model runoff from numerous sub-catchments with
individual percent imperviousness and sewage
transport in a sewage network. This software can
simulate flow from catchments to the sewer based
on their actual spatial geometry and the
corresponding hydrological parameters.
According to [18] the volumes and peaks of
runoff are comparable to the ones using the traditional approach. The specific result from surface
runoff modelling is the primary input data for
modelling sewer flow and overflow. Therefore
the method described is promising and useful
already. However, even though the first trial
using remote sensing technique results in similar
peak flow and runoff volume, some refinements
are desirable [18]. The classifications based on the
remote sensing technique can and should be
adjusted, e.g., to adjust for shadowing from trees
and more precise classification of some specific
soils, e.g., sandy areas [18].
Modelling of Water Transport in the
Sewer System
The last step in the modelling approach is the
transport of water into the sewer system. At this
point in the process of modelling, any significant
differences in the modelling approaches in [18]
should not be apparent. The uncertainties
connected to using airborne images as input for
analyzing overflow and sewage transport are similar to using the traditional approach, as observed
in the specific case of the comparison made at
Amager Øst.
Future Directions
The example of the modelling tools and remote
sensing technique mentioned in this chapter for
urban drainage modelling is generally applicable
in many different contexts. More significant and
more autonomous digital image analysis and classification for use in urban drainage modelling are,
however, needed. It is desirable to take advantage
of sensors that can provide information at the pixel
level, of, for example, aerial photography and
remote sensing as [18] demonstrated was possible.
The technique may be an option for a simpler and
faster approach to setting up a model for the analysis of water transport and drainage in, e.g., urban
areas. However, more case studies are needed and
an understanding as to when it is economical to use
such technology for efficient classification and calculation of percent imperviousness and other runoff and surface data characteristics.
References
1. Ferrier RC, Jenkins A (2010) The catchment management concept. In: Ferrier RC, Jenkins A (eds) Handbook of catchment management, vol 1. Blackwell,
Oxford
2. Thorndahl S et al (2017) Weather radar rainfall data in
urban hydrology. Hydrol Earth Syst Sci 21:1359–1380
3. United Nations, SDG (2015) Sustainable development
goals, 17 goals to transform our world. [Online].
https://www.un.org/sustainabledevelopment/sustaina
ble-development-goals/
4. United Nations, Goal 13 (2015) Take urgent action to
combat climate change and its impacts. [Online].
https://www.un.org/sustainabledevelopment/climatechange-2/
5. Intergovernmental Panel on Climate Change
(2014) Climate change 2014 synthesis report summary
for policymakers
6. Garnier J et al (2013) Modeling historical changes in
nutrient delivery and water quality of the Zenne River
(1790s–2010): the role of land use, waterscape and
urban wastewater management. J Mar Syst 128:62–76
7. Spildevandskomiteen (2018) Skrifter. [Online].
https://universe.ida.dk/spildevandskomiteen/skrifter/
8. American, Society of Civil Engineers (ASCE)
(2013) Standard guidelines for the design, installation,
and operation and maintenance of urban subsurface
drainage. American Society of Civil Engineers, ProQuest Ebook Central, Reston. https://ebookcentral.pro
quest.com/lib/sdub/detail.action?docID=3115658
9. Spildevandskomiteen.
Spildevandskomiteens
regnmålersystem. SVK bestilling . [Online] Danmarks
Meteorologiske Institut. http://svk.dmi.dk/
10. Spildevandskomiteen (2014) Skrift nr. 30. Opdaterede
klimafaktorer og dimensionsgivende regnintensiteter.
[Online]. [Cited: 05 07 2018.] https://ida.dk/sites/
default/files/svk_skrift30_0.pdf
11. DHIGROUP. Modelling of storm water drainage network and sewer collection systems using MIKE
URBAN. MIKE URBAN. [Online] DHIGROUP.
[Cited: 19 10 2017.] https://www.mikepoweredbydhi.
com/products/mike-urban
12. DHI. MIKE URBAN documentation. MOUSE reference manual. [Online] DHIGROUP. [Cited: 20 01
Urban Drainage Modelling for Management of Urban Surface Water
235
individual percent imperviousness and sewage
transport in a sewage network. This software can
simulate flow from catchments to the sewer based
on their actual spatial geometry and the
corresponding hydrological parameters.
