Smart ICT for Weather and Water


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Presentation highlights the potential of satellite data products, modeling tools and Smart-ICT platform to assist flood-based farming to enable rural people to overcome poverty and improve food productivity while reducing water consumption.

The project demonstrates for the last two flood seasons how satellite data can detect the extent and duration of flooding in various irrigation block and the authorities can make use of such information to know when and where the flood waters are reaching the farm fields and how many days it got inundated. We have also showcased how flood forecasting tools can help downstream authorities to make operational planning including maintenance of irrigation blocks and early warning for local communities.

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  • HEC- Hydrological Engineering Center ModelsHMS – Hydrologic Modeling SystemsRAS – River Analasis System
  • Smart ICT for Weather and Water

    1. 1. Water for a food-secure world 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
    2. 2. Water for a food-secure world 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.
    3. 3. 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
    4. 4. Water for a food-secure world Flood Inundation Products
    5. 5. Water for a food-secure world 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
    6. 6. Water for a food-secure world OPERATIONAL FLOOD INUNDATION MAPPING (MODIS + Landsat Images) • Weekly inundation mapping services • High. Res. Flood maps from Landsat • Fieldlook Dissemination
    8. 8. Water for a food-secure world 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
    9. 9. 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
    10. 10. Water for a food-secure world 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.
    11. 11. Water for a food-secure world BIAS-CORRECTION OF SATELLITE RAINFALL ESTIMATES
    12. 12. Water for a food-secure world 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;
    13. 13. Water for a food-secure world 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
    14. 14. Water for a food-secure world 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
    15. 15. Water for a food-secure world Flood Extent and Flood Hydrograph – Gash Catchment
    16. 16. Water for a food-secure world Near-Real Time Flood Forecasting 2013 Flood Seasons • Tested 2013 flood year using previous models • 3-hourly TRMM Precipitation data
    17. 17. 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)
    18. 18. 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
    19. 19. Water for a food-secure world 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)
    20. 20. Water for a food-secure world Contact: Giriraj Amarnath, IWMI, Colombo
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