Soil moisture and its importance/measurements

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Soil moisture and its importance

Soil moisture

The soil medium is often divided into three phases consisting of liquid, gaseous, and solid phases. Soil matter, the sum of the mineral matter and the organic matter, represents the solid phase amounting about to 50 % of the entire soil medium (Hillel, 1980). Pore space represents the other 50 %, which consists of the liquid phase (i.e., the soil water) and the gaseous phase (i.e., the soil atmosphere) (Hillel, 1980). The components of the soil medium are displayed in Fig. 2.1. Pore spaces between soil particles can be filled by air or water, the latter is often referred to as soil moisture and is also known as soil water content. In other words, the quantity of water that is present in the unsaturated zone, held in the soil between the surface and the groundwater level, is known as soil moisture. The soil water moves freely down by gravity and up by capillary force. It is then extracted by plant roots, evaporates at the surface, or recharges the groundwater (Strangeways, 2000). It is a small fraction of the world’s fresh water supply (Dingman, 2002), and it is generally expressed in gravimetric units (g/cm3), volumetric units (m3/m3; m3 water per m3 bulk soil volume) or percent (% vol.) (Dingman, 2002; Smith & Mullins, 2000).
Soil is saturated when the pore spaces between the soil particles are totally filled by water without any air pockets (See Fig. 2.1). This water, within a day or longer, drains-with the exception if the water table is within the soil which occurs quite often- downwards and away under gravity and leaves the soil at the so called “field capacity” with certain quantity of water that holds against gravity (Twarakavi et al., 2009; Veihmeyer & Hendrickson, 1931). At this point, the spaces between the soil particles are filled with a mixture of water and air pockets (see Fig. 2.1). When the plants can no longer extract the necessary water for growth and therefore suffer and they start to wilt before dying, the soil is described as at “wilting point” (see also Fig. 2.1) (Briggs & Shantz, 1912).
Fig. 2 – 1 Components of soil medium (After O’Geen, 2012).
The capacity of the soil to store water depends on the size, type, shape, the properties of the solid phase (in particular its electrical charges), and the continuity of the pores of the soil. Temporal variations and spatial distribution of soil moisture can be influenced by precipitation, soil texture, topography, organic matter content, porosity, soil structure, and vegetation and land cover. Soil texture (i.e. percentage of clay, sand, and silt) and soil structure control the water-holding capacity while topography (i.e. variations in slope and aspect) affects soil moisture distribution i.e. soil moisture movements. Table 2.1 presents the influence of the relief elements (aspect & slope) on the spatial distribution of soil moisture.
The soil moisture values represent the ratio of soil moisture on a slope and soil moisture on a flat surface with the same type of soil and vegetation for four aspects (North, South, East and West) and for four slope parts(upper, middle, lower and the foot of a slope) for summer period of the year (Svetlitchnyi et al., 2003). Soil, for instance, is dryer at flat surface than at foot of slop, and the slopes face west and south are dryer than the slopes which face east and north, this may be explained by the relatively high radiation exposure of the sun (Svetlitchnyi et al., 2003). The effects of north and south may be not equal in the Northern and Southern Hemisphere.
Vegetation (i.e. vegetation type and density) influences infiltration, runoff, and evapotranspiration, thus, influences the variations of soil moisture at different space and time-scales (English et al., 2005). In addition, climate (i.e. precipitation, solar radiation, wind, and humidity) controls the dynamics of soil moisture. Precipitation is the most important climatic forcing for soil moisture content and its distribution, which induces along with evaporation the trends in aridity and saturation of soil (D’Odorico & Porporato, 2004; Koster et al., 2003).

