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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 #306436

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

item Anderson, Martha
item ZOLIN, C. - Collaborator
item HAIN, C. - University Of Maryland
item Semmens, Kathryn
item YILMAZ, M.T. - Collaborator
item Gao, Feng

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/4/2015
Publication Date: 2/12/2015
Citation: Anderson, M.C., Zolin, C., Hain, C., Semmens, K.A., Yilmaz, M., Gao, F.N. 2015. Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013. Journal of Hydrology. doi: 10.1016/j.jhydrol.2015.1001.1005.

Interpretive Summary: During the past decade, several extreme drought and flooding events have occurred over Brazil, impacting both the heath of the Amazon rainforest and crop yields in agricultural states to the east. Because ground-based monitoring networks (rain and streamflow gauges) are limited in parts of Brazil, particularly in remote parts of the Amazon, it is difficult to fully assess impacts of such events spatially, at a national scale. Imagery from satellites, quantifying anomalies in green biomass and precipitation rates, have been widely used to provide adequate spatial and temporal sampling for monitoring applications. However, such products have yielded conflicting evidence regarding ecosystem response to drought, particularly over the Amazon which is subject to prolonged periods of cloud cover and episodes of intense biomass burning - both leading to contamination in satellite imagery. In this study, we compare standard satellite products for monitoring biomass (leaf area index, LAI) and precipitation with results from the Evaporative Stress Index (ESI), which quantifies anomalies in vegetation water use as derived from satellite imaging. The ESI records areas of excess and deficient water use in comparison with normal conditions, and therefore provides information regarding waterlogging and vegetation stress. The comparison shows strong anticorrelation between LAI, precipitation and ESI over the rainforest system, which could be due either to contamination problems or real biophysical response. Tighter coupling between indicators is observed over agricultural states. The fact that these three independent drought indicators give consistent information over crop and grasslands implies that they may be useful for early yield forecasting and drought mitigation efforts in these states.

Technical Abstract: Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and functioning have been attributed to cloud and aerosol contamination of shortwave reflectance composites, particularly over the rainforested regions of the Amazon basin which are subject to prolonged periods of cloud cover and episodes of intense biomass burning. This study compares timeseries of satellite-derived maps of LAI from the Moderate Resolution Imaging Spectroradiometer (MODIS) and precipitation from the Tropical Rainfall Mapping Mission (TRMM) with a diagnostic Evaporative Stress Index (ESI) retrieved using thermal infrared remote sensing over South America for the period 2003-2013. This period includes several severe droughts and floods that occurred both over the Amazon and over unforested savanna and agricultural areas in Brazil. Cross-correlations between absolute values and standardized anomalies in monthly LAI and precipitation composites as well as the actual-to-reference evapotranspiration (ET) ratio used in the ESI were computed for representative forested and agricultural regions. The correlation analyses reveal strong anticorrelation between LAI and precipitation anomalies over the Amazon, but better coupling over regions vegetated with shorter grass and crop canopies. The ESI was more consistently correlated with precipitation patterns over both landcover types. Temporal comparisons between ESI and TRMM anomalies suggest longer moisture buffering timescales in the deeper rooted rainforest systems. Diagnostic thermal-based retrievals of ET and ET anomalies, such as used in the ESI, provide independent information on the impacts of extreme hydrologic events on vegetation health in comparison with VI and precipitation-based drought indicators, and used in concert may provide a more reliable evaluation of natural and managed ecosystem response to changing climate regimes.