This session explores innovative science and applications advancing flood detection, mapping, monitoring, and response using Earth observations and complementary approaches. Satellite-derived products from optical sensors (e.g., MODIS, VIIRS, Landsat, HLS, Planet) and SAR platforms (e.g., Sentinel-1, NISAR, and commercial small-sat SAR such as Umbra, Capella, and ICEYE) can provide critical near-real-time information to characterize flood dynamics and support situational awareness. We invite contributions leveraging these and other datasets to improve understanding of flood processes across spatial and temporal scales. The session also encourages the integration of artificial intelligence, machine learning, and data-driven approaches to enhance flood prediction, mapping accuracy, and operational utility, alongside traditional statistical and physics-based models. Topics may include multi-sensor flood mapping, extreme precipitation drivers, flood risk and vulnerability, urban and coastal flooding, infrastructure impacts, and applications supporting preparedness, response, and recovery. Interdisciplinary and stakeholder-driven contributions are encouraged.

• GC - Global Environmental Change
• H - Hydrology
• NH - Natural Hazards
• SY - Science and Society