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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 #320133
Title: Monitoring agricultural water use, water productivity and drought using multi-platform satellite data

Author
item Anderson, Martha
item HAIN, C. - University Of Maryland
item Gao, Feng
item Yang, Yun
item OTKIN, J. - University Of Wisconsin
item Kustas, William - Bill

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 8/24/2015
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: To meet the food supply needs of the world’s growing population, global food production will need to roughly double by 2050. This increased production must be accomplished within the constraints of a non-uniform distribution of freshwater resources, an amplifying climate cycle, and concern for environmental impacts of agriculture. To make significant strides in improving the production capacity and resiliency of global agricultural systems, we must first better understand the variability embedded in landscapes under current conditions in terms of water use and water productivity as it relates to different land and crop management strategies. Such studies are well suited to remote sensing data from medium resolution satellite systems such as Landsat, which provides information about land and water use at the scales at which they are being managed (< 100 m). Unfortunately, these medium resolution systems do not provide land-surface temperature data at the temporal frequency required to adequately support water-use (evapotranspiration; ET) mapping in many parts of the world. This presentation will discuss methodologies for producing daily ET estimates over a broad range in spatial scales (field-to-globe) by fusing information from multiple satellite systems with different spatiotemporal mapping characteristics. These ET datasets can be used to investigate relationships between water use dynamics and land-cover/land-use and water management strategy, and to map water productivity (kilograms of yield per cubic meter of water used over the growing season) at landscape scale. Temporal anomalies in ET can provide an early indication of vegetation stress due to drought or other stressors, signaled by elevated canopy temperatures accompanying the decreased transpiration rates. Example applications of data fusion in mapping water resources and monitoring drought and yield over several continents will be discussed, with special focus on the Near East – North African region.