Using a Diagnostic Soil-Plant-Atmosphere Model for Monitoring Drought at Field to Continental Scales

Abstract

Drought assessment is a complex undertaking, 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, groundwater 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 – a useful diagnostic of vegetation health. Here we describe a remotely sensed Evaporative Stress Index (ESI) based on anomalies in actual-to-reference ET ratio. Actual ET is retrieved from thermal remote sensing data using a diagnostic soil-plant-atmosphere modeling system forced by measurements of morning land-surface temperature (LST) rise from geostationary satellites. In comparison with vegetation indices, LST is a relatively fast-response variable, with the potential for providing early warning of crop stress reflected in increasing canopy temperatures. Spatiotemporal patterns in ESI have been compared with patterns in the U.S. Drought Monitor and in standard precipitation-based indices, demonstrating reasonable agreement. 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 geostationary and polar orbiting systems through data fusion, the ESI has unique potential for sensing moisture stress at field scale, with potential benefits to yield estimation and loss compensation efforts. The ESI is routinely produced over the continental U.S. using data from the Geostationary Operational Environmental Satellites, with expansion to North and South America underway. In addition drought and ET monitoring applications are being developed over Africa and Europe using land-surface products from the Meteosat Second Generation (MSG) platform.