real time flood risk forecasting presentation

Real Time Flood Risk ForecastingN8594694 Brendan Coulter

Development of a simplistic flood forecasting model from freely available information

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FloodingDesign runoff levels are exceededRiverine: river overtopping their banks Flash flooding: exceeds stormwater drainage capacity Coastal: caused by storm surgeBrendan CoulterReal Time Flood Risk Forecasting2

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Purpose of researchConsequences Economic, Environmental, and Loss of LifeProvide early warning to reduce impacts Easily accessible to areas in needExtensive knowledge of hydrology not requiredBrendan CoulterReal Time Flood Risk Forecasting3

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outlineData acquisition Modelling programs and creation Risk analysis Future considerationsBrendan CoulterReal Time Flood Risk Forecasting4

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Data AcquisitionRainfall data Water flow Forecasted rainfall Catchment features Data analysis Brendan CoulterReal Time Flood Risk Forecasting5

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Water data Historical and current rainfall data Source: Bureau of Meteorology Waterway depth and flowSource: Department of Natural Resources and Mines Brendan CoulterReal Time Flood Risk Forecasting6

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Forecasted RainfallPivotal in flood risk forecasting Provided by Bureau of Meteorology as a graphic:Rainfall Chances of rainfall minimum of certain quantitiesData needs to be processed before used in model Brendan CoulterReal Time Flood Risk Forecasting7

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Temporal Rainfall DistributionForecast rainfall Total daily quantities Required to be analysed and processedCreation of temporal distribution Statistical analysis of past storm events Application for a time series

Brendan CoulterReal Time Flood Risk Forecasting8

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Temporal Rainfall DistributionForecast rainfall Total daily quantities Required to be analysed and processedCreation of temporal distribution Statistical analysis of past storm events Application for a time series


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Rainfall ProbabilityBureau of Meteorology forecast rain: Rainfall quantities Minimum of 50% probability Anther simulation based on the same model parameters required: Highly likely: 75 90% chance, smaller discharge and flood peaksWorst case scenario: 25% chance, significantly higher values produced


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Catchment featuresBrendan CoulterReal Time Flood Risk Forecasting11Current watercoursesPath water will takeVegetation and impervious surfaces Affects total runoff and runoff velocity Obstructions Alteration to watercoursesStoragesFeatures that retain water, such as depressions and dams

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Flood ModellingRainfall Runoff: Converts rainfall into discharge after lossesImage displays the processFlood Routing: Creates Hydrograph from upstream conditionsPopular methods include Muskingum

Conceptual: Artificial Neural Networks Based off neurons in the brain


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Model CreationMIKE Urban: Chosen as flash flooding has higher consequences and more difficult to predictCombines rainfall runoff and flood routingThree input categories: Drainage System NetworkCatchment and Sub-Catchment DataBoundary ConditionsBrendan CoulterReal Time Flood Risk Forecasting13

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Model InputsNetworkNodes (Manholes, basins, and outlets)Links (Pipes and channels)CatchmentsCatchment area and drainageAlso requires parameters such as ToC and ImperviousnessBoundary Conditions Rainfall time series inputBrendan CoulterReal Time Flood Risk Forecasting14

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Model CalibrationUse Trial and Error method to calibrate parameters:Initial Loss (Less sensitive to small rainfall, reduces peaks)Reduction Factor (Reduces flood peaks)Time of Concentration (Changes shape of hydrograph)Time-Area Curve (Changes shape of hydrograph)Confirm with statistical parameters:Root Mean Square Error (RMSE)Coefficient of Determination (CD)


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True Data UpdateErrors increase over timeInitial Conditions and Catchment Parameters update:Initial Conditions: Apply most recent observed data and re-run modelCatchment Parameters Update: Re-do calibration with newly recorded observational data


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Model OutputCatchment Runoff VolumeWater level in networkDischarge throughout networkFlow Velocities


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Risk AssessmentBrendan CoulterReal Time Flood Risk Forecasting18

LikelihoodSeverityFloodwater Depth (0-4)Water velocity (0-4)Location Importance (0-4)

Models combined at beginning or after final assessment

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Risk Assessment 2Examples of actions for different risk levels;Low risk: monitor situationModerate: broadcast warningsHigh risk: AlertExtreme risk: broadcasting of top priority flood warnings through all means necessary, mitigation of impacts of forecast floodBrendan CoulterReal Time Flood Risk Forecasting19

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Flood Warning BroadcastGoverned by Australias Emergency Warnings ArrangementsResponsibility on state and territory governmentsDelivery throughSocial MediaNews SourcesOnlineRadio


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RecommendationsProof-of-Concept ModelAdaption to worldwide scale (Picture of globe on right)Further analysis on temporal rainfall distributionFurther research into downstream considerationsComplete automation of the process


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ConclusionsBrendan CoulterReal Time Flood Risk Forecasting22

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2016Recording (2)Voice Recorder2016RecordingVoice Recorder2016Voice RecorderSlide 3- Consequences and Purpose2016Voice RecorderSlide 4 - Overview2016Voice RecorderSlide 5 - Data Acquisition2016Voice RecorderSlide 6 - Water Data2016Voice RecorderSlide 7 - Forecasted Rainfall2016Voice RecorderSlide 8 - Temporal Distribution2016Voice RecorderSlide 8 - Part 22016Voice RecorderSlide 9 - Rainfall Probability2016Voice RecorderSlide 10 - Catchment Features2016Voice RecorderSlide 11 - Flood Modelling2016Voice RecorderSlide 13 - Model Creation2016Voice RecorderSlide 14 - Model Inputs2016Voice RecorderSlide 15 Model Calibration2016Voice RecorderSlide 16 - True Data Update2016Voice RecorderSlide 17 - Model Output2016Voice RecorderSlide 18 RA 12016Voice RecorderSlide 19 RA22016Voice RecorderSlide 20 - Flood Warning Broadcast2016Voice RecorderSlide 21 - Recommendations2016Recording (3)Voice Recorder

real time flood risk forecasting presentation

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