Allocation under variable flow
Long flow records and climate-adjusted projections test whether fixed allocation volumes in a basin agreement can be met in dry years, and how proportional rules would behave.
GRF · Climate and Nature Governance
Hydrology and water science for climate and nature governance
Hydrology describes how water moves through catchments, aquifers and rivers. In basin and water governance it provides the flow, storage and variability evidence on which allocation rules, treaty shares and drought procedures depend, and it shows how upstream decisions travel downstream.
01Register
Key facts.
Method recordSTEM method
- MethodHydrology and water science
- StewardWater Nexus
- Applied inClimate and Nature Governance
- Data4 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What hydrology and water science does here.
Hydrology studies the movement, distribution and quality of water across the land surface, subsurface and atmosphere. It underpins the assessment of floods, droughts and water supply, which affect food, energy, health and infrastructure together. In climate and hazards, biodiversity and nature, water and food and agriculture, hydrological estimates set design standards for dams, levees and drainage and inform water allocation between competing users. They link climate hazards to downstream effects on power generation, crops and public health. The canonical description is on the STEM Commons.
Upstream project effects
Hydrological models estimate how a proposed dam or abstraction changes flow timing and quantity downstream, as evidence for notification and joint assessment.
Shared monitoring design
Gauging networks and data exchange protocols are designed so that riparian parties share the same flow record.
03Geography
Water now in the Andes.
Rain, flood water, root-zone soil moisture and population density over the Andes, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 4
Water now, for this page
About this layer
- Evidence
- Estimated
- Source
- GPM IMERG (NASA GES DISC)
- Provider
- NASA GES DISC
- Licence
- NASA open data
- Vintage
- daily; Satellite estimate, near real time
- Newest at build
- 2026-10-12
- Resolution
- about 2 km grid
- Uncertainty
- Satellite estimate, near real time. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled
- Source
- SMAP Level 4 (NASA NSIDC DAAC)
- Provider
- NASA NSIDC DAAC
- Licence
- NASA open data
- Vintage
- daily; Model with satellite data assimilated
- Newest at build
- 2026-10-11
- Resolution
- about 2 km grid
- Uncertainty
- Model with satellite data assimilated. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (latest month GIBS publishes)
- Source
- GRACE-FO JPL mascons (NASA JPL PO.DAAC)
- Provider
- NASA JPL PO.DAAC
- Licence
- NASA open data
- Vintage
- monthly; Satellite gravimetry; latest month GIBS publishes
- Newest at build
- 2022-07-01
- Resolution
- about 2 km grid
- Uncertainty
- Satellite gravimetry; latest month GIBS publishes. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds and overpass timing leave gaps)
- Source
- VIIRS NOAA-20 375 m (FIRMS) (NASA LANCE FIRMS)
- Provider
- NASA LANCE FIRMS
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds and overpass timing leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 500 m grid
- Uncertainty
- Satellite hot-spot detections for the day shown, including gas flares and industrial heat; not a confirmed fire, an incident report or a warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Water now, framed on the Andes.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA GPM IMERG Early · U.S. Geological SurveySources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- SMAP Level 4 soil moisture and snow mass, NASA Global Modeling and Assimilation Office; distributed by the NASA National Snow and Ice Data Center DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- GRACE and GRACE-FO JPL mascon solution, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Live: NASA GPM IMERG Early. We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
- Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (14 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- Root-zone soil moisture, 0 to 100 cm: SMAP Level 4, NASA NSIDC DAAC · 11 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Water storage anomaly, monthly: GRACE-FO JPL mascons, NASA JPL PO.DAAC · July 2022
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
04Data
What the method consumes.
Datasets and records used by hydrology and water science on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| GRDC river discharge records | Observed flows | OBSERVED |
| GRACE terrestrial water storage | Groundwater and storage change | OBSERVED |
| FAO AQUASTAT | Withdrawals by sector | ESTIMATED |
| Basin model outputs | Scenario flows | MODELLED |
05Policy scenarios
Compare instruments: rules, incentives and information.
Three families of instruments side by side against the baseline, each with its own lag and adoption speed, under the coverage and compliance you set; effect sizes are teaching values to replace with evidence. Scenario: named assumptions about the future, not a forecast. The map on this page shows The Andes; the model itself is not tied to a place.