According to [18] the volumes and peaks of
runoff are comparable to the ones using the traditional approach. The specific result from surface
runoff modelling is the primary input data for
modelling sewer flow and overflow. Therefore
the method described is promising and useful
already. However, even though the first trial
using remote sensing technique results in similar
peak flow and runoff volume, some refinements
are desirable [18]. The classifications based on the
remote sensing technique can and should be
adjusted, e.g., to adjust for shadowing from trees
and more precise classification of some specific
soils, e.g., sandy areas [18].
Modelling of Water Transport in the
Sewer System
The last step in the modelling approach is the
transport of water into the sewer system. At this
point in the process of modelling, any significant
differences in the modelling approaches in [18]
should not be apparent. The uncertainties
connected to using airborne images as input for
analyzing overflow and sewage transport are similar to using the traditional approach, as observed
in the specific case of the comparison made at
Amager Øst.
Future Directions
The example of the modelling tools and remote
sensing technique mentioned in this chapter for
urban drainage modelling is generally applicable
in many different contexts. More significant and
more autonomous digital image analysis and classification for use in urban drainage modelling are,
however, needed. It is desirable to take advantage
of sensors that can provide information at the pixel
level, of, for example, aerial photography and
remote sensing as [18] demonstrated was possible.
The technique may be an option for a simpler and
faster approach to setting up a model for the analysis of water transport and drainage in, e.g., urban
areas. However, more case studies are needed and
an understanding as to when it is economical to use
such technology for efficient classification and calculation of percent imperviousness and other runoff and surface data characteristics.
References
1. Ferrier RC, Jenkins A (2010) The catchment management concept. In: Ferrier RC, Jenkins A (eds) Handbook of catchment management, vol 1. Blackwell,
Oxford
2. Thorndahl S et al (2017) Weather radar rainfall data in
urban hydrology. Hydrol Earth Syst Sci 21:1359–1380
3. United Nations, SDG (2015) Sustainable development
goals, 17 goals to transform our world. [Online].
https://www.un.org/sustainabledevelopment/sustaina
ble-development-goals/
4. United Nations, Goal 13 (2015) Take urgent action to
combat climate change and its impacts. [Online].
https://www.un.org/sustainabledevelopment/climatechange-2/
5. Intergovernmental Panel on Climate Change
(2014) Climate change 2014 synthesis report summary
for policymakers
6. Garnier J et al (2013) Modeling historical changes in
nutrient delivery and water quality of the Zenne River
(1790s–2010): the role of land use, waterscape and
urban wastewater management. J Mar Syst 128:62–76
7. Spildevandskomiteen (2018) Skrifter. [Online].
https://universe.ida.dk/spildevandskomiteen/skrifter/
8. American, Society of Civil Engineers (ASCE)
(2013) Standard guidelines for the design, installation,
and operation and maintenance of urban subsurface
drainage. American Society of Civil Engineers, ProQuest Ebook Central, Reston. https://ebookcentral.pro
quest.com/lib/sdub/detail.action?docID=3115658
9. Spildevandskomiteen.
Spildevandskomiteens
regnmålersystem. SVK bestilling . [Online] Danmarks
Meteorologiske Institut. http://svk.dmi.dk/
10. Spildevandskomiteen (2014) Skrift nr. 30. Opdaterede
klimafaktorer og dimensionsgivende regnintensiteter.
[Online]. [Cited: 05 07 2018.] https://ida.dk/sites/
default/files/svk_skrift30_0.pdf
11. DHIGROUP. Modelling of storm water drainage network and sewer collection systems using MIKE
URBAN. MIKE URBAN. [Online] DHIGROUP.
[Cited: 19 10 2017.] https://www.mikepoweredbydhi.
com/products/mike-urban
12. DHI. MIKE URBAN documentation. MOUSE reference manual. [Online] DHIGROUP. [Cited: 20 01
Urban Drainage Modelling for Management of Urban Surface Water
235