The increasing rainfall variability in West Africa is a great challenge for crop productivity in small-scale farming systems, thus jeopardizing food security. Rainfed rice is particularly sensitive to inconsistent rainfall, especially during the reproductive stage. It is, therefore, necessary to develop management practices suited to the change of rainfall pattern over the growth seasons. In this study, the modeling technology with the rice model ORYZA (v3) was used to identify appropriate rainfed rice growing seasons for a better adaptation of farmers to climate variability. The potential yields, the favorable sowing periods, the optimum sowing dates, and the attainable yields of two contrasted cultivars were determined. After successfully calibrating and validating the model, it predicted potential yields of 5.5 to 6.5 tons/ha for the early maturing variety WAB56-104 (90-100 days), while potential yields of 4 to and 5.5 tons/ha was predicted for the late maturing variety CG14 (115-125 days). In rainfed conditions, two favorable sowing periods were identified from the model scenario analysis. The first period spans from late February to late April and the second from late July to early September. Farmers can double their actual yield of 1.5 tons/ha if they follow the recommended sowing dates and good agricultural practices. Indeed, the yield of 3.5 tons/ha was found with the variety WAB 56-104 sown on around 16 April in San-Pedro and around 2 April in Dimbokro. The yield of 3 tons/ha for the variety CG14 could be achieved if the sowing is done on around 18 March in San-Pedro and around 21 March in Dimbokro.

Schistosomiasis is a parasitic disease widespread in Côte d'Ivoire. Due to lack of attention, little is currently known about the pattern of the spread of schistosomiasis and the potential links with climate variability. The aim of this study to examine the relationship between the variability of climate parameters and the spatiotemporal distribution urinary schistosomiasis. The data used in rainfall, temperature and the number bilharzia cases recorded over the period 1996-2013. Overall, the results show a significant decrease of schistosomiasis in region Marahoué. The spatial distribution shows that large cities and areas near rivers and lakes are the most endemic. The analyzes indicate a decrease in schistosomiasis during the rainy season from april to july and increased during the dry season from december to march. In addition, a significant linear correlation was found between the annual mean maximum temperature (0.8 to Bouaflé, 0.66 and 0.34 to Sinfra Zuénoula).

This study aims to assess the evolution of water balance parameters watershed Comoe in a context of climate change. Using the GR2M hydrological model, climate data from the climate model RegCM3 under the A2 emission scenario were simulated to get infiltration, runoff and evaporation and plant transpiration for the periods 1991-2000, 2031-2040 and 2091-2100. Similarly, monthly hydrological and climatic data were used to calibrate the parameters of GR2M hydrological model over the period 1961-1990. The calibration of the hydrological model gave Nash values between 57% to 72%. At validation, Nash criterion varies from 51% to 75%. The results of projection, revealed a decrease in runoff of 18.8% to 34% in 2031-2040 and 40% to 73% in 2091-2100 horizon in different localities. Refills of sheets that are through infiltration could decrease by 7% to 13% in 2031-2040 horizon and 49.3% to 70% in 2091-2100. The decrease in these two consecutive hydrological parameters is, firstly, to falling precipitation of 7.17% and, secondly, an increase in the evaporation and plant transpiration via the temperature increase of 3.6