Meet HYDRIS: The Satellite-Powered Breakthrough in Flood Risk Intelligence

Flooding is the world’s costliest natural disaster, and its impacts are escalating. The United Nations Office for Disaster Risk Reduction reports that floods make up 35–40% of all weather-related disasters. Between 1970 and 2019, water-related hazards accounted for half of all disasters and 45% of reported deaths, and since 2000, recorded flood events have surged by 134%.

Yet despite this growing risk, most flood-forecasting systems still rely on coarse soil-moisture data, leaving a critical blind spot: the subsurface processes that determine how landscapes absorb, store, and release water.

Without this deeper hydrological visibility, models struggle to anticipate the onset, scale, and movement of flood events, particularly under rapidly changing climatic and land-use conditions. Engineers, planners, and risk analysts are left making high-stakes decisions with incomplete inputs, often leading to underestimated flood extents and delayed response times.

HYDRIS (Hydrological Risk Intelligence from Satellite) offers a new way forward.

Hydris: A next-generation soil moisture model powered by satellites

Determined to find more effective ways to support operational flood forecasting and early warning systems, Geofem’s remote sensing experts set about creating a next-generation, high-resolution, satellite-based soil moisture model — funded by the European Union-NextGenerationEU and developed under the Fast Track to Innovation programme.

Geofem’s unique approach to soil moisture detection

Geofem’s soil moisture detection combines cutting-edge remote sensing with advanced modelling to deliver unprecedented accuracy and detail.

This enables reliable, fine-scale insights that support better flood prediction and land management:

• Multi-depth soil moisture estimation using both C-band and L-band SAR 

• 10-metre spatial resolution, compared to today’s KM resolution products 

• Advanced data fusion of SAR, optical data, DEM, vegetation indices, soil texture & climate variables 

• Hybrid AI + physical modelling framework for higher reliability 

• Near real-time monitoring for catchment-scale flood prediction 

• Integration-ready for hydrological models, GIS systems, and early-warning platforms 

From space to strategy: Operational flood intelligence for real decisions

Traditional flood models often fail to accurately account for antecedent soil moisture conditions, a critical factor that determines whether rainfall infiltrates the ground or turns into dangerous surface runoff.

HYDRIS directly addresses this gap—enabling more precise, localised, and timely flood risk predictions. As such, the end user can make the most informed and effective decisions:  

• Improved flood forecasting accuracy  • Better asset-level infrastructure protection  • Enhanced climate resilience planning  • Reduced economic losses and improved public safety  • Scalable solutions for governments, insurers, and infrastructure operators

With HYDRIS, satellite-based flood intelligence moves from research to real-world operations, bridging the gap between earth observation and actionable climate risk decision-making. 

Follow our journey and read our insights as we transition HYDRIS from TRL 6 to TRL 8 and prepare it for global commercial deployment!