Over the last few decades, small-scale irrigation has been implemented in Burkina Faso as a strategy to mitigate the impacts of adverse climate conditions. However, the development of irrigated perimeters around small and medium water reservoirs has put the water resources under significant pressure, given the uncontrolled exploitation and lack of efficacious management plan. Insights into changes in irrigated areas around these reservoirs are therefore crucial for their sustainable management while meeting the different agricultural water needs. They will help to center policy priorities in terms of major impacts on the reservoirs; and thereby elaborate relevant mitigation and/or adaptation strategies. The main objectives of this study were to (1) quantify the changes in irrigated land areas surrounding the Mogtedo water reservoir between 1987 and 2015; and (2) determine whether the irrigable potential of this reservoir could sustainably meet the agricultural water needs under a more variable and changing climate. A low-cost remote sensing method based on Landsat imagery (Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager) and using Support Vector Machine (SVM) classification was developed to detect the changes in proportion of land use/land cover (LULC) in the Mogtedo region. A forward and backward change detection analysis requiring agronomic expertise was also applied to correct the pixels temporal trajectories. In addition, an intensity analysis was performed to assess land changes at time intervals, category, and transition levels. Five main LULC classes were identified: bare and hydromorphic soils, irrigated and rainfed agricultural areas, and water bodies. Overall, the classification of LULC was satisfactory with the overall accuracy and kappa coefficients ranging from 94.22 to 95.60% and 0.92 to 0.94, respectively. Results showed that LULC transformations were faster between 2000 and 2015, compared to the 1987–2000 period. The majority of categories (LULC classes) were active in terms of intensity of change (gain or loss) during the 1987–2000 and 2000–2015 periods, except hydromorphic soils. During these periods, the transition from rainfed agricultural areas to irrigated agricultural areas were targeted and stationary. Our findings revealed a 54% increase in irrigated areas between 1987 and 2015. The reservoir water volume decreased markedly from 9,077,000 m³ to 7,100,000 m³ during the same period. Such a decrease threatens the satisfaction of agricultural water requirements, since the reservoir is the unique source of irrigation water in the region. It could potentially lead to conflicts between users if adequate strategies for the sustainable management of the Mogtedo reservoir are not implemented. The methodology used in this study also addressed the challenge of building up historical spatial information database in data-scarce environments, and could be replicated readily in regions or countries like Burkina Faso.

Traditional methods based on field campaigns are generally used to assess the performance of irrigation schemes in Burkina Faso, resulting in labor-intensive, time-consuming, and costly processes. Despite their extensive application for such performance assessment, remote sensing (RS)-based approaches remain very much underutilized in Burkina Faso. Using multi-temporal Landsat images within the Python module for the Surface Energy Balance Algorithm for Land model, we investigated the spatiotemporal performance patterns of the Kou Valley irrigation scheme (KVIS) during two consecutive cropping seasons. Four performance indicators (depleted fraction, relative evapotranspiration, uniformity of water consumption, and crop water productivity) for rice, maize, and sweet potato were calculated and compared against standard values. Overall, the performance of the KVIS varied depending on year, crop, and the crop’s geographical position in the irrigation scheme. A gradient of spatially varied relative evapotranspiration was observed across the scheme, with the uniformity of water consumption being fair to good. Although rice was the most cultivated, a shift to more sweet potato farming could be adopted to benefit more from irrigation, given the relatively good performance achieved by this crop. Our findings ascertain the potential of such RS-based cost-effective methodologies to serve as basis for improved irrigation water management in decision support tools.

