http://197.159.135.214/jspui/handle/123456789/916 2026-04-23T16:34:12Z http://197.159.135.214/jspui/handle/123456789/945 Numerical Assessment of Hydrodynamic Trends and Groundwater Recharge through Long Chronicle Data in the Bagré Dam, Burkina Faso: Implications for Climate Change and Dam Management Operations Orowale, Triumph Prosper In the context of climate change and the subsequent pressure of human activities, there is abounding need to establish a clear relationship between reservoir storage, rainfall, and groundwater recharge in Bagre dam, Burkina Faso. Hydrodynamic variables collected in and around the operations of Bagré dam (e.g., evaporation, inflow, irrigation, spillage, water level, rainfall) were analysed, using the singular spectrum analysis to delineate the trends and variability over the 1993-2022 period. Additional sensitivity assessments were conducted on groundwater data between 2002 and 2022, using linear and polynomial models to predict the impact of the reservoir water level on the groundwater; Pettitt and Mann Kendall test to evaluate the significance level of the trends and a water table fluctuation and infiltration models were developed to delve into the influence of the reservoir water level and rainfall on groundwater recharge in and around the Bagré Dam. The result shows that there is an increasing trend of spillage due to increasing inflow. Evaporation trend is decreasing, and irrigation trend is increasing. Rainfall trend is decreasing from 2012, and the reservoir water level is relatively stable. The statistical indices showed strong, moderate, and very low relationship with the water level. The percentage of groundwater recharge percentage is between 25-28%, which is stable due to the constant availability of surface water. The Mann Kendall and Pettitt tests show an increasing trend and breaking points on most of the piezometer profiles. Inflows rise has affected the dam stability while spill over led to flooding downstream of the Bagre Dam. The reservoir water level is improving the groundwater recharge, which will enable agricultural practice irrespective of the seasons around the dam. These results suggest that future ground water trends and variability in and around the Bagré Dam can be predicted using the variables from dam management operations. A Thesis submitted to the West African Science Service Center on Climate Change and Adapted Land Use and Université Joseph KI-ZERBO, Burkina Faso in partial fulfillment of the requirements for the Master of Science Degree in Informatics for Climate Change 2023-07-14T00:00:00Z http://197.159.135.214/jspui/handle/123456789/944 Analysis of the recent evolution of dry spells in Burkina Faso Coulidaiti, Seraphin Palamanga Ousseini Changes in the distribution of precipitation frequency and intensity can affect dry and wet spells, which will have an impact on climate-sensitive sectors, most notably agriculture. This study set out to analyze the variations of onset and cessation dates of the rainy season, to understand dry spells nature and their drivers in Burkina Faso. We used daily rainfall data of 10 synoptic stations from the National Meteorological Agency, the Madden-Julian Oscillation (MJO) and El Nino-Southern-Oscillation (ENSO) indices for the period 1991-2020 are then used to identify the onset and the cessation of the rainy season and their anomalies using the definitions of Sivakumar and (Kasei and Afuakwa) for season onset dates, and the definitions of Maikano and (Kasei and Afuakwa) for the season cessation dates, dry spells frequencies, longest dry spells, average dry spells duration and the modulation of the MJO and the ENSO in the occurrence of dry spells. All these parameters were computed between the onset and the cessation of the season and these dates were determined from May to October. Statistical analysis was made using Kendall's Nonparametric Test for Monotonic Trend, standard deviation, and simple linear model to assess trends in these variables. We used R programming language to extract and analyze the dry spells and the two modes, the onset and cessation dates are computed using second-order Markov chain with Instat software. We found that both changed with rainfall onsets having a more important change. The longest dry spells are identified at the cessation of the season compared with the onset of the season and there is a moderate frequency in the occurrence of DS. Across the studied period, most dry spells fluctuate between 5 and 15 days. Some phases of the MJO such as phases 5 and 7 increase the likelihood of DSs and phases 1 and 2 decrease it. At the interannual scale, the ENSO influences DS characteristics with El Nino that increase the likelihood of the DSs occurrence. To help different stakeholders with their decision-making, it would be helpful to identify the distributions and patterns of critical dry spells and explore the possibility of predicting the patterns of dry spells in the future. A Thesis submitted to the West African Science Service Center on Climate Change and Adapted Land Use and Université Joseph KI-ZERBO, Burkina Faso in partial fulfillment of the requirements for the Master of Science Degree in Informatics for Climate Change 2023-01-01T00:00:00Z http://197.159.135.214/jspui/handle/123456789/943 Assessing the Impact of Climate Extreme Events and Conflicts on Internal Migration in Burkina Faso: the Case of Internal Displacement Adzavon, Koffi Doh David Climate extreme events (floods, storms) and conflicts are still major problems for the sedentary life of the Sahelian populations. In recent years, floods, storms and conflicts (violent, non-violent or demonstrations) have been alarming in Burkina Faso. This study aims to assess the impact of extreme weather events and conflicts on internal displacement in Burkina Faso. The study used monthly data on floods, storms, violent and non-violent conflicts and demonstrations from 2018 to 2022. We used the dynamic modelling approach (ARDL) to identify and model short and long run relationships. Internal displacement forecasts for 2025 were made using the ARIMA modelling method. The results showed that, unlike storms, floods have affected all regions of Burkina Faso. Demonstrations are little known, whereas violent and non-violent conflicts are better known in the Sahel and Eastern regions and are spreading rapidly to other regions. The ARDL results showed that in the short run, the number of violent events, demonstrations and storms have a positive effect when they occur, while floods have a negative effect on the displacement of people. In the long run, violent events, storms and floods have a positive effect on the displacement of people in Burkina Faso. Forecasts show that the number of displaced people will rise to 2.6 million by early 2025. Conflict management, therefore, needs to be taken seriously so that the number of displaced persons can be considerably reduced. In addition, climate measures and actions must be taken to reduce the effects of storms and floods on people’s displacement. A Thesis submitted to the West African Science Service Center on Climate Change and Adapted Land Use and Université Joseph KI-ZERBO, Burkina Faso in partial fulfillment of the requirements for the Master of Science Degree in Informatics for Climate Change 2023-01-01T00:00:00Z http://197.159.135.214/jspui/handle/123456789/942 Agricultural soil characterization and crop recommendation using deep learning algorithms: Model Selection and AI Application Development Ali Abdou, Moussa Agriculture is vital, and soil is a fundamental component with unique characteristics for different crops. This thesis research aimed to develop a deep learning-based system for soil type classification. It explores the performances of eight CNNs architectures namely, DenseNet201, MobileNetV3Large, VGG16, VGG19, InceptionV3, ResNet50, Xception, and a novel architecture referred to as simple_architecture, for accurately classifying agricultural soil types found in Maradi, Niger. The research methodology encompasses data collection, cleaning, preprocessing, model building, hyperparameter optimization, model compilation, and the development of an AI-based application. The findings highlight that ResNet50 and DenseNet201 were better than other models for all performance metrics. Thus, the developed application is meant to empower farmers to optimize their practices in the face of land degradation and climate change challenges. A Thesis submitted to the West African Science Service Center on Climate Change and Adapted Land Use and Université Joseph KI-ZERBO, Burkina Faso in partial fulfillment of the requirements for the Master of Science Degree in Informatics for Climate Change 2023-01-01T00:00:00Z