Search

Understanding the impact of water availability on vegetation growth in the context of climate change is crucial for assessing the resilience of vegetation to environmental shifts. In this study, the relationship between vegetation growth and water availability was studied using a variety of indicators. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and Solar-Induced Chlorophyll Fluorescence (SIF) were utilized as vegetation growth indicators, while the standardized precipitation evapotranspiration index (SPEI) and soil moisture indicators served as water use indices. To investigate the vegetation response to water deficit in the Loess Plateau during the growing season from 2000 to 2020, Spearman's rank correlation coefficients were calculated using a 5-year sliding window approach. The spatial and temporal heterogeneity of vegetation response to water deficit during the growing seasons were also explored. The results showed that: (1) with the improvement of moisture conditions, vegetation growth recovered significantly, and there was no expansion trend for vegetation water deficit. (2) The most sensitive timescale of vegetation to water deficit was 6–8 months; the response degree and sensitivity of vegetation to water surplus and deficit were the highest from June to August; and broadleaved forest was the vegetation type most sensitive to water deficit in the early growing season, while grass was the vegetation type most sensitive to water deficit during the mid and late growing seasons. (3) Soil moisture emerged as the dominant factor influencing vegetation growth in the Loess Plateau, followed by precipitation, albeit to a lesser extent. These findings contribute to understanding the mechanism and characteristics of the response of vegetation to climate fluctuations induced by global climate change. [ABSTRACT FROM AUTHOR]

As the most frequent and longest-lasting climate-related disasters, droughts are complex processes caused by hydrological imbalance, and have significant effects on ecosystem function and socioeconomic development. However, most conventional satellite-based drought indices and combined drought indices are mechanically constrained by the fact that they were developed and evaluated for a specific climate or critical ecological region, especially in China. A comprehensive drought index should be developed for extensive application in different climate-hydrology regions. To address this problem, an optimised principal component analysis method (PCA-RF) was proposed to support drought assessment across the transitional area between the humid and arid regions in central China, including the Loess Plateau (LP) and Qinling Mountains (QL). This method eliminated the causal relationships of non-linear changes for multi-aspect parameters such as land surface temperature, precipitation and soil moisture, and was used in developing a new index named "Meteorological drought index by PCA-RF methods (PMDI)". The results showed that PMDI had higher correlations and lower root mean square error than other drought indices (established using the empirical-weights method) with the 1-month standardized precipitation evapotranspiration index (SPEI-1). That means PMDI performed well in meteorological drought monitoring. Additionally, the normalized difference vegetation index (NDVI) and solar-induced chlorophyll fluorescence (SIF) were utilised to evaluate PMDI effectiveness in detecting vegetation response to drought, which represents agricultural drought. The results indicated that correlations between PMDI and vegetation indices (VIs) were stronger when severe or extreme droughts occurred, and that their relationships were affected by the high spatiotemporal heterogeneity in vegetation change over the LP and QL. Overall, PMDI was shown here to be a very suitable index for monitoring meteorological drought (short-term) and has effective action in capturing the response of vegetation signals to agriculture drought events (long-term). Given the excellent performance of PMDI in diverse climate-hydrology conditions of our study regions, we concluded that the PMDI has considerable potential as a drought monitoring methodology on a larger spatial scale. • A new drought index was developed (PMDI), which integrated multiple sources of information describing different aspects. • PMDI performed well in different climate-hydrology regions for short- and long-term drought monitoring. • PMDI has reasonably good potential applicability in drought monitoring on a larger spatial scale. [ABSTRACT FROM AUTHOR]