GRA · Development Finance Nexus
Spatial financeWhere capital meets hazard, exposure and transition
Food, water and energy investment
Investment in food systems, water supply and energy builds the services every other sector depends on, and the three share their risks. A drought cuts hydropower and irrigated yields at once; tariffs below cost weaken the utilities that lenders and guarantors rely on; a price shock raises import bills and borrower stress together. This page sets out how risk propagates across these sectors in development finance, which records evidence it, and who decides.
Food, water and energy investment on the record.
Food, water and energy investment: how the risk develops.
Essential service resilience. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Shared resource, shared shock
Hydropower, irrigation and urban supply draw on the same rivers and aquifers. A dry year reduces all three, so a portfolio that looks diversified across sectors can carry one correlated exposure.
Utility finances carry sector risk
Tariffs below cost recovery, high losses and late payment by public customers weaken utility balance sheets. Lenders then rely on sovereign support, and sector risk becomes a contingent liability of the state.
Offtaker risk in power
Independent power projects depend on a purchase agreement with a state utility. When the offtaker cannot pay, risk passes to liquidity facilities, payment guarantees, the treasury and political risk insurers.
Price and weather in food
Fertiliser, fuel and grain price swings and weather shocks hit smallholder incomes, agribusiness borrowers and food import bills in the same season, when food security programmes also need finance.
A drought index against its attachment point.
How a dry season is read against the point where drought cover starts to pay. Synthetic season and design terms.
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 |
|---|---|---|---|---|
| Operating cost coverage of utilities | ratio of operating revenue to operating cost | annual | Utility financial statements | Published statistics |
| Non-revenue water | percent of system input volume | annual | IBNET, utility records | Published statistics |
| Electric power transmission and distribution losses | percent of output | annual | World Development Indicators | Published statistics |
| Offtaker payment delay to producers | days of receivables outstanding | quarterly | Utility and regulator reports | REPORTED |
| Access to electricity | percent of population | annual | Tracking SDG7 | ESTIMATED |
| Moderate or severe food insecurity | percent of population | annual | FAO Food Insecurity Experience Scale | ESTIMATED |
| Area equipped for irrigation | hectares | periodic | FAO AQUASTAT | Published statistics |
| Private participation commitments in energy and water | US dollars | annual | World Bank PPI database | REPORTED |
How a local shock becomes a system outage.
How much of the networks an operator, insurer or lender depends on stays working after a local shock, and how much the coupling between them amplifies it. Teaching model with stated illustrative values, not a prediction. The map on this page shows Southern Africa; the model itself is not tied to a place.
Controls
- Assets per layer
- 18
- Hazard footprint
- 8% of area
- Assets that depend on another layer
- 60%
- Spare capacity (tolerance)
- 30%
Readouts
- Assets hit by the hazard
- 7%
- Assets still working
- 31%
- Amplification of the initial damage
- 9.3 times
- Steps to settle
- 5
Numbers, methods and sources
| Step | Water working (%) | Power working (%) | Telecoms working (%) |
|---|---|---|---|
| 0 | 94 | 94 | 89 |
| 1 | 72 | 72 | 78 |
| 2 | 33 | 61 | 33 |
| 3 | 33 | 50 | 22 |
| 4 | 33 | 44 | 22 |
| 5 | 33 | 39 | 22 |
Methods
- Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
- Overload cascades Motter and Lai (2002), Physical Review E 66
- Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
- Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
- Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
- 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:
- Major roads Natural Earth
- Railways Natural Earth
- Seaports Natural Earth
- Airports Natural Earth
- Urban extents Natural Earth
- Night lights tonight, outages (VIIRS Day/Night Band) NASA/NOAA VIIRS (Suomi NPP) · register nasa.gibs.context-live-layers
- Natural events (NASA EONET) NASA EONET · register nasa.eonet.events
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Development Finance Nexus in Foundry
- Tested at Development Finance Nexus in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Development Finance Nexus in Reports
- Taught in Faculty of Finance and Economics in Academy
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 |
|---|---|---|
| World Bank Private Participation in Infrastructure database | Project-level private commitments in energy, water, transport and digital infrastructure in low and middle income countries | CC BY 4.0 |
| IBNET (World Bank) | Benchmarking indicators for water and sanitation utilities | Terms per database |
| Tracking SDG7 (IEA, IRENA, UN DESA, World Bank, WHO) | Access, clean cooking, renewables, efficiency and international public flows for energy | Free, attribution |
| FAOSTAT and AQUASTAT | Production, prices, food security and irrigation statistics | Free, attribution, FAO terms |
| WRI Aqueduct | Water stress, drought and flood risk layers | CC BY 4.0 |
| IJGlobal transaction database | Project finance transactions with sponsors, lenders, instruments and dates | Proprietary, subscription |
| National energy and water regulators | Tariff decisions, performance and compliance reports | Public records, terms per regulator |
Trace a shock in food, water and energy investment to the balance sheet.
Assembled from the Nexus Standards area profile Disaster and climate risk finance: the shocks it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Pick an initiating shock and step through the cascade to see which exposures it reaches and where losses could concentrate. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise, not a forecast, a valuation, a rating or investment advice. To model a place of your own choosing, open the full System Builder.
