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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #390595
Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Microwave-based soil moisture improves estimates of vegetation response to drought in China

Author
item QUI, J. - Sun Yat-Sen University
item Crow, Wade
item DONG, J. - Tianjin University
item LI, Y. - Beijing Normal University
item GARCIA, M. - Universidad Politécnica De Madrid
item SHANGGUAN, W. - Collaborator

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/17/2022
Publication Date: 8/18/2022
Citation: Qui, J., Crow, W.T., Dong, J., Li, Y., Garcia, M., Shangguan, W. 2022. Microwave-based soil moisture improves estimates of vegetation response to drought in China. Remote Sensing of Environment. 849:157535. https://doi.org/10.1016/j.scitotenv.2022.157535.
DOI: https://doi.org/10.1016/j.scitotenv.2022.157535

Interpretive Summary: During agricultural drought, vegetation is faced with competing risks tied to its regulation of stomatal openings. Leaving leaf stomata open increases the rate of water loss through transpiration. On the other hand, closing leaf stomata decreases the uptake of carbon dioxide and thus reduces photosynthetic productivity. Different types of vegetation apply contrasting strategies to the regulation of leaf stomata during severely water-limited conditions. This paper describes a new remote sensing technique for detecting the expression of such strategies at large spatial scales. Results of this analysis provide an improved characterization of ecosystem-level response to drought that can be compared to predictions made by earth system models tasked with describing the impact of climate change on agriculture. Therefore, results from this analysis will eventually be used to improve USDA’s ability to predict the impact of enhanced water cycle variability on domestic and international food and fiber production.

Technical Abstract: The increased frequency and severity of drought has heightened concerns over the risk of hydraulic vegetative stress and premature mortality within the global ecosystem. Unfortunately, most land surface models (LSMs) continue to underestimate ecosystem resilience to drought - which degrades the credibility of model-predicted ecohydrological responses to climate change. This study investigates the response of ecosystem-level vegetation adaption to water-stress conditions using microwave-based vegetation optical depth and soil moisture retrievals. Based on the estimated isohydricity/anisohydricity spectrum, we find that isohydric vegetation exhibits higher water use efficiency (WUE) than anisohydric vegetation due to their more rigorous stomatal control and higher tolerance of carbon starvation risk. In addition, the introduction of microwave soil moisture improves the accuracy of isohydricity/anisohydricity estimates compared to those obtained using microwave vegetation optical depth alone. Results of this study provide justification for the use of microwave-based soil moisture retrievals to enhance stomatal conductance parameterization within LSMs.