Spatial variability of root zone soil water status and of fertilizer N uptake by forage crops

Hangs, R. D., Schoenau, J. J., Van Rees, K. C. J. and Knight, J. D. 2012. The effect of irrigation on nitrogen uptake and use efficiency of two willow ( Salix spp.) biomass energy varieties. Can. J. Plant Sci. 92: 563–575. Nitrogen (N) fertilizers historically have been applied to support increased productivity of purpose-grown willow (Salix spp.) biomass energy plantations. However, a frequently observed lack of willow growth response to added fertilizer N is often attributed to poor fertilizer use efficiency. The objective of this study was to determine the effect of irrigation on the recovery of broadcast15N-labelled fertilizer, applied during the final year of a 3-yr rotation, by two willow varieties. A split-split-plot experiment was established on a fertile heavy clay soil in Saskatoon, SK, Canada, which consisted of two willow varieties (Charlie and SV1), three irrigation treatments (no irrigation, 75%, and 100% field capacity), and two fertilization treatments (1× and 2× the recommended fertilizer rate of 100:30:80:20 N:P:K:S; kg ha−1). Irrigation increased fertilizer N uptake by Charlie, but had no effect on the amount taken up by SV1, which was attributed to greater N use efficiency of SV1 compared with Charlie when irrigated. Eighty-two percent of the applied fertilizer N was accounted for in the following sinks: 43% in the soil (0–60 cm), 31% in the willow tissues (i.e., stems, leaves, stump, and roots), 7% in the LFH layer, and <1% in the non-crop vegetation; the balance (approximately 18%) was presumed lost primarily through denitrification from the poorly drained soil, but possibly some may have leached below the root zone as well. Although the willow varieties accessed only a portion of the applied fertilizer N during the year of application, the majority of the residual fertilizer N was conserved within the production system and, therefore, remained available for willow uptake in subsequent years.

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Predicting Soil Water Content on Rainfed Maize through Aerial Thermal Imaging

AgriEngineering ◽

10.3390/agriengineering3040059 ◽

2021 ◽

Vol 3 (4) ◽

pp. 942-953

Author(s):

Matheus Gabriel Acorsi ◽

Leandro Maria Gimenez

Keyword(s):

Linear Regression ◽

Spatial Variability ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Water Status ◽

Canopy Temperature ◽

Crop Water ◽

Soil Water Status ◽

Physical Attributes

Restrictions on soil water supply can dramatically reduce crop yields by affecting the growth and development of plants. For this reason, screening tools that can detect crop water stress early have been long investigated, with canopy temperature (CT) being widely used for this purpose. In this study, we investigated the relationship between canopy temperature retrieved from unmanned aerial vehicles (UAV) based thermal imagery with soil and plant attributes, using a rainfed maize field as the area of study. The flight mission was conducted during the late vegetative stage and at solar noon, when a considerable soil water deficit was detected according to the soil water balance model used. While the images were being taken, soil sampling was conducted to determine the soil water content across the field. The sampling results demonstrated the spatial variability of soil water status, with soil volumetric water content (SVWC) presenting 10.4% of variation and values close to the permanent wilting point (PWP), reflecting CT readings that ranged from 32.8 to 40.6 °C among the sampling locations. Although CT correlated well with many of the physical attributes of soil that are related to water dynamics, the simple linear regression between CT and soil water content variables yielded coefficients of determination (R2) = 0.42, indicating that CT alone might not be sufficient to predict soil water status. Nonetheless, when CT was combined with some soil physical attributes in a multiple linear regression, the prediction capacity was significantly increased, achieving an R2 value = 0.88. This result indicates the potential use of CT along with certain soil physical variables to predict crop water status, making it a useful tool for studies exploring the spatial variability of in-season drought stress.

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State-space approach to evaluate spatial variability of field measured soil water status along a line transect in a volcanic-vesuvian soil

Hydrology and Earth System Sciences ◽

10.5194/hess-14-2455-2010 ◽

2010 ◽

Vol 14 (12) ◽

pp. 2455-2463 ◽

Cited By ~ 22

Author(s):

A. Comegna ◽

A. Coppola ◽

V. Comegna ◽

G. Severino ◽

A. Sommella ◽

...

Keyword(s):

Time Series ◽

Spatial Variability ◽

State Space ◽

Soil Water ◽

Hydraulic Properties ◽

Water Status ◽

State Space Model ◽

Pressure Head ◽

Line Transect ◽

Soil Water Status

Abstract. Unsaturated hydraulic properties and their spatial variability today are analyzed in order to use properly mathematical models developed to simulate flow of the water and solute movement at the field-scale soils. Many studies have shown that observations of soil hydraulic properties should not be considered purely random, given that they possess a structure which may be described by means of stochastic processes. The techniques used for analyzing such a structure have essentially been based either on the theory of regionalized variables or to a lesser extent, on the analysis of time series. This work attempts to use the time-series approach mentioned above by means of a study of pressure head h and water content θ which characterize soil water status, in the space-time domain. The data of the analyses were recorded in the open field during a controlled drainage process, evaporation being prevented, along a 50 m transect in a volcanic Vesuvian soil. The isotropic hypothesis is empirical proved and then the autocorrelation ACF and the partial autocorrelation functions PACF were used to identify and estimate the ARMA(1,1) statistical model for the analyzed series and the AR(1) for the extracted signal. Relations with a state-space model are investigated, and a bivariate AR(1) model fitted. The simultaneous relations between θ and h are considered and estimated. The results are of value for sampling strategies and they should incite to a larger use of time and space series analysis.

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