Frequency Analysis and New Cartography of Extremes Daily Rainfall Events in Côte d’Ivoire

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

doi:10.3923/jas.2010.1684.1694

Cited by 12 publications

(4 citation statements)

References 21 publications

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“…Table S2 shows a list of papers where the GEV and a broad pool of non-asymptotic probability distributions are used to represent the maximum annual daily precipitation. Using standard goodness-of-fit tests, or statistical indicators, many of these experiments (which often involve a large number of alternatives–even more than 30 28 ) came to the conclusion that the GEV is not always the best probability distribution to represent the maximum annual daily precipitation; in some cases the GEV works better in humid sites than in dry sites 29 – 31 . While comparing extreme-value-type distributions versus standard probability distributions might be questionable 32 , 33 , we argue that, from a statistical point of view, it is always possible to test the agreement between a data sample and a probability distribution and a better agreement for a non-asymptotic distribution should be critically addressed in view of possible non-asymptotic conditions.…”

Section: Introductionmentioning

confidence: 99%

Superstatistical distribution of daily precipitation extremes: A worldwide assessment

Michele

Avanzi

2018

Sci Rep

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Maximum annual daily precipitation is a fundamental hydrologic variable that does not attain asymptotic conditions. Thus the classical extreme value theory (i.e., the Fisher-Tippett’s theorem) does not apply and the recurrent use of the Generalized Extreme Value distribution (GEV) to estimate precipitation quantiles for structural-design purposes could be inappropriate. In order to address this issue, we first determine the exact distribution of maximum annual daily precipitation starting from a Markov chain and in a closed analytical form under the hypothesis of stochastic independence. As a second step, we formulate a superstatistics conjecture of daily precipitation, meaning that we assume that the parameters of this exact distribution vary from a year to another according to probability distributions, which is supported by empirical evidence. We test this conjecture using the world GHCN database to perform a worldwide assessment of this superstatistical distribution of daily precipitation extremes. The performances of the superstatistical distribution and the GEV are tested against data using the Kolmogorov-Smirnov statistic. By considering the issue of model’s extrapolation, that is, the evaluation of the estimated model against data not used in calibration, we show that the superstatistical distribution provides more robust estimations than the GEV, which tends to underestimate (7–13%) the quantile associated to the largest cumulative frequency. The superstatistical distribution, on the other hand, tends to overestimate (10–14%) this quantile, which is a safer option for hydraulic design. The parameters of the proposed superstatistical distribution are made available for all 20,561 worldwide sites considered in this work.

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Section: Introductionmentioning

confidence: 99%

Superstatistical distribution of daily precipitation extremes: A worldwide assessment

Michele

Avanzi

2018

Sci Rep

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“…The amount of rainfall is higher in the humid equatorial climate, with a yearly mean of 1800 mm. The western part is characterized by mountain climate (between As described in previous studies (Goula et al, 2010), the lithology is characterized by the birimian formation, granitoid eburnean and archeen formation.…”

Section: Site Descriptionmentioning

confidence: 91%

Spatial and Temporal Evolution of Low Water Flows in the Sassandra River Catchment Area in Cote d’Ivoire

Anouman¹,

N'go²,

Soro³

et al. 2019

GEP

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In a context of climate change and declining water resources, knowledge of low flow is essential. Present study deals with the spatial and temporal evolution of the streams low flow in Sassandra river. In the study, 12 stations of the Sassandra sub-basins (Sassandra, N'zo, Lobo, and Davo) were selected according to the availability and quality of long-term data. Annual, monthly and daily low flow data from twelve hydrological stations of the Sassandra watershed were used and cover the period from 1970 to 2015. The methodology used is concerned with extracting the low flow data and analyzing and evaluating the trends (Mann-Kendall) and change-point (cumulate sum) of low flow data. Statistical tests are applied to the mean and variance of the low-flow series. The results of the statistical tests show more trends and change points on the mean than on the variance. Significant trends show an increase in low flow waters. The significant change point detected by the cumulative sums test generally occurs between 1990-2007. In addition, tributaries are more affected by significant trends and change point detection than Sassandra river.

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“…The results showed that the drought duration and inter-arrival time followed the Weibull distribution, and the drought severity followed the gamma distribution. Similar to mentioned literatures, many others researchers made the goodness of fit tests for different types of hydrological series, and the best PDFs were not the same at different regions or periods (e.g., Gunasekara and Cunnane,1991;Onoz and Bayazit, 1995;Onoz and Bayazit, 2001;Bi et al, 2010;Lansigan, 2009;Sandoval and Raynal-Villasenor, 2008;Shao et al, 2004). Therefore, there is not universal applicability to the selection of best PDF, and it should be selected based on the practical observations and effective comparison and testing.…”

Section: Introductionmentioning

confidence: 97%

Evaluating the Three Methods of Goodness of Fit Test for Frequency Analysis

Wang

2015

JRACR

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In hydrological statistics, the traditional assessment of goodness of fit test is interested in the testing precision to the sample generated from supposed PDF. However, the ability to reject the hypotheses when the supposed PDF is different from real PDF should be also emphasized. In addition, the sensitivity of test method to series length is important in hydrological analysis. Three methods of goodness of fit test that include Chi-Square (C-S), Kolmogorov-Smirnov (K-S), and Anderson-Darling (A-D) tests are applied in this study. The results of power test indicate that the most powerful tests for normal, uniform, P3, and Weibull distribution are K-S, C-S, and A-D tests, respectively. The test method with the best comprehensive power is C-S test, followed by K-S and A-D test.

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Frequency Analysis and New Cartography of Extremes Daily Rainfall Events in Côte d’Ivoire

Cited by 12 publications

References 21 publications

Superstatistical distribution of daily precipitation extremes: A worldwide assessment

Superstatistical distribution of daily precipitation extremes: A worldwide assessment

Spatial and Temporal Evolution of Low Water Flows in the Sassandra River Catchment Area in Cote d’Ivoire

Evaluating the Three Methods of Goodness of Fit Test for Frequency Analysis

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