Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #300994

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

Location: Hydrology and Remote Sensing Laboratory

Title: Drought monitoring using remote sensing of evapotranspiration

item Anderson, Martha
item Hain, C
item Otkin, J
item Zhan, X
item Kustas, William - Bill
item Semmens, Kathryn

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 12/9/2013
Publication Date: 12/9/2013
Citation: Anderson, M.C., Hain, C., Otkin, J., Zhan, X., Kustas, W.P., Semmens, K.A. 2013. Drought monitoring using remote sensing of evapotranspiration [abstract]. InterDrought Project Workshop "Remote Sensing Tools in Drought Monitoring", February 26-28, 2014, Brno, Czech Republic.

Interpretive Summary:

Technical Abstract: Drought assessment is a complex endeavor, requiring monitoring of deficiencies in multiple components of the hydrologic budget. Precipitation anomalies reflect variability in water supply to the land surface, while soil moisture (SM), ground and surface water anomalies reflect deficiencies in moisture storage. In contrast, evapotranspiration (ET) anomalies provide unique yet complementary information, reflecting variations in actual water use by crops and direct evaporation from the soil. For example, precipitation- and ET-based anomalies may differ significantly in regions of intensive irrigation, shallow water table, or deep rooting depth – areas where plants may be more resilient to soil moisture deficiencies inferred from rainfall patterns. In addition, an ET-based index can better capture impacts of hot, windy conditions leading to “flash droughts”, where anomalously high water use precipitates rapid decay in soil moisture and crop condition. Here we describe a remotely sensed Evaporative Stress Index (ESI) based on anomalies in actual-to-reference ET ratio, and compare with patterns in precipitation-based drought indicators. Actual ET is derived from thermal remote sensing, using the morning land-surface temperature (LST) rise observed with geostationary satellites within a diagnostic soil-plant-atmosphere modeling system. In comparison with vegetation indices, LST is a fast-response variable, with the potential for providing early warning of crop stress reflected in increasing canopy temperatures. Spatiotemporal patterns in ESI reasonably match those in precipitation-based indices (such as SPI and modeled SM) and patterns in the U.S. Drought Monitor. However, because ESI does not use precipitation as an input, it provides an independent assessment of evolving drought conditions, and is more portable to data-sparse parts of the world lacking dense rain-gauge and Doppler radar networks. Integrating LST information from polar orbiting systems, the ESI has unique potential for sensing moisture stress at field scale, benefiting yield estimation and loss compensation efforts. Techniques for identifying flash drought events will be demonstrated, as well as ESI performance over the heat-induced drought events of 2012. The ESI is routinely produced over the continental U.S. using data from GOES, with expansion to North and South America underway. In addition, drought monitoring applications are being developed over Africa and Europe using Meteosat land-surface products.