Sustainability

The exacerbation of climate change-induced droughts, among other weather extremes, is escalating into a critical global challenge particularly in arid regions like the Southwestern U.S. where droughts pose grievous environmental and socio-economic threats. Increasingly frequent, intense, and enduring droughts are commonplace generally in Western U.S. inflicting damages on crops and aggravating record-breaking wildfires year after year. Drought is the second-most expensive natural disaster in the U.S. behind hurricanes, costing an average of $9.6 billion in damages per event. Therefore, continuous innovation and deployment of cost-effective and time-efficient water resources monitoring tools could help mitigate severe environmental and socio-economic impacts of droughts which currently impact livestock and wildlife management in Southwest U.S. A recent innovation as a potential climate change adaptation solution is the Surface Water Identification and Forecasting Tool (SWIFT). The Google Earth Engine-based tool is a remote sensing-based technology that leverages optical imagery derived from Landsat 8 OLI and Sentinel-2 Multispectral Instrument (MSI), and radar imagery from Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR) to monitor near real-time the availability of water in stock ponds and tanks. As drought conditions are expected to worsen with rising global temperatures, SWIFT is designed to provide a valuable and affordable stock water monitoring solution for cattle producers and land managers, etc.

This interview provides an in-depth look at my expertise and experience in water resource management, environmental conservation, and the integration of AI and remote sensing technologies in Burkina Faso. My passion for water management stems from my desire to protect precious resources and my belief in the essential importance of providing water to communities, a principle reinforced when I joined the Ministry of Agriculture in 2021. As a Water and Environment Specialist at the General Office of Agro-Pastoral Development and Irrigation, I am responsible for irrigation systems, lowland rice-growing areas, and the protection of water infrastructure, while integrating innovation and remote sensing technologies to improve performance. My work also focuses on community conservation, including the removal of invasive aquatic plants from reservoirs and the treatment of gullies to combat soil erosion. I have experience in remote sensing and AI-based applications such as ML and DL for monitoring flood risks, erosion, and irrigation systems. I use machine learning algorithms such as CNN, Random Forest, U-Net, and SVM to analyze satellite images, predict the spread of invasive plants, and optimize water use. My research on integrating traditional knowledge into water management highlights the SoaSoagha concept, a collective work approach in Burkina Faso that promotes community conservation. Traditional rainwater harvesting, floodplain management, and small earthen dams (soussous) align with modern hydrological models, while sacred forests and customary water rights have been revealing, demonstrating indigenous methods of ecosystem protection. My project on AI-powered aquatic invasive plant management integrates machine learning (Satellite image analysis to classify areas with a high probability of aquatic plant presence), deep learning (Precise segmentation of invasive plants, such as water hyacinth and others, in these identified areas), and community engagement to extract, classify, and convert plants into compost, biogas, and biochar. My work highlights the importance of combining technological innovation and traditional knowledge to strengthen climate resilience, ensure water security, and promote sustainable development in Burkina Faso and beyond.

This interview provides an in-depth look at my expertise and experience in water resource management, environmental conservation, and the integration of AI and remote sensing technologies in Burkina Faso. My passion for water management stems from my desire to protect precious resources and my belief in the essential importance of providing water to communities, a principle reinforced when I joined the Ministry of Agriculture in 2021. As a Water and Environment Specialist at the General Office of Agro-Pastoral Development and Irrigation, I am responsible for irrigation systems, lowland rice-growing areas, and the protection of water infrastructure, while integrating innovation and remote sensing technologies to improve performance. My work also focuses on community conservation, including the removal of invasive aquatic plants from reservoirs and the treatment of gullies to combat soil erosion. I have experience in remote sensing and AI-based applications such as ML and DL for monitoring flood risks, erosion, and irrigation systems. I use machine learning algorithms such as CNN, Random Forest, U-Net, and SVM to analyze satellite images, predict the spread of invasive plants, and optimize water use. My research on integrating traditional knowledge into water management highlights the SoaSoagha concept, a collective work approach in Burkina Faso that promotes community conservation. Traditional rainwater harvesting, floodplain management, and small earthen dams (soussous) align with modern hydrological models, while sacred forests and customary water rights have been revealing, demonstrating indigenous methods of ecosystem protection. My project on AI-powered aquatic invasive plant management integrates machine learning (Satellite image analysis to classify areas with a high probability of aquatic plant presence), deep learning (Precise segmentation of invasive plants, such as water hyacinth and others, in these identified areas), and community engagement to extract, classify, and convert plants into compost, biogas, and biochar. My work highlights the importance of combining technological innovation and traditional knowledge to strengthen climate resilience, ensure water security, and promote sustainable development in Burkina Faso and beyond.