5.2. Assimilation with microwave-based data

Data assimilation procedures are downscaled schemes of microwave-based soil moisture, which has a scale of several tens of kilometers, to one to a couple of kilometers. These schemes have recently been improved [47–50] using visible, near-infrared, and thermal-infrared satellite data, which have more precise spatial resolution than microwaves. These procedures can be competitive with thermal inertia procedures to derive surface soil moisture. However, one weak point with regard to microwave-based soil moisture (soil moisture active passive: SMAP) was noted, and it was a dry down process occurred after an antecedent rainfall that was too rapid for in-situ soil moisture measurement [50]. By contrast, the thermal inertiaderived soil moisture agreed fairly well with the in-situ soil moisture found in several dry down processes (M2018). This agreement may be because the sensing depth of the surface microwave-based soil moisture was shallower than the in-situ measurement and sensitive to the soil moisture itself [51], whereas the representative depth scale of the FRM is not as sensitive to soil moisture and almost agrees with the in-situ measuring depth (M2018). Regarding the spatial resolution of the satellite sensors, an Earth observing satellite with a more precise spatial resolution in the visible, near-infrared, and thermal-infrared bands, the Global Change Observation Mission-Climate (GCOM-C), was recently launched in 2017 by the Japan Aerospace Exploration Agency (JAXA), and the data will be available for general use within 1 year. Its LST spatial resolution is 500 m, twice than that of the MODIS resolution, which will benefit both data assimilation and thermal inertia procedures. Another GCOM-C type satellite will hopefully be able to be operated like MODIS. On the other hand, microwave-based soil moisture can be obtained almost every day regardless of the sky conditions (leading to partial lack of data in some regions due to the satellite orbit). There are trade-offs that have between the above described advantages and disadvantages of the respective procedures.

on the estimated thermal inertia values after Fécan [55]. The threshold wind speed or friction velocity for dust emissions according to surface soil moisture was examined using carefully designed wind tunnel experiments with multiple soil types, and the threshold friction velocity was found to be related to the soil matric potential and not aligned with the gravimetric soil moisture for the examined soil types [55–58]. The matric potential is not as readily available as the soil moisture, otherwise the function connecting the two variables is known in advance. Considering that it should be difficult to obtain the relationship between thermal inertia and matric potential, and practical relationships between thermal inertia-derived soil moisture and

Thermal Inertia-Based Method for Estimating Soil Moisture

http://dx.doi.org/10.5772/intechopen.80252

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In the region where the Earth's surface and subsurface are seasonally frozen, dust emissions begin to occur (early spring) when only the surface is melted and dry but not the subsurface just beneath a thin surface layer. The thermal inertia at the representative depth is still affected by the frozen soil, but the surface radiative temperature is highly positive in degrees Celsius due to the dried surface, which is suitable for dust emission (in other words, high erodibility) if the wind is necessarily strong. The temperature difference was up to at most 20C (unpublished result). Dust emission is likely to occur in early spring when the meteorological conditions are likely to be windy; however, an empirical relationship between thermal inertiaderived soil moisture and threshold wind speed using observations during spring to early autumn [28] is difficult to apply because thermal inertia is likely to be underestimated in early spring possibly due to the large difference between the surface and the subsurface temperatures. There is no common formulation for thermal inertia-derived soil moisture with regard to

Monitoring the spatial distribution of surface soil moisture over a wide agricultural area is required for optimal water management. An example presented by Minecapllia et al. [30] showed the spatial distribution of thermal inertia over a small-scale cultivated field using

Root zone soil moisture has been examined in several studies [50, 59], using a thermal inertia procedure with the FRM applied to the soil water transport and data assimilation procedures, respectively. All of the studies noted that the initial values of the root zone soil moisture were significant for reducing the simulation error. It was noted that the FRM applied to soil moisture was not straight-forward like the soil temperature because of the nonlinearity in soil water transport that representatively appeared in the Richards equation [34, 59]. Various processes of water transport in soil such as infiltration, redistribution, and vapor transport should be

The precise spatial resolution of satellite LST is better used for coinciding topography or land use on approximately a 1-km scale. Overlaying or assimilating thermal inertia-derived soil moisture over a common scale of topography or land use in the range of a watershed should contribute to the water budget estimation (discharge, infiltration, and evapotranspiration) when precipitation is known. If agricultural land use is resolved at a 1-km resolution, it is

threshold wind speed with regard to individual soil types are required.

the threshold wind speed in early spring or other seasons.

airborne thermal images taken in the daytime and nighttime.

5.4. Water budget and management

improved [60].

The Global Satellite Mapping of Precipitation (GSMaP) [52] operated by JAXA is a system that measures the spatio-temporal distribution of precipitation at the Earth's surface on a 0.1 spatial scale and a 1-hour temporal scale, and the latest data are added every hour. In arid and semi-arid regions far from rivers, short-term discharge and infiltration should be negligible, accordingly the water budget is calculated using the thermal inertia-derived soil moisture and GSMaP precipitation. Currently, there is not adequate accuracy for both variables to calculate a water budget, but it is worth tackling this issue to estimate regional water cycles and resources.
