Assessing the remote sensing derived Evaporative Stress Index with ground observations of crop condition to advance drought early warning

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Thursday, 6 February 2014: 11:45 AM
Room C209 (The Georgia World Congress Center )
Kathryn A. Semmens, USDA/ARS, Beltsville, MD; and M. C. Anderson, I. Mladenova, C. Hain, J. A. Otkin, and N. Guindin

Drought has significant impacts over broad spatial and temporal scales, and information about the timing and extent of such conditions is of critical importance to many end users in the agricultural and water resource management communities. The ability to accurately monitor effects on crops, and provide early warning of developing vegetation stress, will provide valuable information for mitigating negative impacts of drought. This research assesses the potential of the thermal remote sensing based Evaporative Stress Index (ESI) as a relatively early indication of declining crop condition using county level crop condition (CC) and soil moisture (SM) weekly reports from the USDA National Agricultural Statistics Service (NASS) collected by trained observers on the ground in crop growing counties in the contiguous United States (CONUS). Spatial and temporal correlations between these datasets will be explored over a variety of temporal and spatial scales, as well as for different crop types and phenologic stages. Preliminary analysis shows that monthly ESI agrees well with the ground observations, suggesting the ESI as a valuable, spatially continuous dataset for improving drought modeling efforts. In addition, stress-induced changes in ESI are hypothesized to precede declines in crop cover fraction, typically observed using optical vegetation indices such as the Normalized Difference Vegetation Index. Increases in canopy and soil temperatures (detectable via thermal remote sensing) are hypothesized to occur before crop biomass is visibly affected by soil moisture depletion. Spatiotemporal agreement between NASS CC and SM observations, gridded over CONUS, will be assessed in comparison with ESI data fields and other standard drought indictors to identify optimal indices for early detection of degrading crop conditions. Analysis over the time period 2002-2013 will allow the relationships to be assessed in a variety of climatological conditions (i.e. wet and dry years, etc.). This research, by comparing both remote sensing and ground observations, provides a unique and valuable perspective of evapotranspiration and drought estimation with implications for modeling and operational decision making.