Sampling procedures for throughfall monitoring: a simulation study

A - Papers appearing in refereed journals

Zimmermann, B., Zimmermann, A., Lark, R. M. and Elsenbeer, H. 2010. Sampling procedures for throughfall monitoring: a simulation study. Water Resources Research. 46, p. W01503.

AuthorsZimmermann, B., Zimmermann, A., Lark, R. M. and Elsenbeer, H.
Abstract

What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.

KeywordsEnvironmental Sciences; Limnology; Water Resources
Year of Publication2010
JournalWater Resources Research
Journal citation46, p. W01503
Digital Object Identifier (DOI)doi:10.1029/2009WR007776
Open accessPublished as green open access
FunderHSBC Climate Partnership
Earthwatch Institute
Smithsonian Tropical Research Institute (STRI)
World Wildlife Fund - WWF
DAAD - Deutscher Akademischer Austausch Dienst - German Academic Exchange Service - Germany
Biotechnology and Biological Sciences Research Council
German Research Foundation (DFG)
Funder project or codeCentre for Mathematical and Computational Biology (MCB)
Complex spatial variation of environmental variables: sampling, prediction and interpretation
Publisher's version
Output statusPublished
PublisherWiley
American Geophysical Union
Grant IDE1 255/6-1
ISSN0043-1397

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