scholarly journals The SMOS-Derived Soil Water EXtent and equivalent layer thickness facilitate determination of soil water resources

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Boguslaw Usowicz ◽  
Mateusz Lukowski ◽  
Jerzy Lipiec
Keyword(s):  
Soil Moisture ◽  
Water Resources ◽  
Soil Water ◽  
Penetration Depth ◽  
Layer Thickness ◽  
Classical Statistics ◽  
Soil Water Resources ◽  
The Impact ◽  
Equivalent Layer ◽  
Smos Satellite

Abstract The assessment of water resources in soil is important in understanding the water cycle in the natural environment and the processes of water exchange between the soil and the atmosphere. The main objective of the study was to assess water resources (in 2010–2013) in the topsoil from satellite (SMOS) and in situ (ground) measurements using the SWEX_PD approach (Soil Water EXtent at Penetration Depth). The SWEX_PD is a result of multiplying soil moisture (SM) and radiation penetration depth (PD) for each pixel derived from the SMOS satellite. The PD, being a manifold of the wavelength λ0 equal to 21 cm, was determined from the weekly SMOS L2 measurement data based on the real and imaginary part of complex dielectric constant. The SWEX_PD data were compared with soil water resources (WR) calculated from the sum of components derived from multiplication of soil moisture (SM) and layer thickness in nine agrometeorological stations located along the eastern border of Poland. Each study site consisted of seven neighbouring Discrete Global Grid pixels (nodes spaced at 15 km) including the central ones with agrometeorological stations. The study area included different types of soils and land covers. The agreement between the water resources obtained from the SWEX_PD and ground measurements (WR) was quantified using classical statistics and Bland–Altman's plots. Calibrated Layer Thickness (CLT = dbias) from 8 to 28 cm was obtained with a low values of bias (close to zero), limits of agreements, and confidence intervals for all the SWEX_PD, depending on the pixel location. The results revealed that the use of the SWEX_PD for assessing soil water resources is the most reliable approach in the study area. Additionally, the data from Bland–Altman plots and the equation proposed in these studies allowed calculation of the Equivalent Layer Thickness (ELT = $$d_{ei}^{SWEX}$$ d ei SWEX ), which corresponds to the water resources derived from the SMOS satellite at the same time as (SM) measurements performed in the agrometeorological stations. The ranges of the mean, standard deviation, minimum, maximum, and coefficient of variation (CV) of ELT among all pixels and stations were 8.28–28.7 cm, 3.27–12.66 cm, 3.03–10.87 cm, 19.23–94.97 cm, and 24.72–98.79%, respectively. The ranges of the characteristics depended on environmental conditions and their means were close to the values of the calibrated layer thickness. The impacts of soil texture, organic matter, vegetation, and their interactive effects on the differentiation and agreement of soil water resources obtained from SWEX_PD vs. data from ground measurements in the study area are discussed. Further studies are required to address the impact of the environmental factors to improve the assessment of soil water resources based on satellite SM products (retrievals).

scholarly journals Evaluation of Soil Moisture Variability in Poland from SMOS Satellite Observations

2019 ◽  
Vol 11 (11) ◽  
pp. 1280 ◽  
Author(s):  
Bogusław Usowicz ◽  
Jerzy Lipiec ◽  
Mateusz Lukowski
Keyword(s):  
Soil Moisture ◽  
North West ◽  
Moisture Contents ◽  
North East ◽  
The North ◽  
Linear Distance ◽  
Classical Statistics ◽  
Ocean Salinity ◽  
North Eastern ◽  
Smos Satellite

