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Which sampling design to monitor saturated hydraulic conductivity?
Author(s) -
Hassler S. K.,
Lark R. M.,
Zimmermann B.,
Elsenbeer H.
Publication year - 2014
Publication title -
european journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 1351-0754
DOI - 10.1111/ejss.12174
Subject(s) - sampling (signal processing) , sampling design , stratified sampling , simple random sample , hydraulic conductivity , spatial variability , statistics , stratification (seeds) , environmental science , sample size determination , scale (ratio) , soil science , range (aeronautics) , hydrology (agriculture) , mathematics , computer science , soil water , geology , engineering , cartography , geotechnical engineering , geography , population , filter (signal processing) , sociology , biology , germination , computer vision , seed dormancy , botany , demography , dormancy , aerospace engineering
Summary 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.