Home > Research > Publications & Outputs > Catchment-Scale Flood Modelling in Data-Sparse ...

Links

Text available via DOI:

View graph of relations

Catchment-Scale Flood Modelling in Data-Sparse Regions Using Open-Access Geospatial Technology

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
Article number512
<mark>Journal publication date</mark>25/08/2020
<mark>Journal</mark>ISPRS International Journal of Geo-Information
Issue number9
Volume9
Number of pages19
Publication StatusPublished
<mark>Original language</mark>English

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.