Irrigation scheme appraisal
Crop water requirements, soil suitability and yield response are combined with water availability to test whether a scheme's projected yields and incomes hold under dry years.
GRA · Development Finance Nexus
Spatial financeWhere capital meets hazard, exposure and transition
Agricultural, soil and food science inform development finance for farming, irrigation, agribusiness and food security. They explain how weather, soils, pests and markets shape yields and incomes, and so the repayment capacity of farmers, the viability of irrigation schemes and the design of crop insurance.
Agricultural science studies crop and livestock production, soil processes and food systems. It explains how weather, pests, soil degradation and markets combine to affect yields and food availability. In development finance, critical infrastructure and economic development, agricultural assessment supports early warning of food shortages, crop insurance design and adaptation planning. It connects climate, water and trade risks to nutrition and price stability. The canonical description is on the STEM Commons.
Crop water requirements, soil suitability and yield response are combined with water availability to test whether a scheme's projected yields and incomes hold under dry years.
Yield records and satellite vegetation indices are used to design indices for agricultural insurance and to check basis risk, the gap between index payouts and farmers' actual losses.
Soil surveys and erosion assessments identify where land degradation threatens yields and where restoration belongs in a project's design and safeguards.
How a dry season is read against the point where drought cover starts to pay. Synthetic season and design terms.
Datasets and records used by agricultural, soil and food 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 |
|---|---|---|
| Agricultural census and yield statistics | Baseline production and yields | Published statistics |
| Satellite vegetation indices | Crop condition and index design | MODELLED |
| Soil surveys | Suitability and degradation | OBSERVED |
| Weather station records | Crop model forcing and index triggers | OBSERVED |
| FAOSTAT prices and trade | Market context for incomes | Published statistics |
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Development finance · Agricultural science · Run R-2474
red: result above guideline
| S-37 | Projects | 10.7 | 7 | Above |
| S-37 | Safeguard | 8.9 | 9 | Near |
| S-18 | Disbursement | 1.4 | 8 | Near |
| S-36 | Adaptation | 1.6 | 9 | Below |
Crop models are compared with observed yields across sites and seasons. Replicated field trials and multi-model intercomparisons test robustness.
| Check | How it is done |
|---|---|
| Crop model comparison | Simulated yields are compared with observed yields across sites and seasons before use in appraisal |
| Basis risk testing | Index payouts are compared with recorded farm losses in past seasons |
| Smallholder representation | Data are checked for coverage of smallholder systems before conclusions are drawn for them |
Models often omit management practices, pests and extreme events that drive actual losses. Smallholder systems are underrepresented in data.
How much output, and so revenue, is lost beyond the sector hit first, the indirect exposure a lender or investor carries through suppliers and customers. 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
Readouts
| Sector | Peak inoperability (%) | Output weight (%) |
|---|---|---|
| Farming | 30.73 | 17.2 |
| Fertiliser and inputs | 2.21 | 15.3 |
| Food processing | 2.87 | 23.4 |
| Transport | 2.73 | 13.4 |
| Wholesale and retail | 1.09 | 21.5 |
| Energy | 1.48 | 9.2 |
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:
Across the six pillars, led by Nexus Consortium
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
Systems and couplings
Controls
NS-0 Constitution and principlesNS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9 Contextual UNIs (deployments, instances, programme instances)NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14 Conformance and crosswalk to external standardsNRS-F8 Parametric and index-based risk transferNRS-F7 Disaster risk finance and pre-arranged financeNRS-H113 Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-H114 Hazard family: Macroeconomic and fiscal shocks (NHS-1 soc.macro-fiscal)NRS-D1 Risk-informed development and project screeningNRS-H28 Hazard family: Climate-state shifts (NHS-1 eco.climate-state)Observation
Example geography
Food Nexus stewards agricultural, soil and food science for the Consortium and reviews how it is applied across platforms.
The sectors that carry exposure in agricultural science for development finance and how a loss in one passes to the others, across portfolios and public finances.
Signature
Food and its partners
Food gives nutrition to health (0.7), land conversion to biodiversity (0.6) and withdrawals and runoff to water (0.3).
W · E · I · F · H · B
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.
How a shock in agricultural science for development finance reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
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