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| Titel |
A new methodology for dynamic modelling of health risks arising from wastewater influenced urban flooding |
| VerfasserIn |
Claus Jørgensen, Ole Mark, Slobodan Djordjević, Michael Hammond, David M. Khan, Anders Erichsen, Ann Dorrit Enevoldsen, Gerald Heinicke, Birgitte Helwigh |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250110518
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| Publikation (Nr.) |
 EGU/EGU2015-10521.pdf |
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| Zusammenfassung |
| Indroduction
Urban flooding due to rainfall exceeding the design capacity of drainage systems is a
global problem and it has significant economic and social consequences. While the cost of the
direct flood damages of urban flooding is well understood, the indirect damages, like the
water borne diseases is in general still poorly understood. Climate changes are expected to
increase the frequency of urban flooding in many countries which is likely to increase water
borne diseases.
Diarrheal diseases are most prevalent in developing countries, where poor sanitation, poor
drinking water and poor surface water quality causes a high disease burden and
mortality, especially during floods. The level of water borne diarrhea in countries with
well-developed water and waste water infrastructure has been reduced to an acceptable
level, and the population in general do not consider waste water as being a health
risk.
Hence, exposure to wastewater influenced urban flood water still has the potential to
cause transmission of diarrheal diseases.
When managing urban flooding and planning urban climate change adaptations, health
risks are rarely taken into consideration. This paper outlines a novel methodology for linking
dynamic urban flood modelling with Quantitative Microbial Risk Assessment (QMRA). This
provides a unique possibility for understanding the interaction between urban flooding and
the health risks caused by direct human contact with flood water and provides an option for
reducing the burden of disease in the population through the use of intelligent urban flood risk
management.
Methodology
We have linked hydrodynamic urban flood modelling with quantitative microbial risk
assessment (QMRA) to determine the risk of infection caused by exposure to wastewater
influenced urban flood water. The deterministic model MIKE Flood, which integrates the
sewer network model in MIKE Urban and the 2D surface model MIKE21, was
used to calculate the concentration of pathogens in the flood water, based on either
measured waste water pathogen concentrations or on assumptions regarding the
prevalence of infections in the population. The exposure (dosage) to pathogens was
estimated by multiplying the concentration with literature values for the ingestion
of water for different exposure groups (e.g. children, adults). The probability of
infection was determined by applying dose response relations and MonteCarlo
simulation.
The methodology is demonstrated on two cases, i.e one case from a developing country
with poor sanitation and one case from a developed country, where climate adaptation is the
main issue: The risk of cholera in the City of Dhaka, Bangladesh during a flood event 2004,
and the risk of bacterial and viral infections of during a flood event in Copenhagen, Denmark
in 2011.
Results
PIC
The historical flood events in Dhaka (2004) and Copenhagen (2011) were successfully
modelled. The urban flood model was successfully coupled to QMRA. An example of the
results of the quantitative microbial risk assessment given as the average estimated risk of
cholera infection for children below 5 years living in slum areas in Dhaka is shown in the
figure.
Similarly, the risk of infection during the flood event in Copenhagen will be presented in
the article.
Conclusions
We have developed a methodology for the dynamic modeling of the risk of infection
during waste water influenced urban flooding. The outcome of the modelling exercise
indicates that direct contact with polluted flood water is a likely route of transmission of
cholera in Dhaka, and bacterial and viral infectious diseases in Copenhagen. It demonstrates
the applicability and the potential for linking urban flood models with QMRA in order to
identify interventions to reduce the burden of disease on the population in Dhaka City and
Copenhagen. |
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