Abstract
Consistent data are seldom available for whole-catchment flood modelling in many developing regions, hence this study aimed to explore an integrated approach for flood modelling and mapping by combining available segmented hydrographic, topographic, floodplain roughness, calibration, and validation datasets using a two-dimensional Caesar-Lisflood hydrodynamic model to quantify and recreate the extent and impact of the historic 2012 flood in Nigeria. Available segments of remotely-sensed and in situ datasets (including hydrological, altimetry, digital elevation model, bathymetry, aerial photo, optical imagery, and radar imagery data) available to different degrees in the Niger-South hydrological area were systematically integrated to draw maximum benefits from all available data. Retrospective modelling, calibration, and validation were undertaken for the whole Niger- South hydrological catchment area of Nigeria, and then these data were segmented into sub-domains for re-validation to understand how data variability and uncertainties impact the accuracy of model outcomes. Furthermore, aerial photos were applied for the first time in the study area for flood model validation and for understanding how different physio-environmental properties influenced the synthetic aperture radar flood delineation capacity in the Niger Delta region of Nigeria. This study demonstrates how the complementary strengths of open, readily available geospatial datasets and tools can be leveraged to model and map flooding within acceptable levels of uncertainty for flood risk management.
Highlights
The magnitude and frequency of flood events are continuously increasing due to climate change and anthropogenic factors that will exacerbate flood impact into the foreseeable future [1]
This study explores an integrated approach for flood modelling and mapping by combining available segmented hydrographic, topographic, floodplain roughness, calibration, and validation datasets using a two-dimensional Caesar-Lisflood hydrodynamic model to quantify and recreate the extent and impact of the historic 2012 flood in Nigeria
A similar model performance variation was observed by Skinner et al [13], where model performance uncertainty increased with data ambiguity
Summary
The magnitude and frequency of flood events are continuously increasing due to climate change and anthropogenic factors that will exacerbate flood impact into the foreseeable future [1]. The total global cost of coastal and river flood damage in 2010 stood at US $46 trillion and is projected to increase to US $158 trillion by 2050 in business-as-usual conditions [2] Factors such as population growth and urban sprawl towards floodplains contribute to the high cost of flood disasters [3], especially in developing regions where urban planning regulations are less stringent and the vulnerable are disproportionately affected by floods due to limited institutional and technical coping capacity, including limited data availability due to financial, institutional, operational, and technical shortcomings [4]. Accurate information on flood magnitude, including inundation extent, depth, and propagation velocity, are essential to inform flood risk management interventions [7] Such information is typically generated by flood modelling and mapping processes such as flood frequency analysis, hydrodynamic modelling, flood hazard mapping, and impact mapping [8]. Flood maps can be presented in probabilistic or deterministic formats, depending on the purpose, type of flood information, and accompanying uncertainty to be communicated [15,16]
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