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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Alexi Analysis of Water Consumption in the Nile Basin

Authors
item Anderson, Martha
item Yilmaz, Mustafa

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: May 18, 2011
Publication Date: July 7, 2011
Citation: Anderson, M.C., Yilmaz, M.T. 2011. ALEXI analysis of water consumption in the Nile Basin [abstract]. Meeting of Managing Water under Climate Chinge in Blue Nile Headwaters, July 7-10, 2011. 2011 CDROM.

Technical Abstract: Remote sensing can be used to generate diagnostic estimates of evapotranspiration (ET) that provide information regarding consumptive water use across landscapes. These satellite-based assessments can be a valuable complement to prognostic simulations of basin-scale water budgets, providing an independent evaluation of components that are not easily captured without extensive a priori knowledge, including diversions/extractions for irrigated agriculture, and ET enhancements in regions of shallow water table (e.g., wetlands, riparian areas). In addition, convergence of evidence from two independent modeling techniques provides additional confidence in model results in areas lacking extensive groundtruth data. In this talk, we discuss use of a remote sensing surface energy balance algorithm (ALEXI), forced by satellite measurements of insolation and land-surface temperature, in an application over the Nile River Basin. Several years of ALEXI output over the Basin is being compared with prognostic output from a prognostic, Nile-adapted Land Data Assimilation System for purposes of supplying objective, spatially continuous hydrologic information for the Nile Basin States. We will demonstrate the unique value of remote sensing as a check on hydrologic models, and identify areas where further model refinement appears necessary.

Last Modified: 12/25/2014
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