Paper
26 October 2004 Modeling seasonal actual evapotranspiration with remote sensing and GIS in Khorezm region, Uzbekistan
Christopher Conrad, Gerd R. Rucker, Christian Schweitzer, Stefan Dech, Mohammad Mohsin Hafeez
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Abstract
Seasonal evapotranspiration is an essential measure to model crop growth and hydrological balances particularly for irrigation agriculture in semi-arid environments. Hydrological models traditionally integrate single-spot measurements of meteorological stations to estimate potential evapotranspiration. During the last years, the application of thermal remote sensing data in combination with meteorological data of soil-vegetation-atmosphere models facilitated the estimation of actual evapotranspiration on a large scale. This study employed multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) data to apply the Surface Energy Algorithm for Land (SEBAL) model to the heterogeneous environment of the Khorezm region, Uzbekistan. Further meteorological data was used to extrapolate actual evapotranspiration to seasonal actual evapotranspiration. The validation of the modeled actual evapotranspiration showed acceptable accuracy when compared to the limited point-based ground truth data. The integration of a rule-based land use classification with higher spatial resolution revealed the necessity to include sub-pixel knowledge of land use distribution to interpret the modeling results. First evaluations of the water distribution and consumption situation were achieved by interpretation of modeled seasonal actual evapotranspiration with hydrological GIS information.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christopher Conrad, Gerd R. Rucker, Christian Schweitzer, Stefan Dech, and Mohammad Mohsin Hafeez "Modeling seasonal actual evapotranspiration with remote sensing and GIS in Khorezm region, Uzbekistan", Proc. SPIE 5568, Remote Sensing for Agriculture, Ecosystems, and Hydrology VI, (26 October 2004); https://doi.org/10.1117/12.565611
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Cited by 3 scholarly publications.
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KEYWORDS
Data modeling

MODIS

Atmospheric modeling

Remote sensing

Meteorology

Geographic information systems

Vegetation

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