at 6 p.m. and 6 a.m. (local solar time), respectively [59, 76]. SMAP includes a 6 m
diameter conically scanning, deployable mesh reflector antenna which is shared by
both the radiometer and the radar. One of the advantages of SMAP over SMOS is it
combines an L-band radar with an L-band radiometer integrating the strengths of
both active and passive remote sensing for improved soil moisture monitoring. As a
result, the resolution of its soil moisture products is supposed to be high (~3 km).
However the satellite’s radar instrument stopped working on July 7, 2015, due to a
problem in the radar’s high-power amplifier [77]. Currently the SMAP can only
retrieve soil moisture products from its radiometer with a resolution around 36 km
[78]. Another advantage of SMAP is it includes a special flight hardware which is
useful in detecting and filtering radio-frequency interference (RFI), so in many
RFI-affected regions, the data loss problem can be prevented [79].
3 Hydrological Evaluation of Satellite Soil Moisture
As aforementioned, satellite remote sensing techniques are a major tool in retrieving
soil moisture information on a large scale [11] and are able to provide soil moisture
observations globally [58]. In particular, the data acquired by microwave sensors,
both active and passive, have been employed to provide detailed soil moisture
variability in recent years [80]. Due to SMOS’s longer period of data records,
numerous studies have been carried out. Therefore, this paper focuses on discussing
the issues related to its hydrological applications only (nevertheless, the discussions
are general and applicable to other similar satellites).
SMOS soil moisture is calculated from the multi-angular and fully polarised
L-band passive microwave measurements [75]. A number of studies have reported
SMOS soil moisture retrieval, downscaling, and its validation against point-based
in situ measurements over different regions [20, 68, 81–86]. However, in situ
measurements are not directly relevant to hydrological modelling because they
cannot be directly placed into a state variable of a hydrological model. On the
other hand, some attempts have been made on hydrological evaluations of SMOS
soil moisture, such as the ones carry out by [8, 11, 20–22]. The results show the
SMOS soil moisture is not accurate enough for direct hydrological modelling usage,
and additional work such as using separated algorithms for high- and low-vegetated
seasons is needed for improved performance [8].
In comparison with shorter-wavelength satellites such as AMSR-E, SMOS
generally provides more accurate soil moisture information. However some studies
demonstrate that AMSR-E is actually more accurate than SMOS over certain regions
[87–89]. From the temporal availability point, SMOS soil moisture observations
are significantly less available than AMSR-E’s, as shown in Fig. 4.
Satellite Remote Sensing of Soil Moisture for Hydrological Applications. . .
269
diameter conically scanning, deployable mesh reflector antenna which is shared by
both the radiometer and the radar. One of the advantages of SMAP over SMOS is it
combines an L-band radar with an L-band radiometer integrating the strengths of
both active and passive remote sensing for improved soil moisture monitoring. As a
result, the resolution of its soil moisture products is supposed to be high (~3 km).
However the satellite’s radar instrument stopped working on July 7, 2015, due to a
problem in the radar’s high-power amplifier [77]. Currently the SMAP can only
retrieve soil moisture products from its radiometer with a resolution around 36 km
[78]. Another advantage of SMAP is it includes a special flight hardware which is
useful in detecting and filtering radio-frequency interference (RFI), so in many
RFI-affected regions, the data loss problem can be prevented [79].
3 Hydrological Evaluation of Satellite Soil Moisture
As aforementioned, satellite remote sensing techniques are a major tool in retrieving
soil moisture information on a large scale [11] and are able to provide soil moisture
observations globally [58]. In particular, the data acquired by microwave sensors,
both active and passive, have been employed to provide detailed soil moisture
variability in recent years [80]. Due to SMOS’s longer period of data records,
numerous studies have been carried out. Therefore, this paper focuses on discussing
the issues related to its hydrological applications only (nevertheless, the discussions
are general and applicable to other similar satellites).
SMOS soil moisture is calculated from the multi-angular and fully polarised
L-band passive microwave measurements [75]. A number of studies have reported
SMOS soil moisture retrieval, downscaling, and its validation against point-based
in situ measurements over different regions [20, 68, 81–86]. However, in situ
measurements are not directly relevant to hydrological modelling because they
cannot be directly placed into a state variable of a hydrological model. On the
other hand, some attempts have been made on hydrological evaluations of SMOS
soil moisture, such as the ones carry out by [8, 11, 20–22]. The results show the
SMOS soil moisture is not accurate enough for direct hydrological modelling usage,
and additional work such as using separated algorithms for high- and low-vegetated
seasons is needed for improved performance [8].
In comparison with shorter-wavelength satellites such as AMSR-E, SMOS
generally provides more accurate soil moisture information. However some studies
demonstrate that AMSR-E is actually more accurate than SMOS over certain regions
[87–89]. From the temporal availability point, SMOS soil moisture observations
are significantly less available than AMSR-E’s, as shown in Fig. 4.
Satellite Remote Sensing of Soil Moisture for Hydrological Applications. . .
269