Search USGSSearch

USGS · 70019164

A new method for automated dynamic calibration of tipping-bucket rain gauges

Abstract

Existing methods for dynamic calibration of tipping-bucket rain gauges (TBRs) can be time consuming and labor intensive. A new automated dynamic calibration system has been developed to calibrate TBRs with minimal effort. The system consists of a programmable pump, datalogger, digital balance, and computer. Calibration is performed in two steps: 1) pump calibration and 2) rain gauge calibration. Pump calibration ensures precise control of water flow rates delivered to the rain gauge funnel; rain gauge calibration ensures precise conversion of bucket tip times to actual rainfall rates. Calibration of the pump and one rain gauge for 10 selected pump rates typically requires about 8 h. Data files generated during rain gauge calibration are used to compute rainfall intensities and amounts from a record of bucket tip times collected in the field. The system was tested using 5 types of commercial TBRs (15.2-, 20.3-, and 30.5-cm diameters; 0.1-, 0.2-, and 1.0-mm resolutions) and using 14 TBRs of a single type (20.3-cm diameter; 0.1-mm resolution). Ten pump rates ranging from 3 to 154 mL min −1 were used to calibrate the TBRs and represented rainfall rates between 6 and 254 mm h −1 depending on the rain gauge diameter. All pump calibration results were very linear with R 2 values greater than 0.99. All rain gauges exhibited large nonlinear underestimation errors (between 5% and 29%) that decreased with increasing rain gauge resolution and increased with increasing rainfall rate, especially for rates greater than 50 mm h −1 . Calibration curves of bucket tip time against the reciprocal of the true pump rate for all rain gauges also were linear with R 2 values of 0.99. Calibration data for the 14 rain gauges of the same type were very similar, as indicated by slope values that were within 14% of each other and ranged from about 367 to 417 s mm h −1 . The developed system can calibrate TBRs efficiently, accurately, and virtually unattended and could be modified for use with other rain gauge designs. The system is now in routine use to calibrate TBRs in a large rainfall collection network at Yucca Mountain, Nevada.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M.D. Humphrey, J.D. Istok, J.Y. Lee, J.A. Hevesi, A. L. Flint. 1997. A new method for automated dynamic calibration of tipping-bucket rain gauges. https://doi.org/10.1175/1520-0426(1997)014%253c1513%3Aanmfad%253e2.0.co%3B2

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Evaluating unsupervised methods to size and classify suspended particles using digital in-line holography

Substantial information can be gained from digital in-line holography of marine particles, eliminating depth-of-field and focusing errors associated with standard lens-based imaging methods. However, for the technique to reach its full potential in oceanographic research, fully unsupervised (automated) methods are required for focusing, segmentation, sizing and classification of particles. These computational challenges are the subject of this paper, in which we draw upon data collected using a variety of holographic systems developed at Plymouth University, UK, from a significant range of particle types, sizes and shapes. A new method for noise reduction in reconstructed planes is found to be successful in aiding particle segmentation and sizing. The performance of an automated routine for deriving particle characteristics (and subsequent size distributions) is evaluated against equivalent size metrics obtained by a trained operative measuring grain axes on screen. The unsupervised method is found to be reliable, despite some errors resulting from over-segmentation of particles. A simple unsupervised particle classification system is developed, and is capable of successfully differentiating sand grains, bubbles and diatoms from within the surf-zone. Avoiding miscounting bubbles and biological particles as sand grains enables more accurate estimates of sand concentrations, and is especially important in deployments of particle monitoring instrumentation in aerated water. Perhaps the greatest potential for further development in the computational aspects of particle holography is in the area of unsupervised particle classification. The simple method proposed here provides a foundation upon which further development could lead to reliable identification of more complex particle populations, such as those containing phytoplankton, zooplankton, flocculated cohesive sediments and oil droplets.

Journal of Atmospheric and Oceanic Technology

A twenty-first century California observing network for monitoring extreme weather events

During Northern Hemisphere winters, the West Coast of North America is battered by extratropical storms. The impact of these storms is of paramount concern to California, where aging water supply and flood protection infrastructures are challenged by increased standards for urban flood protection, an unusually variable weather regime, and projections of climate change. Additionally, there are inherent conflicts between releasing water to provide flood protection and storing water to meet requirements for water supply, water quality, hydropower generation, water temperature and flow for at-risk species, and recreation. In order to improve reservoir management and meet the increasing demands on water, improved forecasts of precipitation, especially during extreme events, is required. Here we describe how California is addressing their most important and costliest environmental issue – water management – in part, by installing a state-of-the-art observing system to better track the area’s most severe wintertime storms.

California

A modified beam-to-earth transformation to measure short-wavelength internal waves with an acoustic Doppler current profiler

The algorithm used to transform velocity signals from beam coordinates to earth coordinates in an acoustic Doppler current profiler (ADCP) relies on the assumption that the currents are uniform over the horizontal distance separating the beams. This condition may be violated by (nonlinear) internal waves, which can have wavelengths as small as 100-200 m. In this case, the standard algorithm combines velocities measured at different phases of a wave and produces horizontal velocities that increasingly differ from true velocities with distance from the ADCP. Observations made in Massachusetts Bay show that currents measured with a bottom-mounted upward-looking ADCP during periods when short-wavelength internal waves are present differ significantly from currents measured by point current meters, except very close to the instrument. These periods are flagged with high error velocities by the standard ADCP algorithm. In this paper measurements from the four spatially diverging beams and the backscatter intensity signal are used to calculate the propagation direction and celerity of the internal waves. Once this information is known, a modified beam-to-earth transformation that combines appropriately lagged beam measurements can be used to obtain current estimates in earth coordinates that compare well with pointwise measurements. ?? 2005 American Meteorological Society.

Journal of Atmospheric and Oceanic Technology