Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2010, Vol. 7, No. 3, pp. 254-263
Моделирование вертикальных потоков влаги и тепла
с поверхности речного водосбора с использованием оценок
характеристик подстилающей поверхности
по спутниковым данным
Е.Л. Музылев
1, А.Б. Успенский
2, З.П. Старцева
1, Е.В. Волкова
2, А.В. Кухарский
21 Институт водных проблем РАН, Москва, 119333, ул.Губкина, 3
2 ГУ Научно-исследовательский центр космической гидрометеорологии "Планета", Москва, 123242, Б.Предтеченский пер., 7
The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) has been developed
designing for calculation of water and heat balance components as well as vertical soil temperature and moisture
distributions and soil surface and foliage temperatures. The model is meant for utilizing estimates of vegetation
characteristics and land surface temperature (LST) retrieved from AVHRR/NOAA and MODIS/EOS Terra & Aqua
measurement data in cloud-free conditions. Calculations have been carried out for the part of the Kursk region with
area about 10000 km2 for vegetation seasons of 2005-2008.
To provide effective assimilation of satellite data in the SVAT model the ability has been investigated to replace
ground-based estimates of leaf area index LAI, vegetation cover fraction B and LST using as the model parameters
and input variable, correspondingly, by their AVHRR- or MODIS-based analogues. The approach has been also
developed to account for space variability of above satellite-derived estimates. The SVAT model calculations of
water and heat balance components, as well as vegetation cover and soil surface temperatures for region under investigation
have been carried out for different scenarios of LAI and B estimating from AVHRR/3, MODIS, and
ground-based data for named vegetation seasons. The acceptable accuracy levels of above values assessment have
been achieved under all scenarios of parameter and input model variable specification.
Keywords: modeling water and heat transfer, satellite data thematic processing, space variability of land surface characteristics
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