Objectives: This study investigates the performance of two machine-learning algorithms in classifying land areas across the Upper-Comoé basin in Burkina Faso. Methods: Within the Google Earth Engine data processing environment, Support Vector Machine (SVM) and the Random Forest (RF) algorithms were applied to a Landsat-8 OLI image of March 2019, to discriminate agricultural land areas, with an emphasis on irrigated areas. Findings: The results indicated good to excellent classification performance, with overall accuracies and Kappa coefficients between 71% and 99%, and 0.66 and 0.99, respectively. The RF method outperformed the SVM in terms of mapping "accuracy", but in terms of spatial distribution of classes, the SVM method provided a mapping close to reality, due to the density of the classes generated. Novelty: Our findings suggest that remote sensing can constitute a tool fully adapted to the needs of services in charge of agricultural water management in Burkina Faso. Keywords: Irrigation, Random Forest, Support Vector Machine, Google Earth Engine, Burkina Faso

Due to the semi-arid nature of the Sahelian countries in Africa, irrigation infrastructures are essential in supporting the improvement of agricultural production. Their proper operation is, therefore, a key indicator for the sustainable development of agriculture in this region. However, there is a lack of critical assessment on the operating state of these hydro-agricultural facilities in Burkina Faso. In this study, we applied a multiple correspondence analysis (MCA) to 4070 hydro-agricultural facilities from 1950 to 2020 and classified them according to the Permanent Interstate Committee for Drought Control in the Sahel’s (CILSS) typology classification system (Type 1 to Type 5). The MCA made it possible to see the relationships between a development typology and variables such as “functionality”, “condition of the development”, or “year of construction”. The results indicate that the irrigated lands with surface areas of less than 100 ha, which were funded by the government or organizations (associations, NGOs) and managed by local communities, are the least functional ones and in bad condition. Their dysfunction indeed conceals deep-seated causes that have not yet been resolved as the infrastructures keep on deteriorating. Therefore, establishing a sustainable and efficient management system for these agricultural infrastructures is imperative. The findings of this study can be used as a practical decision-making tool for implementing agricultural policies in the Sahel region.

Spatio-temporal analysis of rainfall trends in a watershed is an effective tool for sustainable water resources management, as it allows for an understanding of the impacts of these changes at the watershed scale. The objective of the present study is to analyze the impacts of climate change on the availability of surface water resources in the Nakanbe–Wayen watershed over the period from 1981 to 2020. The analysis was conducted on in situ rainfall data collected from 14 meteorological stations distributed throughout the watershed and completed with CHIRPS data. Ten precipitation indices, recommended by the ETCCDI (Expert Team on Climate Change Detection and Indices), were calculated using the RClimDex package. The results show changes in the distribution of annual precipitation and an increasing trend in annual precipitation. At the same time, a trend towards an increase in the occurrence and intensity of extreme events was also observed over the last 4 decades. In light of these analyses, it should be emphasized that the increase in precipitation observed in the Nakanbe–Wayen watershed is induced by the increase in the occurrence and intensity of events, as a trend towards an increase in persistent drought periods (CDD) is observed. This indicates that the watershed is suffering from water scarcity. Water stress and water-related hazards have a major impact on communities and ecosystems. In these conditions of vulnerability, the development of risk-management strategies related to water resources is necessary, especially at the local scale. This should be formulated in light of observed and projected climate extremes in order to propose an appropriate and anticipated management strategy for climate risks related to water resources at the watershed scale.

In Burkina Faso, small-scale, community-managed irrigation systems play a crucial role in stabilizing agricultural production and improving food security. Over the past three decades, the state has transferred the management of these irrigation systems to local farmer organizations in the hope of improving efficiency and sustainability. This study assesses the long-term performance of six irrigation perimeters Dakiri, Gorgo, Itenga, Mogtedo, Savili, and Wedbila through an in-depth analysis of governance models, infrastructure conditions, and financial sustainability. Performance indicators such as relative water supply (RWS), gross production per unit of irrigation water (PbIr), and water charge recovery rates were used to assess the effectiveness of farmer-led irrigation management. The results reveal persistent governance and financial challenges as well as issues such as water wastage and low yield persisting, despite decades of implementation of farmer-led management. The degradation of irrigation infrastructure, coupled with declining water fee collection rates, threatens the sustainability of these systems. A comparative analysis of international cases suggests that a hybrid governance model, in which the state provides technical and financial support while strengthening accountability mechanisms, could improve the performance of these irrigation systems. This study recommends a shift towards greater state intervention, improved financial mechanisms, and the adoption of digital monitoring tools to ensure a more efficient and sustainable management framework.