Active Microwave Systems for Monitoring Drought Stress - Monitoring and Predicting Agricultural Drought: A Global Study - page 114

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cultural applications mainly the soil moisture content within the reach of
the plant roots is of interest (Jones et al., 2000). To estimate the water
content at deeper levels using scatterometer data, Wagner et al. (1999b)
proposed a two-layer water balance model that transforms the highly vari-
able surface soil moisture series into a red-noise-like profile of soil moisture
time series. When soil hydrologic properties (wilting level, field capacity,
and total water capacity) are known, the water content available to plants
can be estimated. Over the Ukraine, a comparison with gravimetric soil
moisture data from the agro-meteorological station network showed that
the soil moisture content in the 0-100-cm layer can be estimated with an
accuracy of about 5% volumetric soil moisture. A comparison with in situ
soil moisture data from a network of 20 TDR (time domain reflectory)
probes in the Duero-Basin in Spain yielded an accuracy of better than 3%
volumetric soil moisture for the same layer (Scipal et al., 2003).
Timely information about the regional soil moisture conditions from
remote-sensing data is useful for assisting agro-meteorological analysis.
The information content can be further enhanced by comparing the present
year with the long-term mean and modeling the timing of crop water stress
(Barron et al., 2003). Given the availability of nine years of ERS-1/2 scat-
terometer data, soil moisture anomalies can be easily calculated. Figure 8.2
shows how scatterometer-derived soil moisture anomalies for the months
February and March 1999 over Southeast Asia (including India) compare
to rainfall anomalies derived from a globally gridded precipitation data
produced by the Global Precipitation Climatology Center (GPCC, 2003).
In both data sets, anomalous dry conditions centered over southern China
can be recognized.
To assess the timing of water availability during critical crop-growth
stages, remotely sensed soil moisture data must be combined with crop-
growth models. In a study conducted over Russia and the Ukraine, scatter-
ometer-derived soil moisture data were used as input to a crop growth
model WOFOST (Supit et al., 1994). This model simulates the daily growth
of a specific crop using weather and soil data and following the hierarchical
distinction between potential and limited production. The ratio between
potential and limited production is the indicator of drought stress. The
scatterometer-derived soil moisture is used to replace the soil moisture
estimates normally derived using water budget models. The results of the
study suggested that provincial yield assessment can be improved through
the use of remotely sensed soil moisture information (Wagner et al., 2000).

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C onclusions
Radars can potentially be used to monitor soil moisture, plant moisture
content, and vegetation production. For example, it has been demonstrated
that drought conditions can be inferred from scatterometers by calculating
soil moisture anomaly indicators or by using the remotely sensed param-
eters as input to the more complex crop-growth models to capture cumu-