The Global Centre for Risk and Innovation (GCRI)
Water systems need energy and energy systems need water. Pumping, treatment and desalination draw power; hydropower, thermal cooling and fuel production draw water. Drought and heat stress both at once, and a failure in one propagates into the other within hours. This page sets out the couplings, how they are measured, and what the coupled evidence serves.
Water NexusWireframe of the working environment, not a live screen. Names and values are placeholders.
Pumping, cooling, hydropower and demand. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Hydropower depends on inflow and head; thermal plants on cooling water below a temperature limit; some fuels on process water. Low rivers and warm water curtail generation when demand peaks.
Groundwater pumping, long-distance conveyance, treatment and desalination are energy-intensive. An outage stops supply unless storage and backup are in place.
Heat raises cooling demand, irrigation demand and electricity demand together while lowering supply on both sides. The coupling turns a hazard into a compound event.
Reservoir releases serve generation, irrigation, flood control and ecosystems at once. A rule curve is a cross-sector decision whether or not it is governed as one.
Where this page’s subject sits in the world: boundaries and context now, the field layers when the interactive map loads.
MapWorld map in the Equal Earth projection, land and boundaries from Natural Earth (public domain). The interactive map loads through the Nexus Foundry plugin (globe or flat view).
The systems this subject touches, the method at its core and the decisions it informs.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Hydropower generation against inflow | gigawatt hours; cubic metres per second | daily | Operator records, gauges | OFFICIAL |
| Cooling-water temperature margin | degrees Celsius below the permit limit | daily | Station sensors | OBSERVED |
| Energy intensity of water supply | kilowatt hours per cubic metre | monthly | Utility metering | OBSERVED |
| Water intensity of generation | litres per megawatt hour | annual | Plant reporting | OFFICIAL |
| Coincident peak index | dimensionless | daily | Demand records across sectors | ESTIMATED |
| Reserve margin at evening peak | percent | daily | Grid operator | OFFICIAL |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| Grid and hydropower operators | Generation, inflow, reserve margin and curtailment records | By agreement |
| Global Runoff Data Centre and national gauges | River flow at intakes and dams | Data policy; by agreement |
| ERA5 and CHIRPS | Temperature and rainfall forcing | Free and open; public domain |
| Water utility metering | Energy per cubic metre by works | By agreement |
| Global Power Plant Database (WRI) | Plant locations, fuel and capacity | Free and open, attribution |
Water Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Grid operators and energy ministries | How much replacement capacity to secure before a dry season and at what cost | Inflow forecasts, hydropower curtailment scenarios, reserve margins at peak |
| Reservoir operators and basin authorities | How to set releases when generation, irrigation and ecosystems compete | Coupled scenarios with each use’s loss stated separately |
| Utilities and civil protection | Which works lose supply first in an outage and how long storage lasts | Dependency map with endurance hours; outage scenarios by feeder |
During heatwaves and droughts, rivers run low and warm. Thermal plants may have to reduce output when cooling water is scarce or too warm to discharge within environmental limits, just as electricity demand for cooling rises. Hydropower output falls with reservoir levels. At the same time, water utilities pump harder and further, and desalination plants draw heavily on the grid.
Power outages stop pumps and treatment, so electricity failure becomes water failure within hours. Choices about the energy transition matter: some low-carbon options, such as wind and solar photovoltaics, use little water in operation, while others, such as some forms of hydrogen production, bioenergy and carbon capture, can add water demand.
Joint water and power system models test drought scenarios, using hydrology and water science and forecasting and time-series analysis. Coupling different model types introduces its own uncertainties.
Inventories of water use per unit of energy and energy use per unit of water. Plant-level data are often unpublished.
Scenarios of flow and temperature translated into capacity constraints, with uncertainty quantification. Results are scenarios, not forecasts.
| Method | Applied here | Canonical page |
|---|---|---|
| Hydrology and water science | Hydrology and water science in this field | STEM Commons |
| Forecasting and time-series analysis | Forecasting and time-series analysis in this field | STEM Commons |
| Sensors, IoT and observation networks | Sensors, IoT and observation networks in this field | STEM Commons |
| Uncertainty quantification and model validation | Uncertainty quantification and model validation in this field | STEM Commons |
| Extreme value theory and tail risk | Extreme value theory and tail risk in this field | STEM Commons |
Operator records are often confidential, so coupled models rely on agreements or on coarser public data. Cooling-water limits and curtailment rules differ by plant and permit. The coupled model shows where failures propagate; it does not forecast the grid.
| Link | Relationship | Why |
|---|---|---|
| Hydropower and water | Related topic | Water infrastructure research explains dependency; energy research explains generation and grid exposure. |
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.