Characterizing Drought Patterns and Vegetation Responses in Northeast China: A Multi-Temporal-Scale Analysis Using the SPI and NDVI

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Abstract

Drought significantly reduces global agricultural productivity and destabilizes ecosystems. As the primary grain-producing region and a key ecological buffer zone in China, Northeast China is experiencing intensifying drought stress. However, the regional-scale characteristics of refined drought and the impact mechanisms on different types of vegetation in the Northeast are rarely investigated. In this study, we analyzed the spatial and temporal characteristics of drought over 30-, 60-, 90-, 180-, 270-, and 360-day time scales in Northeast China using the Standardized Precipitation Index (SPI) based on high-precision daily precipitation data simulated by CLM3.5 from 2008 to 2023. Additionally, we used the MODIS Normalized Difference Vegetation Index (NDVI) to elucidate the response of vegetation to drought across different land use types. The results showed that SPI-30 was the most sensitive for drought detection, and there was a clear trend of drought aggravation in the northern part of the Northeast region. The strongest correlation between vegetation and drought was found in September. A significant lag in the response of vegetation to drought was observed in May, June, July, and August, with the best correlation observed at a one-month lag. In addition, the degree of response to drought varies among different types of vegetation. Grasslands are the most sensitive to drought, while woodlands and wetlands have a weaker response. This study provides a reference for assessing the dynamics of refined climates at different spatial and temporal scales and offers actionable insights for ecosystem management in climate-sensitive agricultural regions.

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Zhang, Y., Liu, Y., Chen, L., Sun, J., Sun, Y., Peng, C., … Wu, Y. (2025). Characterizing Drought Patterns and Vegetation Responses in Northeast China: A Multi-Temporal-Scale Analysis Using the SPI and NDVI. Sustainability (Switzerland), 17(12). https://doi.org/10.3390/su17125288

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