Can vegetation optical depth reflect changes in leaf water potential during soil moisture dry-down events?

环境科学 植被(病理学) 遥感 含水量 水分 水文学(农业) 土壤科学 地质学 气象学 地理 岩土工程 医学 病理
作者
Yao Zhang,Sha Zhou,Pierre Gentine,Xiangming Xiao
出处
期刊:Remote Sensing of Environment [Elsevier]
卷期号:234: 111451-111451 被引量:37
标识
DOI:10.1016/j.rse.2019.111451
摘要

Abstract Plant water use strategy is one of the key factors to predict drought impact on vegetation and land-atmosphere fluxes. Vegetation optical depth (VOD) based on microwave radiative transfer inversion has recently been used to assess plant water use strategy. However, VOD is sensitive to both total aboveground biomass (AGB) and leaf water content, with only the latter being a proxy of leaf water potential whose diurnal variation can be used to characterize vegetation iso/anisohydricity. In this study, by using a network of soil water measurements (used as a proxy for predawn leaf water potential), satellite retrieved normalized difference vegetation index (NDVI, as a proxy for AGB), and two satellite VOD products from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) sensor, we compare three linear models and one machine learning model to investigate to what extent can VOD be used to represent leaf water potential changes during soil moisture dry-down periods. Linear models with both NDVI and leaf water potential, on average, can explain 33% and 51% of VOD variations of each product respectively. Models using only NDVI explain 27% and 46% of the VOD variance, compared to less than 10% by models using leaf water potential only. With the NDVI and leaf water potential (full) model, leaf water potential contributes around 17% of the VOD variance, which is smaller than NDVI (33%). The machine learning model has overall better performance than the linear models, and also highlight the dominant contribution of AGB to VOD signals. After the AGB contribution to VOD is eliminated by normalizing daytime VOD with nighttime VOD, the residuals carry the information of diurnal variations of leaf water potential and calculations from both VOD datasets are consistent with each other (r = 0.42 ± 0.17, P  VOD daytime VOD nighttime to soil water potential can also be used as a new metric for ecosystem iso/anisohydricity. Our study demonstrates that a large proportion of variations in VOD are caused by AGB for temperate ecosystems, and higher accuracy VOD products with additional root-zone soil water potential are needed for ecosystem iso/anisohydricity estimations.

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