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Study Finds Global Slowdown in Urban Land Subsidence

| Source: ANTARA_ID Translated from Indonesian | Infrastructure
Study Finds Global Slowdown in Urban Land Subsidence
Image: ANTARA_ID

Beijing (ANTARA) — Global urban land subsidence varies considerably, but has generally slowed in recent years, according to a study by a Chinese research team published on 12 October in the journal Nature Cities.

Researchers from Peking University, South China Normal University and other institutions systematically assessed subsidence between 2014 and 2023 in 465 cities worldwide, each with a population of more than one million.

Land subsidence is a global problem that poses major challenges to the safety of urban infrastructure and sustainable development.

According to the study, the most severe subsidence occurred in Southeast Asia, West-Central Asia and North America. Cities cited as examples include Mexico City and Toluca in Mexico, and Medan and Bandung in Indonesia. Mexico City recorded the most intense local subsidence, at a rate exceeding 0.2 metres a year.

Although subsidence remains widespread, global urban subsidence has generally slowed in recent years. The research team detected a significant slowdown in many cities in Southeast and East Asia.

This suggests that water allocation and groundwater-management measures in the two regions have been effective, said Hu Xie, a member of the research team at Peking University.

“In particular, in China’s Beijing-Tianjin-Hebei urban agglomeration, large-scale water-diversion projects such as the South-to-North Water Diversion Project, together with stronger groundwater management, have helped replenish groundwater in some areas, significantly reducing subsidence,” Hu said.

The team also developed an open platform for global urban land subsidence, offering the public a searchable dataset in a visual format.

As geological and groundwater big data accumulate and artificial intelligence (AI) and complex models advance, analyses of the causes of subsidence and risk assessments will have a stronger data and methodological foundation, said Tao Shengli, a researcher at Peking University.

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