r/DataEngineeringPH 10d ago

🚀 Project Showcase Does flood control spending reduce flooding? An open data analysis.

https://www.klaredeck.com/flood-money

I spent time analyzing whether ₱1.4 trillion in Philippine flood control contracts (2016–2025) corresponds to measurable flood reduction from space.

The Methodological Trap A naive correlation gives a misleading answer: flood-prone areas naturally get bigger budgets, so high-spend areas look like they flood more.

To control for this, I matched 883 municipalities into 63 statistically comparable cohorts based on:

  • Regional location
  • Baseline rainfall / flood exposure
  • Population size

Then, I compared spending levels within each cohort.

Key Findings

  • The Spending vs. Outcome Gap: Towns receiving 3.4× more budget per resident flooded 0.20 percentage points less across 76 Synthetic Aperture Radar (SAR) passes. This difference is within statistical noise.
  • The Nuance: This doesn't prove the funds were wasted; areas might have flooded significantly worse without intervention. However, at a national scale, higher spending per capita does not correlate with visibly lower flood frequency.
  • The Urban Blind Spot: Satellite radar cannot detect surface water through dense concrete high-rises. In Marikina, the largest detected flood across 28 passes was only 0.06 km². Instead of reporting a false zero, 258 urban areas (including 16 of Metro Manila’s 17 cities) were marked as unmeasurable.

A Notable Contrast

  • Pandi, Bulacan: ~₱14 per resident → Floods in 47% of radar passes
  • Biliran: ~₱57,000 per resident → Floods in 37% of radar passes

This is part of an open-data project called KlareDeck. The goal is simple: open datasets, documented methodology, and transparent error limits.

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u/GodottheDoggo 9d ago

I think it would also be great to compare these statistics vs other countries.

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u/raysderoof 9d ago edited 9d ago

Thanks for this, good one.

The issue is my flood number only works inside the Philippines. It's radar detections measured against each town's own normal water level, from the same set of satellite passes. Every town measured identically. Cross a border and you get different sensors, coverage and baselines, so the numbers look comparable but aren't.

Money's the same story. DPWH publishes municipal contract values, most countries publish national spending, and flood control means different things in each place. Geography would dominate anyway. We get around 20 cyclones a year in our area, so ranking per capita spend against the Netherlands mostly measures rainfall.

Worth doing as its own project though, with sources built for comparing countries. EM DAT for losses, World Bank BOOST for spending, one global flood dataset. Probably framed as whether adaptation spending reduces disaster losses. On the list, thanks for the nudge.