TITLE:
Analysis of Extreme Rainfall Events in the Oti Watershed, Togo (West Africa)
AUTHORS:
Koungbanane Dambré, Kodja Japhet Domiho, Lemou Faya, Totin Vodounon Henri Sourou, Amoussou Ernest
KEYWORDS:
Climate Change, Rainfall Indices, Rainfall Trends, Simulated Rainfall, Oti Watershed
JOURNAL NAME:
American Journal of Climate Change,
Vol.14 No.2,
May
21,
2025
ABSTRACT: Global climate change, characterised mainly by an upsurge in extreme rainfall events, is affecting the precarious economies of most vulnerable countries. The aim of this study is to analyze extreme rainfall events in the Oti watershed, which is characterised by high climatic variability. Daily observed and simulated rainfall and temperature data from two models (CCLM4.8 = Climate Limited-area Modeling Community 4.8 and REMO = Regional Model) in the Cordex programme were used. The data is subjected to statistical processing methods. Climatic indices were calculated using RclimDex software. The results obtained show a spatio-temporal variability in observed and simulated rainfall that follows an increasing north-south gradient. A break in stationarity was observed in 1998 in the rainfall data series, showing a change in the behavior of maximum daily rainfall from 1961-2022. Both models overestimate observed rainfall, with deviations of 1.95 for the CCLM4.8 and 8.53 for the REMO. This shows that the CCLM4.8 is more realistic in reproducing observed rainfall, is therefore validated for the rainfall projection. The rainfall indices show a non-statistically significant increase in PRCPTOT, R99p, RX1day, RX5 days and CWD on the one hand, and a decrease in the SDII, R10 mm, R20 mm and R95p indices on the other for the observed rainfall. For simulated rainfall, the RCP 8.5 and RCP 4.5 scenarios predict an upward trend in some indices and a downward trend in others from 2025 to 2069. Thus, the RCP 8.5 scenario predicts an increase in Rx1day, SDII and R99P from 2025 to 2069. The RCP 4.5 scenario also predicts an upward trend in Rx1day, Rx5days and R99P over the same period. This study provides a clearer picture of how extreme rainfall could change, and is a tool to help plan and manage flood risk in the Oti watershed in Togo.