Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous through fall studies relied on method-of-moments variogram estimation and sample sizes <<200, currently available data are prone to large uncertainties. (C) 2016 Elsevier B.V. All rights reserved

Quantifying transpirable soil water and its relations to tree water use dynamics in a water-limited pine forest

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Spatial variability of throughfall and stemflow in an exotic pine plantation of subtropical coastal Australia

Large-scale exotic pine plantations have been developed for timber production in subtropical Australia. Few studies investigate the spatial variability of both throughfall and stemflow in such managed pine plantations despite their acknowledged effects on the heterogeneity of hydrological and biochemical processes of forested ecosystems. To examine the spatial variability of rainfall under a 12-year-old pine plantation in a subtropical coastal area of Australia, we observed gross rainfall, throughfall and stemflow over a 1-year period. Our results show that the spatial variability of gross rainfall within a 50 m × 50 m plot is minimal. Throughfall is significantly different among three tree zones (midway between rows, west and east side of trunks), particularly for rainfal