to a true dry weather flow. On a network monitoring and control basis, this takes up
capacity in the network, but, by analysis, the very nature and behaviour of the flow,
together with rainfall patterns, can give clues to the location of the break within the
gravity sewer environment. This can allow for infiltration points to be localised with
relatively small costs when compared with CCTV methodologies of infiltration
identification.
The last input into the sewage collection network is, of course, rainfall. The main
detection method is a combination of weather radar, rain gauges and artificial
intelligence, enabling the prediction of the impact of a rainfall event on the sewer
[11]. Although weather radar is well established, the current techniques in terms of
the wastewater network have not allowed the resolution of data that is required, and
there are very few techniques in place that will then translate this into impact on the
sewerage environment using a model-based approach.
The main challenge is one of resolution. When the UK meteorological office
looks at weather, they look at it on a national basis, and the resolution of the weather
radar is for grids that are 13 km wide and 13 km long (169 m
2 grids). Allowing for
the surface area of England and Wales, this splits the UK up into 895 grids. There are
approximately 10,000 WTW in this area of which 3,742 works treat greater than
50 m
3 /day and are numerically consented. Hence, in reality, the Meteorological
office data has not currently got the resolution necessary for a smart wastewater
network. In this case, the resolution of the weather radar data has to be much finer,
and also work in conjunction with rainfall data to predict what the impact of a storm
event will be on the network. This moves C-Band Weather radar (the technology that
the Meteorological Office use) to X-Band Weather radar which measures on a much
smaller scale, with the disadvantage that many more radar units are required
[12]. Rico-Ramirez et al. [13] show the considerable uncertainty in radar rainfall
estimates and how this raises implications for modelling. Also, in Schellart et al.
[14], the difficulty of using rainfall nowcasts for predicting sewer flows is discussed.
From this it can be seen that the challenges of measuring the inputs into the
wastewater network are large with:
• Domestic wastewater monitoring not established, as it is not financially viable.
• Industrial wastewater monitoring well established and input volumes known,
although the accuracy of the installed flow meters are not always known, as the
maintenance of the meters is sporadic.
• Inputs from infiltration can be estimated but are very changeable due to climatic
changes and underlying soil conditions.
• Weather radar and the impact of rainfall on the network system are improving as
technology improves, and there are some systems available at the current time
that will allow this to happen.
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O. Grievson
capacity in the network, but, by analysis, the very nature and behaviour of the flow,
together with rainfall patterns, can give clues to the location of the break within the
gravity sewer environment. This can allow for infiltration points to be localised with
relatively small costs when compared with CCTV methodologies of infiltration
identification.
The last input into the sewage collection network is, of course, rainfall. The main
detection method is a combination of weather radar, rain gauges and artificial
intelligence, enabling the prediction of the impact of a rainfall event on the sewer
[11]. Although weather radar is well established, the current techniques in terms of
the wastewater network have not allowed the resolution of data that is required, and
there are very few techniques in place that will then translate this into impact on the
sewerage environment using a model-based approach.
The main challenge is one of resolution. When the UK meteorological office
looks at weather, they look at it on a national basis, and the resolution of the weather
radar is for grids that are 13 km wide and 13 km long (169 m
2 grids). Allowing for
the surface area of England and Wales, this splits the UK up into 895 grids. There are
approximately 10,000 WTW in this area of which 3,742 works treat greater than
50 m
3 /day and are numerically consented. Hence, in reality, the Meteorological
office data has not currently got the resolution necessary for a smart wastewater
network. In this case, the resolution of the weather radar data has to be much finer,
and also work in conjunction with rainfall data to predict what the impact of a storm
event will be on the network. This moves C-Band Weather radar (the technology that
the Meteorological Office use) to X-Band Weather radar which measures on a much
smaller scale, with the disadvantage that many more radar units are required
[12]. Rico-Ramirez et al. [13] show the considerable uncertainty in radar rainfall
estimates and how this raises implications for modelling. Also, in Schellart et al.
[14], the difficulty of using rainfall nowcasts for predicting sewer flows is discussed.
From this it can be seen that the challenges of measuring the inputs into the
wastewater network are large with:
• Domestic wastewater monitoring not established, as it is not financially viable.
• Industrial wastewater monitoring well established and input volumes known,
although the accuracy of the installed flow meters are not always known, as the
maintenance of the meters is sporadic.
• Inputs from infiltration can be estimated but are very changeable due to climatic
changes and underlying soil conditions.
• Weather radar and the impact of rainfall on the network system are improving as
technology improves, and there are some systems available at the current time
that will allow this to happen.
120
O. Grievson