General importance of soil moisture for the environment and our climate system

Water is a vital source of all life on Earth’s climate system. It circulates continuously between oceans, the atmosphere, and land surface due to the solar energy. This circulation and conservation of the Earth’s water, known as the water cycle (see Fig. 2.2), is a critical component for our climate system.
A schematic diagram of this global water cycle with the quantities of water volumes and fluxes are shown in Fig. 2.3. Fig. 2.3 illustrates the qualitative proportions of the global water reservoirs and transports. However, precise values are not known yet; therefore, the specified numbers can differ from others given in the literature.
Fig. 2 – 3 Schematic diagram of the Earth’s water cycle. Reservoir volumes (boxes) are stated in 103 km3, water fluxes (arrows) in 103 km3 per year. Adapted from Oki (1999).
Although the soil moisture only represents a small proportion (0.05 %) of the total of fresh water volume, as can be seen in Fig. 2.3 compared to the other components, its influence on the global water cycle is of great importance and it plays a major role in the water cycle. Soil moisture is a key variable in the exchanges of water, energy, carbon between the land surface interface and the atmosphere. It is also an important factor in many fields: in atmospheric circulation (Walker & Houser, 2004), as soil moisture influences energy and mass transfer across the landscape boundary (Arora & Boer, 2006; Findell & Eltahir, 2003), in water resources management, for instance in flood analyses and drought monitoring (Michele
& Salvadori, 2002), in agricultural management, by defining appropriate irrigation amounts and intervals (Hanson et al., 2000), in soil science, it is a key parameter in ecology and biogeochemistry to determine potential land slide and can help in soil erosion’s predictions in semi-arid areas (Kiome, 1992), and in plant biology, soil moisture is the key factor for plant water stress (Veihmeyer & Hendrickson, 1950).
More specifically, soil moisture can be of significant importance resource for plants as well as for human activities:
a) The soil moisture of the root zone is a limiting factor for plant growth, and it is optimal when not too dry and not too wet over a long time period for plants to survive. Therefore, information of the appropriate amount of soil water is essential for cultivation of plants and agriculture in general. This helps in irrigating crop fields more efficiently. Furthermore, information of soil moisture patterns helps agronomist to enhance irrigation’s scheduling and better crop yield predicting in arid and semi-arid areas (Tao et al., 2003).
b) The soil moisture is a variable of major importance to assess the potential for risks in the case of extreme events. Soil moisture conditions (excessively saturated or dry) can be signs of warning of subsequent flooding (as the occurrence and intensity of flooding are strongly influenced by the soil’s ability to take up a certain amount of water) or drought (Dingman, 2002; Richter & Semenov, 2005).
c) Soil moisture plays an important role in the hydrological models, as it controls the re-distribution of the precipitation into runoff and infiltration. Therefore, accurate observations of soil moisture are essential before estimating water fluxes (Parajka et al., 2006).
d) Soil moisture plays an important role in meteorological and climate models, as its temporal variation and spatial distribution play a major role in the partitioning of the solar energy into sensible and latent heat fluxes at both global and local scales (Robock et al., 1998). Soil moisture availability plays a significant role in the biases of surface temperature in climate models (Cheruy et al., submitted for publication). Accurate estimates of soil moisture are necessary for improving numerical weather predictions, whereas inaccurate soil moisture initialization leads to large errors in climate predictions (Robock et al., 1998; Rowntree & Bolton, 1983).
e) Soil moisture spatio-temporal variations over land influence runoff, inflow, controls evaporation and transpiration, thus regulates the extent of groundwater recharges (Mohanty & Skaggs, 2001). More generally, soil moisture influences the discharge which is the most accessible fresh water resource.

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Measurements of soil moisture

There are different methods for soil moisture measurements employed for different applications. These include measurements techniques: (i) direct and indirect in-situ measurements (e.g. radiological methods, neutron attenuation, gamma absorption, soil-water dielectrics, microwave probe, etc.) and (ii) emerging technologies (remote sensing), and estimation techniques: (i) land surface models and (ii) integration of the previous methods in the so called assimilation. All these methods differ significantly by the accuracy, complexity, technique, and spatio-temporal scales. These methods are briefly presented in the following sections.

In-situ measurements

In-situ measurements methods have several common advantages including, but not limited to, relatively accurate for the sampling point and measurements of soil moisture could be taken at several depths. On the other hand, there are common disadvantages including, but not limited to, local scale and thus cannot be representative for larger scales, time consuming, and costly. Nevertheless, models and remote sensing up to date use in-situ measurements to calibrate and validate their predictions and observations, respectively.