Soil moisture (SM) data play an important role in agriculture, hydrology, and climate sciences. In this study, we examined the spatial-temporal variability of soil moisture using Soil Moisture Ocean Salinity (SMOS) satellite measurements for Poland from a five-year period (2010–2014). SMOS L2 v. 551 datasets (latitudinal rectangle 1600 × 840 km, centered in Poland) averaged for quarterly (three months corresponding to winter, spring, summer, and autumn) and yearly values were used. The results were analysed with the use of classical statistics and geostatistics (using semivariograms) to acquire information about the nature of anisotropy and the lengths and directions of spatial dependences. The minimum (close to zero) and maximum soil moisture values covered the 0.5 m3 m−3 range. In particular quarters, average soil moisture did not exceed 0.2 m3 m−3 and did not drop below 0.12 m3 m−3; the corresponding values in the study years were 0.171 m3 m−3 and 0.128 m3 m−3. The highest variability of SM occurred generally in winter (coefficient of variation, CV, up to 40%) and the lowest value was recorded in spring (around 23%). The average CV for all years was 32%. The quarterly maximum (max) soil moisture contents were well positively correlated with the average soil moisture contents (R2 = 0.63). Most of the soil moisture distributions (histograms) were close to normal distribution and asymmetric data were transformed with the square root to facilitate geostatistical analysis. Isotropic and anisotropic empirical semivariograms were constructed and the theoretical exponential models were well fitted (R2 > 0.9). In general, the structural dependence of the semivariance was strong and moderate. The nugget (C0) values slightly deceased with increasing soil moisture while the sills (C0 + C) increased. The effective ranges of spatial dependence (A) were between 1° and 4° (110–440 km of linear distance). Generally, the ranges were greater for drier than moist soils. Anisotropy of the SM distribution exhibited different orientation with predominance from north-west to south-east in winter and spring and changed for from north-east to south-west or from north to south in the other seasons. The fractal dimension values showed that the distribution of the soil moisture pattern was less diverse (smoother) in the winter and spring, compared to that in the summer and autumn. The soil moisture maps showed occurrence of wet areas (soil moisture > 0.25 m3 m−3) in the north-eastern, south-eastern and western parts and dry areas (soil moisture < 0.05 m3 m−3) mainly in the central part (oriented towards the south) of Poland. The spatial distribution of SM was attributed to soil texture patterns and associated with water holding capacity and permeability. The results will help undertake appropriate steps to minimize susceptibility to drought and flooding in different regions of Poland.

scholarly journals Erratum to: Exploitation of patchy soil water resources by the clonal vine Ficus tikoua in karst habitats of southwestern China

2010 ◽  
Vol 33 (1) ◽  
pp. 103-103
Author(s):  
Chang-Cheng Liu ◽  
Yu-Guo Liu ◽  
Ke Guo ◽  
Da-Yong Fan ◽  
Li-Fei Yu ◽  
...  
Keyword(s):  
Water Resources ◽  
Soil Water ◽  
Southwestern China ◽  
Soil Water Resources ◽  
Karst Habitats

Area-representative validation of remotely sensed high resolution soil moisture using a cosmic-ray neutron sensor

2020 ◽  
Author(s):  
Dragana Panic ◽  
Isabella Pfeil ◽  
Andreas Salentinig ◽  
Mariette Vreugdenhil ◽  
Wolfgang Wagner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Root Zone ◽  
Spatial Scales ◽  
Temporal Frequency ◽  
Cosmic Ray ◽  
Irrigation Scheduling ◽  
Water Index ◽  
The Impact

