Monday, 8 January 2018: 11:45 AM
Room 18A (ACC) (Austin, Texas)
This presentation will describe the development of a global agricultural monitoring tool, with a focus on providing early warning of developing vegetation stress for agricultural decision-makers and stakeholders at relatively high spatial resolution (5-km). The tool is based on remotely sensed estimates of evapotranspiration, retrieved via energy balance principals using observations of land surface temperature. The Evaporative Stress Index (ESI) represents anomalies in the ratio of actual-to-potential ET generated with the thermal remote sensing based Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance model. The LST inputs to ESI have been shown to provide early warning information about the development of vegetation stress with stress-elevated canopy temperatures observed well before a decrease in greenness is detected in remotely sensed vegetation indices. Whereas many drought indicators based on precipitation or atmospheric conditions capture meteorological drought, the ESI is one of few indicators of agricultural drought that reveals actual vegetation stress conditions realized on the ground. As a diagnostic indicator of actual ET, the ESI requires no information regarding antecedent precipitation or soil moisture storage capacity - the current available moisture to vegetation is deduced directly from the remotely sensed LST signal. This signal also inherently accounts for both precipitation and non-precipitation related inputs/sinks to the plant-available soil moisture pool (e.g., irrigation, tile drainage) which can modify crop response to rainfall anomalies. Independence from precipitation data is a benefit for global agricultural monitoring applications due to sparseness in existing ground-based precipitation networks, and time delays in public reporting. Even as satellite precipitation monitoring has closed some of the observational gaps, these data are usually provided at coarse resolution with accuracy dependent on extensive calibration with ground-based precipitation estimates. Several enhancements to the current ESI framework will be addressed as requested from project stakeholders: (a) integration of “all-sky” MW Ka-band LST retrievals to augment “clear-sky” thermal-only ESI in persistently cloudy regions; (b) operational production of ESI Rapid Change Indices which provide important early warning information related to onset of actual vegetation stress; and (c) assessment of ESI as a predictor of global yield anomalies; initial studies have shown the ability of intra-seasonal ESI to provide an early indication of at-harvest agricultural yield anomalies. The ESI-GDPS will serve the decision support needs of the three primary project stakeholders: the USDA Foreign Agricultural Service, the International Center for Biosaline Agriculture’s MENA Regional Drought Management System and the G20 GEOGLAM Crop Monitor Initiative for the Agricultural Market Information System (AMIS) and for Early Warning.
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