DTE Hydrology Next

Context

As climate crisis alters the global water cycle, intensifying precipitation, accelerating snowmelt and increasing soil moisture loss, the frequency and severity of hydro-meteorological extremes grow with it.

Decision-makers urgently need systems that can predict and monitor these events and support smarter management of water resources.

Managing floods, landslides and droughts requires something that has never existed before: the ability to see the entire water cycle, from rainfall to river flow to groundwater, at high resolution, in near real time, and at the scale of a continent.

The Digital Twin Earth (DTE) programme launched by the European Space Agency (ESA) answers this need: it merges Earth Observation (EO) data with Artificial Intelligence and advanced modelling to build virtual replicas (digital twins) of Earth’s systems. Its outputs feed directly into the European Union’s Destination Earth (DestinE) initiative.

Within this framework, hydrology is one of the domains where the digital twin approach can make the biggest difference.

The project

DTE Hydrology Next is an ESA project prototyping a full end-to-end demonstrator of a Digital Twin Earth for hydrology, targeting high resolution spatial and temporal scales (1 km and 1 hour).

Building on the success of the previous DTE Hydrology and DTE Hydrology Evolution projects, originally developed over the Po River Valley and the Mediterranean region, this next phase extends capabilities to a wider scale, covering Europe and selected areas in Africa and Central America.

MEEO’s role

To achieve this, MEEO leverages EDEN, a DestinE core service, which harmonises a wide variety of EO datasets and Digital Twin data, making them seamlessly available through a single cloud-based infrastructure.

Within DTE Hydrology Next, MEEO is responsible for data conversion, access and visualisation, the technological layers that turn complex simulations into knowledge that can be explored and understood.

On top of EDEN, MEEO develops the DTE Hydrology platform that empowers users to:

• Explore the outputs of the hydrological models as interactive maps.
• Navigate EO data and anomalies, from historical records to predictive forecasts.
• Fully interact with the project’s use-case results, comparing scenarios and supporting decision making.

Roadmap

Phase 1 – Data Inputs & Retrieval

• Multi-source data acquisition: ingestion of raw data from Earth Observation satellites (Sentinel-1, 2, 3, ASCAT, Meteosat), in-situ sensors and atmospheric reanalysis.
• Retrieval algorithms: advanced processing pipelines transform raw signals into high-quality geophysical variables.
• High-resolution mapping: precision-targeted mapping at 1 km spatial and 1-day to 1- hour temporal resolution.

Phase 2 – The DTE Hydrology Datacube 2.0

A unified, multi-dimensional datacube structuring ten key hydrological variables: Precipitation (P), Soil Moisture (SM), Groundwater (GW), Reservoir Level (RW), Flooded Areas (F), Snow Water Equivalent (SWE), Evaporation (E), Reservoir Volume (RV), Irrigation Water Use (IWU) and River Discharge (Q).

Phase 3 – Analytical Layer & Modelling

Datacube variables feed into a suite of hydrological, hydraulic and geo-hydrological models to simulate real-world water behaviour, featuring two key advancements:

• Accounting for human factors in the “new” water cycle: incorporating data like irrigation significantly improves model performance, especially for the representation of summer low flows.
• Uncertainty & reliability: shifting towards probabilistic digital twins that deliver a reliable range of outcomes rather than a single and rigid answer.

Phase 4 – Decision Support & Impact

The system delivers operational and actionable tools across two distinct fronts:

• What-if scenarios (long-term planning): simulate the long-term impacts of land-use changes and climate projections, e.g. on future flood and drought risks.
• Monitoring (current status): tracking real-time environmental status, e.g. drought progression and water resource availability.

Concrete applications include landslide inventory (Italy), what-if flood risk prediction (Rhine) and what-if for water resources management (Po river).