Geoscience Reference
In-Depth Information
lower than that of earlier missions, like AMSR-E and ASCAT. In November 2009, the
ESA Earth Explorer mission SMOS was launched followed by another L-band mission,
NASA/CONAE Aquarius (Le Vine et al.
2006
), in June 2011. Aquarius measures various
elements of the hydrological cycle, and its coarse resolution makes it less attractive for soil
moisture estimation. The NASA mission SMAP is focused on soil moisture and freeze-
thaw detection and is scheduled for launch in 2014 (Entekhabi et al.
2010a
). To illustrate
the importance of soil moisture information, Table
2
identifies key benefits from satellite
soil moisture measurements.
A special issue on soil moisture from the SMOS mission has recently appeared in the IEEE
Transactions on Geoscience and Remote Sensing (Kerr et al.
2012a
). The papers in this
special issue describe the SMOS mission (Mecklenburg et al.
2012
); the radiometric per-
formance (Kainulainen et al.
2012
); the SMOS soil moisture retrieval algorithm (Kerr et al.
2012b
; Mattar et al.
2012
); the impact of radio frequency interference (RFI) on the SMOS
soil moisture measurements (Castro et al.
2012
; Misra and Ruf
2012
; Oliva et al.
2012
);
Table 2
Key benefits expected from satellite soil moisture observations
Area
Products
Comment
Meteorology
NWP models
Soil moisture plays a fundamental role in the transfer of water and
energy between the surface and the atmosphere. Introduction of
this variable in current NWP models will allow improving
predictions, especially important under adverse meteorological
conditions
Climatology
Models
Variability of the soil moisture time series with a long integration
period may provide relevant information for the study of climate
change
Risk
Management
Flooding risk map
The soil's risk of flooding is significantly conditioned by the
amount of water stored in the vadose zone. The generation of this
type of products will require the inclusion of soil moisture data in
hydrological and NWP models (precipitation predictions)
Fire risk map
The risk of fire is determined by several factors, including
meteorological, geophysical and biophysical factors. The
information on soil moisture may be directly assimilated in
drawing up fire risk maps as they provide direct information on
evapotranspiration, water content assimilated by vegetation and
quality of vegetation
Famine risk map
The merging of geopolitical, meteorological/climatological
information and data in the quality and estimates of agricultural
and/or marine products (derived with the help of soil moisture
data) may be of great use in early prediction of famine episodes
in areas of Earth where resources are scarce
Drought risk model
Analysing soil moisture trends in large areas may serve to generate
drought models, along with data from other sensors
Agriculture
Agricultural
production
estimate
On the basis of soil moisture data and by means of the application
of hydrological models, it is possible to determine the amount of
water assimilated by the vegetation, a value that is very useful for
estimating agricultural production
Hydrology
Models
The content of water stored in the soil is an important parameter to
be taken into consideration in any hydrological model, as it is an
indispensable variable in understanding the water cycle
Table adapted from
http://www.cp34-smos.icm.csic.es/index.htm
