How do spatial throughfall patterns reflect in soil moisture patterns?

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>

2020 ◽  
Vol 12 (11) ◽  
pp. 234
Author(s):  
Alexsandro dos Santos Brito ◽  
Paulo Leonel Libardi ◽  
Jaedson Cláudio Anunciato Mota ◽  
Sergio Oliveira Moraes

The knowledge on the temporal stability of spatial variability of soil water storage in the crops’ root zone is of fundamental importance for soil and water management. The objective of this work was to characterize the temporal distribution of water storage in a Latossolo vermelho amarelo and identify field locations with spatial patterns of high, intermediate and low soil water storage, in 13 samplings every 14 days. The assessed period included periods of drying and water recharge of the soil, along which soil water content was determined at 60 sampling points arranged in a 5 × 5 m grid covering an area of 1250 m2 (25 × 50 m). Soil water content was determined by means of a neutron probe, at soil depths of 0.2, 0.4, 0.6, 0.8 and 1.0 m. Soil water storage was calculated by Simpson’s rule and data were analyzed by the temporal persistence of the spatial pattern. Maximum values of soil water storage were obtained at the portion of the area with water flux concentration (sampling points 4, 28 and 57), with and without outliers, and low values of soil water storage were obtained at the highers levels of the site (sampling points 12, 18 and 19), with and without outliers. The sites representing the mean soil water storage were 32, 51 and 11, considering outliers, and 8, 11 and 53, without considering outliers.


2016 ◽  
Vol 30 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Aura Pedrera-Parrilla ◽  
Eric C. Brevik ◽  
Juan V. Giráldez ◽  
Karl Vanderlinden

Abstract Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.


Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 153-162 ◽  
Author(s):  
Antonio Carlos Andrade Gonçalves ◽  
Marcos Antonio Trintinalha ◽  
Marcos Vinicius Folegatti ◽  
Roberto Rezende ◽  
Cássio Antonio Tormena

Irrigated agricultural fields usually show variable crop water demand. If water application is done to match this spatially variable demand, the water use efficiency can be substantially improved. Soil water management by irrigation has been one of the most important factors to increase crop yield. To look for the economic viability of the process, the use of several inputs, particularly water, should be done with high efficiency levels. Historically, irrigation uniformity has been evaluated above the soil surface, in which applied water was the only factor to be taken into account. However, the crop will respond to soil water content uniformity, which can differ from the uniformity of water application. To evaluate temporal stability of spatial pattern of soil water storage (SWS), this work was done on a Brazilian clayed soil. Volumetric water content from soil surface to 0,30m depth, was measured by TDR in 80 points regularly spaced (3 x 3 m) on an experimental area cultivated with bean crop, irrigated by conventional sprinkling. The evaluations were done immediately before and after a water application by irrigation. Experimental semivariograms made from values obtained in the field showed that SWS distribution was spatially structured and strongly stable in time, being regulated mainly by intrinsic factors of the soil. In addition, obtained results showed that water application uniformity did not influence the spatial distribution pattern of SWS in these soil conditions.


CATENA ◽  
2008 ◽  
Vol 73 (1) ◽  
pp. 125-133 ◽  
Author(s):  
A.K. Guber ◽  
T.J. Gish ◽  
Y.A. Pachepsky ◽  
M.T. van Genuchten ◽  
C.S.T. Daughtry ◽  
...  

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