This document outlines a proposed model for real-time flood risk forecasting using freely available data. It discusses developing a simplistic model to provide early flood warnings and reduce impacts. The model would acquire rainfall, water flow, and catchment data then use a program like Mike Urban to simulate runoff and routing to output discharge, water levels and risks. The risks would be assessed on likelihood and severity of flooding to issue warnings through various channels. The goal is to create a concept model that could be adapted worldwide to help flood-prone areas.

1. REAL TIME FLOOD
RISK
FORECASTING
N 8 5 9 4 6 9 4 B R E N D A N C O U LT E R
Development of a simplistic flood forecasting
model from freely available information

2. FLOODING
DESIGN RUNOFF LEVELS ARE
EXCEEDED
• Riverine: river overtopping their banks
• Flash flooding: exceeds stormwater drainage capacity
• Coastal: caused by storm surge
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3. PURPOSE OF RESEARCH
• Consequences – Economic, Environmental, and Loss of Life
• Provide early warning to reduce impacts
• Easily accessible to areas in need
• Extensive knowledge of hydrology not required
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4. OUTLINE
• Data acquisition
• Modelling programs and creation
• Risk analysis
• Future considerations
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5. DATA ACQUISITION
• Rainfall data
• Water flow
• Forecasted rainfall
• Catchment features
• Data analysis
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6. WATER DATA
• Historical and current rainfall data
• Source: Bureau of Meteorology
• Waterway depth and flow
• Source: Department of Natural
Resources and Mines
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7. FORECASTED RAINFALL
• Pivotal in flood risk forecasting
• Provided by Bureau of Meteorology as a graphic:
• Rainfall
• Chances of rainfall – minimum of certain
quantities
• Data needs to be processed before used in model
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8. TEMPORAL RAINFALL
DISTRIBUTION
• Forecast rainfall
• Total daily quantities
• Required to be analysed and processed
• Creation of temporal distribution
• Statistical analysis of past storm events
• Application for a time series
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9. TEMPORAL RAINFALL
DISTRIBUTION
• Forecast rainfall
• Total daily quantities
• Required to be analysed and processed
• Creation of temporal distribution
• Statistical analysis of past storm events
• Application for a time series
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10. RAINFALL PROBABILITY
• Bureau 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 peaks
• Worst case scenario: 25% chance, significantly higher values
produced
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11. CATCHMENT FEATURES
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CURRENT WATERCOURSES
• Path water will take
VEGETATION AND IMPERVIOUS SURFACES
• Affects total runoff and runoff velocity
OBSTRUCTIONS
• Alteration to watercourses
STORAGES
• Features that retain water, such as depressions and dams

12. FLOOD MODELLING
RAINFALL RUNOFF:
• Converts rainfall into discharge after
losses
• Image displays the process
FLOOD ROUTING:
• Creates Hydrograph from upstream
conditions
• Popular methods include Muskingum
CONCEPTUAL:
• Artificial Neural Networks – Based off
neurons in the brain
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13. MODEL CREATION
MIKE URBAN:
• Chosen as flash flooding has higher consequences and more
difficult to predict
• Combines rainfall runoff and flood routing
THREE INPUT CATEGORIES:
• Drainage System Network
• Catchment and Sub-Catchment Data
• Boundary Conditions
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14. MODEL INPUTS
NETWORK
• Nodes (Manholes, basins, and outlets)
• Links (Pipes and channels)
CATCHMENTS
• Catchment area and drainage
• Also requires parameters such as ToC and Imperviousness
BOUNDARY CONDITIONS
• Rainfall time series input
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15. MODEL CALIBRATION
• Use “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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16. TRUE DATA UPDATE
• Errors increase over time
• Initial Conditions and Catchment Parameters update:
• INITIAL CONDITIONS:
Apply most recent observed data and re-run model
• CATCHMENT PARAMETERS UPDATE:
Re-do calibration with newly recorded observational data
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17. MODEL OUTPUT
• Catchment Runoff Volume
• Water level in network
• Discharge throughout network
• Flow Velocities
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18. RISK ASSESSMENT
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LIKELIHOODSEVERITY
• Floodwater Depth (0-4)
• Water velocity (0-4)
• Location Importance (0-4)
• Models combined at beginning or after final assessment

19. RISK ASSESSMENT 2
• Examples of actions for different risk levels;
• Low risk: monitor situation
• Moderate: broadcast warnings
• High risk: Alert
• Extreme risk: broadcasting of top priority flood warnings
through all means necessary, mitigation of impacts of forecast
flood
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20. FLOOD WARNING BROADCAST
• Governed by “Australia’s Emergency Warnings
Arrangements”
• Responsibility on state and territory governments
• Delivery through
• Social Media
• News Sources
• Online
• Radio
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21. RECOMMENDATIONS
• Proof-of-Concept Model
• Adaption to worldwide scale (Picture of globe on right)
• Further analysis on temporal rainfall distribution
• Further research into downstream considerations
• Complete automation of the process
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22. CONCLUSIONS
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