Premium
Interpretation of lysimeter weighing data affected by wind
Author(s) -
Nolz Reinhard,
Kammerer Gerhard,
Cepuder Peter
Publication year - 2013
Publication title -
journal of plant nutrition and soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.644
H-Index - 87
eISSN - 1522-2624
pISSN - 1436-8730
DOI - 10.1002/jpln.201200342
Subject(s) - lysimeter , oscillation (cell signaling) , calibration , lever , wind speed , environmental science , sprayer , mathematics , meteorology , simulation , computer science , statistics , geology , physics , engineering , soil science , chemistry , geotechnical engineering , mechanical engineering , biochemistry , soil water
Weighing lysimeters are valuable devices for measuring water‐balance components with high temporal resolution and high accuracy. However, some older lysimeter facilities still operate with lever‐arm‐counterbalance weighing systems that are sensitive to disturbances, e.g., forces exerted by wind. Filtering and averaging are commonly used for processing noisy raw data. We studied some data of a lever‐arm weighing system and performed additional experiments in order to (1) determine the measurement accuracy of the current weighing scheme (facility, and measuring and averaging procedure) regarding wind effects, (2) describe the oscillation behavior, (3) test the mechanical performance of the system, and (4) adapt the averaging procedure with respect to improved interpretation of the weighing data. The measurement accuracy for a wind velocity < 5 m s –1 , measured in 10 m height, was ≈ ± 0.4 kg (equivalent to ± 0.14 mm); at a higher wind velocity, the accuracy was three times lower, but there was no linear relationship. Additional experiments showed that the weighing system is oscillating with more or less irregular amplitudes. A loading–unloading experiment delivered proper results of the measured loads. The mechanical system reacted immediately, and no directional effects were found. However, small changes of < 1 kg could hardly be determined due to the oscillations. A time series of raw data measured every 2 s served as basis for improving the averaging method. A moving average from 64 values was computed representing the currently used method, and serving as reference. With this procedure an accuracy of ± 0.38 kg could be reached. Averaging 150 values led to an accuracy of ± 0.28 kg (0.1 mm) for a wind velocity < 5 m s –1 .