In the modern era, vegetation dynamics is an important aspect of climate change studies. The present study examined spatiotemporal changes of (NDVI) normalized difference vegetation index in the Korama basin (Southern Zinder of Niger) from 2000 to 2018, and their correlation with climatic factors was predicted. To analyze the change of vegetation cover, geographical information system, MODIS_NDVI, remote sensing, and climate variables (e.g., temperature and precipitation) datasets were used. Further, the correlation was performed for different years of vegetation types during the growing season (June–October). Our results show an increasing trend in average maximum annual NDVI across the Korama River Basin in the years 2000 and 2018. Conversely, significantly increasing trends in most of the areas were reported. Moreover, in downstream the vegetation cover is increased in Matameye and Magaria, but with a smaller increase in the upstream rate in Mirriah. Furthermore, a decrease in the surface water was observed in the Tessaoua, Matameye, and Magaria sections of the study region in 2000 and 2018, while a rise in water surface area was observed in Matameye and Magaria in the years 2006 and 2012. During rainy and dry seasons, NDVI correlated differently with temperature and precipitation with strong seasonal variations, while the mean vegetation period of NDVI does not show any significant change. In addition, moderate increase was observed in years 2000 and 2012 (r: 0.22; P: 0.50; R2: 0.05; r: 0.31; P: 0.34, R2: 0.10, respectively), and weak decrease in 2006 and 2018 (r: 0.61; P: 0.04; R2: 0.37; r: 0.58; P: 0.06, R2:0.33, respectively). The analysis indicates that climatic parameters such as precipitation and temperature are the main limiting factors affecting the vegetation growth. Indeed, the trends calculated by the correlation analysis showed that as climate factors increased (July, August, and September), the NDVI value increased at a rate of 0.16, reflecting the best growth in vegetation and rise in water bodies, although significantly decreased during years. This study would be highly useful in choice-making for sustainable water resource management in the Korama watershed in Southern Zinder, Niger.

Identifying ecologically fragile areas by assessing ecosystem vulnerability is an essential task in environmental conservation and management. Benin is considered a vulnerable area, and its coastal zone, which is subject to erosion and flooding effects, is particularly vulnerable. This study assessed terrestrial ecosystems in Benin by establishing a hybrid ecological vulnerability index (EVI) for 2016 that combined a composite model based on principal component analysis (PCA) with an additive model based on exposure, sensitivity and adaptation. Using inverse distance weighted (IDW) interpolation, point data were spatially distributed by their geographic significance. The results revealed that the composite system identified more stable and vulnerable areas than the additive system; the two systems identified 48,600 km2 and 36,450 km2 of stable areas, respectively, for a difference of 12,150 km2, and 3,729 km2 and 3,007 km2 of vulnerable areas, for a difference of 722 km2. Using Moran’s I and automatic linear modeling, we improved the accuracy of the established systems. In the composite system, increases of 11,669 km2 in the potentially vulnerable area and 1,083 km2 in the highly vulnerable area were noted in addition to a decrease of 4331 km2 in the potential area; while in the additive system, an increase of 3,970 km2 in the highly vulnerable area was observed. Finally, southern Benin was identified as vulnerable in the composite system, and both northern and southern Benin were identified as vulnerable in the additive system. However, regardless of the system, Littoral Province in southern Benin, was consistently identified as vulnerable, while Donga Province was stable.

Flash floods are among the most common natural hazards in Egyptian and Arabian deserts. In this work, we utilized two Sentinel-1 and Sentinel-2 satellite images, before and after the flash flood, SRTM, and geolocated terrestrial photos captured by volunteers. This paper aims to three substantial objectives: (1) monitoring the flash flood impacts on Wadi El-Natrun region based on free satellite data and mapping the destroyed vegetation cover; (2) the integration of the free remote sensing data, geolocated terrestrial photos, and GIS techniques, along with hydrologic and hydraulic modeling, to evaluate the impact of flash flood hazards on the study area; and (3) assistance of the decision-makers in planning the required protective works to avoid the probable flooding. Two scenarios have been applied to estimate the flash flood effect. The first scenario has relied on Sentinel-1/2 data fusion before and after the flash flood, while the second scenario has been implemented based on the integration of the Sentinel-2 images and hydrologic and hydraulic flood modeling with the help of ArcGIS software to simulate the flash flood route. The results demonstrated that although the first scenario is an efficient solution for continuous monitoring of the change in the water bodies, it is limited in the detection of the submerged vegetation area. On the other hand, the second scenario provided the flash flood route and hydrological parameters, which determine the hazard degree of the basins, thus helping the decision-maker to manage the flood risk. Moreover, the second scenario surpasses the first one by estimating the destroyed infrastructure. Consequently, the second scenario is appropriate to assess the flash flood impacts and mitigate its influence in the future.

A systematic method, incorporating the revised universal soil loss equation model (RUSLE), remote sensing, and the geographic information system (GIS), was used to estimate soil erosion potential and potential area in the Maradi region of south-central Niger. The spatial trend of seasonal soil erosion was obtained by integrating remote sensing environmental variables into a grid-based GIS method. RUSLE is the most commonly used method for estimating soil erosion, and its input variables, such as rainfall erosivity, soil erodibility, slope length and steepness, cover management, and conservation practices, vary greatly over space. These factors were calculated to determine their influence on average soil erosion in the region. An estimated potential mean annual soil loss of 472.4 t/ac/year, based on RUSLE, was determined for the study area. The potential erosion rates varied from 14.8 to 944.9 t/ac/year. The most eroded areas were identified in central and west-southern areas, with erosion rates ranging from 237.1 to 944.9 t/ac/year. The spatial erosion maps can serve as a useful reference for deriving land planning and management strategies and provide the opportunity to develop a decision plan for soil erosion prevention and control in south-central Niger.