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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 #310129
Title: Multi-scale assessment of water availability and agricultural drought: from field to global scales

Author
item Anderson, Martha
item HAIN, C. - University Of Maryland
item Gao, Feng
item Semmens, Kathryn
item Yang, Yun
item Schull, Mitchell
item Kustas, William - Bill

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 9/29/2014
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Given growing pressures on freshwater resources due to increasing populations, evolving landuse and changing climate, there is a need for timely information on water availability and drought over a wide spectrum of spatial scales: from scales of individual farm fields to inform production decisions and local water management, to continental and global scales for realtime monitoring of emerging food and water security flashpoints. To support these monitoring needs, satellite retrievals of land-surface temperature (LST) derived from thermal infrared (TIR) imagery have demonstrated significant value for multi-scale mapping of surface moisture conditions, consumptive water use (or evapotranspiration; ET) and vegetation health. Soil surface temperature increases with decreasing water content, while moisture depletion in the plant root zone leads to stomatal closure, reduced transpiration, and elevated canopy temperatures that can be effectively detected from space. In land-surface modeling, TIR imagery can serve as an effective substitute for precipitation data, providing much-needed water information in data-poor regions of the world. This paper discusses a multi-scale thermal remote sensing modeling system that fuses flux assessments generated with TIR imagery collected by multiple satellite platforms to estimate daily surface fluxes from field to global scales. The Landsat series of polar orbiting systems has collected TIR imagery at 60-100 m resolution (8-16 day revisit) since the 1980s, providing spatiotemporal capabilities for monitoring historical and realtime ET and vegetation stress/drought globally at the scale of human management – nominally, the field scale. Recent experiments have demonstrated that the temporal sampling of high resolution TIR imaging systems can be further enhanced by fusing lower spatial (1 km) but higher temporal resolution ET retrievals using TIR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments (1 km; ~daily) and from geostationary (GEO) weather satellites (3-10 km; 15 minute intervals). We describe implementations of a prototype Landsat-MODIS-GEO ET data fusion over agricultural and natural landscapes under rainfed and irrigated water management and demonstrate added value in comparison with a simple Landsat-only interpolation scheme – particularly when a rainfall event occurs between Landsat overpasses. Potential applications for fused ET datasets will be discussed, with societal benefits in the areas of food and water security.