This model considers an open manhole which discharges directly into the surface. Despite the fact that in some countries this aspect is something normal during urban flooding events (in Portugal for example the Civil Protection has to remove all the gates to avoid blockages as showed in figure 105a and 105b), manholes are covered by gridlines which influence the discharge of the flow.
Figure 105– a) Viana do Castelo, urban inundation (Source ARMENIO BELO/LUSA, accessed the 06/06/2014 http://www.tvi24.iol.pt/sociedade/mau-tempo-lisboa-cheias-inundacoes-meteorologia-
tvi24/1203790-4071.html) b) Another example, urban inundation and gate removal. (Photo LUIS PARDAL/GLOBAL IMAGENS, accessed the 06/06/2014
(Right)http://www.jn.pt/PaginaInicial/Sociedade/Interior.aspx?content_id=2862575)
Hence future work will focus on designing a “lid” above the manhole to make the system more realistic and provide more datasets with different configurations.
As described, computer models are inherently problematic to verify due to the difficultly of acquiring reliable data during the flood event and most models are calibrated using only an estimated measure of the extent of flooding. Similarly, existing models do not currently attempt to quantify the transport and fate of sewer derived pollutants and hence it is difficult to assess the risk of exposure and the potential impact of flood waters on health. Manholes are interaction points where there is a critical transfer of flow and pollution and this process is difficult to quantify due to the complex and time varying nature. Understanding such behaviour is essential to accurately evaluate urban flood risk by hydraulic models.
Modelling the transport of harmful contaminants/pollutants from sewer interface points is a relevant step to increase the accuracy of computer models and it has only recently been attempted (Pathirana, 2011). Coupled with studies of health risk from exposure to flood water (Fewtrell et al, 2011) such models could be used to predict both areas most at risk from contamination and the potential health impacts of flood events. The large
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number of uncertainties involved (e.g. impact of urban topographies on hydraulic profiles, storage zones and dispersion) means that such modelling is at an early stage, and is extremely prone to inexact calibration and verification.
The next feasible outputs from this experimental facility will provide the first data sets for such advanced calibration and verification, thereby providing enhanced opportunities for the prediction of accurate combination between flood flow and contaminant movement during flood events. The results will subsequently be used to improve the accuracy of commercial modelling software with significant benefits in the evaluation of flood risk and the prioritisation of asset investment.
Future work will utilise this unique surface/subsurface together with numerical and computational advances in the solution of the hydraulic and pollutant transport equations. The main challenge will consider the experimentally investigation of the transport of soluble material from sewers to surface flows via manholes and determine the transport and mixing characteristics in typical overland shallow flow flooding conditions.
Pollutant transport through the system will be quantified in both steady and time varying flow conditions. In time varying tests, dye will be injected into the pipe immediately prior to a manhole surcharge event to simulate contaminates being flushed through the system and quantify the total transfer of mass to surface flow via an individual manhole. Different surface topographical setups (Figure 106) will be tested to determine how features influence mass transport in surface flow via the creation of turbulent structures, local velocity shear and trapping zones (characterised with PIV measurements, using the equipment designed and tested during the final part of this research). Three test surface topographies will be installed and tested which are designed to simulate the effect of typical street features. The geometry of surface features will be based on the sewer scaling.
1. Featureless bed – Initial tests to characterise mixing over a range of flow conditions. 2. Road and pavement – At low flows, pavements will promote transverse velocity
gradients and shear. At higher flows, flow will overtop pavements, potentially creating turbulent mixing layers and considerable extra velocity shear.
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3. Trapping zones - A range of street features may act as trapping zones and affect the transport of pollutants. Such zones will be simulated by constructing gaps in the pavement profile.
Dimensionless mixing coefficients (i.e. normalised by flow depths and shear velocities) within the surface flow will be determined. Characterisation of the velocity fields via PIV developed during this research will be determined. Mixing coefficients will be initially quantified for the featureless bed in steady uniform flow conditions via both analytical and numerical solutions. By achieving that, a unique data set that will be made available to other researchers and software developers.
Once these results will be provided, considering that hydraulic models are increasingly being used to plan significant asset investment and form the basis of flood awareness/warning schemes, there will be significant benefits in terms of more efficient drainage design/investment and increased resilience to flood events.
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