Controls
- Baseline trend of the outcome
- 2.0% a year
- Coverage of the instrument
- 70%
- Compliance
- 75%
- Effect size, against the teaching value
- 100%
- Years ahead
- 20 years
Readouts
- Largest reduction at the horizon
- Defences and storage
- Its reduction against the baseline
- 24%
Numbers, methods and sources
| Year | Baseline | Defences and storage | Land-use rules | Warnings and preparedness |
|---|---|---|---|---|
| 0 | 100.0 | 99.7 | 98.9 | 98.7 |
| 1 | 102.0 | 101.5 | 100.4 | 98.7 |
| 2 | 104.0 | 103.1 | 101.8 | 97.5 |
| 3 | 106.1 | 104.4 | 102.8 | 96.8 |
| 4 | 108.2 | 105.2 | 103.6 | 97.5 |
| 5 | 110.4 | 105.2 | 104.1 | 99.0 |
| 6 | 112.6 | 104.4 | 104.3 | 100.9 |
| 7 | 114.9 | 102.7 | 104.3 | 102.8 |
| 8 | 117.2 | 100.6 | 104.3 | 104.9 |
| 9 | 119.5 | 98.9 | 104.4 | 107.0 |
| 10 | 121.9 | 97.9 | 104.7 | 109.1 |
| 11 | 124.3 | 97.9 | 105.3 | 111.3 |
| 12 | 126.8 | 98.6 | 106.3 | 113.5 |
| 13 | 129.4 | 99.8 | 107.6 | 115.8 |
| 14 | 131.9 | 101.3 | 109.1 | 118.1 |
| 15 | 134.6 | 103.1 | 110.8 | 120.5 |
| 16 | 137.3 | 105.0 | 112.7 | 122.9 |
| 17 | 140.0 | 107.0 | 114.8 | 125.3 |
| 18 | 142.8 | 109.1 | 116.9 | 127.8 |
| 19 | 145.7 | 111.3 | 119.1 | 130.4 |
| 20 | 148.6 | 113.5 | 121.4 | 133.0 |
Methods
- Tools of government Hood (1983), The Tools of Government, Macmillan
- Carrots, sticks and sermons Bemelmans-Videc, Rist and Vedung (1998), Transaction
- Diffusion of innovations Rogers (2003), Diffusion of Innovations, Free Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Borders Natural Earth
- Cities Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Climate and Nature Governance in Foundry
- Tested at Climate and Nature Governance in Universe
- Codified in Climate and Earth Systems in Standards
- Published in Climate and Nature Governance in Reports
- Taught in Faculty of Earth and Environmental Sciences in Academy
06Validation
How results are checked.
Models are calibrated on one period of observed flows and tested on an independent period or neighbouring catchment. Skill scores and comparison with surveyed flood extents are used to judge performance.
| Check | How it is done |
|---|---|
| Record length and gaps | Flow statistics state record length, gaps and how they were filled |
| Model calibration | Basin models are calibrated and validated on separate periods |
| Non-stationarity | Trends are tested before historical statistics are used for future allocation |
Assumptions of stationarity weaken as climate and land use change. Ungauged basins, karst aquifers and rapid urbanisation are poorly represented by parameters fitted elsewhere.
07Anticipatory action
From forecast to early action, by pillar.
The chain from an impact model to an evaluated early action, each step with the pillar that runs it, and the decisions that stay with the authorities. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Andes; the model itself is not tied to a place.
- Risk and impact model Foundry
Impact thresholds are set from hazard, exposure and vulnerability. Coughlan de Perez and others (2015) - Trigger and protocol agreed Nexus Standards
A forecast probability and lead time that trigger action are written down in advance. Coughlan de Perez and others (2015) - Pre-arranged finance Competent authority (outside the programme)
Funds are committed before the event by those who hold them. WMO (2022) - Simulation exercise Universe
The protocol is exercised end to end before it is needed. WMO (2022) - Forecast crosses the trigger Foundry
The forecast is read against the trigger; the decision to act is recorded. Coughlan de Perez and others (2015) - Early action Competent authority (outside the programme)
Responders act in the window before the impact, under their own mandates. WMO (2022) - Training of responders Risk Academy
Responders learn the protocol and its limits. WMO (2022) - Evaluation published Reports
What was triggered, what was done and what it avoided is published. Coughlan de Perez and others (2015)
Methods
- Forecast-based financing Coughlan de Perez and others (2015), NHESS 15
- Early warnings for all WMO (2022), Executive Action Plan 2023–2027
- Layered drawing of directed graphs Sugiyama, Tagawa and Toda (1981), IEEE SMC 11
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Climate and Nature Governance in Foundry
- Tested at Climate and Nature Governance in Universe
- Codified in Climate and Earth Systems in Standards
- Published in Climate and Nature Governance in Reports
- Taught in Faculty of Earth and Environmental Sciences in Academy
08Connections
Topics that rely on this method.
