This course explores the remote sensing dataset and the application of various sensors for water resource monitoring and management. Cloud-Based Data Processing techniques applied on Python libraries for accessing, manipulating, and analyzing earth observation datasets (CHRIPS, Landset/ Sentinel) for water and food security. 

This course explores the application of Earth Observation (EO) technologies to monitor and manage transboundary water resources. The course will explore the rate of water scarcity, conflict concerns, need for sustainable management and increasing demands on its resources. Techniques such as remote sensing, GIS, hydrological modeling, relevant open source tools such as SWAT+ model and generally Earth observation (EO) techniques will be employed to address climate change and water-related crisis and policies for sustainable management.


The "Mapping for Flood Modelling" course provides foundational knowledge and practical skills essential for assessing and managing flood risks in vulnerable regions. This course integrates mapping techniques, topographic analysis, and flood modeling to enhance understanding of water flow and accumulation in sub-basins—critical areas for predicting and mitigating flood events.

Participants will engage in hands-on training and interactive workshops, utilizing satellite data and ground measurements to create accurate flood maps and models.

Through real-world case studies, participants will learn about successful flood modelling, underscoring the importance of community engagement and collaboration. Ultimately, the course aspires to strengthen resilience in affected areas, contributing to safer and more sustainable environments for communities facing the threats of extreme weather and flooding.