Recent studies have shown that globally, riverine and coastal floods are increasing in intensity and duration. In addition, the number of people living in flood-prone areas has increased substantially during the last two decades. Therefore, monitoring and predicting floods in support of early warning, response, and relief operations have become major foci for disaster management activities worldwide. Remote sensing observations from optical and Synthetic Aperture Radar (SAR) sensors are routinely used for detecting and mapping flooding. Moreover, empirical methodologies developed using remote sensing observations of rainfall, terrain, soil moisture, and landcover, as well as weather modeling data have been used for flood monitoring. Sophisticated and complex land hydrology and runoff routing models are also being used for mapping and predicting riverine and urban flooding.
ARSET has offered several trainings on flood monitoring based on optical and SAR observations in the past. This two-part training will focus on recent developments and updates in flood monitoring tools and flood modeling techniques. Specifically, an overview of the Hydrological Modeling and Analysis Platform (HyMAP), a routing model used with NASA’s Land Information System (LIS), and examples of flood modeling cases will be presented in this training.
Relevant UN Sustainable Development Goals:
• Goal 11: Make cities and human settlements inclusive, safe, resilient and sustainable
• Target 11.5: By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situations
• Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries
Course Format: Two, 2-hour parts