&lt;p&gt;Reliable measurements of soil moisture (SM) are required for many applications worldwide, e.g., for flood and drought forecasting, and for improving the agricultural water use efficiency (e.g., irrigation scheduling). For the retrieval of large-scale SM datasets with a high temporal frequency, remote sensing methods have proven to be a valuable data source. (Sub-)daily SM is derived, for example, from observations of the Advanced Scatterometer (ASCAT) since 2007. These measurements are available on spatial scales of several square kilometers and are in particular useful for applications that do not require fine spatial resolutions but long and continuous time series. Since the launch of the first Sentinel-1 satellite in 2015, the derivation of SM at a spatial scale of 1 km has become possible for every 1.5-4 days over Europe (SSM1km) [1]. Recently, efforts have been made to combine ASCAT and Sentinel-1 to a Soil Water Index (SWI) product, in order to obtain a SM dataset with daily 1 km resolution (SWI1km) [2]. Both datasets are available over Europe from the Copernicus Global Land Service (CGLS, https://land.copernicus.eu/global/). As the quality of such a dataset is typically best over grassland and agricultural areas, and degrades with increasing vegetation density, validation is of high importance for the further development of the dataset and for its subsequent use by stakeholders.&lt;/p&gt;&lt;p&gt;Traditionally, validation studies have been carried out using in situ SM sensors from ground networks. Those are however often not representative of the area-wide satellite footprints. In this context, cosmic-ray neutron sensors (CRNS) have been found to be valuable, as they provide integrated SM estimates over a much larger area (about 20 hectares), which comes close to the spatial support area of the satellite SM product. In a previous study, we used CRNS measurements to validate ASCAT and S1 SM over an agricultural catchment, the Hydrological Open Air Laboratory (HOAL), in Petzenkirchen, Austria. The datasets were found to agree, but uncertainties regarding the impact of vegetation were identified.&lt;/p&gt;&lt;p&gt;In this study, we validated the SSM1km, SWI1km and a new S1-ASCAT SM product, which is currently developed at TU Wien, using CRNS. The new S1-ASCAT-combined dataset includes an improved vegetation parameterization, trend correction and snow masking. The validation has been carried out in the HOAL and on a second site in Marchfeld, Austria&amp;#8217;s main crop producing area. As microwaves only penetrate the upper few centimeters of the soil, we applied the soil water index concept [3] to obtain soil moisture estimates of the root zone (approximately 0-40 cm) and thus roughly corresponding to the depth of the CRNS measurements. In the HOAL, we also incorporated in-situ SM from a network of point-scale time-domain-transmissivity sensors distributed within the CRNS footprint. The datasets were compared to each other by calculating correlation metrics. Furthermore, we investigated the effect of vegetation on both the satellite and the CRNS data by analyzing detailed information on crop type distribution and crop water content.&lt;/p&gt;&lt;p&gt;[1] Bauer-Marschallinger et al., 2018a: https://doi.org/10.1109/TGRS.2018.2858004&lt;br&gt;[2] Bauer-Marschallinger et al., 2018b: https://doi.org/10.3390/rs10071030&lt;br&gt;[3] Wagner et al., 1999: https://doi.org/10.1016/S0034-4257(99)00036-X&lt;/p&gt;

scholarly journals The Relationship between Soil Moisture and LAI in Different Types of Soil in Central Eastern China

2016 ◽  
Vol 17 (11) ◽  
pp. 2733-2742 ◽  
Author(s):  
Li Liu ◽  
Renhe Zhang ◽  
Zhiyan Zuo
Keyword(s):  
Particle Size ◽  
Soil Moisture ◽  
Soil Water ◽  
Water Retention ◽  
Eastern China ◽  
Soil Water Retention ◽  
Different Types ◽  
Central Eastern ◽  
The Impact ◽  
The Relationship

Abstract As important parameters in the land–atmosphere system, both soil moisture (SM) and vegetation play a significant role in land–atmosphere interactions. Using observational data from clay and sand stations over central eastern China, the relationship between leaf area index (LAI) and SM (LAI–SM) in different types of soil was investigated. The results show that the LAI–SM correlation is significantly positive in clay but not significant in sand. The physical causes for the discrepant LAI–SM correlations in different types of soil were explored from the perspectives of evapotranspiration (ET) and soil water retention. In clay stations, increasing LAI is associated with greater soil-water-retention capacity. Although the increasing LAI corresponds to increasing ET, the impact of ET on SM is weak because of the small particle size of soil. Consequently, the LAI–SM relationship in clay is significantly positive. In sand stations, ET is negatively correlated with SM owing to the large soil particle size, resulting in a negative LAI–SM correlation in sand. However, soil water retention is weakened by the increased LAI, which may be an important factor causing the insignificant LAI–SM correlation in sand.

Soil water drying and recharge rates as affected by tillage under continuous barley and barley-canola cropping systems in northwestern Canada

2001 ◽  
Vol 81 (1) ◽  
pp. 45-52 ◽  
Author(s):  
R H Azooz ◽  
M A Arshad
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Sandy Loam ◽  
Time Domain Reflectometry ◽  
Sandy Loam Soil ◽  
Soil Conditions ◽  
Silt Loam ◽  
Silt Loam Soil ◽  
Loam Soil ◽  
The Impact

