Abstract
Flood modelling and mapping typically entail flood frequency estimation, hydrodynamic modelling and inundation mapping, which require specific datasets that are often unavailable in developing regions due to financial, logistical, technical and organizational challenges. This review discusses fluvial (river) flood modelling and mapping processes and outlines the data requirements of these techniques. This paper explores how open-access remotely sensed and other geospatial datasets can supplement ground-based data and high-resolution commercial satellite imagery in data sparse regions of developing countries. The merits, demerits and uncertainties associated with the application of these datasets, including radar altimetry, digital elevation models, optical and radar images, are discussed. Nigeria, located within the Niger river basin of West Africa is a typical data-sparse country, and it is used as a case study in this review to evaluate the significance of open-access datasets for local and transboundary flood analysis. Hence, this review highlights the vital contribution that open access remotely sensed data can make to flood modelling and mapping and to support flood management strategies in developing regions.
Highlights
Introduction to Flood Modelling and MappingManaging floods effectively requires a good understanding of historical flood trends, future expectations, and identification of locations likely to be impacted by flooding
This review focuses on the integration of open-access satellite data into fluvial flood mapping processes to compensate for data sparsity faced in developing regions, uses a Nigerian case study to assess the possibility of leveraging on global geospatial technology for local and transboundary flood management
River discharge and water level often used as initial/boundary conditions for hydrodynamic and hydrological models are rarely available at most remote locations of many developing regions due to factors previously highlighted in Section 2 [23,39]
Summary
Managing floods effectively requires a good understanding of historical flood trends, future expectations, and identification of locations likely to be impacted by flooding. One of the core objectives of the PUB is to “Advance the technological capability around the world to make predictions in ungauged basins firmly based on local knowledge of the climatic and landscape that controls hydrological processes, along with access to the latest data sources, and through these means constrain the uncertainty in hydrological predictions” [27] This objective aligns seamlessly with remote sensing (RS), considering that it provides an alternative data source to improve our understanding of local hydrology and associated uncertainties in flood mapping for data-sparse regions [28]. This review focuses on the integration of open-access (freely available) satellite data into fluvial (river) flood mapping processes to compensate for data sparsity faced in developing regions, uses a Nigerian case study to assess the possibility of leveraging on global geospatial technology for local and transboundary flood management. Hydrology 2018, 5, x available datasets and sources needed for every flood‐mapping step listed in Table 1 are explored in this review
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