Temporal variability of soil water storage evaluated for a coffee field

Abstract

Abstract. Sampling field soils to estimate soil water content and soil water storage (S) is difficult due to the spatial variability of these variables, which demands a large number of sampling points. Also, the methodology employed in most cases is invasive and destructive, so that sampling in the same positions at different times is impossible. However, neutron moderation, time domain reflectrometry, and, more recently, frequency domain reflectrometry methodologies allow measurements at the same points over long time intervals. This study evaluates a set of neutron probe data, collected at 15 positions placed randomly along a coffee crop contour line, over 2 years at 14-day intervals. The temporal stability of S was again demonstrated, so that wetter or dryer locations remain so over time, and the definition of such positions in the field reduces the number of sampling points in future S evaluations under similar conditions. An analysis was made to determine the minimum number of sampling points to obtain the average S of the field within a chosen level of significance. Classical statistical analysis indicated that the 15 measurement positions could be reduced to four or even to one position to obtain a reliable field S average. State-time analysis showed S estimations depend more on previous measurements of rainfall P (52%) than on evapotranspiration ET (28%) and S (20%). The analysis also showed that ET was not realistically estimated from previous measurements of S; it was more dependent on previous measurements of ET (59%) than on P (30%) and S (9%). This statistical procedure showed great advantages over classical multiple regressions. Future studies of this type should be carried out at regularly spaced observation points in a grid, in order to allow a 2-D and 3-D state-space-time analysis.

Temporal variability and covariance structures of soil temperature in a sugarcane field under different management practices in southern Brazil

“…8(b and c) and 9(b and c)). Timm et al (2011) also reported similar findings when 50% and 75% of data were omitted during state-time analysis of soil water storage, evapotranspiration and precipitation in a coffee field in Brazil. Fig.…”

“…These results of this study agreed with findings of a similar study by Dourado-Neto et al (1999) on state-space analysis of soil water content and temperature in a sugarcane field. Likewise, Timm et al (2011) working on temporal variability of soil water storage of an irrigated-coffee field found higher coefficients of determination in estimating soil water storage by state-time analysis in comparison to classical multiple regression. The state-time analysis also revealed that, since the observation of a variable is an estimate of its true value, the analysis automatically considers that each measurement possesses an explicit observation as well as model error (denoted as v t ) (Nielsen and Wendroth, 2003).…”

Spatio-temporal variability behavior of land surface soil water content in shrub- and grass-land

“…Spearman rank correlation coefficients of soil moisture between different dates were in general significant at P b 0.05 except for a few cases (data not shown), implying that θ tended to be temporally stable to some extent at different times as also observed for 0-1.0 m soil water storage in a coffee field (Timm et al, 2011). The relatively lower Spearman rank correlation coefficients usually corresponded to the greater values of RE%, and vice versa (Fig.…”

Spatial behaviour of soil moisture in the root zone of the Caatinga biome

“…Its distribution is the main object of study in investigations into the water balance of the different layers present in a soil profile (CRUZ et al, 2005;PARAJKA et al, 2006;PENNA et al, 2009). However, one of the biggest challenges facing these investigations relates to estimating the soil water content, since in the field there is significant variability of both space and time (GAO et al, 2011;TIMM et al, 2011), mainly arising from the variability of both the physical and water characteristics of the soil (CAJAZEIRA; ASSIS JUNIOR, 2011). To this end, the spatial variability of these properties must be well known in order to minimize errors when taking samples and in soil management (GREGO;VIEIRA, 2005;SOUZA et al, 2004).…”