution : Daily & 8 days
• Spatial resolution – 250-500 m
• Period : 2012 and 2013
• Indices : EVI, NDWI, LSWI, NDSI
• DVEL (EVI-LSWI) was used to
discriminate between Water pixels
and Non–water pixels. If the
smoothed DVEL is less than 0.05 pixel
is assumed to be a Water pixel;
• Several procedure further
differentiate between permanent
water bodies and temporary Flood
pixels

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Flood Inundation Products

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IDENTIFYING FARM-LEVEL FLOOD EXTENT
USING GIS
• Analysis shows some farmers received excess water and this
resulted in decrease in crop productivity (field site evaluated)
• Vice-versa some farms received 1 or 2 weeks, resulted in low
biomass

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OPERATIONAL FLOOD INUNDATION MAPPING
(MODIS + Landsat Images)
• Weekly inundation mapping services
• High. Res. Flood maps from Landsat
• Fieldlook Dissemination

SEASONAL FLOOD EXTENT IN GASH IRRIGATION SCHEME

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Development of Flood Forecasting System using
HEC-HMS + Satellite Rainfall Estimates
Basin Characteristics
25 sub-basin
Watershed ~20,000km2
12 river segments
HMS Parameters
Loss (SCS Curve Number)
Transform (SCS Unit Hydrograph)
Baseflow (Constant Monthly)
Routing (Muskingum)
Model Inputs
5 raingauges (Ethiopia)
El Gera flow data (GRTU)
TRMM, RFE, CMORPH SRE Data
DEM, LULC, FAO Soil Data

SRTM DEM
HEC-GeoHMS
Slope, watershed and
flow direction developed
Hydrological
modeling
HEC-HMSRainfall:
• Meteo. Stations
• Satellite estimates
• GCM CCAFS Data
Interaction between HEC-
RAS and HEC-HMS to get
outflow relationship
Peak Flows
Land Use
Land Classification
Data
Hydraulic structures
inputted into
Drainage System
Geometry
HEC-RAS
HEC-GeoRAS
Drainage network
characterized
SRTM DEM
TIN
Finalized Geometry
HEC-RAS
Hydraulic
Modeling
HEC-GeoRAS
Flood Inundation Extent
Stream Centerline
Banks
Flowpaths
Cross sections
Hydraulic
Structure Data
Current | Future
Development of Flood Forecasting System using HEC Tools
*HEC-RAS support from HRC (Wad Medani)
& M.Sc Students internship

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BIAS-CORRECTION OF SATELLITE RAINFALL ESTIMATES
• Satellite-based rainfall estimates (SREs)
provide an alternative source of rainfall
data for hydrological modeling
• Real-time SREs are highly suitable for
water resource modeling. however an over
or underestimation in the actual rainfall
amount could lead to uncertainties in
volume error
• In the case of Gash catchment, significant
proportion of the watershed is in Ethiopia
and Eretria has very few, if any, weather
recording stations.
• This is a prime example of where SREs
may be of benefit for filling in gaps in a
ground based data acquisition network.

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BIAS-CORRECTION OF SATELLITE RAINFALL ESTIMATES

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BIAS-CORRECTION OF SATELLITE RAINFALL
ESTIMATES
Daily precipitation sum for 2009 for the uncorrected and corrected SRE
(distribution method)
Improved SRE with R2 value of 0.68 was achieved;

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Model Calibration and Validation : Kassala Bridge Station
NSE RE% Y
Calibration 2011 0.79 -0.05 0.94
Validation 2007 0.72 -0.17 0.87
2012 0.71 -0.06 0.65
0
50
100
150
200
250
300
350
400
1-Jul-11 1-Aug-11 1-Sep-11 1-Oct-11
Discharge(m3/sec)
Simulated Discharge Observed Discharge
0
100
200
300
400
500
600
30-Jun-07 18-Jul-07 5-Aug-07 23-Aug-07 10-Sep-07 28-Sep-07
Discharge(m3/sec)
Simulated Discharge Observed Discharge
0
50
100
150
200
250
300
350
400
450
21-Jun-12 21-Jul-12 21-Aug-12 21-Sep-12
Discharge(m3/sec)
Simulated Discharge Observed Discharge
Calibration : 2011 Validation : 2007
Validation : 2012
Station: Kassala Bridge (Gash Catchment)
Observed vs. Simulated Discharge

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Development of Flood Forecasting System
using HEC-HMS
• Model calibration from 2011
• 2007, 2010 and 2012 for validation
• Model performance in estimating peak flood discharge and
lag time were reasonably good
• Catchment having no gauge stations
• Used bias corrected satellite rainfall estimates
• Abstraction + Ground water extraction
• El Gera flow data measurement (float method + calculation)
• Parameters can be improved further with local measurements

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Flood Extent and Flood Hydrograph – Gash Catchment

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Near-Real Time Flood Forecasting
2013 Flood Seasons
• Tested 2013 flood year using previous models
• 3-hourly TRMM Precipitation data

1-D Hydrodynamic model for Gash Catchment
Modeling of water levels for different discharges
Modeling of flood extent using
HEC-RAS with flow rate of
2000m3/Sec
133 cross section along the Gash River (field survey 2013)

USAGE OF SATELLITE ALTIMETRY IN FLOOD
FORECAST RATING CURVE
- Today there are several
altimetry satellite data e.g.,
ENVISAT, JASON-2, ICESAT,
Sentinel etc. to provide
elevation information
-
- Example of altimeter derived
water level for Kassala bridge
(Virtual station Track 528)
- Using altimeter and Manning
equation and available cross
section we can provide
downstream water level as
early warning tool

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MAJOR OUTPUTS
• Successfully implemented the potential of satellite data in operational
flood inundation extent for 2012 and 2013 flood seasons
• Successfully tested operational flood forecasting tool for the 2013 flood
seasons using hydrological modeling tools
• 2 Research publications in progress
• Dissemination in various events
– World Irrigation Forum (Turkey, 2013)
– Nile Blue Perspective Conference (Sudan, 2013)
– India Geospatial Forum and ICT4D (India, Kenya - 2014)
• Capacity building programme:
– Remote Sensing and GIS for flood inundation mapping (March 2013) in Wad
Medani (35 participants)
– Development of flood forecasting tools for the Gash catchment (August 2013)
in Kassala (20 participants)

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http://www.guardian.co.uk/technology/2011/jul/24/mobile-phones-africa-microfinance-farming
Contact: Giriraj Amarnath, IWMI, Colombo
a.giriraj@cgiar.org