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Sökning: id:"swepub:oai:DiVA.org:kth-287127" > Analysis of rainfal...

Analysis of rainfall extremes in the Ngong River Basin of Kenya : Towards integrated urban flood risk management

Juma, B. (författare)
Olang, L. O. (författare)
Hassan, M. (författare)
visa fler...
Chasia, S. (författare)
Bukachi, V. (författare)
Shiundu, P. (författare)
Mulligan, Joe (författare)
KTH,Strategiska hållbarhetsstudier
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 (creator_code:org_t)
Elsevier, 2020
2020
Engelska.
Ingår i: Physics and Chemistry of the Earth. - : Elsevier. - 1474-7065 .- 1873-5193.
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Extreme rainfall events are a major cause of highly disruptive flooding in small urban watersheds with limited flood risk management systems. In the Ngong River Basin of Kenya, such floods affect more than 0.5 Million residents within the Kibera informal settlements of Nairobi. However, there is paucity of information about the characteristics of the extreme rainfalls to support flood risk management. This study investigated the best-fit probability distribution models for the extreme rainfalls of the Ngong Basin using Block Maxima approach as a basis for anticipatory flood risk management. Daily rainfall data for the period between 1968 and 2017 were acquired from the existing two rainfall stations to support the analysis at monthly, seasonal and annual timescales. The Gamma, Pearson Type III, Gumbel and Generalized Extreme Value distributions were selected and applied to each timescale. Parameters of the distributions were determined using the Maximum-Likelihood estimator. The validity of the fitted probability models was tested using the Kolomogorov- Smirnov, Anderson-Darling and Cramer von Misses measures for Goodness of Fit. The best-fit probability distributions were subsequently used to establish the rainfall frequencies and return levels at annual timescales. The results show that Pearson Type III provided the best fit at monthly timescales during the dry spell months, while the Generalized Extreme Value distribution provided best results during the wet periods. At seasonal timescales, the Gamma distribution was noted to be the best-fit model. The return levels developed could essentially support the design of urban flood control structures for appropriate flood risk management.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Vattenteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Water Engineering (hsv//eng)

Nyckelord

Extreme rainfalls
Goodness-of-Fit
Multi-timescales
Probability distributions
Return period
Flood control
Maximum likelihood estimation
Rain
Risk assessment
Risk management
Uncertainty analysis
Watersheds
Flood risk management
Generalized extreme value distribution
Informal settlements
Maximum likelihood estimator
Probability distribution model
Probability models
Rainfall frequency
Urban flood control
Floods

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