Temporal-Spatial changes of monthly vegetation growth and their driving forces in the ancient Yellow river irrigation system, China

Kailong Li, Guohe Huang (Corresponding Author), Xiaoyue Zhang, Chen Lu, Shuo Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)


Irrigation systems play vital roles not only in food production but also in supporting ecosystems. Understanding how the ecosystem has evolved in response to human activities is crucial for sustainable food production, especially for arid and semi-arid regions. In this study, we examined the trends of vegetation growth on a monthly basis in the ancient Yellow River irrigation system in Ningxia, China. We used the leaf area index (LAI) to characterize the vegetation growth from 2007 to 2019. The LAI trends were associated with a series of driving forces, explaining the spatial and temporal change of vegetation growth. With the provision of the Wilks feature importance method, 2-month averaged air temperature and irrigation were identified as the two most important variables for monthly LAI simulation. Future climate projections based on the Regional Climate Model system (RegCM) suggested dryer and longer summers under the RCP 8.5 scenario. These changes will increase the crop water demand during the growing months. In the future, water conflict might be further intensified in May, in which the present irrigation water has already led to a decreased crop growth. Our findings demonstrated that the Mann Kendall monthly trend analysis could provide more helpful information for monitoring the vegetation growth than the trend analysis on a yearly and seasonal basis.

Original languageEnglish
Article number103911
JournalJournal of Contaminant Hydrology
Publication statusPublished - Dec 2021


  • Leaf area index
  • Mann Kendall trend analysis
  • Reginal climate model projection
  • Stepwise clustered analysis

ASJC Scopus subject areas

  • Environmental Chemistry
  • Water Science and Technology


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