A Reproducible Open-Data Workflow for Identifying Coastal Electrical Infrastructure Exposure to Flood and Coastal Hazards: A Comparative Application in Jamaica and Mozambique
This paper presents a reproducible, open-data geospatial workflow implemented in QGIS to assess coastal electrical infrastructure exposure to flood and coastal hazards, demonstrating its effectiveness through contrasting applications in Jamaica and Mozambique that reveal distinct vulnerability patterns driven by their respective island and deltaic geographies.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Imagine you are a detective trying to find out which parts of a city's power grid are most likely to get soaked when the sky opens up. But here's the twist: you can't use expensive, secret maps, and you can't hire a team of high-tech consultants. You only have a free, open-source map app (called QGIS) and some global data that anyone can download.
That is exactly what this paper does. The authors built a "digital flood detector" to see how much of the electrical infrastructure in two very different places—Jamaica (a small island) and Mozambique (a large country on the African mainland)—is sitting in danger zones. They didn't just guess; they ran a specific, repeatable workflow to find the "wet spots" before the water even arrives.
The Three-Tool Detective Kit
To solve the mystery of "who gets wet," the team used three clever tricks, all free and open:
- The "Blue Spot" Radar: Think of this like finding the lowest points in a bathtub. If you pour water in, where does it pool? The team adapted a method usually used for roads (to see where puddles form) to look at power lines and plants. They looked for "blue spots"—depressions in the ground where water would get stuck and might drown the equipment sitting there. They set a rule: they only counted puddles deeper than 0.3 m and wider than 1,800 m². Anything smaller was too tiny to see with their 30 m resolution map.
- The "Slope & Flow" Scanner: This tool looks at the shape of the land. If you were a raindrop, where would you slide? The team used a "Topographic Convergence Index" (TCI) to guess which areas naturally collect water from uphill. It doesn't predict exactly how deep the flood will be, but it highlights the "soggy zones" where water loves to hang out.
- The "Coastal Hula Hoop": They drew two invisible rings around the entire coastline: one 1 km wide and one 5 km wide. Anything inside these rings is considered at risk from storm surges, salt water, and rising seas.
The Tale of Two Countries
The team tested their kit on two very different characters: Jamaica and Mozambique.
Jamaica: The Island with a Coastal Crowd
Jamaica is a small island where almost everyone has electricity. The team found that the power plants are packed tightly along the coast.
- The Result: A whopping 70% of the power plants are within 5 km of the ocean. Half of them are within just 1 km.
- The Flood Risk: About 51% of the power lines run through areas the scanner marked as "high flood risk" or "blue spots."
- The Catch: The team discovered a major problem with global maps: standard flood maps (like the JRC Global Flood Hazard maps) completely ignore Jamaica because the island is too small for their rules. This means Jamaica is often invisible to big global risk tools, so the team had to build their own "soggy zone" map using the land shape instead.
Mozambique: The Mainland with a Waterlogged Heart
Mozambique is a large country with a lower electrification rate (about 36%). Its power plants are spread out, with many deep in the interior near big rivers, not just on the coast.
- The Result: Only 27% of the power plants are within 5 km of the coast.
- The Flood Risk: Here is the shocker: 83% of the power lines run through "high flood susceptibility" zones. That is much higher than Jamaica!
- The Blue Spots: 59% of the lines cross a "blue spot" depression.
- Why? Mozambique has huge, flat, delta-like areas (like the Zambezi river delta) where water spreads out everywhere. The land shape itself is a giant sponge.
What the Paper Rules Out (The "Not-So-Secret" Secrets)
The authors are very clear about what their map cannot do. They explicitly state that:
- They are not predicting exact flood depths. They aren't saying, "This pole will be underwater by 2 meters." They are saying, "This area looks like a place where water collects."
- They are not seeing tiny puddles. Because their map is 30 m per pixel (like a giant mosaic tile), they can't see small puddles around a single pole or a small substation in a city. If a depression is too small or shallow (less than 0.3 m), their tool misses it.
- They are not using secret data. They didn't use expensive, private flood models or high-tech LiDAR scans. They used only free, global data. This means they might miss some details that a super-precise local map would catch, but they proved you can still get a useful "big picture" without spending a fortune.
- They are not looking at every wire. They only looked at big power plants and high-voltage transmission lines. They didn't (and couldn't) map the tiny wires that go to individual houses because that data isn't available for free.
How Sure Are They?
The authors are very confident in their method but humble about the precision.
- Proven: They proved that their workflow works. They ran the exact same steps on two totally different countries and got results that made perfect sense for each place (Jamaica's coastal plants vs. Mozambique's inland flood lines).
- Suggested: They suggest that this "low-cost" map is a great first step. It's like a smoke alarm: it tells you where to look closer. They argue that once you find these "high risk" zones, you should go there with expensive, high-resolution tools (like LiDAR) to get the real details.
- Measured: They measured the exposure percentages exactly as listed above (e.g., 70%, 83%, 51%). These numbers are based on the data they had, which they admit is incomplete for some areas (like missing some small power plants in Mozambique).
The Big Takeaway
This paper is a playbook for countries that can't afford expensive consultants. It shows that you can use free tools to find the "wet spots" on your power grid.
The main finding is that geography is destiny. In Jamaica, the danger is the ocean (coastal exposure). In Mozambique, the danger is the flat, swampy land (inland flood exposure). But in both places, the power lines are running right through the danger zones.
The authors aren't saying the problem is solved. They are saying, "Here is a free, reproducible way to find the biggest risks so you can stop guessing and start fixing." They suggest that if you want to protect your power grid, you need to know where the water wants to go, and this workflow is a great, low-cost way to find out.
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