B090-06
Using microwave remote sensing of vegetation water content to understand ecosystem-scale responses to drought

Monday, 14 December 2020: 20:50
Virtual
Alexandra G Konings, Stanford University, Department of Earth Sciences, Stanford, CA, United States, Nataniel Holtzman, Stanford University, Department of Earth System Science, Stanford, CA, United States, Yanlan Liu, Duke University, Nicholas School of the Environment, Durham, NC, United States, Krishna Rao, Stanford University, Stanford, CA, United States, Leander DL Anderegg, University of California Berkeley, Berkeley, CA, United States and Park Williams, Columbia University, Lamont -Doherty Earth Observatory, Palisades, NY, United States
Recorded Presentation
Abstract:
Plant hydraulics modulate the negative effects of hydrological drought (i.e. decreased soil water availability and increased vapor pressure deficit) on plant health. Plant physiology, functional diversity, and spatial environmental heterogeneity all influence where, when, and how drought affects the overlying vegetation. Accounting for these sources of heterogeneity to predict spatial patterns in vegetation drought response is challenging due to the small scale at which plant physiology and function is measured in the field. Remote sensing, which is by nature spatially extensive, can help scale our understanding of plant water relations. In particular, microwave remote sensing observations are sensitive to vegetation water content. Because plant relative water content and leaf (or xylem) water potential are monotonically related, microwave remote sensing observations are therefore sensitive to leaf water potential. In this talk, we will present recent field observations at Harvard Forest, Massachusetts, demonstrating that vegetation optical depth (VOD) – a quantity derived from microwave radiometry – is sensitive to leaf and (to a lesser degree) xylem water potential. VOD displayed the characteristic diurnal cycle of leaf water potential and was highly correlated to it (R = 0.79). We will also demonstrate two possible applications of remotely sensed vegetation water content observations that can be used for improved drought monitoring. First, we will discuss how VOD can be used in a data-assimilation framework to derive ecosystem-scale plant hydraulic traits such as P50, maximum stomatal conductance, etc. This can be used for improved parametrization of models that incorporate plant hydraulics, a necessary component for adequately capturing drought response. Secondly, we will discuss how radar-based microwave remote sensing of live fuel moisture content – a measure of vegetation water content used in the wildfire community – can be used for improved estimation of fire risk.
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