Update of Intensity-Duration-Frequency Curves for Precipitation of Short Durations in Tropical Area of West Africa (Cote D'ivoire)

Soro, Gbombélé; Bi, Tié Albert Goula; Kouassi, F. W.; Srohourou, Bernard

doi:10.3923/jas.2010.704.715

Cited by 16 publications

(8 citation statements)

References 27 publications

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“…This can mainly be explained by the scarcity of rainfall networks in West Africa and the difficulty to collect the data from national meteorological services. Most of the existing studies propose point inference of extreme rainfall distribution on regions of limited extension that locally provide multidecadal point rainfall series (e.g., Mohymont and Demarée [2006] for Congo, Endreny and Imbeah [2009] for Ghana, Emile et al [2008] and Soro et al [2010] for Ivory Coast, and Oyegoke and Oyebande [2008] and Okonkwo and Mbajiorgu [2010] for Nigeria). To our knowledge, the only work of regional bearing is the recent publication by Paeth et al [2010], who tried to characterize the year 2007 that was affected by extended floods by analyzing different rainfall data set (monthly rain gauges and satellite products).…”

Section: Region and Datamentioning

confidence: 99%

Extreme rainfall in West Africa: A regional modeling

Panthou

Vischel

Lebel

et al. 2012

Water Resources Research

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[1] In a world of increasing exposure of populations to natural hazards, the mapping of extreme rainfall remains a key subject of study. Such maps are required for both flood risk management and civil engineering structure design, the challenge being to take into account the local information provided by point rainfall series as well as the necessity of some regional coherency. Two approaches based on the extreme value theory are compared here, with an application to extreme rainfall mapping in West Africa. The first approach is a local fit and interpolation (LFI) consisting of a spatial interpolation of the generalized extreme value (GEV) distribution parameters estimated independently at each station. The second approach is a spatial maximum likelihood estimation (SMLE); it directly estimates the GEV distribution over the entire region by a single maximum likelihood fit using jointly all measurements combined with spatial covariates. Five LFI and three SMLE methods are considered, using the information provided by 126 daily rainfall series covering the period . The methods are first evaluated in calibration. Then the predictive skills and the robustness are assessed through a cross validation and an independent network validation process. The SMLE approach, especially when using the mean annual rainfall as covariate, appears to perform better for most of the scores computed. Using the Niamey 104 year time series, it is also shown that the SMLE approach has the capacity to deal more efficiently with the effect of local outliers by using the spatial information provided by nearby stations.

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Section: Region and Datamentioning

confidence: 99%

Extreme rainfall in West Africa: A regional modeling

Panthou

Vischel

Lebel

et al. 2012

Water Resources Research

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“…This is especially the case in many tropical regions, such as West Africa; in fact, one reason being that a harsh environment and resource scarcity have made it very challenging to operate recording raingauge networks. The few IDF studies available in the region (Oyebande, 1982;Mohymont et al, 2004;Oyegoke and Oyebande, 2008;Soro et al, 2010) are essentially empirical with no theoretical background that allows for the upgrade of their results in order to produce IDAF curves. ARF studies are still fewer, the most noticeable being an attempt by Rodier and Ribstein (1988) and Ribstein and Rodier (1994) at computing ARF values for a return period of 10 years, with no explicit inference of the areal rainfall distributions.…”

Section: G Panthou Et Al: Characterising the Space-time Structure Omentioning

confidence: 99%

Characterising the space–time structure of rainfall in the Sahel with a view to estimating IDAF curves

Panthou

Vischel

Lebel

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Intensity-duration-area-frequency (IDAF) curves are increasingly demanded for characterising the severity of storms and for designing hydraulic structures. Their computation requires inferring areal rainfall distributions over the range of space scales and timescales that are the most relevant for hydrological studies at catchment scale. In this study, IDAF curves are computed for the first time in West Africa, based on the data provided by the AMMA-CATCH Niger network, composed of 30 recording rain gauges having operated since 1990 over a 16 000 km 2 area in south-western Niger. The IDAF curves are obtained by separately considering the time (intensity-duration-frequency, IDF) and space (areal reduction factor, ARF) components of the extreme rainfall distribution. Annual maximum intensities are extracted for resolutions between 1 and 24 h in time and from point (rain gauge) to 2500 km 2 in space. The IDF model used is based on the concept of scale invariance (simple scaling) which allows the normalisation of the different temporal resolutions of maxima series to which a global generalised extreme value (GEV) is fitted. This parsimonious framework allows one to use the concept of dynamic scaling to describe the ARF. The results show that coupling a simple scaling in space and time with a dynamical scaling that relates to space and time allows one to satisfactorily model the effect of space-time aggregation on the distribution of extreme rainfall.

