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Dynamic real-time volumetric correction for tipping-bucket rain gauges

Sypka, Przemysław
Agricultural and forest meteorology 2019 v.271 pp. 158-167
algorithms, buckets, digital database, hills, laboratory experimentation, mathematical models, microprocessors, rain, rain gauges, rain intensity, temperate zones, vegetation
Tipping bucket rain gauges are the most popular devices for determining rainfall intensity and precipitation depth. Even though application of a tipping bucket gauge presupposes calibration, they are susceptible to various random, mechanical, and systematic errors. In general, precipitation measurements may be underestimated by 5% to 40%. This paper presents a method of determining volumetric correction that compensates for systematic errors caused by variable rainfall intensity. The main goal of this study was to develop a suitable mathematical model that can be readily implemented in real time during field measurements, including the possibility of compensation of each individual tip. The developed algorithm is based on a “tip interval” recording method; this is in contrast to the standard measurement method, which is based on “tip count” and nominal tip volume. Such a solution may be applied to any kind of tipping-bucket rain gauge and can be effortlessly implemented in modern digital data loggers. In addition, smaller canisters may be used in a seesaw-like mechanism that provides accurate measurements over a considerably wider range of rainfall rates, even including extreme rainfall. During meticulous laboratory experiments, various tipping buckets with nominal volumes of 3 cm3, 4 cm3, 5 cm3, 10 cm3 and 200 cm3 were tested over a wide range of simulated precipitation rates from 8 mm·h−1 to 500 mm·h−1. The extent of error reduction was 5.2%, 11.4%, 17.7%, 25.8% and 37.7% for rainfall intensities of 50 mm·h-1, 100 mm·h-1, 200 mm·h-1, 300 mm·h-1 and 500 mm·h-1, respectively (assuming that the nominal volume of the tipping bucket was 4 cm3 and the collection area of the rain gauge was 200 cm2). Besides scrupulous laboratory tests, the presented algorithm was verified during field measurements at 29 research sites located in a temperate climate region in two vegetation zones: foothills and lower montane. The results of this research will considerably enhance the accuracy of the precipitation data that are essential in various hydrological studies.