09Twin and cascade simulator
Exercise the cascade with the people who decide.
Assembled from the Nexus Standards area profile Climate adaptation and transition risk: the hazards it names, the systems and communities that carry the loss, the controls and institutions that dampen it and the data that observe it. Pick an initiating event and step through the cascade to see where mandates meet and which decisions fall to whom. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise for dialogue, not a forecast, an assessment or a position. To model a place of your own choosing, open the full System Builder.
Hazards
- Sea-level rise
- Heatwave
- Windstorm
- Flash flood
- Meteorological drought
- Groundwater depletion
- Widespread power outage (set off downstream)
- Large forest disturbance (set off downstream)
- Wildfire (set off downstream)
- Extreme fire weather (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
- Flash drought (set off downstream)
- Snow drought (set off downstream)
- Ground-level ozone episode (set off downstream)
- Debris flow (set off downstream)
- Hydrological drought (set off downstream)
- Peat and underground fire (set off downstream)
Systems and couplings
- Climate adaptation and transition risk
- Climate risk standards Mechanism
- Financial and economic risk standards Cascade
- Energy risk standards Feedback
- Water risk standards Maladaptation risk
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-X1Climate change risk and adaptationNRS-T16AI agents and autonomous decision systems riskNRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-I7Intelligence applications: grounded retrieval, reasoning and decision supportNRS-K20Domain pack profile: Climate adaptation (DOMAIN-020)NRS-K21Domain pack profile: Climate mitigation carbon (DOMAIN-021)
Observation
- CMIP6 climate projections (Copernicus Climate Data Store) (listed for reference)
- NGFS Scenario Explorer (listed for reference)
- ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
- World Bank Open Data and World Development Indicators API (listed for reference)
- Number of countries with nationally determined contributions, long-term strategies, national adaptation plans and adaptation communications
- Number of countries that adopt and implement national DRR strategies in line with the Sendai Framework
Example geography
- Pacific Island states: 150 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
10Stewardship
Who maintains the method.
Water Nexus stewards hydrology and water science for the Consortium and reviews how it is applied across platforms.
11Sector signature
Who a decision on hydrology and water science for climate and nature governance reaches.
The sectors a policy on hydrology and water science for climate and nature governance has to coordinate: a choice in one ministry lands in the others.
Select corners · hover lines6 / 15 relations
Signature
Water and Biodiversity
Water gives biodiversity environmental flows (0.6): the strongest relations between the sectors this subject joins.
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.43 share of total
Strongest relations in play
- Food → Biodiversity · land conversion0.6
- Water → Energy · cooling water and hydropower0.6
- Water → Food · irrigation0.8
- Water → Biodiversity · environmental flows0.6
12Connected
Where this page leads across the Consortium.
13Instruments and commitments
Instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Mandates and agreements over time
The agreements that set mandates and commitments on hydrology and water science for climate and nature governance, from adoption to their current horizon.
- 1992UNFCCC and Convention on Biological DiversityUnited Nations
- 2015Sendai Framework for Disaster Risk ReductionUNDRR
- 20152030 Agenda and the Sustainable Development GoalsUnited Nations
- 2015Paris AgreementUNFCCC
- 2022Kunming-Montreal Global Biodiversity FrameworkCBD
- 2023First global stocktake under the Paris AgreementUNFCCC
- 2030Horizon of the 2030 Agenda and the Sendai FrameworkUnited Nations
Sendai Framework for Disaster Risk Reduction · UNDRRParis Agreement · UNFCCC2030 Agenda and the Sustainable Development Goals · United NationsInternational Health Regulations · WHO
14Questions
Questions and answers.
What are the limits of hydrology and water science in this field?
Assumptions of stationarity weaken as climate and land use change. Ungauged basins, karst aquifers and rapid urbanisation are poorly represented by parameters fitted elsewhere.
How are results checked?
Models are calibrated on one period of observed flows and tested on an independent period or neighbouring catchment. Skill scores and comparison with surveyed flood extents are used to judge performance.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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