Streamflow & Flood — inflow and flood-risk intelligence for hydropower and reinsurers

Every river — including the ungauged ones — read from orbit before a gauge sees it.

A river gauge is a confession after the fact: it tells you what has already passed the post. And most of the world’s rivers have no gauge at all. We read the river network the other way round — from the contributing catchment downward, observing snowpack water content, rainfall, evapotranspiration and soil moisture from orbit, and resolving the flow reach by reach across basins that have never carried an instrument. Each forecast arrives as a calibrated scenario band, never a single deceptive line, so turbines, flood reserve and treaty exposure are all set against an honest, quantified range.

THE ARGUMENT IN ONE LINE

A catchment-wide streamflow and low-flow outlook with a calibrated P10–P90 band on every horizon, extended into ungauged basins from the physics of the catchment — and benchmarked, where gauges exist, river by river against national networks, with skill reported per basin rather than buried in a flattering average.

August 2025, ranked by how far each reach fell.

Ranked horizontal-bar chart of the major European river reaches that ran most below normal in August 2025, measured as a standardized discharge anomaly against the 2015-2024 August normal, biggest drop at the top

WHICH RIVERS SUFFERED MOST · AUGUST 2025 TRUNK-FLOW SHORTFALL vs THE 2015–2024 NORMAL · REAL OBSERVATIONS, RANKED BY SEVERITYSTANDARDIZED DISCHARGE ANOMALY · CONTAINS MODIFIED THIRD-PARTY DATA

The chart above is not a projection. It ranks Europe’s major river reaches by how far their trunk flow fell below normal in August 2025 — each bar a standardized discharge anomaly measured against that same reach’s own 2015–2024 August record, biggest drop at the top. The Atlantic-facing basins took the hardest hit: the Garonne ran roughly three-quarters below its August normal, the Loire close to two-thirds down, with the Drava, Weser and Meuse all sharply drawn down behind them. These are measured shortfalls, reach by reach — not a single continental average that would have hidden exactly where the water went missing.

That is the whole problem in one view. The places where low flow bites hardest — headwaters, tributaries, the small basins that feed a hydropower scheme or a city intake — are exactly the places a national gauge network thins out. Orbit does not thin out. It reads the filled and the unfilled, the watched and the unwatched, on the same pass.

The rivers no instrument watches — read anyway.

Most rivers are ungauged. A gauge is a pole in the water with a budget behind it, and budgets concentrate on the big, navigable, politically visible reaches. The headwater that fills a reservoir, the tributary that floods a town, the cross-border stretch where nobody owns the meter — these run blind. When a gauge does exist, it answers one question, at one cross-section, for water that has already gone by.

We invert the geometry. Instead of waiting at a point for water to arrive, we observe the contributing catchment that produces the flow: the snowpack holding next season’s melt, the soil moisture deciding whether rain runs off or soaks in, the rainfall and evapotranspiration that close the water balance. A hydrological model, anchored to that physics and corrected wherever a gauge exists, then resolves discharge along every reach of the network — gauged or not. The ungauged basin is not skipped; it is estimated from the same observed inputs as its measured neighbours, and it ships with a wider, honest uncertainty band to show it.

This is the part of the product that has no substitute. A gauge network can only report where it has gauges. A catchment read from orbit reaches the reaches that matter precisely because nobody else can see them.

The questions an operator and an underwriter both ask.

No single accuracy percentage is quoted below. The differentiator is a calibrated scenario band on every forecast and per-basin skill you can audit against independent gauges.

A · ACCURACY & VALIDATION

How do I know the forecast holds?

Because it is shipped as a calibrated scenario band with guaranteed coverage, not a single line, and because the band is verified out of sample. When we state a P10–P90 range, the realised flow falls inside it at the stated frequency — that is the property an operator schedules against and an underwriter prices against. Skill is benchmarked basin by basin against national hydrological gauge networks and reported per basin, release by release.

Independent referee. National river-gauge networks are the reference; the comparison is re-run with each release.
Honesty rule. Basins below the skill threshold ship with a "low confidence" label rather than being dropped or dressed up.
Validation pack. Per-basin skill tables ship with the product and stay current for the contract.

B · RESOLUTION & UPDATE FREQUENCY

How fine, how often?

Spatial: resolved per basin / catchment and per gauge node, with the contributing area observed pixel by pixel rather than as a single point.

Temporal: refreshed as new satellite passes arrive — optical depends on clear sky, while radar continues through cloud to keep the catchment observed.

C · INTEGRATION

How does it reach my systems?

API — per-node flow scenarios and flood-risk values.
GeoTIFF — catchment and inundation-extent rasters.
PDF report — basin outlook brief for operations and treaty files.

The API delivers tag-style values and bands that a SCADA / dispatch or hydro-scheduling system can ingest as derived inflow inputs.

D · TECHNOLOGICAL LIMITATIONS — HANDLED HONESTLY

Where lead time shortens, and what we do about it

Lead time is honest, not uniform. It is strongest when inflow is snowmelt-driven and the catchment is densely observed, and it shortens for flashy, rain-driven flood events where the signal develops in hours, and where persistent cloud thins the optical record. We do not paper over this: the scenario band widens automatically as predictability falls, so a hard-to-forecast catchment shows a visibly wider range rather than a confident wrong number. Cloud gaps in optical sensing are bridged with radar, which keeps water extent and soil-moisture signals flowing through weather that blinds optical sensors.

Sparsely gauged mountain basins, which are hard to verify, are labelled low-confidence rather than presented at face value.

E · COMPLIANCE & STANDARDS

Where it fits

Outputs are designed to support flood-risk assessment, water-agency planning and dam operating-rule reviews, with an auditable basis that can be checked against national gauges. Processing runs under EU data residency.

We do not claim an official hydrological-forecasting designation we do not hold, and we say so. The product complements national services; it does not impersonate one.

F · DELIVERY FORMATS

What you actually receive

API with per-node flow scenarios + flood-risk values
GeoTIFF catchment / inundation rasters
Vector tables (CSV / GeoPackage)
PDF basin outlook reports
SCADA / dispatch-ingestible feed

G · FORECAST HORIZON

How far ahead it speaks

Horizon runs from a short range for flash, rain-driven flood events up to a multi-week outlook where inflow is snowmelt-driven and the catchment is well observed. Every horizon carries its own band — the further out, the wider the spread — so turbine scheduling, flood-reserve drawdown and treaty exposure are each set against an honest, quantified range.