Hazards
- Tropical cyclone
- Earthquake
- Ice-jam flood
- 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)
- Aftershock sequence (set off downstream)
- Fault surface rupture (set off downstream)
- Soil liquefaction (set off downstream)
- Slope slide (set off downstream)
- Rockfall (set off downstream)
- Tsunami (set off downstream)
- Building collapse (set off downstream)
Systems and couplings
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-F8Parametric and index-based risk transferNRS-F7Disaster risk finance and pre-arranged financeNRS-H113Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-H114Hazard family: Macroeconomic and fiscal shocks (NHS-1 soc.macro-fiscal)NRS-D1Risk-informed development and project screeningNRS-H28Hazard family: Climate-state shifts (NHS-1 eco.climate-state)
Observation
- ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
- CHIRPS quasi-global gridded precipitation (listed for reference)
- USGS earthquake GeoJSON summary feeds (listed for reference)
- Total public international support for national disaster risk reduction actions (Sendai indicator F-1)
- Direct economic loss attributed to disasters in relation to global GDP
Example geography
- Western Europe: 152 hexagonal cells
- Rain rate, last half hour (IMERG), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
Who decides, and what the evidence serves.
Development Finance 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 |
|---|---|---|
| Energy and water regulators | Whether tariffs and subsidies cover the cost of reliable service | Cost coverage, losses, arrears and service quality records |
| Finance ministries and debt management offices | Whether to support a utility or an offtake agreement with a guarantee | Utility financial evidence, the contingent liability register, the record of similar projects |
| Development finance institutions and project lenders | Whether revenues can withstand drought, price and offtaker shocks at the same time | Correlated scenarios, offtaker payment record, water and price evidence |
| Agriculture ministries and food security programme boards | Which investments in irrigation, storage and markets reduce exposure to the next shock | Yield, price and water evidence with labels, distribution of benefits |
Outputs this topic produces
- Cross-sector dependency maps for water, energy and food portfolios
- Utility financial viability evidence framed for lender review
- Correlated drought and price shock scenarios across a portfolio
- Question sets on offtaker, tariff and subsidy risk
Where exposure in food, water and energy investment travels.
The sectors that carry exposure in food, water and energy investment and how a loss in one passes to the others, across portfolios and public finances.
Signature
Water, Energy and Food
Water gives energy cooling water and hydropower (0.6); 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
- Energy → Infrastructure · power for transport and telecoms0.8
- Water → Energy · cooling water and hydropower0.6
- Water → Food · irrigation0.8
- Infrastructure → Water · pipes, dams and treatment works0.6
What the industry asks.
When essential services fail, everything else follows: health, education, livelihoods and business. Investments in one system affect the others: an irrigation scheme changes water available for towns, a hydropower dam changes river flows for farming, and electricity prices shape the cost of pumping and cold storage. Investment decisions that consider these links reduce the risk of solving one problem by creating another.
- Which essential services are most exposed to climate, hazard and price shocks, and how interdependent are they?
- How do investments in one system affect resource availability and risk in the others?
- Are tariffs and revenues sufficient to operate and maintain services, and who bears the cost when they are not?
- How do investments affect access and affordability for poor households?
What food, water and energy investment means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Transmission channels
How a shock in food, water and energy investment reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
How risk and finance interact.
Essential services are coupled through resources, prices and institutions.
Supply and irrigation
Water investments face competing demands and changing availability. Science: Water Nexus.
Generation and access
Power systems support pumping, processing and storage, and face fuel price and climate risks. Science: Energy Nexus.
Agricultural value chains
Investments in production, storage and markets depend on water and energy. Science: Food Nexus.
A common pattern in essential service investment is the gap between building and operating. New assets are financed, but revenues and budgets do not cover their operation and maintenance, and service quality declines. Evidence that links investment to long-term operating sustainability, including the affordability of tariffs for poor households, gives financiers and governments a more realistic picture of resilience.
How the evidence is built, and its limits.
- 01
Integrated assessment
Linked analysis of water, energy and food systems, drawing on agricultural, soil and food science and engineering. Models depend on behavioural and policy assumptions.
- 02
Utility financial analysis
Assessment of tariffs, costs and financial sustainability of service providers.
- 03
Spatial analysis
Mapping of resources, demand and hazards using geospatial information systems.
- 04
Affordability analysis
Household survey data on spending and access, with limited frequency.
How it is studied, and what the methods cannot say.
- 01Economics and development economicsEconomic appraisal of a project · Debt sustainability context · Tariff and subsidy incidenceApplied here
- 02Agricultural, soil and food scienceIrrigation scheme appraisal · Index insurance and credit designApplied here
- 03Geospatial information systemsSafeguard screening of a project footprint · Physical climate exposure of assetsApplied here
- 04Decision analysis under uncertaintyRobust choice of design standard · Multi-criteria pipeline screeningApplied here
- 05Causal inference and impact evaluationEvaluating a credit line or guarantee · Infrastructure impact on householdsApplied here
Questions and answers.
What is offtaker risk?
Why look at food, water and energy together?
Does the PPI database show how projects performed?
Why consider food, water and energy together?
Are tariffs a resilience issue?
Does GRA recommend utility investments?
How does this relate to the food-system platform at GCRI?
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