GCRI · Campaigns
Water and food awareness
Water and food reach most people through systems they never see: catchments, treatment works, irrigation, supply chains and markets. Public awareness of those systems is usually low until a shortage, a contamination notice or a price spike makes them visible, and then attention fades again. This page sets out how understanding of life-support systems forms, how advisories about water and food are received, how rumours spread in scarcity, and what evidence the authorities who issue advice can use.
Water and food awareness on the record.
Water and food awareness: how the risk develops.
Campaigns rooted in life-support systems. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Dependence is invisible
A tap and a shop shelf hide the catchment, the treatment works, the farm and the supply chain behind them. People reason about what they can see, so conservation or food-waste messages that do not connect the household to the system are hard to act on or to judge.
Attention rises and falls with crisis
Public attention follows an issue-attention cycle: concern spikes during drought restrictions, outbreaks or price shocks and declines as coverage moves on. Advice learned in one crisis is often forgotten before the next, and seasonal campaigns compete with that decay.
Advice meets constraint
Households asked to save water or change diets differ in what they control: tenants, informal settlements and low-income households have fewer options. Messages that place responsibility on individuals while leaving structural causes unmentioned can be read as unfair and lose credibility.
Rumour spreads in scarcity
During shortages and contamination events, rumours about safety, hoarding and causes travel through messaging apps and local networks. Reports of panic buying can prompt the behaviour they describe. Boil-water and do-not-use notices are misread when their wording, scope and duration are unclear.
Water now in South Asia.
Crop greenness, root-zone soil moisture and population density over South Asia, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Water now, for this page
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- MODIS Terra NDVI (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite index; clouds leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 250 m grid
- Uncertainty
- Satellite greenness index over the 8 days to the date shown; an indicator of crop and pasture condition, not a yield estimate or a food security warning.
- 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
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. 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
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 South Asia.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 JPL OPERA DIST-ALERTSources 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
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and 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
- 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
- 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.
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). 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).
- 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
- Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 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
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
Awareness campaigns on water and food link to health and nature.
Campaign evaluations are designed for the Evidence Brief series, including null results. Claims in campaign materials cite their sources.
- Local campaign needs.
- Evaluation partners.
Campaign wave tracker.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Campaign wave tracker
Water and food awareness · Wave 2 · Campaign area North
- People reached127913Active
- Consent complete, % of participants97Normal
- Knowledge score change0.2pointsNormal
- Open feedback items16Watch
Preparedness actions by area
Messages under test
| Prepare a water reserve | A | 37 | Keep |
| Know your warning levels | B | 30 | Keep |
| Check on neighbours | A | 68 | Keep |
Safeguarding and consent
- S-1Minor enrolled without guardian recordPause and verify2 d
- S-2Withdrawal requestData deleted, logged3 d
What is measured, and how well.
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 |
|---|---|---|---|---|
| Comprehension of boil-water and do-not-use notices | percent of sampled residents correctly stating the action | per event | Post-event household survey | REPORTED |
| Satisfaction with local water quality | percent of respondents | annual | Gallup World Poll | REPORTED |
| Population using safely managed drinking water | percent of population | annual | WHO/UNICEF Joint Monitoring Programme | ESTIMATED |
| Experience of food insecurity | prevalence by Food Insecurity Experience Scale class | annual | FAO survey module | ESTIMATED |
| Understanding of food date labels | percent of respondents distinguishing use-by from best-before | per survey wave | Eurobarometer and national surveys | REPORTED |
| Media attention to water and food shortages | articles per week | weekly | News archive content analysis | OBSERVED |
| Search interest in restrictions and advisories | relative interest index | weekly | Search engine query-volume indices | ESTIMATED |
| Languages and formats of advisories | count of languages and accessible formats issued | per advisory | Audit of issued notices | DECLARED |
Model water and food awareness as a system. Run the cascade.
Assembled from the Nexus Standards area profile Information integrity and trust: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Civil unrest
- Ice-jam flood
- Tropical cyclone
- Heatwave
- HIV epidemic
- Dam failure
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- Extreme fire weather (set off downstream)
- Wildfire (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-2Citation and attribution format for UNIsNS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-12Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)NRS-H52Hazard family: Information-integrity attacks (NHS-1 cyber.integrity)NRS-X7Information integrity and public trustNRS-U23Universe platform profile: ReportsNRS-A4Zero-trust verification of standards and conformanceNRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-H72Hazard family: Novel entities and emerging contaminants (NHS-1 poll.novel-entities)
Observation
- GDELT event database and global knowledge graph (listed for reference)
- Our World in Data datasets (listed for reference)
- Number of countries that adopt and implement guarantees for public access to information
Example geography
- The Horn of Africa: 253 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
Where the evidence comes from.
