Role of soil properties in controlling the spatial variations of soil water content in varied fields

2017 ◽  
Vol 06 (03) ◽  
Author(s):  
Qu Jili ◽  
Hu Da
2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Glécio Machado Siqueira ◽  
Jorge Dafonte Dafonte ◽  
Montserrat Valcárcel Armesto ◽  
Ênio Farias França e Silva

The apparent soil electrical conductivity (ECa) was continuously recorded in three successive dates using electromagnetic induction in horizontal (ECa-H) and vertical (ECa-V) dipole modes at a 6 ha plot located in Northwestern Spain. One of the ECadata sets was used to devise an optimized sampling scheme consisting of 40 points. Soil was sampled at the 0.0–0.3 m depth, in these 40 points, and analyzed for sand, silt, and clay content; gravimetric water content; and electrical conductivity of saturated soil paste. Coefficients of correlation between ECaand gravimetric soil water content (0.685 for ECa-V and 0.649 for ECa-H) were higher than those between ECaand clay content (ranging from 0.197 to 0.495, when different ECarecording dates were taken into account). Ordinary and universal kriging have been used to assess the patterns of spatial variability of the ECadata sets recorded at successive dates and the analyzed soil properties. Ordinary and universal cokriging methods have improved the estimation of gravimetric soil water content using the data of ECaas secondary variable with respect to the use of ordinary kriging.


2020 ◽  
Vol 53 (7) ◽  
pp. 941-949
Author(s):  
M. I. Makarov ◽  
R. V. Sabirova ◽  
M. S. Kadulin ◽  
T. I. Malysheva ◽  
A. I. Zhuravleva ◽  
...  

2011 ◽  
Vol 51 (No, 7) ◽  
pp. 296-303 ◽  
Author(s):  
T. Behrens ◽  
K. Gregor ◽  
W. Diepenbrock

Remote sensing can provide visual indications of crop growth during production season. In past, spectral optical estimations were well performed in the ability to be correlated with crop and soil properties but were not consistent within the whole production season. To better quantify vegetation properties gathered via remote sensing, models of soil reflectance under changing moisture conditions are needed. Signatures of reflected radiation were acquired for several Mid German agricultural soils in laboratory and field experiments. Results were evaluated at near-infrared spectral region at the wavelength of 850 nm. The selected soils represented different soil colors and brightness values reflecting a broad range of soil properties. At the wavelength of 850 nm soil reflectance ranged between 10% (black peat) and 74% (white quartz sand). The reflectance of topsoils varied from 21% to 32%. An interrelation was found between soil brightness rating values and spectral optical reflectance values in form of a linear regression. Increases of soil water content from 0% to 25% decreased signatures of soil reflectance at 850 nm of two different soil types about 40%. The interrelation of soil reflectance and soil moisture revealed a non-linear exponential function. Using knowledge of the individual signature of soil reflectance as well as the soil water content at the measurement, soil reflectance could be predicted. As a result, a clear separation is established between soil reflectance and reflectance of the vegetation cover if the vegetation index is known.


1988 ◽  
Vol 18 (4) ◽  
pp. 427-434 ◽  
Author(s):  
Richard Barry ◽  
André P. Plamondon ◽  
Jean Stein

An analysis of hydrologic soil properties and the prediction of volumetric soil water content during four summers have been done for a site located in the balsam fir (Abiesbalsamea (L.) Mill.) forest of the Lac Laflamme watershed. The hydrologic properties were used to identify three different soil layers, THIRSTY, a soil moisture model using the Penman evapotranspiration formula, was applied to predict daily volumetric water content of these layers. Predictions of soil moisture with the calibrated model were close to the observed data for the median layer (20–60 cm from the soil surface) and less accurate for the surface layer (0–20 cm) where important transpiration activities take place. The model appeared unreliable for predicting soil water content of the bottom layer (60–100 cm) which was often saturated by groundwater. The calibration of the model required modifications of the observed values of the available water content at field capacity and the relative root density factor and was adjusted with the crop coefficient of the Penman evapotranspiration formula. These modifications of observed physical parameters raise the question of the feasibility of extrapolating the model to other sites without extensive calibration. The high sensitivity to variations of the crop coefficient applied to the evapotranspiration equation indicated that a more physically based transpiration model, supported by field-oriented process studies, would be required to improve the model's performance.


2021 ◽  
Author(s):  
Christine Fischer ◽  
Murray Lark ◽  
Johanna C. Metzger ◽  
Thomas Wutzler ◽  
Anke Hildebrandt

<div> <p>This study investigates whether and how vegetation cover affects the spatial heterogeneity and vertical penetration of water through the Upper Critical Zone (UCZ). We assessed rainfall, throughfall and soil water contents on a 1‐ha temperate mixed beech forest plot in Germany. Throughfall and soil water content in two depths (7.5 cm and 27.5 cm) were measured on an event basis during the 2015 - 2016 growing season in independent high‐resolution stratified random designs. We calculated the increase of soil water content (Δθ) due to the rainfall by the difference between measurements at the beginning (pre-event) and the maximum soil water content after the end of rainfall event (post-event). Since throughfall and soil water content cannot be assessed at the same location, we used kriging to derive the throughfall values at the locations where soil water content was measured. We explore the spatial variation and temporal stability of throughfall and soil water content and evaluate the effects of throughfall, soil properties (field capacity and air capacity), and vegetation parameters (next tree distance) on soil water content variability.</p> <p>Throughfall patterns were related to canopy density although correlation length decreased with increasing event size. Temporal stability was high, leading to persistently high and lower input locations across rainfall events.</p> <p>A linear mixed effect model analysis confirmed that the soil water content increase due to precipitation depended on throughfall patterns, in that more water was stored in the soil where throughfall was enhanced. This was especially the case in large events and in both investigated soil depths. However, we also identified additional factors that enhanced or decreased water storage in the soil, and probably indicate fast drainage and runoff components. Locations with low topsoil water content tended to store less of the available water, indicating the role of preferential flow. In contrast in subsoil, locations with high water content, and probably poor drainage, stored less water, indicating lateral flow. Also, distance to the next tree and air capacity modified soil water storage.</p> <p>Spatial soil water content patterns shortly before a rainfall event (pre-event conditions) seem to be a key factor in soil water content increase, and also explained much of soil water content shortly after the rainfall event. Pre-event soil water content was mostly driven by random local effects, probably microtopography and root water uptake, which were not quantified in this study. The remaining spatial variation was explained by air capacity in both soil layers, indicating the role of macroporosity.</p> <p>Our findings show at the same time systematic patterns of times and locations where the soil capacity to store water is reduced and water probably conducted quickly to greater depth. Not only soil moisture patterns but also deeper percolation may depend on small scale spatial heterogeneity of canopy input patterns.</p> </div>


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