Tingyu Li , Shaoqiang Wang , Zhuoying Deng , Jinghua Chen , Bin Chen , Zhewei Liang , Xuan Chen , Yunhao Jiang , Peng Gu , Leigang Sun
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引用次数: 0
Abstract
Extreme climate events, particularly droughts, pose significant threats to vegetation, severely impacting ecosystem functionality and resilience. However, the limited temporal resolution of current satellite data hinders accurate monitoring of vegetation's diurnal responses to these events. To address this challenge, we leveraged the advanced satellite ECOSTRESS, combining its high-resolution evapotranspiration (ET) data with a LightGBM model to generate the hourly continuous ECOSTRESS-based ET (HC-ETECO) for the middle and lower reaches of the Yangtze River Basin (YRB) from 2015 to 2022. This dataset showed strong agreement with both ground-based and satellite observations. Utilizing the SPEI, we identified the significant drought period: September to November 2019 and August to September 2022. By integrating hourly Solar-Induced Chlorophyll Fluorescence (SIF) data, we observed that during drought period, the typical afternoon peak in SIF was absent. In contrast to non-drought period, morning photosynthesis and SIF-based Water Use Efficiency (WUESIF) anomalies were primarily driven by high Vapor Pressure Deficit (VPD), while the afternoon reductions were influenced by both high VPD and low Soil Moisture (SM) as the drought progressed. Our simulated HC-ETECO data revealed that ET in the middle and lower reaches of the YRB was consistently lower than normal during drought period. Attribution analysis indicated that this reduction was primarily driven by midday temperature increases and high VPD, suggesting that vegetation in the region copes with drought stress predominantly by limiting water loss. These findings highlight the utility of the generated high-resolution ET dataset in advancing our understanding of vegetation dynamics under drought climate conditions. This work provides critical insights for enhancing climate adaptation strategies and enhancing ecosystem management practices in the face of increasing climate variability.
极端气候事件,特别是干旱,对植被构成重大威胁,严重影响生态系统的功能和复原力。然而,当前卫星数据的有限时间分辨率阻碍了对植被对这些事件的日响应的准确监测。为了应对这一挑战,我们利用先进的ECOSTRESS卫星,将其高分辨率蒸散发(ET)数据与LightGBM模型相结合,生成了2015年至2022年长江流域中下游(YRB)逐小时连续的ECOSTRESS ET (HC-ETECO)。该数据集与地面和卫星观测结果非常吻合。利用SPEI,我们确定了严重干旱期:2019年9月至11月和2022年8月至9月。通过对逐小时太阳诱导叶绿素荧光(SIF)数据的综合分析,发现干旱期没有典型的下午SIF峰值。与非干旱期相比,上午光合作用和水分利用效率(WUESIF)异常主要受高水汽压差(VPD)驱动,而下午的减少则受到高水汽压差和低土壤水分(SM)的共同影响。模拟的HC-ETECO数据显示,干旱时期长江中下游ET持续低于正常水平。归因分析表明,这种减少主要是由正午温度升高和高VPD驱动的,这表明该地区植被主要通过限制水分流失来应对干旱胁迫。这些发现强调了生成的高分辨率ET数据集在促进我们对干旱气候条件下植被动态的理解方面的实用性。这项工作为在日益增加的气候变率面前加强气候适应战略和加强生态系统管理实践提供了重要见解。
期刊介绍:
The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere.
The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.