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An analysis of spatiotemporal variations of soil and vegetation moisture from a 29‐year satellite‐derived data set over mainland Australia
Author(s) -
Liu Yi Y.,
van Dijk Albert I. J. M.,
de Jeu Richard A. M.,
Holmes Thomas R. H.
Publication year - 2009
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2008wr007187
Subject(s) - environmental science , vegetation (pathology) , water content , evapotranspiration , satellite , climatology , hydrology (agriculture) , atmospheric sciences , geology , medicine , ecology , geotechnical engineering , pathology , aerospace engineering , engineering , biology
The spatiotemporal behavior of soil and vegetation moisture over mainland Australia was analyzed using passive microwave observations by four satellites going back to late 1978. Differences in measurement specifications prevented merging the data directly. A continuous product was developed for Australia by scaling percentiles of the cumulative moisture distribution within each grid cell to the percentiles of a reference sensor. The coefficient of correlation and root‐mean‐square error between rescaled values and the reference generally suggest good agreement. Using the merged data product, a strong El Niño–Southern Oscillation signal in near‐surface hydrology across Australia was confirmed. Spatial patterns of trends in annual averages show that western and northwestern Australia have experienced an increase in vegetation moisture content, while the east and southeast experienced a decrease. Soil moisture showed a similar spatial pattern but with larger regions experiencing a decrease. This could be explained by decreasing rainfall and increasing potential evapotranspiration during the extended winter period (May–September). The results give us reasonable confidence in the time series of soil and vegetation moisture derived by the scaling method developed in this study. Development of a global data set along these lines should enable better estimation of hydrological variables and should increase understanding of the impacts of ocean circulations on terrestrial hydrology and vegetation dynamics.