Lou Moin Sandrine Tivoli^1,, Koffi Eugène Kouakou¹, Kouadio Assemien François Yao², Amani Michel Kouassi¹

Heavy rainfall is recognized as the main factor in the flood risk occurrence. Analysis of daily meteorological data provides insight into the current situation and helps manage future extreme events with a view to preventing flood risks in a given region. This study aimed to determine the spatio-temporal evolution of 10 rainfall indices over the period 1983-2020 in order to highlight the risk of flooding in the Cavally watershed. The daily data used were processed and then integrated into the RClimdex model to calculate the 10 rainfall indices, which are: PRCPTOT, CWD, RX1day, RX5day, RX10, RX20, RX25, R95p, R99p, and SDII. The Man-Kendall trend test and Sen's slope estimator were used in the analysis of meteorological data. Although not all trends are significant, the results show a general downward trend in total annual precipitation (PRCPTOT), the number of days with heavy and very heavy precipitation (R10 and R20), and the number of very wet days (R95p). On the other hand, maximum 1-day precipitation amount (RX1day), maximum 5-day precipitation amount (RX5day), and the number of extremely wet days (R99p) showed an upward trend. These positive trends are causing increasingly frequent flooding in the central and southern parts of the study area. It is therefore necessary to implement adaptation measures to protect this heavily agricultural area.

Rainfall indices, climate change, flood, Cavally watershed