Application of remote sensing to flood hazard and risk Mapping 24 

Most flood studies have primarily focussed on flow forecasting and communication issues, and less on flood risk mapping (Smithers et al., 1997; Tanavud et al., 2004; Uddin et al., 2013). Islam and Sado (2002) in Bangladesh, Asante et al. (2005) in Mozambique, and lately Uddin

et al., 2013 in Pakistan, demonstrated that effective communication platforms should also

include flood risk mapping. The main objective of flood risk mapping is to prepare flood hazard and vulnerability maps and identify the flood risk areas. Birkmann (2006) and Moel et al. (2009) concluded that, in the field of flood management, risk and vulnerability have different

meanings. All definitions (e.g. Black, 1994; Islam and Sado, 2002; Tanavud et al., 2004; Samuels and Gouldby, 2009; Madsen et al., 2007; Samarasinghe et al., 2010; Uddin et al., 2013) agree that risk is a combination of the physical characteristics of the flood event (the hazard) and its potential consequences: vulnerability is the likelihood that a habitat, community or individual of a species will be exposed to an negative external factor to which it is sensitive (Bohle, 2001; Bogardi and Birkmann, 2004; Kubal, et al., 2009).

According to Bollin et al. (2003), Kugler et al. (2007) and Ho et al. (2010), flood hazard maps contain information about the probability and/or magnitude of a flood event (e.g. flood extent areas generated from DEM or satellites images) and flood risk maps contain additional information about the consequences (e.g. number of people, and socio-economic infra-structure). An example of flood hazard and risk assessment for the Sindh Province in Pakistan is presented in Figure 2.6.

a) b)

Figure 2.6: Example of flood hazard and risk calculations – Sindh Province, Pakistan. (a) the district-wise flood hazard areas, (b) the total number of affected people, by level of risk (Source: Uddin et al., 2013)

In southern Africa, and Mozambique in particular, there are relatively few studies which relate to the development of frameworks for flood hazard and risk mapping – although three studies by USGS and ARA-Sul (2005), Fonseca (2012), SEMEC (2004) demonstrated the application of Digital Elevation Models (DEMs) in flood risk determination. SEMEC (2004) applied these methods for flood risk analysis in six major river basins in Mozambique: the Maputo; Incomati; Limpopo; Save; Pungue and Zambezi River basins. The extent of inundation by past floods was delineated on digital maps drawn mainly from available data sources. Additional Landsat satellite imagery was acquired for 2001 floods in the Limpopo, Incomati, Zambezi and Licungo Rivers basins. Flood levels, estimated by hydraulic modelling, were compared with digital topographic data to interpret and delineate the expected extent of inundation of 1 in 10, 1 in 25, and 1 in 100 year flood return periods. The benefits of flood mapping using remote sensing

techniques in Mozambique were first proposed by INGC (under the FEWS-Net (2000) project funded by USAID) in the Limpopo Basin. The purpose of the mapping was to assess the impact of the year 2000 floods in the Lower Limpopo Basin. Landsat Satellite images were used and combined with flood extent data derived from a Digital Elevation Model of 90 m x 90 m spatial resolution. Such approaches have, as yet, not been used in the flood-prone Lower Zambezi area in Mozambique (INGC, 2009).

2.4.1. Satellites images

A number of high profile flooding events – including Bangladesh in 1987 and 1988 (Islam and Sado, 2002), the Mississippi in 1993 (Kunkel et al., 1994) and the Limpopo, Incomati and Zambezi floods in 2000 (Showstack, 2001) – have drawn attention to the need for new and improved methods for modelling large scale flood events. Reviews conducted after these floods (Kunkel et al., 1994; Droegemeier et al., 2000) identified the need for flood maps to enable hydrologists to predict areas that could be impacted as a result of forecast flows. Rapid progress has been made in the use of remote sensing techniques for flood inundation mapping (Islam and Sado, 2002; Asante et al., 2005). The application of satellite imagery from optical sensors including SPOT (Blasco et al., 1992), AVHRR (Zhou et al., 2000) and LANDSAT (Mayer and Tung, 2002) are well documented. The limitation of satellite images is the difference in the dates when images were taken – which may not correspond exactly to the occurrence of a flood event (Hess et al., 1995; Ho et al., 2010).

2.4.2. Digital Elevation Model (DEM)

Apart from satellite imagery, other methods of flood inundation mapping, based on the topography of the land surface, are required for the development of maps that can be used for flood warning purposes. Digital Elevation Model (DEMs) are the most common method used for representing topography and for visualising inundation in flood mapping applications (Kennie and Petrie, 1990; Bates and DerRoo, 2000; Faber, 2010). Kwak et al. (2012) demonstrated DEMs are most preferred for topographic data representation for applications over large areas. During the southern Africa floods of 2000, inundated areas 20 to 30 kilometres wide were observed along major rivers (such as the Limpopo and the Incomati) in Mozambique (Asante et al., 2005). Given that channel or floodplain cross-section data are typically collected, using survey equipment, less than 200 metres apart and that depth estimates along a typical cross-section are spaced at 10 or 30 metres apart (Faber, 2010), a huge volume of data would be required to adequately cover such a vast area. This makes field survey approaches both excessively expensive – the manpower required is extensive – and impractical (because the survey equipment is bulky and the data require a huge amount of computer storage and processing resources) for mapping the flood extent of large-scale

flooding events. Mapping of the routed flows onto the floodplain is commonly done using the highest resolution DEM available (Oliveira and Loucks, 1997; and Horritt and Bates, 2001b). Mapping performed in this way takes advantage of the 3D representation of topography, as offered by the DEM, while still using simple, steady state flow computations (Jones et al., 1998). Asante et al. (2005) presented one such application: a DEM was used to represent topography in a three-dimensional hydraulic model, for mapping the extent of inundation experienced in past floods in the Incomati River Basin in Mozambique.