Spatio-Temporal Characteristics and Trend Analysis of Grassland Ecosystem Drought in Asia From 2010 to 2018

Abstract

Under the background of global climate change, the impact from drought on the ecosystem exhibits the characteristics of complexity and multi-process, especially for the main component, which is the grassland ecosystem of the overall ecosystem. Identifying past droughts and predicting future ones is vital in limiting their effects. However, the random and non-linear nature of drought variables makes accurate drought prediction still a challenging scientific problem. In this study, the boundaries, Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) of Asian Grassland Ecosystem (AGE) were obtained by Google Earth Engine (GEE), which were used to construct LST-EVI feature spaces to calculate the dry-wet edge fitting equations and Temperature Vegetation Drought Index (TVDI). Mann–Kendall test and Sen trend degrees were further used to analyze the drought trend of AGE. The results showed that there were obvious spatial differences in the wet and dry conditions of AGE, which showed that the TVDI increased from east to west and from north to south, with humid areas mainly concentrated in northern Asia and severe drought areas concentrated in southern Asia. From 2010 to 2018, the area of humid areas and severe drought areas of AGE decreased, and some humid areas changed to normal areas or even drought areas, while the drought in severe drought areas was alleviated. The results of the Sen trend test further show that the aggravating trend of drought in severe drought areas of South Asia is relatively low, and some areas show a trend of changing to humidity. However, there is an obvious aggravating trend of drought in humid areas or low drought areas of South Asia, these areas should also be the focus areas for drought prevention in the future. This study identified the spatio-temporal distribution characteristics and evaluated the evolution trend of the drought of AGE, which is of great significance to the management and prevention of drought of AGE.

Prediction and assessment of meteorological drought characteristics in China based on a future climate model

“…Trend analysis is a method used to predict the trend of variables through linear regression analysis (Zhang et al, 2021). We used linear regression to explore the spatial trends in annual-scale SPEI over time, which was calculated using the following formula:…”