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Intensity-Duration-Frequency (IDF) rainfall curves, for data series and climate projection in African cities.

De Paola F, Giugni M, Topa ME, Bucchignani E - Springerplus (2014)

Bottom Line: Quantifying the potential effects of climate change and adapting to them is one way to reduce urban vulnerability.In order to estimate the contingent influence of climate change on the IDF curves, the described procedure was applied to the climate (rainfall) simulations over the time period 2010-2050, provided by CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici).The evaluation of the IDF curves allowed to frame the rainfall evolution of the three case studies, considering initially only historical data, then taking into account the climate projections, in order to verify the changes in rainfall patterns.

View Article: PubMed Central - PubMed

Affiliation: DICEA, Università di Napoli Federico II, Napoli, Italy ; AMRA S.c.a r.l, Via Nuova Agnano, Napoli, Italy.

ABSTRACT
Changes in the hydrologic cycle due to increase in greenhouse gases cause variations in intensity, duration, and frequency of precipitation events. Quantifying the potential effects of climate change and adapting to them is one way to reduce urban vulnerability. Since rainfall characteristics are often used to design water structures, reviewing and updating rainfall characteristics (i.e., Intensity-Duration-Frequency (IDF) curves) for future climate scenarios is necessary (Reg Environ Change 13(1 Supplement):25-33, 2013). The present study regards the evaluation of the IDF curves for three case studies: Addis Ababa (Ethiopia), Dar Es Salaam (Tanzania) and Douala (Cameroon). Starting from daily rainfall observed data, to define the IDF curves and the extreme values in a smaller time window (10', 30', 1 h, 3 h, 6 h, 12 h), disaggregation techniques of the collected data have been used, in order to generate a synthetic sequence of rainfall, with statistical properties similar to the recorded data. Then, the rainfall pattern of the three test cities was analyzed and IDF curves were evaluated. In order to estimate the contingent influence of climate change on the IDF curves, the described procedure was applied to the climate (rainfall) simulations over the time period 2010-2050, provided by CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici). The evaluation of the IDF curves allowed to frame the rainfall evolution of the three case studies, considering initially only historical data, then taking into account the climate projections, in order to verify the changes in rainfall patterns. The same set of data and projections was also used for evaluating the Probable Maximum Precipitation (PMP).

No MeSH data available.


Related in: MedlinePlus

Variation of monthly extreme rainfall for different return period for Addis Ababa (using historical data and climate projections – scenario RCP 8.5).
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Fig4: Variation of monthly extreme rainfall for different return period for Addis Ababa (using historical data and climate projections – scenario RCP 8.5).

Mentions: The distribution of monthly maximum rainfall was also evaluated, using the distribution of Gumbel. Therefore the mean value, the standard deviation and the coefficient of variation, shown in Table 2, have been evaluated considering both the historical data and the climate projections (scenario RCP 8.5), including the assessment of the variation as a function of the return period. Figure 4 shows the monthly variation of the rainfall extremes for different values of return period, highlighting that the months of April and August are those in which the most extreme values have been evident.Table 2


Intensity-Duration-Frequency (IDF) rainfall curves, for data series and climate projection in African cities.

De Paola F, Giugni M, Topa ME, Bucchignani E - Springerplus (2014)

Variation of monthly extreme rainfall for different return period for Addis Ababa (using historical data and climate projections – scenario RCP 8.5).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4320185&req=5

Fig4: Variation of monthly extreme rainfall for different return period for Addis Ababa (using historical data and climate projections – scenario RCP 8.5).
Mentions: The distribution of monthly maximum rainfall was also evaluated, using the distribution of Gumbel. Therefore the mean value, the standard deviation and the coefficient of variation, shown in Table 2, have been evaluated considering both the historical data and the climate projections (scenario RCP 8.5), including the assessment of the variation as a function of the return period. Figure 4 shows the monthly variation of the rainfall extremes for different values of return period, highlighting that the months of April and August are those in which the most extreme values have been evident.Table 2

Bottom Line: Quantifying the potential effects of climate change and adapting to them is one way to reduce urban vulnerability.In order to estimate the contingent influence of climate change on the IDF curves, the described procedure was applied to the climate (rainfall) simulations over the time period 2010-2050, provided by CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici).The evaluation of the IDF curves allowed to frame the rainfall evolution of the three case studies, considering initially only historical data, then taking into account the climate projections, in order to verify the changes in rainfall patterns.

View Article: PubMed Central - PubMed

Affiliation: DICEA, Università di Napoli Federico II, Napoli, Italy ; AMRA S.c.a r.l, Via Nuova Agnano, Napoli, Italy.

ABSTRACT
Changes in the hydrologic cycle due to increase in greenhouse gases cause variations in intensity, duration, and frequency of precipitation events. Quantifying the potential effects of climate change and adapting to them is one way to reduce urban vulnerability. Since rainfall characteristics are often used to design water structures, reviewing and updating rainfall characteristics (i.e., Intensity-Duration-Frequency (IDF) curves) for future climate scenarios is necessary (Reg Environ Change 13(1 Supplement):25-33, 2013). The present study regards the evaluation of the IDF curves for three case studies: Addis Ababa (Ethiopia), Dar Es Salaam (Tanzania) and Douala (Cameroon). Starting from daily rainfall observed data, to define the IDF curves and the extreme values in a smaller time window (10', 30', 1 h, 3 h, 6 h, 12 h), disaggregation techniques of the collected data have been used, in order to generate a synthetic sequence of rainfall, with statistical properties similar to the recorded data. Then, the rainfall pattern of the three test cities was analyzed and IDF curves were evaluated. In order to estimate the contingent influence of climate change on the IDF curves, the described procedure was applied to the climate (rainfall) simulations over the time period 2010-2050, provided by CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici). The evaluation of the IDF curves allowed to frame the rainfall evolution of the three case studies, considering initially only historical data, then taking into account the climate projections, in order to verify the changes in rainfall patterns. The same set of data and projections was also used for evaluating the Probable Maximum Precipitation (PMP).

No MeSH data available.


Related in: MedlinePlus