CityFIT Urban Guide: Modelling and Deploying indicators of Property Exposure to Flooding in Lagos using LIDAR DEM and DSM data

Sulaiman Mosuro

RESEARCH CONTEXT

The prevalence of flood following heavy precipitation is a vivid and daunting problem in the coastal city of Lagos mostly exacerbated by restricted drainage channels, poorly engineered structures, urbanization processes and the uncontrolled siting of buildings on flood plains. An understanding of floodplain characteristics and storm water flow mechanisms is essential in the efficient management of urbanizing cities. Flood prediction models benefits in giving informed guidance aimed towards ameliorating the impacts of inundation hazards in urbanizing areas as it aids in the capacity for timely public enlightenment on potential flood hazards raising preparedness and minimizing loss.

The propagation of flood inundation in urban catchments is highly dependent on the surface topography, land cover and the representation of structure in elevation data used in modelling. Components of flood prediction modelling addressed by this project include determining:

How well LIDAR derived digital elevation data captures floodplain surface forms, their utility in profiling cross-sections for flow hydraulics modelling and how well it can be used in determining structural influences on flood propagation, velocities and depths
How might flood exposure indicators be modelled and promptly disseminated to assist in flood response, preparedness, urban planning and in model validation and refinement

PROJECT OBJECTIVES
The following objectives are set for this research:

To develop a flood propagation model consisting of an Hydrologic model of discharge rates and a flow hydraulics model using elevation, land cover and precipitation data
To assess the impacts and susceptibility of structures to flood dynamics by utilizing both DEM and DSM in models
To map risk levels associated to properties based on their exposure level to flood depths and velocities
To prototype a portable application for disseminating flood warning levels, time-series charts and maps of at-risk areas and an event reporting interface for recording flood event details

STUDY AREA, DATA AND METHODS

A case study area of 132km2 lying between 3.22° - 3.23° E and 6.42° – 6.52° N in Lagos Nigeria is selected for this research.

Flood inundation is simulated using two modelling components namely the Hydrologic Model a rainfall-runoff model that transforms precipitation data into overland discharge and the Hydraulic Model used to determine water surface levels, flooding depth, extents and flow distribution velocities.

Datasets used for the study include LIDAR DEM and DSM data, Land use, soil and precipitation data

Description: Nigeria.emf

Figure 1: Map of Nigeria showing Lagos State

$Description: M:\Dissertation\data\map\LAGMap.png$

Figure 2: LIDAR DSM of Study site in context of the whole State

Modelling processes are executed using HEC Tools including HMS, RAS, GeoHMS and GeoRAS. Intermediate procedures including the creation of steady flow cross-section geometric data, composite land use etc. were automated using scripts (python and perl) developed in this research. Thw modelling workflow is outlined in the Figure below

Figure 3: Workflow chart for flood inundation modelling, analysis and deployment

RESULTS

Figure 4: Map of flood depths over time for the July 10, 2011 event, overlaid on DSM

Property risk levels were mapped by associating exposure indicators of flood depth and flow velocities to units of the address parcel layer. The ratings were based on the magnitudes of these flood characterisitics in the neighbourhood of the affected units.

$Description: M:\Dissertation\Work\Infrastructure_ZoneStats\Infra Risk Map -Depth.png$

Figure 5: Map showing risk levels associated to Properties and Infrastructure based of Flood depth

Inundation extents and flood depths for DSM profiled models cover larger areas than that of their counterpart DEM runs. This is as a result of the fact that structure present in the DSM reduces area that can be occupied by flood water thereby increasing depth and coverage

Figure 6: Comparison of water stages derived from DEM and DSM model simulations for the same rainfall volume

A symmetric difference of the DEM profiled floodplain, with that of the DSM resulted in a layer showing areas potentially protected by presence of structures and the zones that are potential receptors of diverted flood due to structural influence on the flow propagation

$Description: M:\Dissertation\images\Structure Influence.png$

Figure 7: Map showing structural influence on flood propagation created by a symmetric difference of the flood extents maps from DEM and DSM models

RESULT DISSEMINATION

A portable android application was prototyped for disseminating time-series flood model information and for reporting details of flood events as they occur to serve for model calibration and enhancement, thereby completing the flood modelling lifecycle.

Mobile Texhnology

Figure 8 and 9: Flood Modelling Lifecycle, showing the utility of mobile devices for dissemination and reporting; Architecture of developed mobile application showing the methods and data it utilizes for result visualisation and event reporting

A graphing activity displays charts of discharge rates, precipitation volume and flood depths over the time period of the event. The map interface contain flood extent layers simulated at specific time steps navigable using the seek bar and overlaid on a google satellite base map.

Figure 10 and 11: Android activities showing graph plots of discharge rate, rainfall and flood depths; flood map overlays and event reporting forms. A touch motion on the graph changes the text displays to those of the current time position. The map activity shows an overlay of flood extent navigable over time using the seek bar/time glider. Map tools allow toggling layer and interactive selection on map to reveal additional information

CONCLUSION

This research saw the creation of a floodplain inundation model suitable for predicting the propagation of flood and the influence of structural form to the flow dynamics of inundation in the study site. The model consists of a hydrologic component that returns the discharge hydrograph of the runoff from precipitation events factoring processes of infiltration loss, concentration lag and topography. The hydraulic component determines water surface levels, flow velocities and flood depths of the inundated area over time.
A comparative analysis of the results of simulation by DEM and DSM allowed for the identification of areas that may benefit from flood defence structures and the consequence of such to other locations. Flood model characteristics of depth and velocity have shown good promise in the assignment of risk levels to properties for evaluating their exposure and vulnerability.
A portable android application was prototyped for disseminating time-series flood model information and for reporting details of flood events as they occur to serve for model calibration and enhancement, thereby completing the flood modelling lifecycle.

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