Research & Data
The public datasets, institutional sources, and analytical evidence behind Amman Water Intelligence.
The project combines urban-development evidence, water-risk data, climate context, and Jordan-specific system evidence, while preserving each source's own geographic limitations rather than flattening them into a single false resolution.
Five core research sources
Each source is used only for what it can responsibly support. Where a dataset has a boundary — spatial resolution, time period, or scope — that boundary is stated alongside it.
- Historical population and built-up evidence.
- Supports comparison of development pressure across standardized study zones.
- Does not directly measure real-estate investment or water-service performance.
- Underlying water-risk context.
- Baseline period: 1979–2019.
- 2030 BAU future conditions use a 2015–2045 chronic-period median across five climate models.
- Operates at a broader spatial resolution — not presented as neighborhood-level utility data.
- Rainfall context.
- Annual Africa dataset, 1981–2025.
- 0.05° grid cells, area-weighted to each 2 km study buffer.
- Rainfall change is context — not a measure of municipal water-supply performance.
- National and system-level water context.
- Used as policy and system background, not as neighborhood-level measurement.
- Amman system context.
- System-level operational evidence only.
- Does not provide comparable neighborhood-level performance across all eight pilot locations.
From independent sources to one screening framework
Each dataset feeds a distinct piece of context. Not every dataset operates at the same geographic resolution — that distinction is kept visible through the integration step, not resolved away.
Integrated Screening Framework
Not every dataset operates at the same geographic resolution — the framework combines them without pretending otherwise.
Not every input measures at the same scale
Mixing resolutions without labeling them is how screening tools quietly turn into false precision. This project keeps the resolution of every input visible instead.
Development-pressure indicators (GHSL) are compared across the eight standardized 2 km study zones.
Water-risk and rainfall datasets (Aqueduct, CHIRPS) operate at a broader spatial resolution than the pilot zones.
National and utility evidence (National Water Strategy, Miyahuna) is system-level, not neighborhood-level.
- The eight pilot areas use identical 2 km study zones.
- Development indicators can be compared across those standardized zones.
- Water-risk datasets may operate at broader basin or grid resolution.
- System-wide statistics are not converted into fake neighborhood precision.
- Resolution labels stay visible instead of implying all inputs are building-level measurements.
Every calculation traces back to its source input
The underlying project workbooks retain the full working, not just the final scores. The research was structured so any figure can be traced back to where it came from.
Five phases, one question at a time
Proof of Concept
Can public evidence support a meaningful Amman water-development comparison?
Development Pressure
Where has development grown, and where is it projected to grow?
Underlying Water Risk
What water-stress and rainfall context surrounds each zone?
Integration
Where do development momentum and water constraint overlap?
Communication
Which findings are robust enough to present and use as a screening tool?
What this research supports — and does not
- Compare standardized 2 km development-pressure zones.
- Prioritize locations for deeper investigation.
- Explain the interaction between urban growth and water constraint.
- Test whether conclusions change under alternative weighting rules.
- Predicting household or building outage frequency.
- Claiming neighborhood pipe pressure without network data.
- Treating rainfall change as municipal water availability.
- Calling lower-ranked locations water safe.
- Making a property investment recommendation from the screen alone.