IWMI’S FLOOD RISK ASSESSMENT AND MODELING
IWMI’S FLOOD RISK ASSESSMENT AND MODELINGRESEARCH IN ASIA AND AFRICAGiriraj AmarnathInternational Water Management Institute (IWMI),Colombo, Sri LankaWater for a food-secure worldwww.iwmi.org
THE PROBLEM Floods – primary natural disasters Precipitation intensity and variability is projectedto increase – increasing risks of floodingglobally and in Asia Global flood losses in 2011 100 Billiono Largest global losses: Thailand (Jun-Nov) 40-50B Australia (Jan-Feb) 20-30B Hurricane Irene (Aug) 5-10BMay rise to over 450B by 2030Water for a food-secure worldwww.iwmi.org
GLOBAL FLOOD RISK RANKING Flooding major concern in many emerging markets– Risks based on flood exposure and economic growth– Thailand (2011 flood losses of 40-50B) only ranks 7th– Highest risk regions where streamflow data are limitedRisk Rank(high to low)Source: Swiss Re, “Natural catastrophes and man-made disasters in 2011: historic lossessurface from record earthquakes and floods”, Sigma No 2/2012.
Sample X-yr flood map;shaded by water depth(shallow-blue to deep-red) Challenge to validatehydraulic model producingcontinuous water surface w/point measurements54321Station (m)Will these locations flood?Water Level (m) Water Level (m)UNDERSTANDING FLOOD RISK – “AT A SITE”Discharge (m3/s)gaugelocation
UNDERSTANDING FLOOD RISK – “GLOBAL TO LOCAL ” Satellites/Models provide consistent data for ? km of river reaches, ofwhich many (?%) river reaches are needed for Engineering andInsurance Applications Can lead to X-yr flood hazard meaning same everywhere Help in aggregate analyses at Global, Regional & Local scales
Mapping Flood Hotspots for Climatic Change
CATASTROPHIC FLOODS IN ASIA: 1900-2011 Collated from 6 global sources 4000 floods globallyAround 35% - in AsiaCountryFloodOccurrenceIndia237China P Rep209United desh83Iran Islam Rep72Pakistan72Vietnam67Annual Flood Occurrence 10 days 50 days 50daysFlood DurationWater for a food-secure worldwww.iwmi.org
IDENTIFYING FLOOD HOTSPOTS 100 km grid over the globe; numbers of floods in each cell over 1900-2011Water for a food-secure worldwww.iwmi.org
CHARACTERISING FLOOD HOTSPOTSAGRICULTURE;PAGE (2005)POPULATIONCIESIN - 2010FLOOD EXPOSEDGDPWB, 2010Water for a food-secure worldwww.iwmi.org
CHARACHERIZING FLOOD HOTSPOTS Globally - 90 grid cells with catastrophicflood occurrence 5;60% of these cells -in Asia Estimated total over these hotspots: – annual economic loss due to floods - 20bn– 30 million affected people– 500,000 km2 of affected croplandsWater for a food-secure worldwww.iwmi.org
SUB-CONTINENTAL SCALE FLOOD MAPPINGExamples from SA and SEA – MODIS imagesIndusMekongAugust 18, 2009August 26, 2010August 17, 2010August 24, 2011Water for a food-secure worldwww.iwmi.org
FLOOD INUNDATION MAPPING ALGORITHMMODIS 8-day composites of surface reflectance (MOD09A1)NDSICloudmaskNDVISnowmaskLSWIEVIPermanent WatermaskVegetation Croparea Interim Map of inundated areasDEMGlobal WetlandDatabase Validation and Accuracyassessment MODIS surface reflectanceGlobalTemporal resolution : 8 daysSpatial resolution – 500 mPeriod : 2000 – 2011Indices : EVI, NDWI, LSWI, NDSIDVEL (EVI-LSWI) was used todiscriminate between Water pixelsand Non–water pixels. If thesmoothed DVEL is less than 0.05 pixelis assumed to be a Water pixel;Several procedure furtherdifferentiate between permanentwater bodies and temporary FloodpixelsApplied in South AsiaBeing applied in South East AsiaFinal map of inundated areas (2000 – 2011)Water for a food-secure worldwww.iwmi.org
FLOOD MAPPING RESULTS– GANGES EXAMPLEMODIS Satellite ImagePhoto omCakenberghe/IWMISep 22, 2011Water for a food-secure worldEstimated inundation extentwww.iwmi.org
SOUTH ASIA FLOOD MAPPING PRODUCTS 8-days maps of inundation extent2010 Annual maps of maximum inundation Inter-annual variation of regionalflooding extent Spatial distribution of start – enddates, and duration of inundationcycle Basin level flood risk assessmentFloodMixed (Crop)Water bodiesWater for a food-secure worldwww.iwmi.org
SOUTH ASIA PRODUCTS12years flood frequencyFacts and figuresCountryBangladeshArea ,09512.19SriLanka838.2765,6101.28India2010Flood AffectedAreaNepalBig Facts on Floods and CropsFlooding affects 10 million hectares of rice fieldsEstimated 1 billion USD in yield losses per year
EXAMPLE PRODUCTS : INDUS BASINAnnual floods mapsInter-annual variation (2000 – 2011)
RIVER BASIN :FLOOD INUNDATION 76 million population are exposed tofloods 80,000 sq.km of cropland are impactedby flooding Avg. annual flooding in lower ganga 9,300sq.km followed by Gandak andGhaghara basinsRecurrent Floods(12yrs) Affected 2,060Very high15,080,070Total Pop. Affected76,155,560
Flood Data Web Services !!