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 |
|---|---|---|
| WHO/UNICEF Joint Monitoring Programme | Household drinking water, sanitation and hygiene service levels by country | Free to use with attribution |
| FAO Food Insecurity Experience Scale data | Experience-based food insecurity estimates and the survey module behind them | CC BY-NC-SA 3.0 IGO |
| Gallup World Poll | Satisfaction with water quality and access to food by country | Commercial licence; published summaries free to read |
| Special Eurobarometer on food safety | Awareness of food risks and trust in information sources across the EU | Free reuse with attribution |
| UNEP Food Waste Index Report | Household and retail food waste estimates and measurement guidance | Free to use with attribution |
| GDELT Project | Global news coverage, events and themes for attention analysis | Free and open, attribution |
| Drinking water regulator reports and notices | Incidents, advisories and compliance records, such as those of the Drinking Water Inspectorate in England and Wales | Open Government Licence or national terms |
The sector signature of water and food awareness.
The sectors water and food awareness touches and how strongly they depend on each other: what a study has to observe and model together.
Signature
Water and Food
Water gives food irrigation (0.8): the strongest relations between the sectors this subject joins.
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Strongest relations in play
- Food → Biodiversity · land conversion0.6
- Water → Food · irrigation0.8
- Water → Biodiversity · environmental flows0.6
- Food → Health · nutrition0.7
Who decides, and what the evidence serves.
Campaigns 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 |
|---|---|---|
| Drinking water regulators and utilities | How to word, translate, issue and lift boil-water and do-not-use notices | Comprehension evidence on notice wording; reach of channels; language needs |
| Water allocation authorities | When to ask for voluntary saving and how to explain mandatory restrictions | Awareness and attention data; fairness concerns raised by affected groups |
| Food safety authorities | How to communicate a recall or contamination risk without causing avoidable alarm | Trust in sources by group; rumour logs; tested message formats |
| Ministries of agriculture and education | Whether to include food systems and water in school and extension programmes | Curriculum reviews; teaching material with stated learning aims |
Outputs this topic produces
- Explainers tracing household water and food back to the systems that supply them
- Plain-language advisory templates with comprehension test records, for issuing authorities to adapt
- Structured rumour and question logs for shortage and contamination events
- Teaching material on catchments, supply chains and food waste
How water and food awareness is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
System model
The couplings between the systems in water and food awareness: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask.
- 01
What do people misunderstand about supply?
Common gaps in knowledge about sources, treatment, storage, distribution and the links between water, energy and food.
- 02
Which behaviours matter?
Household water safety, food storage, waste and conservation, and which of them have meaningful effect at scale.
- 03
How are shocks explained?
How to describe drought, contamination or price spikes without causing hoarding or panic.
- 04
Who is most exposed?
Households without secure connections, storage or income buffers, and how to reach them.
What drives the outcome.
Water and food systems are tightly coupled. Agriculture uses most of the freshwater withdrawn worldwide, food processing and cold chains depend on electricity, and water treatment depends on energy and chemicals. A drought can therefore reach consumers as a water restriction, a power shortage and a food price rise at once.
Public behaviour interacts with these systems. Conservation during drought can relieve pressure on supply; panic buying can create the shortages people fear. Trust in tap water affects whether households buy bottled water or use unsafe sources. Food safety at home depends on understanding storage, temperature and contamination.
Awareness alone rarely changes behaviour. Campaigns work best when they pair information with practical, affordable actions and when the messenger is trusted locally.
How evidence is gathered, and where it stops.
| Method | What it shows | Its limit |
|---|---|---|
| Knowledge surveys | Baseline understanding of sources and risks | May miss groups without connections |
| Utility and market data | Changes in consumption or demand during a campaign | Many other factors move the same figures |
| Focus groups | Why people act as they do | Not statistically representative |
| Scientific review | Accuracy of claims about supply and safety | Local conditions vary and must be checked |
How it is studied, and what the methods cannot say.
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Why treat water and food together?
Do water-saving campaigns reduce use?
Why are boil-water notices misunderstood?
Does Campaigns issue water or food advice?
Does the platform issue water or food safety advice?
Why link water and food in one topic?
Who reviews the science?
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