Serigne Mbacké Coly

Accurately capturing rainfall patterns is crucial for hydrometeorological applications, particularly in regions like Burkina Faso, West Africa, where rainfall variability significantly impacts water resources and agricultural productivity. However, challenges remain in identifying the most reliable rainfall products for such purposes. This research evaluates the effectiveness of satellite precipitation products (SPPs) and soil moisture-derived rainfall products (SM2RPPs) in representing rainfall patterns in Burkina Faso. Results show that SPPs generally perform better than SM2RPPs across daily to annual timescales. An analysis of total bias components highlights that hit biases dominate but are more pronounced in SM2RPPs. Systematic errors contribute significantly to these hit biases, indicating the potential for improvement through bias correction. Wavelet analysis reveals that both SPPs and SM2RPPs capture seasonal and annual rainfall variability effectively. However, all products exhibit limitations in accurately representing extreme rainfall indices, although SPPs demonstrate superior performance compared to SM2RPPs. While SM2RPPs currently underperform relative to SPPs in Burkina Faso, they show promise for hydrometeorological applications and could achieve comparable or improved results with enhanced bias correction techniques.

Since the droughts of the 1970s–1980s, populations in the Sahel region have opted for a mass exodus to more humid urban or rural centers. Migrations or exoduses have accelerated in recent decades due to environmental degradation and unfavorable climatic conditions. Insufficient harvests are the main reason for migration for the majority of migrants in the Sahelian areas. Migration is a major adaptation strategy to cope with extreme climatic conditions, thus requiring quantification in the destination area. The aim of this paper is to propose a metapopulation model to approximate reality by identifying the transition from one socioeconomic vulnerability group to another, from a less favorable area to favorable area in terms of natural resources, depending on the strategies, policies, and climate variability. The model was used to analyze the dynamics of socioeconomic vulnerability to study the impact of migration on the dynamics of socioeconomic vulnerability. The developed mathematical model was analyzed. Up to 2050, simulations applied to the Tougou village in northern Burkina Faso show that migration has a positive impact on the socioeconomic vulnerability of the destination area, thereby reducing the vulnerability of the population by 10% when resources are increased by up to 30%.

One of the first environmental crises to attract interest in development initiatives and aid was the great drought of the 1970s in the Sahel. This study investigates the extent of damage caused by natural disasters from one of the most widely used databases—EM-DAT—with a sample size of 16 Sahelian countries over the period 1960–2020. These countries have been divided into three regions: Western Africa Sahel (WAS), Central Africa Sahel (CAS), and Eastern Africa Sahel (EAS). The analyses encompass four categories of natural hazards, namely, biological, climatological, hydrological, and meteorological. We used descriptive and test statistics to summarize the natural disaster records. Through this approach, we explore tendencies to identify the most frequently reported natural hazards; we examine their spatial distribution and evaluate their impacts in terms of socioeconomic damage and causalities. During the study period, a total of 1000 events were recorded in the database. The Western Africa Sahel (WAS) region had the highest number of disasters, with 476 events, followed by the Eastern Africa Sahel (EAS) region with 369 events. The most common hazards in the Sahel were hydrological (41.8%), mainly floods, and biological (39.5%) hazards. Approximately 300 million people in the Sahel were affected by natural hazards, with 59.17% in EAS, 36.48% in WAS, and 4.35% in CAS. Although droughts occurred less frequently (14%), they had a significant impact on the population, affecting 84% of those affected by natural hazards. In general, EAS experiences a higher impact from natural hazards, potentially influenced by the pastoral lifestyle of its population. However, WAS is also very vulnerable to natural hazards especially epidemics and nowadays floods. The uncontrolled urbanization in the area may contribute to this vulnerability.