Table of contents :

1. Introduction
1.1 Background and Motivation
1.2 Dissertation objectives
1.3 Dissertation outline
2. Soil moisture and its importance/measurements
2.1 Soil moisture and its importance
2.1.1 Soil moisture
2.1.2 General importance of soil moisture for the environment and our climate system
2.2 Measurements of soil moisture
2.2.1 In-situ measurements
2.2.2 Remote sensing of soil moisture
2.2.2.1 Optical remote sensing (Visible and near-infrared)
2.2.2.2 Thermal Infrared remote sensing
2.2.2.3 Microwave remote sensing
2.2.3 Soil moisture modelling
2.2.3.1 MERRA-Land
2.2.4 Soil moisture data assimilation
2.2.4.1 SM-DAS-2
3. SMOS/ASCAT/AMSR-E Mission overview
3.1 SMOS
3.1.1 SMOS mission overview
3.1.2 SMOS products overview
3.1.3 SMOS SSM algorithm
3.1.3.1 Input datasets
3.1.3.2 The SMOSL2 algorithm
3.1.3.3 The SMOSL3 SSM algorithm
3.1.4 SMOS RFI issues
3.2 ASCAT
3.2.1 ASCAT mission overview
3.2.2 ASCAT SSM algorithm
3.2.3 ASCAT Products
3.3 AMSR-E
3.3.1 AMSR-E mission overview
3.3.2 AMSR-E VU-NASA algorithm:
3.4 Pre-Processing
4. Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates
4.1 Introduction
4.2 Materials and methods
4.2.1 Global-scale soil moisture datasets
4.2.1.1 SMOSL3
4.2.1.2 AMSRM
4.2.1.3 ECMWF soil moisture analysis
4.2.2 Pre-processing
4.2.3 Comparison metrics
4.2.4 Regional-scale analyses
4.2.5 SSM seasonal anomalies
4.2.6 Global-scale analyses
4.3 Results
4.3.1 Comparison of SMOSL3 ascending and descending overpasses
4.3.2 Comparison of the SSM time series over eight selected sites
4.3.3 Spatial analysis of SSM retrievals at global scale
4.3.4 Biome influence
4.3.5 Influence of leaf area index (LAI)
4.4 Discussion and conclusions
5. Global-scale comparison of passive (SMOS) and active (ASCAT) satellite based microwave soil moisture retrievals with soil moisture simulations (MERRA-Land) 
5.1 Introduction
5.2 Materials and methods
5.2.1 Surface soil moisture datasets
5.2.1.1 SMOSL3
5.2.1.2 ASCAT
5.2.1.3 MERRA-Land
5.2.2 Pre-processing
5.2.3 Comparison using classical metrics
5.2.4 Comparison using Hovmöller diagrams (space–time distribution)
5.2.5 Comparison using triple collocation error model
5.3 Results
5.3.1 Spatial Analysis of SSM retrievals at the global scale
5.3.2 Influence of leaf area index (LAI)
5.3.3 Hovmöller diagrams
5.3.4 Triple collocation error model
5.4 Discussion and conclusions
5.4.1 Summary of the results
5.4.2 Discussion
6. Testing simple regression equations to derive long-term global soil moisture datasets from satellite-based brightness temperature observations
6.1 Introduction
6.2 Materials and methods
6.2.1 Datasets
6.2.1.1 AMSR-E Level 3 brightness temperatures
6.2.1.2 SMOS level 3 soil moisture products
6.2.1.3 ECMWF Soil temperature
6.2.1.4 MODIS NDVI
6.2.2 Methods
6.2.2.1 Regression calibration
6.2.2.2 Producing SSM data
6.3 Results and discussion
6.3.1 Regression calibration
6.3.2 Regression’s quality and new AMSR-E SSM products
6.3.3 Product comparison with original AMSR-E SSM product
6.3.4 Product evaluation against a reference (MERRA-Land)
6.4 Summary and conclusions
7. Conclusions and perspectives
7.1 Summary
7.2 Main conclusions
7.3 Limitations
7.4 Perspectives
References

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