## 1 Introduction  
Drought is one of the most common extreme climatic events globally. Extreme droughts can exert disproportionately severe impacts on natural and human systems [1; 2], such as limiting vegetation growth [3], triggering forest fires [4], causing significant agricultural yield reductions [5], and facilitating biological invasions and ecosystem degradation [1; 6]. Moreover, droughts generate intermittent water cycle disturbances, leading to notable imbalances in the terrestrial carbon cycle [7; 8]. The frequency and intensity of droughts will continue increasing in the 21 st century [9; 10]. As different areas demonstrate various responses to drought stress, it is vital to accurately quantify these responses with reliable indices. In recent studies, using the standardized precipitation evapotranspiration index (SPEI), the spatiotemporal dynamics of drought have been analyzed in regions such as China [11; 12], the Indian monsoon region [13], and Moldova [14]. These studies have shown that SPEI can be used to effectively reflect drought intensity and is suitable for monitoring short- and long-term droughts. Additionally, [15] proposed a vegetation dryness index, namely, the temperature vegetation dryness index (TVDI), based on a simplified interpretation of the normalized difference vegetation index-temperature signal space, for assessing surface moisture conditions. The TVDI has been successfully applied in surface soil moisture status assessment [16; 17]. Monitoring the responses of vegetation can reveal the severe impacts of drought stress on regional ecosystems. Drought significantly affects the productivity of terrestrial ecosystems [18]. Extreme droughts often exert varying impacts on different ecosystems. For example, [PERSON] et al. [19] reported that extreme droughts triggered only extreme ecological responses 15.1% of the time. [PERSON] and [PERSON] [20] revealed that early summer droughts could promote vegetation growth and carbon absorption in the Amazon ecosystem due to increased solar radiation available for plants. [PERSON] et al. [21] found that karst areas exhibited a lower mean annual water use efficiency (WUE) than that in non-karsat areas under drought conditions. Thus, various ecosystems respond differently to droughts. And several vegetation indices have been successfully applied in monitoring these responses to droughts [22; 23; 24]. Particularly, NDVI can be used to monitoring vegetation health, and has been successfully applied in assessing the impact of drought on vegetation health [25]. LAI has also been employed to analyze canopy structure and study the deep-rootedness of local vegetation, while GPP is used to evaluate changes in overall vegetation productivity under drought conditions [26]. Karst areas are formed by the dissolution of soluble carbonate rocks such as limestone, dolomite, gypsum, and rock salt. Surface runoff and groundwater erode these rocks, both chemically and mechanically, leading to the development of underground drainage systems that feature sinkholes and caves [27]. As a result, surface water more easily infiltrates into the ground, leading to a weaker water storage capacity in the basin. Therefore, karst areas are more vulnerable to drought disasters compared to non-karsat areas, making the assessment of ecosystems resilience in karst areas more urgent. Vegetation indices have been successfully used to detect the impacts of extreme climate events, such as droughts and heat waves, on ecosystem productivity [28]. For example, NDVI and GPP have been successfully used to assess the impact of drought stress on the ecological vulnerability of the Loess Plateau [29]. In 2022, China experienced a severe drought event [30]. This widespread drought had varying impacts across different regions of the country. Several factors contributed to these differences. For instance, the central and northern areas of the Tibetan Plateau were severely affected, primarily due to the influence of vegetation types [31].