Integrating both modeling approach and stakeholders’ perspectives to derive past and future trends of land use land cover (LULC) is a key to creating more realistic results on LULC change trajectories and can lead to the implementation of appropriate management measures. This article assessed the past changes of LULC in the Mono River catchment using Landsat images from the years 1986, 2000, 2010, and 2020 by performing Machine Learning Classification Method Random Forest (RF) technique, and using Markov chain method and stakeholder’s perspective to simulate future LULC changes for the years 2030 and 2050. LULC was classified as savanna, cropland, forest, water bodies, and settlement. The results showed that croplands and forests areas declined from 2020 to 2050 with decreases of −7.8% and −1.9%, respectively, a modest increase in settlement (1.3%), and savanna was the dominant LULC in the study region with an increase of 8.5%. From stakeholders’ perspective, rapid population growth, deforestation, rainfall variability/flood, urbanization, and agricultural expansion were the most important drivers associated with the observed LULC changes in the area. Other factors, such as lack of political commitment, distance to river, and elevation were also mentioned. Additionally, most the land-use scenarios identified by stakeholders would intensify land degradation and reduce ecosystem services in the area. By considering all of these potential LULC changes, decision-makers need to develop and implement appropriate solutions (e.g., land use planning strategies, reforestation campaigns, forest protection measures) in order to limit the negative effects of future LULC changes.

Flood damage in West Africa has increased appreciably during the last two decades. Poor communities are more at risk due to the vulnerability of their livelihoods, especially in rural areas where access to services and infrastructures is limited. The aim of this paper is to identify the main factors that contribute to flood risk of rural communities in the Oti River Basin, Togo. A community-based disaster risk index model is applied. The analyses use primary data collected through questionnaires during fieldwork, the analytic hierarchy process (AHP) method, population and housing census data and flood hazard mapping of the study area. The results showed a moderate level of flood risk despite a high level of hazard and vulnerability for all investigated communities. In addition, the results suggest that decreasing vulnerability through creation of new income-generating opportunities and increasing capacity of communities to manage their own flood risk should be paramount in order to reduce flood risk in the study area. The results of this work contribute to the understanding of flood risk and can be used to identify, assess, and compare flood-prone areas, as well as simulating the impacts of flood management measures in the Oti River Basin.

In the Volta River Basin, flooding has been one of the most damaging natural hazards during the last few decades. Therefore, flood frequency estimates are important for disaster risk management. This study aims at improving knowledge of flood frequencies in the Volta River Basin using regional frequency analysis based on L-moments. Hence, three homogeneous groups have been identified based on cluster analysis and a homogeneity test. By using L-moment diagrams and goodness of fit tests, the generalized extreme value and the generalized Pareto distributions are found suitable to yield accurate flood quantiles in the Volta River Basin. Finally, regression models of the mean annual flood with the size of the drainage area, mean basin slope and mean annual rainfall are proposed to enable flood frequency estimation of ungauged sites within the study area.

Flooding is prominent in West Africa, and is expected to be exacerbated, due to global climate and land-use changes. This study assessed the impacts of future climate and land-use changes on flood hazards in the Mono river catchment area of Benin and Togo. Climate scenarios from the representative concentration pathways, RCP 4.5 and RCP 8.5, and land-use projection at the horizon of 2070 were used for runoff simulation at the Athiémé outlet, and flood mapping in the lower Mono river basin. The planned Adjarala dam was also simulated, to evaluate its potential impact. The Soil and Water Assessment Tool (SWAT) was used to investigate the impact of the projected changes on runoff, while the flood-water extent was simulated using the two-dimensional TELEMAC-2D model. TELEMAC-2D was validated with satellite observation and in a participatory way with local stakeholders. SWAT showed good performance during the calibration (KGE = 0.83) and validation (KGE = 0.68) steps. Results show an increase in the magnitude of flood extremes under future climate- and land-use-change scenarios. Events of 10-year return periods during 1987–2010 are expected to become 2-year return-period events under the climate- and land-use-change scenarios considered. The planned Adjarala dam showed potentials for extreme-peak and flood-extent reduction. However, flow-duration curves revealed that the discharge of the river during low-flow periods may also be reduced if the Adjarala dam is built. Adaptation measures as well as sustainable land-use and dam-management options should be identified, to alleviate the impacts of the projected changes.

The expansion of African cities leads to the occupation of peripheral urban areas without respecting planning rules. The Greater Lomé (Togo) is no exception to this phenomenon of high-speed horizontal spreading, which causes recurrent flooding. The objective of this research is to understand the spatio-temporal changes in the dynamics of built-up areas in Greater Lomé. The methodology used is based on the analysis of Landsat images from the years 2007, 2012, 2016, and 2020 coupled with direct field observations and a literature review. The results showed an increase in residential areas to the detriment of the other land use/cover types. Estimated at 15,481 ha in 2007, the built-up area reached 35,521 ha in 2020, an increase of 33% to the detriment of vegetation and cultivation areas. This increase was marked by constructions in the floodplain of the Zio River. The field surveys revealed an increase in the density of most of the agglomerations. From 1863 ha in 2007, they increased to 14,485 ha in 2020, an increase of 12,622 ha or approximately 33%. These results indicate that attention needs to be paid to both the planning and control of the development of spaces in the outlying areas of Greater Lomé.

Understanding how extreme rainfall is changing locally is a useful step in the implementation of efficient adaptation strategies to negative impacts of climate change. This study aims to analyze extreme rainfall over the middle Oti River Basin. Ten moderate extreme precipitation indices as well as heavy rainfall of higher return periods (25, 50, 75, and 100 years) were calculated using observed daily data from 1921 to 2018. In addition, Mann–Kendall and Sen's slope tests were used for trend analysis. The results showed decreasing trends in most of the heavy rainfall indices while the dry spell index exhibited a rising trend in a large portion of the study area. The occurrence of heavy rainfall of higher return periods has slightly decreased in a large part of the study area. Also, analysis of the annual maximum rainfall revealed that the generalized extreme value is the most appropriate three-parameter frequency distribution for predicting extreme rainfall in the Oti River Basin. The novelty of this study lies in the combination of both descriptive indices and extreme value theory in the analysis of extreme rainfall in a data-scarce river basin. The results are useful for water resources management in this area.