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<p>Amid intensifying climate change and human activities, coordinating Urbanization Level (UL) and Water Ecosystem Services (WES) is essential for sustainability in arid regions. Using multi-source remote sensing and socioeconomic data, this study establishes an integrated evaluation framework and applies spatial statistics, a coupling coordination degree (CCD) model, and the XGBoost-SHAP method to examine the spatiotemporal dynamics, coordination patterns, and driving mechanisms of UL and WES in Central Asia from 2000 to 2020. Results show that: (1) UL increased markedly, with high values concentrated in piedmont oases and major urban clusters, while WES declined overall, manifested as reduced water yield and soil retention upstream and increased nitrogen export and food provision in mid- and downstream areas. (2) LISA clustering reveals a clear interaction pattern, with High–High (HH) clusters in midstream urban agglomerations (~ 5%), High–Low (HL) types in downstream conflict zones (~ 1%), and Low–High (LH) types in upstream water-source areas (~ 7%), forming an “upstream LH–midstream HH–downstream HL” gradient. (3) The coupling relationship shifted from relative coordination in upper–middle reaches to severe uncoordination downstream; coordinated areas decreased sharply from 64% to 12%, while uncoordinated areas expanded from 5% to 39%. (4) UL was mainly driven by anthropogenic factors (GDPD, PD, NL, LUI), whereas WES was influenced by both natural factors (PRE, NDVI, PET) and human activities, with Land Use Intensity (LUI) serving as a key common driver linking both systems.</p>

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Coupling Coordination between Urbanization and Water Ecosystem Services in Central Asia and its Driving Mechanisms

  • 期刊论文

  • 发表日期：

    2026年2月23日

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  • Shoufeng Wang,
  • Jia He,
  • Yuxuan Zhou

摘要

Amid intensifying climate change and human activities, coordinating Urbanization Level (UL) and Water Ecosystem Services (WES) is essential for sustainability in arid regions. Using multi-source remote sensing and socioeconomic data, this study establishes an integrated evaluation framework and applies spatial statistics, a coupling coordination degree (CCD) model, and the XGBoost-SHAP method to examine the spatiotemporal dynamics, coordination patterns, and driving mechanisms of UL and WES in Central Asia from 2000 to 2020. Results show that: (1) UL increased markedly, with high values concentrated in piedmont oases and major urban clusters, while WES declined overall, manifested as reduced water yield and soil retention upstream and increased nitrogen export and food provision in mid- and downstream areas. (2) LISA clustering reveals a clear interaction pattern, with High–High (HH) clusters in midstream urban agglomerations (~ 5%), High–Low (HL) types in downstream conflict zones (~ 1%), and Low–High (LH) types in upstream water-source areas (~ 7%), forming an “upstream LH–midstream HH–downstream HL” gradient. (3) The coupling relationship shifted from relative coordination in upper–middle reaches to severe uncoordination downstream; coordinated areas decreased sharply from 64% to 12%, while uncoordinated areas expanded from 5% to 39%. (4) UL was mainly driven by anthropogenic factors (GDPD, PD, NL, LUI), whereas WES was influenced by both natural factors (PRE, NDVI, PET) and human activities, with Land Use Intensity (LUI) serving as a key common driver linking both systems.