Qanats: discovering underground water systems through AI

Today, MSCA postdoctoral fellow Dr. Nazarij Buławka presented in the Tarragona high-school “Pons d’Icart”. The lecture aimed to introduce participants to qanats, sustainable water systems, artificial intelligence in archaeology and to present another point of view of archaeological work, in the context of his MSCA project “UnderTheSands. Ancient irrigation detection and analysis using Advanced remote sensing methods“.

Abstract

Qanats: discovering underground water systems through artificial intelligence

Qanats, also known in Morroco as khettara, are ancient water systems. They use underground channels to transport water from the mountains or underground sources to the cities and agricultural fields. Qanat systems have a rich and fascinating history. They are also listed on UNESCO World Heritage.

Qanats are known by various names in different parts of the world, such as qanat, karez, kārīz, aflaj, foggara, khettara, surangam, and dhwawi. From Chile in the west and western China in the east, these water systems are renowned globally, including Spain and Morroco.

The qanat systems are visible from the surface as lines of holes (shafts) used for ventilation and cleaning. That also allows us to map them using field and remote methods by engineers and archaeologists. Nowadays, mapping can be conducted with the help of artificial intelligence.

A method of detecting qanats on satellite images using artificial intelligence is being developed by the UnderTheSands project, which is led in Tarragona. In this project, we are using an artificial intelligence method – deep learning for image recognition. This approach involves creating neural networks inspired by the way the human brain works. These neural networks are designed to recognise patterns in images, such as distinguishing between cats and dogs. To use this method in archaeology, we specially trained neural networks using images of qanats.


Funded by the European Union (Under The Sands; MSCA-IF-101062705). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

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