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March 10, 2026Scientific Reports1 citationsOpen Access

Identifying time-lag effects of temperature and precipitation on vegetation growth variation in the lower Yellow River of east China

XLXinying LüXYXiao YanYDYifang DUAN

Key Points

  • This research aims to identify how temperature and precipitation variations cause delays in vegetation growth responses along the lower Yellow River.
  • Analyzed MODIS NDVI remote sensing data from 2001 to 2021
  • Employed simple and partial correlation analysis
  • Used multiple regression to assess climate responses
  • Conducted grid-based assessments of vegetation growth
  • NDVI shows a one to two-month lag for temperature response
  • NDVI shows a one to three-month lag for precipitation response
  • NDVI is negatively correlated with temperature and positively with precipitation
  • Cultivated vegetation and coniferous forests demonstrate significant climate response
  • Time-lag effects increase capacity of climate variables to explain vegetation dynamics by 128.98%

Abstract

Addressing the backdrop of global climatic changes and focusing on how vegetation reacts to these shifts,this article acting a imperative significant.This article investigates the administrative jurisdictions in the eastern of lower of the Yellow River.It selects MODIS NDVI remote sensing data spanning from 2001 to 2021 and employs different analysis methods including simple correlation, partial correlation, and multiple regression to quantitatively assess the response of NDVI during the vegetation growth season to climate variations, analyzing it on a grid by grid basis within the research region. Studies have found that: (1) the NDVI’s responsiveness to temperature and precipitation during the peak growth season exhibited a certain delay; A temperature response lag showed one or two months, while a precipitation response lag showed one or three months.(2) Partial correlation analysis demonstrated that NDVI was negatively correlated with temperature, while NDVI was positively correlated precipitation. Moreover, during the growing season, NDVI across various vegetation types revealed a stronger association with precipitation compared to temperature.(3) The cultivated vegetation, coniferous forest, and swamp vegetation exhibit significant responses to climatic changes.(4) When accounting for time-lag effects, it has increased by 128.98% for the capacity of climate variables to interpret vegetation dynamics compared to simultaneous assessments.

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Cite This Study

Lü et al. (2026) studied this question.

synapsesocial.com/papers/69af949670916d39fea4b9dahttps://doi.org/10.1038/s41598-026-41853-0
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