Producinghazard maps in GIS for flood risk management is integral to local levelpreparation. They increase the awareness of the local people for disaster riskmanagement and offer many additional benefits to conventional mapping (Tran et al., 2008). Figure 1 displays a clearflood risk map for the impact of a 1:100 year flood, in Prudhoe. Overlayingmodern infrastructure onto an historic base map clearly shows how thesusceptibility of properties and infrastructure has changed.
For example, theconstruction of new terraced housing on Tyne Gardens, the development ofOvingham School and the demolished Water Works. This information has clearlyinfluence the town to utilize flood plain zoning; creating parks and leavingopen spaces near the river banks and building residential properties at higherelevations, away from the river. This map can be updated with ease to changesin the landscape and used by investors for appropriate developments.Thedata from Figure 1 can be manipulated to produce a graph assessing the change inrisk over time, as shown in Figure 2. This graph shows a clear increased riskof flooding to all types of infrastructure in Prudhoe.
However, the graphoffers no identification nor positioning or extent of damage and is thereforeimpractical without the accompaniment of maps such as figure 1.Asshown below, Manning’s equation is used to estimate the hydraulic properties ofthe 2005 River Tyne floods. The peak discharge measured at the nearestmonitoring station, Bywell, was 1374m3 s-1. Table 1 shows that this figure issix times greater than even the largest estimate of discharge using Manning’sequation. As the equation adopts the assumption that the ground slope is thesame as the water surface slope it is rarely applicable to flood conditions. Toovercome this obstacle the water surface slope (during the flood event) can besurveyed and incorporated into the equation, producing more accurate results.This technique of counteraction was used by Hessel et al.
(2003) when studying Loess in China.From the data availablethe flood outlines fulfil 54.9% of the flood risk, therefore the EnvironmentAgency is over compensating the risk of a flood.
However, the overlapping ofrecorded flooding and flood risk is consistent throughout demonstrating accuracyin flood prediction. The Environment Agency should place more emphasis on theroute of water influenced by man-made features, for example, following a road.Furthermore, this data has no information relating to the depth of the water.The field observations above demonstrate the depth of the flooding, however themap shows no indication of this.
This vital information must be incorporatedinto the flood risk for precautionary actions to be taken. The high resolutionDEM for this area can be used to estimate a fairly accurate flood depth (Rahmanand Tahkur, 2017).Taking aerial imagesimmediately after a disaster event can provide an historical record of theevent and facilitate preparedness of future events. Furthermore, this type ofremote sensing reduces the risk of danger for researchers.Using a DoD has proved advantageous as a mapping mechanism forgeomorphic hazards.
To overcome the difficulty of differentiating the erosionaland depositional features the DoD distinctly shows the direction of volumetricchange. However, DEMs do not provide information concerning river bathymetry(Laks et al., 2017). This can lead toconfusion when assessing the volumetric change of the channel. To achieve thisdata, a cross-section of the River Derwent channel must be determined. However,this is time consuming and expensive to do before and after a flood.
A systematic offset as large as 20m is worrying for the precision ofthis investigation. Inaccurate generalisations regarding lahar depositthickness could result. Assessing the risk of laharflows requires an extensive a priori knowledge of the volcano and observationsfrom previous lahar flows. In this case, Calbuco is a glacier cappedstratovolcano with pyroclastic flows (Russell et al., 2016). Figure 7 shows the lahar routways, initialobservations include the influence of river channels on lahar extent. Thepre-exsisting channels act as motorways for lahar flow, reaching the furthestdistances in these efficient routes to lower eleations. Figure 7 also showslahars deviating fom this path to follow the roads as the deforrested areasprovide less resistance to flow.
According to Franco et al. (2010), the infrastructure most at risk are those closest tothe centre of the river channel, here a house would be ‘wiped out’ by thelahar. Destruction or burial is significantly less on the channel margins, howeverthese properties are still affected. These finding are in concurrance with thefindings in figure 10. The individuals living inclose proximity of the river channels are the most vunerable to the laharimpacts.
Therefore, relocation seems the pragmatic solution, however the broad distribution of tributariesmultiplies the risk of disaster and vulnerability, especially when lahars occursimultaneously, this could lead to unnecessary relocations (Thouret et al.,2013). An alternative solution of reducing the risk is the construction ofdiversion channels before they reach critical areas.
These are equivalent toriver levees in an attempt to reduce flood risk. Using this method ensures thatcommunities can survive small to medium events with little economic impact. Conversely,this may lull the population into a false sense of security, lowering theirperception of the risk (Pierson et al.
2014). The use of a lahar warning systems is already in practice in the areaand seems very effective as 6500 people were evacuated to safety. For aconclusive lahar risk assessment, a more precise delimitation of the areaspreviously affected is required to accurately predict future extents (Leone and Lesales, 2009).Using DAN3D to calculate the maximum extent and thickness oflandslides is advantageous over real-life modelling as it is inexpensive, lesstime consuming and parameters may be varied to the slightest degree.
However,computer programmes cannot predict anomalous nuclei that dictate the massmovement, resulting in inaccurate outcomes (Schraml et al., 2015).Figure 12 uses DAN3D as a modelling techniques for geomorphichazards following the 1991 Mount Cook rock avalanche. The extent and depth ofthe landslide were the known data, however the parameters controlling thesewere not. While the modelled result may be similar to the actual event, thisdoes not equate to the parameters having any similarities. For example, themass doubled before reaching its final extent, this cannot be replicated in thecomputer programme (Evans and DeGraff, 2002).
Therefore, these results must begeneralised with caution.