The aim of this work is to identify and enhance the value of lowlands in the face of the challenges posed by climatic hazards, with a view to the sustainable use of land that represents a major challenge for agriculture in Ivory Coast. The data used in this study are sentinel-2 images for the year 2023. The various methodological approaches used consisted of the combined extraction of vegetation, moisture and topographical indices. Analysis of the results shows that our study area has lowlands covering an area of around 31,100 ha. In the department of Man, 121584 ha of wetlands have been inventoried, covering 12% of the territory. They offer opportunities for a variety of crops, particularly rice and market gardening, and play a crucial role in food security and people’s livelihoods. However, their use faces challenges linked to climatic hazards, water management constraints and land pressure from urban expansion. Lowlands benefit from higher humidity and soils that are often rich in nutrients, which encourages crop growth. Farming in these areas contributes to local food security and can generate additional income for households. At times, these areas are prone to flooding and drought, which can lead to crop losses. It is important to manage these different plots in a sustainable way, taking into account the needs of the local population and the preservation of the environment. This work highlights the effectiveness of the remote sensing-GIS approach for monitoring wetland ecosystems and strategies for adapting to climate change.
This study aims to understand the influence of vegetation cover on the hydrological response of the Hana forest watershed. Using the GR2M hydrological model, hydroclimatic data over the 2000-2018 period were simulated to obtain real evapotranspiration (ETR), infiltration (I), and runoff (R). These different water balance terms were then correlated with a time series of NDVI extracted from MODIS-Terra (MOD13Q1) images over the period 2000-2018. The calibration of the hydrological model over the periods 1984-1989 and 2000-2018, respectively gave good Nash values of 74.1% and 64.6%. The validation, on the whole, gives satisfactory Nash values, except for the 1990-1999 one which is 56.4%. Cusum and t-student tests confirmed a significant break at α=5% in 2009 in the NDVI time series. Statistical analysis around this break date reveals a good correlation between NDVI and rainfall on the one hand and between NDVI and real evapotranspiration on the other hand, with respective correlation coefficients of 0.68, 0.66 for the sub-period 2000-2009. The relationship between NDVI and runoff is relatively weak there with a value of 0.38. Very high correlation coefficient values were obtained over the period 2010-2018 between NDVI and rainfall (0.78), between NDVI and real evapotranspiration (0.72) and between NDVI and runoff (0.68). However, low correlation coefficients of the order of 0.53 and - 0.07 were recorded between the NDVI and infiltration respectively before and after 2009.
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