The Geo-Informatics and Space Technology Development Agency (GISTDA) has unveiled new satellite data showing significant fluctuations in Thailand’s rainfall and flood patterns over the past four years.
The data highlights the variation in flooded areas, which ranged from just 600,000 rai to more than 5 million rai.
The main factors behind this volatility are the El Niño–La Niña phenomena and the movement of tropical storms. In some years, a single storm has been enough to cause devastating flooding over millions of rai of agricultural land and local communities.
This data not only documents past situations but also serves as a critical warning about the challenges of water management and the increasing need for adaptation to more extreme climate conditions.
The most recent satellite images from GISTDA, taken in September, compared flood-affected areas across the country over the last four years. They clearly show the differences between rainy seasons and the impact of various storms.
Flood-affected areas by year:
In 2022, Thailand experienced the highest level of flooding in four years, with over 5.3 million rai affected. In contrast, 2023 saw the least flooding, with just over 675,000 rai inundated.
However, 2025 has already seen significant flooding, with nearly 5 million rai submerged, driven by the combined effects of various climate events.
El Niño-La Niña and tropical storms
According to GISTDA's analysis, the main factors behind the dramatic fluctuations in Thailand's flood levels are global climate phenomena known as El Niño and La Niña (ENSO), which directly impact rainfall patterns in Southeast Asia.
This data underscores the enormous impact that a single tropical storm, even one that doesn’t make direct landfall in Thailand, can have on the flood situation when combined with the La Niña phenomenon.
Some storms that pass through the South China Sea or neighbouring countries can also bring heavy rainfall to Thailand, further exacerbating the flood risks.
Other key factors
Space-based data has become a crucial tool for forecasting, analysing, and assessing risks. This enables both policy-level and operational agencies to use the information to prepare, reduce loss of life and property, and mitigate economic impacts.