Les valeurs extrêmes des variables hydroclimatiques présentent un intérêt tout particulier lorsqu’on parle en termes de risque. L'estimation de la récurrence de pluies extrêmes fournit des éléments indispensables pour la construction d'infrastructures telles que les digues, les ouvrages d'assainissement, etc., afin de protéger efficacement la population et leurs biens. Cet article a pour objectif de trouver une loi théorique qui peut montrer une bonne représentation de la fonction de distribution des pluies journalières maximales annuelles pour la prévention des risques liés aux inondations dans le district d’Abidjan au sud de la Côte d’Ivoire. Les données utilisées couvrent la période allant de 1961 à 2014. Des lois de distribution employées dans la conception des ouvrages hydrauliques ont ainsi été retenues dans cette analyse : la loi de Weibull, la loi de Gumbel et la loi log-normale. Elles ont été ajustées aux pluies journalières maximales annuelles et les paramètres ont été estimés de manière spécifique. Les fréquences empiriques ont été calculées à partir de la relation de Hazen. Les paramètres des différentes lois ont été déterminés par la méthode des moments pondérés. L’ajustement a été apprécié à partir de représentation graphique et du test du χ2. Deux critères (critère d’Akaike et critère bayésien) ont été retenus pour trancher sur le choix des meilleurs modèles. Les différentes lois ont montré en général une bonne adéquation à la série des pluies journalières maximales annuelles de la station de Port-Bouët (Abidjan). Cependant, la loi qui ajuste le mieux les pluies journalières maximales annuelles de la station de Port-Bouët (Abidjan) est la loi de Gumbel. Il est donc recommandé de travailler avec la distribution de Gumbel dans toute étude de dimensionnement d’ouvrages hydrauliques en général et dans le domaine des ouvrages d’évacuation des eaux pluviales en particulier dans le district d’Abidjan.
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The increased pressures on water resources linked to climate and societal changes are recognized as global challenges. The objective of this study is to analyze the impacts of climate change on the water stress of populations in the N'zi (Bandama) watershed in Ivory Coast. The data used (flows, populations, etc.) cover the period 1991-2020. An approach based on the comparison of water resources (standard normalization index, linear regression method, frequency analysis, flow rate index, etc.) and demands through the water needs satisfaction rate index, was applied at interannual and monthly scales. This approach has made it possible to identify the major trends in water stress in Dimbokro populations. It appears that on an interannual scale, the N'zi watershed is in a situation of water stress. The seasonal scale analysis shows that the city of Dimbokro experiences six months (December to May) of water stress. In the future horizons, the water stress of the city of Dimbokro could intensify.
The objective of this study is to analyze the sensitivity of the statistical models regarding the size of samples. The study carried out in Ivory Coast is based on annual maximum daily rainfall data collected from 26 stations. The methodological approach is based on the statistical modeling of maximum daily rainfall. Adjustments were made on several sample sizes and several return periods (2, 5, 10, 20, 50 and 100 years). The main results have shown that the 30 years series (1931-1960; 1961-1990; 1991-2020) are better adjusted by the Gumbel (26.92% -53.85%) and Inverse Gamma (26.92% -46.15%). Concerning the 60-years series (1931-1990; 1961-2020), they are better adjusted by the Inverse Gamma (30.77%), Gamma (15.38% -46.15%) and Gumbel (15.38% -42.31%). The full chronicle 1931-2020 (90 years) presents a notable supremacy of 50% of Gumbel model over the Gamma (34.62%) and Gamma Inverse (15.38%) model. It is noted that the Gumbel is the most dominant model overall and more particularly in wet periods. The data for periods with normal and dry trends were better fitted by Gamma and Inverse Gamma.
Climate change is a reality that affects several climate variables including precipitation. This change and the variability of the climate are considered to be the greatest challenges facing humanity in the decades to come, on all geographic scales and in all economic sectors. In this context of severe climate change, it will be judicious to review the sizing parameters of hydraulic structures. The determination of hydrological standards is necessary within the framework of development projects for the design of hydraulic structures and the storm water management. The objective of this study is to update the parameters of the ORSTOM and CIEH methods. These are annual rainfall normals, extreme rainfall norms, extreme rainfall quantiles as well as the extreme rainfall gradex. The study carried out was based on annual maximum daily rainfall data and annual rainfall data collected over the period 1931-2020 from twenty-six (26) rainfall stations. The methodological approach is based on the one hand on the evaluation of the normals (normals of annual rainfall, norms of extreme rainfall) and on the other hand on the determination of the quantiles of the daily maximum annuals. These quantiles were used to assess the extreme rainfall gradex. The annual rainfall norms evaluated over the period 1931-2020 vary between 1,180 and 1,457.4 mm. As for the normals of the maximum daily rains, they oscillate between 73.61 mm (Agnibilékro) and 136.59 mm (Tabou) with an average of 94.57 mm. The 10-year return period quantiles evaluated over the period 1931-2020 vary between 103 mm (Dimbokro) and 222 mm (Tiassalé) with an average of 143.6 mm. As for the centennial quantiles, they oscillate between 132 mm (Dimbokro) and 326 mm (Tiassalé) with an average of 211.5 mm. An analysis of the extreme rainfall gradex revealed values fluctuating between 0.28 (Dimbokro) and 0.71 (Guiglo) with an average of 0.47 on Ivorian territory. The gradex coefficients determined are all greater than the regional value of 0.38 defined by ORSTOM except for the Dimbokro station (0.28). Indeed, the calculated gradex coefficient biases are all positive (ranging from +2.63 to + 86.84%) except that of Dimbokro (-26.32%). The use of the regional value of 0.38 reflects an under designing of the values of the gradex coefficient for the whole country except the Dimbokro station.
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