Regional frequency analysis of rainfall extremes i

Authors: Cosmo S Ngongondo ChongYu Xu Lena M Tallaksen Berhanu Alemaw Tobias Chirwa

Publish Date: 2011/05/26

Volume: 25, Issue: 7, Pages: 939-955

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Abstract

Rainfall extremes often result in the occurrence of flood events with associated loss of life and infrastructure in Malawi However an understanding of the frequency of occurrence of such extreme events either for design or disaster planning purposes is often limited by data availability at the desired temporal and spatial scales Regionalisation which involves “trading time for space” by pooling together observations for stations with similar behavior is an alternative approach for more accurate determination of extreme events even at ungauged areas or sites with short records In this study regional frequency analysis of rainfall extremes in Southern Malawi large parts of which are flood prone was undertaken Observed 1 3 5 and 7day annual maximum rainfall series for the period 1978–2007 at 23 selected rainfall stations in Southern Malawi were analysed Cluster analysis using scaled atsite characteristics was used to determine homogeneous rainfall regions Lmoments were applied to derive regional index rainfall quantiles The procedure also validated the three rainfall regions identified through homogeneity and heterogeneity tests based on Monte Carlo simulations with regional average Lmoment ratios fitted to the Kappa distribution Based on assessments of the accuracy of the derived index rainfall quantiles it was concluded that the performance of this regional approach was satisfactory when validated for sites not included in the sample data The study provides an estimate of the regional characteristics of rainfall extremes that can be useful in among others flood mitigation and engineering designThe estimation of magnitudes and frequencies of extreme hydrometeorological events such as daily maximum rainfall is central in the design of hydraulic structures flood plain zoning and economic estimation of flood protection projects Noto and La Loggia 2009 Sarkar et al 2009 Often the interest is in the very rare events with return periods T of above 50 or 100 years This mainly owes to their destructive nature to life and infrastructures However reliable estimation of such extreme events requires very long station records if single station data are to be used Availability and quality of such data are often a challenge in many parts of the world especially in the data scarce regions of Africa The Southern Africa region is one such region as it is considered especially vulnerable to and illequipped in terms of adaptation for extreme events such as rainfall droughts and flooding This is due to a number of factors including extensive poverty famine disease and political instability Williams et al 2009 Regional frequency analysis RFA is a commonly used and practical means of providing information at sites with little or no data available Zhang and Hall 2004Various regionalisation techniques have been developed and can be broadly classified into those used for prediction in data scarce areas and those used for RFA Chen et al 2006 Durrans and Tomic 1996 Mazvimavi et al 2004 Sivapalan et al 2003 Hosking and Wallis 1997 Techniques which have been widely applied in rainfall regionalisation include linkage analysis eg Jackson 1972 spatial correlation analysis Gadgil et al 1993 common factor analysis eg Barring 1988 empirical orthogonal function analysis eg Kulkarni et al 1992 principal component analysis PCA eg Baeriswyl and Rebetez 1996 Singh and Singh 1996 cluster analysis eg Easterling 1989 Venkatesh and Jose 2007 combination of PCA and cluster analysis eg Dinpashoh et al 2004 Lmoments in association with cluster analysis eg Schaefer 1990 Guttman 1993 Wallis et al 2007 Satyanarayana and Srinivas 2008 and a combination of Lmoments and generalised least squares regression Haddad et al 2010Past rainfall regionalisation studies in Southern Africa include that of Jackson 1972 who used the spatial correlation based simple linkage analysis on rainfall data from 30 stations in Tanzania between 1930 and 1960 In that study six rainfall homogenous regions were identified PCA based studies include Barring 1988 who identified five main rainfall regions in Kenya based on daily rainfall Van Regenmortel 1995 in which Botswana was categorised into a single rainfall region based on a correlation matrix of 49 daily rainfall stations and Unganai and Mason 2001 who used summer rainfall characteristics in Zimbabwe to identify two major rainfall regions Parida and Moalafhi 2008 applied the Lmoments approach to analyse annual rainfall series for 11 stations in Botswana for the period 1960–2003 The study established that the whole of Botswana behaved homogeneously and the Generalized Extreme Value GEV distribution was accepted as the best model for the data In South Africa Smithers and Schulze 2000a b 2001 2003 also applied the Lmoments approach in various regional rainfall frequency analysisVery few studies on extreme rainfall events for Malawi and specifically our study domain in Southern Malawi an economically very important region are documented in the literature The most notable work on rainfall extremes in Malawi is probably that of Drayton 1980 who analysed 1day annual maximum rainfall from 38 stations across Malawi using the Gumbel Extreme Value I distribution to derive estimates of point daily rainfall with return periods T = 20 and 50 years New et al 2006 however reported that there is some evidence of increasing trends in regionally averaged rainfall on extreme precipitation days and in annual 1 and 5day maximum rainfalls in Southern Africa This apparent need to provide updated knowledge of rainfall extremes using well recognised regionalisation tools in a data scarce region partly motivated this study Drayton 1980 also recommended the application of more robust computer based frequency analysis proceduresThe main aims of this study therefore are 1 to improve the understanding of the regional rainfall characteristics in Southern Malawi as a key factor for regional flood estimation to support flood risk management and 2 to provide a well designed and verified procedure for operational use for RFA of rainfall extremes in data scarce region of African countries The aims will be achieved through the following specific objectives 1 to perform a RFA of 1 3 5 and 7day annual maximum rainfall series AMS1 AMS3 AMS5 AMS7 hereafter in Southern Malawi using the well known Lmoments approach 2 to develop regional index rainfalls for the various annual maximum rainfall series and 3 to evaluate the accuracy of the regional Lmoments approach in estimating design rainfall at sites in the region through uncertainty assessments To our best knowledge the RFA approach used in this study with the most up to date data available is the first of its kind for rainfall extremes in MalawiThe climate of Southern Malawi is tropical wet and dry commonly known as Savanna The main rain bearing system is the InterTropical Convergence Zone ITCZ where the north easterly monsoon and south easterly trade winds converge A distinct rainy season is experienced between November and April when over 80 of the annual rainfall occurs Tropical cyclones originating from the Indian Ocean frequently occur during the rainy season bringing very intense rainfall over few days Annual rainfall varies from 700 mm in the low lying areas to 2500 mm in highlands of Mulanje and Zomba There is considerable sporadic winter rainfall locally called chiperone in the highlands during the period from May to August The winter rains originate from an influx of cool moist southeastern winds Monthly average temperatures are around 10–16°C in the highlands and 21–30°C along the lower Shire valley British Geological Survey 2004 Figure 1 shows the location of the study area and the geographic distribution of the rainfall stations used in this study

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