Tuesday, 9 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
As our world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Prognostic land-surface models require accurate a priori information about global precipitation patterns, soil moisture storage capacity, groundwater tables, and artificial controls on water supply (e.g., irrigation, dams and diversions, inter-basin water transfers, etc.) to reliably link rainfall to evaporative fluxes. In contrast, diagnostic estimates of ET can be generated, with no prior knowledge of the surface moisture state, by energy balance models using thermal-infrared (TIR) remote sensing of land-surface temperature (LST) as a boundary condition. The LST inputs carry valuable proxy information regarding soil moisture and its effect on soil surface evaporation and canopy stresses limiting transpiration. In this project, we propose to generate a high-resolution 375-m ET dataset over the NENA region, generated with the TIR-based Atmosphere-Land-Exchange Inverse (ALEXI) model. ALEXI is based on the Two-Source Energy Balance (TSEB) land surface representation, which partitions fluxes and surface temperature between nominal soil and canopy components within the modeling scene. The dataset will be generated with a recently developed technique, which exploits day-night observations of LST from polar orbiting sensors such as MODIS, and VIIRS to estimate the morning rise in LST needed as a crucial forcing to the ALEXI system. This method has been evaluated against geostationary observations of LST and has been shown to reasonably match high temporal resolutions of mid-morning rise in LST, with errors generally in the 5 to 10% range. The use of polar sensors circumvents the significant resources needed to generate global datasets of morning LST rise (needed by ALEXI) from the current suite of geostationary sensors which are each operated by their own parent organizations which have varying constraints on data sharing. Furthermore, geostationary sensors are limited to a range of around 60N to 60S due to constraints on view angle, while polar sensors provide full global coverage. With the launch of the Suomi NPP platform, high resolution (375-m), twice daily observations of land surface temperature became available from the Visible Infrared Imaging Radiometer Suite (VIIRS). These LST observations serve as the primary input to ALEXI to retrieve Evapotranspiration (along with other surface energy flux components) and provide a significant upgrade over other polar orbiting sensors in terms of spatial resolution, scanning geometry and radiometric accuracy (e.g., MODIS, AVHRR). The proposed system will provide near-real-time satellite retrievals of evapotranspiration over the NENA region which will be used as the primary input and boundary condition to the DisALEXI flux disaggregation system, which when used in concert with 30-m LST from Landsat can provide estimates of water use on the field scale. The proposed system will be a joint effort between the University of Maryland, the Daugherty Water for Food Institute at the University of Nebraska, the USDA Hydrology and Remote Sensing Lab, the International Center for Biosaline Agriculture, and USAID.
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