RAPID EMERGENCY RESPONSE MAPPINGhttp://dx.doi.org/10.1111/jfr3.120452013
Flood Duration : Indus Basin, Pakistan Duration of annual flood inundation is defined from the start andend dates of annual flood inundation Longer flood duration significantly increase the flood risk damage
Spatial Distribution of population growth (1980 – 2000) andlocation of the recent floods mapped using RS 73010.49Sri Lanka20,277,597901,1514.44IndiaNepalFlooding in SA has affected totalpopulation 250million Sub-continental scale, the dynamics of human settlements ( i.e. population growth between 1980and 2000) and the location of latest floods in SA using RS data. Highlights that most of the recent floods (i.e. period 2000 – 2011) have occurred where thepopulation has increased more. Intensive and unplanned urbanization of flood-prone areas, played a major role in increasing thepotential adverse consequences of floods
SOUTH EAST ASIA Flood MappingAugust 2011MODIS Terra ImageMODIS 15 tiles covering SE Asia Total Images (2000 – 2011) 7590MODIS Flood Maps 2011 completed.Validation ongoingTonle Sap Inundation Map (28th August 2011)
Modeling Inundation Extent and Flood Forecasting System
Modeling Flood Inundation Extent usingHEC-HMS (Hydrological Modeling Scheme)Main inputs to the model includes: Watershed stream network and size : 79sub-basins and 53 river reaches, Infiltration loss method : SCS CurveNumber Transform method (excess precipitationto runoff) : SCS Baseflow method: Exponential recession Routing method: Muskingum Meteorological data: 86 rainfall stations Time Span : 1947 – 2005 (most data 1980– 1999) Calibrated and validated for 1987-1999where daily discharge data fro Farakka isavailable Used 4 discharge stations and 1 remotelysensed data for calibration
1997 - 1998Farakka Station1996 - 1997HydrographSimulated vs. ObservedModeling Flood Inundation Extent usingHEC-HMS (Hydrological Modeling Scheme)Flow, Time of Peak and Volume for some HMS calibration eventsFor 96-97: Peak observed discharge: 53125 m3/s peak date: September 4Peak Simulated discharge: 48332 m3/s peak date: August 22For 97-98: Peak observed: 40210 m3/s peak date: September 7Peak Simulated: 43694 m3/s peak date: September 19Average absolute residual error: 5-9% of the peak flow
Modeling Flood Inundation Extent usingHEC-RAS (River Analysis System)Water Surface Profile3D-PlotMain River NetworkCross SectionsOutputs produced by HEC-RAS – Trial run for 97-98 floodRating Curves
Modeling Flood Inundation Extent usingHEC-RAS (River Analysis System)Main inputs to the model includes:Banks River geometry including Stream Centerline,Flow Path Centerline, Floodplain extent,Main Channel Banks, and Cross Sections Mannings n values of cross-sections (range0.03-0.36) RiversInflow hydrographs (or peak flows) at keylocations along the main river network The parameters that can be adjusted arethe Mannings n value and the boundaryconditions like normal or critical depth. Theobserved water elevations are compared tothe simulated ones (Ongoing) Validate the model for other events basedon the calibrated parameters (Ongoing)X-sectionFloodplain
Modeling Flood Inundation Extent usingHEC-RAS (River Analysis System)Outputs produced by HEC-RAS – Trial run for 97-98 floodFlooding Extent and Depth
Flood Inundation Extent – Ganga BasinHEC-RAS Model Flood extent maps derived from RS data areessential calibration data to evaluateinundation models Other outputs such as water depth, flowvelocity are availableMODIS Flood Maps
Ganga FloodPlain Inundation Model (GFIM)Extent of floodplain inundation in GIS format which can be analyzed and overlaid on other spatialdatasets such as riparian vegetation, transport and water infrastructure to address impactsIdentifying vulnerable areas for better flood management
