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Which sampling design to monitor saturated hydraulic conductivity?

机译:哪种采样设计可监测饱和水力传导率?

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Soil in a changing world is subject to both anthropogenic and environmental stresses. Soil monitoring is essential to assess the magnitude of changes in soil variables and how they affect ecosystem processes and human livelihoods. However, we cannot always be sure which sampling design is best for a given monitoring task. We employed a rotational stratified simple random sampling (rotStRS) for the estimation of temporal changes in the spatial mean of saturated hydraulic conductivity (K-s) at three sites in central Panama in 2009, 2010 and 2011. To assess this design's efficiency we compared the resulting estimates of the spatial mean and variance for 2009 with those gained from stratified simple random sampling (StRS), which was effectively the data obtained on the first sampling time, and with an equivalent unexecuted simple random sampling (SRS). The poor performance of geometrical stratification and the weak predictive relationship between measurements of successive years yielded no advantage of sampling designs more complex than SRS. The failure of stratification may be attributed to the small large-scale variability of K-s. Revisiting previously sampled locations was not beneficial because of the large small-scale variability in combination with destructive sampling, resulting in poor consistency between revisited samples. We conclude that for our K-s monitoring scheme, repeated SRS is equally effective as rotStRS. Some problems of small-scale variability might be overcome by collecting several samples at close range to reduce the effect of small-scale variation. Finally, we give recommendations on the key factors to consider when deciding whether to use stratification and rotation in a soil monitoring scheme.
机译:不断变化的世界中的土壤既受到人为压力也受到环境压力。土壤监测对于评估土壤变量的变化幅度及其对生态系统过程和人类生计的影响至关重要。但是,我们无法始终确定哪种采样设计最适合给定的监视任务。我们采用旋转分层简单随机抽样(rotStRS)估算了2009年,2010年和2011年巴拿马中部三个地点的饱和导水率(Ks)的空间平均值的时间变化。为了评估该设计的效率,我们比较了结果使用分层简单随机抽样(StRS)获得的2009年空间均值和方差的估计值,这实际上是在第一次采样时获得的数据,并具有等效的未执行简单随机抽样(SRS)。几何分层的性能较差以及连续几年的测量之间的预测关系较弱,因此没有比SRS更为复杂的抽样设计的优势。分层失败可能归因于K-s的小范围大规模变化。再次访问以前采样的位置是不利的,因为与破坏性采样相结合的小规模差异很大,导致重新访问的样本之间的一致性很差。我们得出结论,对于我们的K-s监视方案,重复SRS与rotStRS一样有效。通过在近距离收集几个样本以减少小规模变异的影响,可以克服小规模变异的一些问题。最后,我们建议在决定是否在土壤监测方案中使用分层和轮换时要考虑的关键因素。

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