In areas of the northwestern Canadian Prairies, barley and canola are grown in a short growing season with high rainfall variability. Excessively dry soil in conventional tillage (CT) in dry periods and excessively wet soil in no-tillage (NT) in wet periods could cause a significant decrease in crop production by influencing the availability of soil water. The effects of CT, NT and NT with a 7.5-cm residue-free strip on the planting rows (NTR) on soil water drying (–dW/dt) and recharge (dW/dt) rates were studied in 1992 and 1993 during wet and dry periods to evaluate the impact of NTR, NT and CT systems on soil moisture condition. The soils, Donnelly silt loam and Donnelly sandy loam (both Gray Luvisol) were selected and soil water content by depth was measured by time domain reflectometry. Water retained at 6 matric potentials from –5 to –160 kPa were observed. In the field study, –dW/dt was significantly greater in CT than in NT in the silt loam for the 0- to 30-cm layer during the first 34 d after planting in 1992. The 0- to 30-cm soil layer in CT and NTR dried faster than in NT during a period immediately following heavy rainfall in the silt loam in 1993. The drying coefficient (–Kd ) was significantly greater in CT and NTR than in NT in the silt loam soil in 1993 and in the sandy loam soil in 1992 in the top 30-cm depth. The recharge coefficient (Kr) was significantly greater in NT and NTR than in CT for the silt loam soil. The NTR system increased the –dW/dt by 1.2 × 10-2 to 12.1 × 10-2 cm d-1 in 1992 and 1993 in the silt loam soil and by 10.2 × 10-2 cm d-1 in 1993 in the sandy loam soil as compared with NT. The dW/dt was 8.1 × 10-2 cm d-1 greater in NTR in 1992 and 1993 in the silt loam soil and was 1.9 × 10-2 greater in NTR in 1992 than in CT in the sandy loam soil. The laboratory study indicated that NT soils retained more water than the CT soils. The NTR practice maintained better soil moisture conditions for crop growth than CT in dry periods than NT in wet periods. Compared with NT, the NTR avoided prolonged near-saturated soil conditions with increased soil drying rate under extremely wet soil. Key words: Water drying, water recharge, water depletion, wet and drying periods, hydraulic properties, soil capacity to retain water

Soil Water Measurement as Basis to Optimize Irrigation Scheduling: A Review

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 553f-554
Author(s):  
A.K. Alva ◽  
A. Fares
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Real Time ◽  
Soil Water Content ◽  
Root Zone ◽  
Soil Water Potential ◽  
Irrigation Scheduling ◽  
Rooting Depth ◽  
The Impact

Supplemental irrigation is often necessary for high economic returns for most cropping conditions even in humid areas. As irrigation costs continue to increase more efforts should be exerted to minimize these costs. Real time estimation and/or measurement of available soil water content in the crop root zone is one of the several methods used to help growers in making the right decision regarding timing and quantity of irrigation. The gravimetric method of soil water content determination is laborious and doesn't suite for frequent sampling from the same location because it requires destructive soil sampling. Tensiometers, which measure soil water potential that can be converted into soil water content using soil moisture release curves, have been used for irrigation scheduling. However, in extreme sandy soils the working interval of tensiometer is reduced, hence it may be difficult to detect small changes in soil moisture content. Capacitance probes which operate on the principle of apparent dielectric constant of the soil-water-air mixture are extremely sensitive to small changes in the soil water content at short time intervals. These probes can be placed at various depths within and below the effective rooting depth for a real time monitoring of the water content. Based on this continuous monitoring of the soil water content, irrigation is scheduled to replenish the water deficit within the rooting depth while leaching below the root zone is minimized. These are important management practices aimed to increase irrigation efficiency, and nutrient uptake efficiency for optimal crop production, while minimizing the impact of agricultural non-point source pollutants on the groundwater quality.

Exploitation of patchy soil water resources by the clonal vine Ficus tikoua in karst habitats of southwestern China

2010 ◽  
Vol 33 (1) ◽  
pp. 93-102 ◽  
Author(s):  
Chang-Cheng Liu ◽  
Yu-Guo Liu ◽  
Ke Guo ◽  
Da-Yong Fan ◽  
Li-Fei Yu ◽  
...  
Keyword(s):  
Water Resources ◽  
Soil Water ◽  
Southwestern China ◽  
Soil Water Resources ◽  
Karst Habitats
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