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

被引:21
作者
Juma, Benard [1 ,3 ,4 ]
Olang, Luke O. [2 ,3 ]
Hassan, Mohammed [2 ]
Chasia, Stanley [1 ,3 ,4 ]
Bukachi, Vera [6 ]
Shiundu, Paul [3 ,5 ]
Mulligan, Joe [6 ,7 ]
机构
[1] Tech Univ Kenya, Dept Geosci & Environm, Nairobi, Kenya
[2] Tech Univ Kenya, Dept Biosyst & Environm Engn, Nairobi, Kenya
[3] Tech Univ Kenya, Ctr Integrated Water Resource Management, Nairobi, Kenya
[4] Tech Univ Kenya, Dept Civil Engn, Nairobi, Kenya
[5] Tech Univ Kenya, Sch Chem & Mat Sci, Nairobi, Kenya
[6] Kounkuey Design Initiat, Nairobi, Kenya
[7] KTH Royal Inst Technol, Stockholm, Sweden
基金
瑞典研究理事会;
关键词
Extreme rainfalls; Multi-timescales; Probability distributions; Goodness-of-Fit; Return period; LAND-COVER CHANGE; FREQUENCY-ANALYSIS; CLIMATE-CHANGE; FUTURE CHANGES; PRECIPITATION; MODEL; DISTRIBUTIONS; PROBABILITY;
D O I
10.1016/j.pce.2020.102929
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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.
引用
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页数:11
相关论文
共 105 条
  • [11] Bhim S., 2012, PROBABILITY ANAL EST
  • [12] Bob A.O., 2015, INFLUENCE MASCARENE, V19, P64
  • [13] Future changes and uncertainty in decision-relevant measures of East African climate
    Bornemann, F. Jorge
    Rowell, David P.
    Evans, Barbara
    Lapworth, Dan J.
    Lwiza, Kamazima
    Macdonald, David M. J.
    Marsham, John H.
    Tesfaye, Kindie
    Ascott, Matthew J.
    Way, Celia
    [J]. CLIMATIC CHANGE, 2019, 156 (03) : 365 - 384
  • [14] Development and assessment of uni- and multivariable flood loss models for Emilia-Romagna (Italy)
    Carisi, Francesca
    Schroeter, Kai
    Domeneghetti, Alessio
    Kreibich, Heidi
    Castellarin, Attilio
    [J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2018, 18 (07) : 2057 - 2079
  • [15] Chikobvu Delson, 2015, S. Afr. j. sci., V111, P01
  • [16] Chin D.A., 2019, J HYDROL ENG, DOI [10.1061/(ASCE)HE.1943-5584.0001858, DOI 10.1061/(ASCE)HE.1943-5584.0001858]
  • [17] Unjust waters: climate change, flooding and the urban poor in Africa
    Douglas, Ian
    Alam, Kurshid
    Maghenda, MaryAnne
    McDonnell, Yasmin
    McLean, Louise
    Campbell, Jack
    [J]. ENVIRONMENT AND URBANIZATION, 2008, 20 (01) : 187 - 205
  • [18] Generalized maximum likelihood estimators for the nonstationary generalized extreme value model
    El Adlouni, S.
    Ouarda, T. B. M. J.
    Zhang, X.
    Roy, R.
    Bobee, B.
    [J]. WATER RESOURCES RESEARCH, 2007, 43 (03)
  • [19] Future changes in rainfall associated with ENSO, IOD and changes in the mean state over Eastern Africa
    Endris, Hussen Seid
    Lennard, Christopher
    Hewitson, Bruce
    Dosio, Alessandro
    Nikulin, Grigory
    Artan, Guleid A.
    [J]. CLIMATE DYNAMICS, 2019, 52 (3-4) : 2029 - 2053
  • [20] Engmann S., 2011, Journal of Applied Quantitative Methods, V6, P1