2025: Asia’s Flood Reality, in Numbers

In late 2025, Asia’s flood problem stopped being a “future climate scenario” and became a documented, quantified disaster:

• A tropical storm system in Southeast Asia killed more than 600 people and affected over 4 million across Indonesia, Thailand, and Malaysia.

• Follow-up coverage showed the death toll in Southeast Asia nearing 800 deaths, with over 600 in Indonesia alone after floods and landslides, plus heavy casualties in southern Thailand.

• Indonesia later reported 1,000 deaths and close to 1 million displaced from rains and floods, explicitly linking impacts to climate change and ecosystem decline.

• A regional analysis estimated at least 1,250 deaths across Asia from 2025 floods, calling for accountability and adaptation, not just recovery.

• The World Meteorological Organization (WMO) highlighted that recent “devastating rainfall in Asia” underlines Asia’s high vulnerability to floods and the need for better early-warning services.

• A 2025 ASEAN trend report shows hydro-meteorological disasters (floods, storms, landslides) remain the dominant risk in Southeast Asia’s disaster profile.

This isn’t “maybe one day”. 2025 data already proves that Asia’s current infrastructure + data stack = not enough.

The Core Problem: Floods Are Local, Data Is Not

Research and official bulletins point to three structural issues:

1. Extreme rainfall is intensifying. WMO’s State of the Climate work and its 2025 Asia rainfall bulletin highlight how warmer air is holding more moisture, leading to heavier downpours and more frequent severe flood events across Asia.

2. Forecasts are improving at the macro level, but not at the neighborhood level. ASEAN’s 25th Climate Outlook Forum (ASEANCOF-25) predicts near- to above-normal rainfall in many parts of the Maritime Continent for winter 2025/2026, with above-average tropical cyclone activity near the Philippines — but these are seasonal outlooks, not street-level tools.

3. Flood risk in countries like Thailand is structurally rising. Krungsri Research (Thailand) estimates that flood risks will continue to increase through 2025, with particularly high risk in September–October, and notes the economic impact on manufacturing, agriculture, and logistics.

So we have regional forecasts and macro reports……but floods in 2025 were triggered by block-level phenomena:

• a single hillside that fails,

• a drain clogged on one street,

• a hyper-local cloudburst that never appears in a sparse station network.

That’s the gap: APAC has climate reports, but not enough real-time, hyper-local sensors.

Why Centralized Infrastructure Can’t Fix This Alone

You don’t need me to tell you government infra is slow — you can see it in the funding data:

• The Asian Development Bank estimates that from 2025 to 2040, Asia needs about $4 trillion (≈$250B per year) for water and sanitation infrastructure, but there’s a $150B annual investment gap already.

When there’s a $150B/year hole just for water/sanitation, “thousands of new high-grade weather and GNSS stations everywhere” is simply not happening through classical capex.

Add the usual friction:

• slow procurement cycles,

• siloed agencies (meteorology, disaster management, urban drainage),

• constrained O&M budgets for sensor maintenance,

• limited coverage in rural, mountainous, or informal urban areas.

That’s why “just let the government deploy more stations” is not a realistic 2025–2030 plan for APAC.

This is exactly the kind of problem DePIN infra is built for: lots of small, distributed devices that need to exist in many places quickly, with shared upside.

WeatherXM — Hyper-Local Weather, Owned and Deployed by the Community

WeatherXM is a DePIN network of physical weather stations that collect hyper-local weather data (rainfall, wind, temperature, humidity, pressure, etc.) and reward station operators in $WXM tokens.

As of 2025, multiple independent sources confirm:

• WeatherXM is a decentralized weather network collecting hyper-local data, with over 5,000 weather stations in 80+ countries.

  • Gate.io (2025): “What is WXM: Understanding the Key Features and Benefits of WeatherXM”

  • SwissBorg Academy (2024 but cited in 2025 context): “What is WeatherXM (WXM)?”

• A 2025 DePINScan article notes WeatherXM has already deployed around 7,000 stations in just two years, emphasizing its ability to scale faster than traditional networks.

  • DePINScan, Jan 2 2025: “WeatherXM: Disrupting the Weather Data Industry in 2025”

  • W3bstream metrics (2025): “WeatherXM’s Ambitious Roadmap for 2025”

• A 2025 product overview mentions WeatherXM stations leveraging a network of over 5,000 stations worldwide to support business decision-making.

  • WeatherXM Datasheet (July 2025): “Weather Stations Overview”

Why this matters for APAC floods

Analytical, based on the data above:

• Government networks give you tens to hundreds of stations per country.

• WeatherXM’s model can give you hundreds to thousands, by making local operators the deployment engine.

• Stations can be targeted to underserved regions (Global South rollout plans explicitly mention this).

For APAC, the implication is straightforward: if you want street-level rainfall and micro-climate data quickly, there is no centralized model that can match this deployment curve per dollar.

GEODNET — The Positioning Layer for Flood Mapping, Drones, and Robotics

GEODNET is a DePIN network of GNSS base stations providing Real-Time Kinematic (RTK) corrections for centimeter-accurate positioning.

• The GEODNET docs describe it as a web3-based RTK network providing precise real-time positioning data using DePIN principles.

  • GEODNET Docs Center:https://docs.geodnet.com/

• The project positions itself publicly as “the world’s largest Web3 blockchain-based precise positioning network” powering robotics and earning GEOD tokens.

  • GEODNET GitHub description:https://github.com/geodnet

• A 2024 Inside GNSS article explains how GEODNET’s decentralized base station approach is scaling GNSS correction network density and coverage globally.

• GEODNET delivers high-precision GNSS corrections suitable for drones, surveying, and robotics.

• It uses a DePIN model to crowdsource station deployment.

Why this matters for floods

Flood modeling and response need:

• updated elevation and terrain maps;

• drones that can safely fly and map disaster zones;

• robots and vehicles that can navigate partially destroyed infrastructure.

Without centimeter-level reference points, your maps and drone imagery are approximate. With GEODNET’s RTK corrections, you can:

• improve the accuracy of digital elevation models;

• stitch post-flood aerial imagery more precisely;

• support autonomous systems in disaster zones.

So the stack becomes:

That’s the combination APAC doesn’t have today at scale.

What Needs to Happen (2025–2030) for DePIN to Actually Matter in APAC Floods

1. Targeted WeatherXM saturation in the most at-risk basins and urban corridors (Mekong, Chao Phraya, Red River, Java/Sumatra corridors, Manila/Philippines archipelago).

2. GEODNET deployment in hydrologically important areas to support drones, modeling, and robotics.

3. Formal APIs and MoUs with at least a few pioneering agencies (a single forward-thinking disaster office in Vietnam or Indonesia is worth more than 50 loose integrations).

4. Structured incentives via SHIFT to keep high-value stations running for multiple years, not months.

5. Cross-border datasets that treat river basins and storm paths as one system, not fragmented by politics.