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“…Since then, different forms of IDFs have been constructed for several regions of the world. In Africa we can cite the studies which utilized statistical method to construct IDF curves: in Congo (Mohymont et al, 2004;Mohymont & Demarée, 2006;Van de Vyver & Demarée, 2010), in Ghana (Endreny & Imbeah, 2009), in Cote d'Ivoire (Soro et al, 2008;Soro et al, 2010) and in Nigéria (Oyegoke & Oyebande, 2008;Okonkwo & Mbajiorgu, 2010). Traditionally the IDF curves are constructed by performing statistical analysis on Annual Maxima Series (AMS) or Partial Duration Series (PDS) by fitting probability distribution for several pre-selected rainfall durations (Bougadis and Adamowski, 2006).…”

Section: Introductionmentioning

confidence: 99%

Estimation of IDF Curves of Extreme Rainfall by Simple Scaling in Northern Oueme Valley, Benin Republic (West Africa)

Agbazo¹,

N’Gobi²,

Kounouhéwa³

et al. 2016

Earth sci. res. j.

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Rainfall intensity-duration-frequency (IDF) curves are of particular importance in water resources management, for example, in urban hydrology, for the design of hydraulic structures and the estimation of the flash flood risk in small catchments. IDF curves describe rainfall intensity as a function of duration and return period, and they are significant for water resources planning, as well as for the design of hydraulic constructions and structures. In this study, scaling properties of extreme rainfall are examined to establish the scaling behavior of statistical non-central moment over different durations. IDF curves and equations are set up for all stations by using the parameter obtained from scaling behavior, the location and scale parameters μ24 and σ24 of the Gumbel distribution (EVI) sample of annual maximum 1440 min rainfall data. In another hand, we have established the IDF curves for ten selected rain gauge stations in the Northern (Oueme Valley) parts of Benin Republic, West Africa by using the simple scaling approach. Analysis of rainfall intensities (5 min and 1440 min rainfall data) from the ten rainfall stations shows that rainfall in north-Benin displays scales invariance property from 5 min to 1440 min. For time scaling, the statistical properties of rainfall follow the hypothesis of simple scaling. Therefore, the simple scaling model applies to the rainfall in (Oueme Valley). Hence, the simple scaling model is thought to be a viable approach to estimate IDF curves of hourly and sub-hourly rainfall form rainfall projections. The obtained scaling exponents are less than 1 and range from 0.23 to 0.59. The empirical model shows that the scaling procedure is a good estimator as it is more efficient and gives more accurate estimates compared with the observed rainfall than the traditional method which only consists the Gumbel model in all stations for lower return periods (T<5 years) but not for higher return periods.Las curvas de precipitación Intensidad-Duración-Frecuencia (IDF) son de particular importancia en el manejo de los recursos hídricos, como es el caso de la hidrología urbana o para el diseño de estructuras hidráulicas y la estimación del riesgo de crecidas en pequeñas captaciones. Las curvas IDF describen la intensidad de las precipitaciones como una función con períodos de duración y recurrencia, lo que las hace significativas en la planeación de recursos hídricos así como en el diseño de construcciones y estructuras hidráulicas. Este estudio examina las propiedades de escala en precipitaciones extremas para establecer un comportamiento en momentos estadísticos marginales en diferentes períodos de duración. Se establecieron las curvas IDF y las ecuaciones para todas las estaciones a partir del parámetro obtenido del comportamiento de escala, la ubicación y los parámetros de escala μ24 and σ24 de la muestra de información de precipitación máxima anual de 1440 minutos de la distribución de Gumbel (EVI). Por otro lado, se establecieron las curvas IDF para 10 estaciones pluviométricas sele...

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Update of Intensity-Duration-Frequency Curves for Precipitation of Short Durations in Tropical Area of West Africa (Cote D'ivoire)

Cited by 16 publications

References 27 publications

Extreme rainfall in West Africa: A regional modeling

Extreme rainfall in West Africa: A regional modeling

Characterising the space–time structure of rainfall in the Sahel with a view to estimating IDAF curves

Estimation of IDF Curves of Extreme Rainfall by Simple Scaling in Northern Oueme Valley, Benin Republic (West Africa)

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