Obtaining the Spatial Distribution of Water Content along a TDR Probe Using the SCEM-UA Bayesian Inverse Modeling Scheme

Soil water content is essential to understand the hydrological cycle. It controls the surface runoff generation, water infiltration, soil evaporation and plant transpiration. This work aims to analyze the spatial distribution of top soil water content and to characterize the spatial mean and standard deviation of top soil water content over time in an experimental catchment located in the Mantiqueira Range region, state of Minas Gerais, Brazil. Measurements of top soil water content were carried out every 15 days, between May/2007 and May/2008. Using time-domain reflectometry (TDR) equipment, 69 points were sampled in the top 0.2 m of the soil profile. Geostatistical procedures were applied in all steps of the study. First, the spatial continuity was evaluated, and the experimental semi-variogram was modeled. For the development of top soil water content maps over time a co-kriging procedure was used having the slope as a secondary variable. Rainfall regime controlled the top soil water content during the wet season. Land use was also another fundamental local factor. The spatial standard deviation had low values under dry conditions, and high values under wet conditions. Thus, more variability occurs under wet conditions.

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Application of Ground-Penetrating Radar and a Combined Penetrometer–Moisture Probe for Evaluating Spatial Distribution of Soil Moisture and Soil Hardness in Coastal and Inland Windbreaks

Geosciences ◽

10.3390/geosciences10060238 ◽

2020 ◽

Vol 10 (6) ◽

pp. 238

Author(s):

Kenta Iwasaki ◽

Makoto Tamura ◽

Hirokazu Sato ◽

Kazuhiko Masaka ◽

Daisuke Oka ◽

...

Keyword(s):

Spatial Distribution ◽

Soil Moisture ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Ground Penetrating Radar ◽

Soil Compaction ◽

Soil Moisture Condition ◽

Soil Hardness ◽

Ground Penetrating

The development of a method to easily investigate the spatial distribution of soil moisture and soil hardness in tree windbreaks is necessary because these windbreaks often decline due to inappropriate soil moisture condition and soil compaction. This research examined the applicability of ground-penetrating radar (GPR) and a combined penetrometer–moisture probe (CPMP) for evaluating the spatial distribution of soil moisture and soil hardness in four windbreaks with different soil characteristics. A GPR-reflecting interface was observed at a less permeable layer in a coastal windbreak and at a depth affected by soil compaction in an inland windbreak with andosol. The spatial distribution of the groundwater table could also be evaluated by examining the attenuation of GPR reflection in a coastal windbreak. In contrast, GPR was not applicable in an inland windbreak with peat because of high soil water content near the soil surface. The CPMP could detect vertical distributions of soil hardness and soil water content regardless of soil type. The CPMP was useful for interpreting GPR profiles, and GPR was useful for interpolating the information about the horizontal distribution of soil moisture and soil hardness between survey points made with the CPMP. Thus, the combination of GPR and a CPMP is ideal for examining the two-dimensional spatial distribution of soil moisture and soil hardness at windbreaks with soils for which both methods are applicable.

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Estimation of root water uptake parameters by inverse modeling with soil water content data

Water Resources Research ◽

10.1029/2003wr002046 ◽

2003 ◽

Vol 39 (11) ◽

Cited By ~ 39

Author(s):

F. Hupet ◽

S. Lambot ◽

R. A. Feddes ◽

J. C. van Dam ◽

M. Vanclooster

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Water Uptake ◽

Inverse Modeling ◽

Root Water Uptake

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Tropospheric moisture and its relation with rainfall due to nor’westers in Bangladesh

MAUSAM ◽

10.54302/mausam.v58i2.1197 ◽

2021 ◽

Vol 58 (2) ◽

pp. 153-160

Author(s):

SAMARENDRA KARMAKAR ◽

MD. MAHBUB ALAM

Keyword(s):

Spatial Distribution ◽

Water Content ◽

Weighted Average ◽

Precipitable Water ◽

Specific Humidity ◽

Standard Errors ◽

Maximum Frequency ◽

Maximum Rainfall ◽

Average Water ◽

Instability Indices

Attempts have been made to compute the precipitable water content of the troposphere, weighted average water vapour and to correlate these parameters with different instability indices and also with the next 24-hr rainfall, next 24-hr maximum rainfall and next 24-hr country averaged rainfall in order to predicting rainfall due to nor’westers in Bangladesh. It has been found that the maximum number of nor’westers occur when the precipitable water is 25-45 mm hr-1 between 1000 and 500 hPa, the maximum frequency being 48 in the range of 35-45 mm hr-1. The spatial distribution of precipitable water indicates that the maximum precipitable water is concentrated over the area near the places of nor’westers. The specific humidity has been found to increase on the dates of occurrence of nor’westers in Bangladesh on most occasions. Maximum number of nor’westers occurs when the weighted average specific humidity between the surface (1000 hPa) and 500 hPa is 8-12 g kg-1, the maximum frequency being 43 in the range of 8-10 g kg-1. The study reveals that nor’westers have been found to occur near or at the eastern end of maximum weighted average specific humidity. It has also been found that nor’westers occur near the point of inter-section of the axes of moist and dry zones. A number of parameters of the troposphere over Dhaka at 0000 UTC on the dates of occurrence of nor’westers such as precipitable water (mm/hr), MSWI, SWI, SWI/TT, (q1000 – q850) weighted averaged specific humidity have statistically significant correlations with next 24-hour rainfall at Dhaka, next 24-hour maximum rainfall in Bangladesh and country averaged rainfall. The correlation co-efficients are relatively small and the standard errors of estimates are higher. The small correlation co-efficients are significant because of the large number of data.

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Spatial variability of soil penetration resistance influenced by season of sampling

Bragantia ◽

10.1590/s0006-87052010000500017 ◽

2010 ◽

Vol 69 (suppl) ◽

pp. 163-173 ◽

Cited By ~ 7

Author(s):

Juan José Bonnin ◽

José Manuel Mirás-Avalos ◽

Kléber Pereira Lanças ◽

Antonio Paz González ◽

Sidney Rosa Vieira

Keyword(s):

Spatial Distribution ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Soil Depth ◽

Indicator Kriging ◽

Data Series ◽

Soil Resistance ◽

Inverse Distance ◽

Cone Index

The aim of this work was to analyze the spatial distribution of soil compaction and the influence of soil water content on the resistance to penetration. The latter variable was described by the cone index. The soil at the study site was a Nitisol and the cone index data were obtained using a penetrometer. Soil resistance was assessed at 5 different depths, i.e. 0-10 cm, 10-20 cm, 20-30 cm, 30-40 cm and deeper than 40 cm, whereas soil water content was measured at 0-20 cm and 20-40 cm. Soil water conditions varied during the different samplings. Coefficients of variation for cone index ranged from 16.5% to 45.8% while those for soil water content varied from 8.96% to 21.38%. Results suggested a high correlation between soil resistance, as assessed by the cone index, and soil depth. However, the expected relation with soil water content was not observed. Spatial dependence was observed in 31 out of 35 data series, both cone index and soil water content. This structure was fitted to exponential models with nugget effect varying from 0 to 90% of the sill value. Four of the data series showed a random behaviour. Inverse distance technique was used in order to map the distribution of the variables when no spatial structure was observed. Ordinary kriging showed a smoothing of the maps compared to those from inverse distance weighing. Indicator kriging was used to map the cone index spatial distribution for recommendation of further soil management.

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