DEVELOPMENT OF FLOOD FORECASTING SYSTEMHEC HMS RASBasin CharacteristicsModel InputsHMS Parameters25 sub-basinWatershed 20,000km212 river segments5 raingauges (Ethiopia)El Gera flow data (GRTU)TRMM, RFE, CMORPH SRE DataDEM, LULC, FAO Soil DataLoss (SCS Curve Number)Transform (SCS Unit Hydrograph)Baseflow (Constant Monthly)Routing (Muskingum)Water for a food-secure worldwww.iwmi.org
DEVELOPMENT OF FLOOD FORECASTING SYSTEMUSING HEC-HMSObserved vs. Simulated flow data “2011 flood season”Observed vs. Simulated flow data “2007 flood season”Water for a food-secure worldwww.iwmi.org
From pixels .to information .to simple action messagesWater for a food-secure worldwww.iwmi.org
SUMMARY Global flood hot spots identified and characterized in terms of economicand human losses Several spatial products quantifying flood inundation pattern in South Asiawith a resolution of 500 m and 8 days available Demonstrated how remote sensing data and Smart-ICT can help farmersfor effective management of land and water resources in Gash Delta Modeling Inundation Extent and Flood Forecasting are important sourcesfor flood mitigation measures and flood managementWater for a food-secure worldwww.iwmi.org
THANK YOUEmail contact: a.giriraj@cgiar.org“ Let not a single drop of water received from rains go wasteinto the sea without benefiting the man and the beast ”Water for a food-secure worldKing Parakramabahu (1153-1186 AD)www.iwmi.org
– Risks based on flood exposure and economic growth – Thailand (2011 flood losses of 40-50B) only ranks 7th – Highest risk regions where streamflow data are limited GLOBAL FLOOD RISK RANKING Source: Swiss Re, Natural catastrophes and man-made disasters in 2011: historic losses sur
Financial Management of Flood Risk isbn 978-92-64-25767-2 21 2016 03 1 P Financial Management of Flood Risk Contents Chapter 1. Introduction: The prevalence of flood risk Chapter 2. Flood risk in a changing climate Chapter 3. Insuring flood risk Chapter 4. Improving the insurability of flood risk C
each FRM Planning cycle will take. FRM Strategies will cover three of these cycles. Timeline of FRM Act Baseline appraisal of current flood risk Opportunities for Natural Flood Management Prioritisation of actions Consultation on FRM Strategies FRM Act 2009 National Flood Assessment Dec 2011 Flood hazard and flood risk maps FRM Strategies 2015 .
1) The HEC-RAS provides the flood profile for the worst flood intensity. This profile will facilitate to adopt appropriate flood disaster mitigation measures. 2) The flood profiles for different flood intensities with different return periods can be plotted at any given cross section of river. Also, such flood
understand and predict. Nearly every community in Nebraska that faces flood risk has had a study conducted to predict the characteristics of a 1% annual chance flood (100-year flood). The Flood Insurance Study and the associated Flood Insurance Rate Map are the best sources of information. The data in these documents mixed with the
the developing countries, including Malaysia, which still depend on hazard maps, while a risk map illustrating the risk of flooding in monetary terms is rarely available. Flood damage is an important tool in the assessment of flood risk. Studies on flood damage assessment in devel-oped countries can be tracked back to Penning-Rowsell
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Canal interacts with the River Trent and flood gates are operated to manage the flood risk. The Canal and River Trust is responsible for managing flood risk from canals. Integrated flooding occurs when two or more flood sources interact. For example, when river levels are high, sew
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