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Large-scale vegetation responses to terrestrial moisture storage changes

机译:大型植被对陆地水分存储变化的响应

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The normalised difference vegetation index (NDVI) is a useful tool for studying vegetation activity and ecosystem performance at a large spatial scale. In this study we use the Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS) estimates to examine temporal variability of the NDVI across Australia. We aim to demonstrate a new method that reveals the moisture dependence of vegetation cover at different temporal resolutions. Time series of monthly GRACE TWS anomalies are decomposed into different temporal frequencies using a discrete wavelet transform and analysed against time series of the NDVI anomalies in a stepwise regression. The results show that combinations of different frequencies of decomposed GRACE TWS data explain NDVI temporal variations better than raw GRACE TWS alone. Generally, the NDVI appears to be more sensitive to interannual changes in water storage than shorter changes, though grassland-dominated areas are sensitive to higher-frequencies of water-storage changes. Different types of vegetation, defined by areas of land use type, show distinct differences in how they respond to the changes in water storage, which is generally consistent with our physical understanding. This unique method provides useful insight into how the NDVI is affected by changes in water storage at different temporal scales across land use types.
机译:归一化植被指数(NDVI)是研究大空间尺度上植被活动和生态系统性能的有用工具。在这项研究中,我们使用重力恢复和气候实验(GRACE)的总储水量(TWS)来检查整个澳大利亚NDVI的时间变化。我们旨在演示一种新方法,该方法揭示不同时间分辨率下植被覆盖的水分依赖性。使用离散小波变换将每月GRACE TWS异常的时间序列分解为不同的时间频率,并在逐步回归中针对NDVI异常的时间序列进行分析。结果表明,分解频率不同的GRACE TWS数据的组合比单独的原始GRACE TWS更好地解释了NDVI的时间变化。通常,尽管草原占主导地位的地区对更高频率的蓄水变化敏感,但NDVI似乎比较短的变化对水的年际变化更为敏感。由土地利用类型的区域定义的不同类型的植被在其对储水量变化的响应方式上表现出明显的差异,这通常与我们的自然认识相符。这种独特的方法有助于洞悉NDVI如何受到土地利用类型不同时间尺度的储水量变化的影响。

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