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Using ancient satellites, scientists have made an incredible discovery: underground aqueducts over 3.000 years old have been revealed
Scientists have used an unlikely tool to locate aqueducts underground over 3.000 years old: American satellites from the Cold War era. A team of researchers in Spain, led by Catalan Institute of Classical Archaeology, is taking advantage of satellite images from the series HEXAGON, known as Big Bird, to improve the detection of ancient underground irrigation systems, known as qanats, in arid regions of the Middle East and North Africa.
These underground aqueducts, essential for the distribution of water in environments desert, are formed by a series of regularly spaced ventilation shafts, which makes them visible in aerial images.
To improve the accuracy of identifying these underground aqueducts, the team of researchers developed a machine learning model that combines images captured by the HEXAGON satellites with images generated by artificial intelligence (AI).
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What are Qanats?
Qanats are underground canal systems designed to transport water from highland or mountainous areas to more arid regions.
These systems allowed ancient civilizations to flourish in areas where water would otherwise be scarce. Originating around 3.000 years ago, many qanats are still in use today. They represent an impressive technological advance for the time, being built based on hydraulic and geological principles that guaranteed a constant flow of water without the use of pumps.
The innovation of qanats lies in their simplicity and efficiency. Vertical shafts dug along the canal route provide ventilation and access for maintenance, while the underground tunnel transports fresh water to areas where it would be impossible to live without this source of irrigation.
In some places, such as Iran, these systems were so important that some were included on the UNESCO World Heritage list, recognizing their historical and cultural value.
Reusing Cold War satellites to find underground aqueducts
The HEXAGON satellites, built by Lockheed Corp. and used by the United States between 1971 and 1986, were originally designed for reconnaissance missions during the Cold War.
These satellites were equipped with two high-resolution film cameras that produced stereo images. Capable of capturing objects smaller than two feet wide from an altitude of 100 miles, the satellites captured detailed images of 877 million square miles of Earth's surface.
These images, despite their age, remain a valuable source of data. By feeding these images into a machine learning model, the Spanish research team was able to improve the detection of qanats, which appear as rows of circular ventilation shafts when viewed from above.
By combining real images with AI-generated images, the model was able to generalize the representation of qanats across different landscapes, resulting in an 88% success rate in identifying underground systems.
Application of the model in different regions
To demonstrate the effectiveness of the model, the team chose three regions known for their ancient qanat systems: Maiwand in Afghanistan; the Gorgan Plain in Iran; and an area west of Rissani in Morocco.
These areas feature diverse landscapes, from arid deserts to mountainous plains, making them ideal for testing the model’s ability to identify qanats in different types of terrain.
By analyzing satellite and AI imagery, the model was trained to recognize the lines of ventilation shafts that indicate the presence of qanats. These access shafts, used for both ventilation and maintenance, are essential to the functioning of underground systems and are one of the main indicators of the presence of a qanat.
Combining real and AI-generated data allowed the model to eliminate most false positives, making the identification process more efficient.
Historical and future importance of qanats
Qanats represent one of the greatest feats of hydraulic engineering in the ancient world. Their importance goes beyond distributing water; they enabled the development of cities and settlements in inhospitable regions, changing the course of history in areas such as the Middle East and North Africa.
The Spanish team's study not only helps identify these ancient systems, but also provides a new tool for archaeologists and historians to study the expansion and impact of ancient civilizations in arid regions.
The reuse of Cold War technologies, such as the HEXAGON satellites, to study 3.000-year-old structures demonstrates how modern science can offer new insights into the past.
Furthermore, the application of this model in different regions may open doors to the identification of other qanat systems that have not yet been mapped, providing valuable information on the history of water use in arid regions.
This knowledge could be crucial to addressing modern challenges related to water scarcity, especially in areas that still rely on traditional irrigation systems.
The discovery and mapping of qanats using Cold War satellites and artificial intelligence represents a significant advance in the field of archaeology. By combining historical imagery with modern technologies, the team of Spanish researchers has managed to develop an effective model for identifying these ancient systems in different landscapes.
This study not only sheds light on the past, but may also provide solutions to current problems related to sustainable water use in arid regions.
