Search Results (3)

The modification of land use is a crucial factor in the dysfunction of ecosystems. It greatly influences the hydrological cycle of basins. This study focused on the Oueme basin, which represents almost half of the total area of Benin, and aimed to describe the current and future evolution of its land cover using the maps of the Land Use Land Cover Dynamics project (1975, 2000, and 2013). A temporal analysis of the surface states was performed with QGIS, and the potential land cover in 2025, 2050, and 2085 was estimated using the Markov chain algorithm in the IDRISI software. The results showed that the Oueme basin was predominantly savanna (77.70% in 1975, 66.29% in 2000, and 57.10% in 2013). Forest areas, which represented the second class in 1975 with a total proportion of 13.34%, gradually decreased to 8.66% and 6.89%, respectively, in 2000 and 2013. Conversely, cultivated areas had more than tripled in 2000 and quadrupled in 2013. Residential areas increased rapidly in the southern part of the basin, with an acceleration in the recent period (6% between 2000 and 2013, against 2% between 1975 and 2000). This probably led to the lower stability rate in this zone (56%) compared to Oueme upper (74%). The recent period was more affected by changes in the surface conditions, and these changes are likely to be amplified in the future (probable total disappearance of forested areas by 2085). We recommend clarifying the impacts that each land use category generates/will generate on the hydrological cycle of this basin. Full article

The vegetation cover of the Ouémé Delta constitutes a biodiversity hotspot for the wetlands in southern Benin. However, the overexploitation of natural resources in addition to the intensification of agricultural practices led to the degradation of the natural ecosystems in this region. The present work aims to reconstruct, using remote sensing, the spatial dynamics of land use in the Ouémé Delta in order to assess the recent changes and predict the trends in its vegetation cover. The methodology was based on remote sensing and GIS techniques. Altogether, this process helped us carry out the classification of Landsat images for a period of 30 years (stating year 1990, 2005, and 2020) via the Envi software. The spatial statistics resulting from this processing were combined using ArcGIS software to establish the transition matrices in order to monitor the conversion rates of the land cover classes obtained. Then, the prediction of the plant landscape by the year 2035 was performed using the “Land Change Modeler” extension available under IDRISI. The results showed seven (07) classes of occupation and land use. There were agglomerations, mosaics of fields and fallow land, water bodies, dense forests, gallery forests, swamp forests, and shrubby wooded savannahs. The observation of the vegetation cover over the period of 15 years from 1990 to 2005 showed a decrease from 71.55% to 63.42% in the surface area of the Ouémé Delta. A similar trend was noticed from 2005 to 2020 when it reached 55.19%, entailing a loss of 16.37% of the surface area of natural habitats in 30 years. The two drivers of such changes are the fertility of alluvial soils for agriculture along and urbanization. The predictive modeling developed for 2035 reveals a slight increase in the area of dense forests and shrubby wooded savannas, contrary to the lack of significant decrease in the area of gallery forests and swamp forests. This is key information that is expected to be useful to both policy and decision makers involved in the sustainable management and conservation of natural resources in the study area. Full article

This work focuses on trend analysis of rainfall, evaporation, temperature, relative humidity, wind speed, and sunshine duration over the Ouémé Delta in Bénin. Eight temperature based indices and fifteen rainfall based indices are computed from 1960 to 2016. Moreover, maximum 1, 2, 3, 5, and 10 days precipitation indices were computed at the monthly scale. Trends are detected at 0.05 confidence level, using a combination of Mann-Kendall and prewhitened Mann-Kendall test. Partial correlation and stepwise regression are used to detect the set of meteorological variables that influence pan evaporation in Ouémé Delta. Results showed intensification of heavy rainfall over Ouémé Delta. Moreover, a significant increasing trend is detected in temperature. As consequence, diurnal temperature significantly decreases as proof of the global warming. Average pan evaporation showed a significant slither increasing trend over the area. Change in pan evaporation can be explained by wind speed and sunshine duration that hold almost 50% of pan evaporation variance. As future temperature is going to be increasing, pan evaporation may increase considerably. So, adaptation measures have to be reinforced in the Ouémé Delta area where farmer are used to rainfed agriculture for food security. Moreover, Ouémé Delta plan have to be developed for it resources sustainability. Full article