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Assessment of OTT Pluvio2 Rain Intensity Measurements

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  • 1 Civil and Environmental Engineering Department, University of Texas at San Antonio, San Antonio, Texas
  • | 2 Industrial Engineering Department, Hacettepe University, Ankara, Turkey
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Abstract

This study investigates the OTT Pluvio2 weighing precipitation gauge’s random and systematic error components as well as stabilization of the measurements on time-varying rainfall intensities (RI) under laboratory conditions. A highly precise programmable peristaltic pump that provided both constant and time-varying RI was utilized in the experiments. Abrupt, gradual step, and cyclic step changes in the RI values were evaluated. RI readings were taken in real time (RT) at different time resolutions (6–60 s) for the RI range of 6–70 mm h−1. Our analysis indicates that the lower threshold for the OTT Pluvio2’s real-time RI measurements should be redefined as 7 mm h−1 at a 1-min resolution. Tolerance intervals containing 95% of the repeated measurements with a probability of 0.95 are given. It is shown that the measurement variances are unequal over the range of RI and the measurement repeatability is not uniform. A statistically significant negative bias was observed for the RI values of 7 and 8 mm h−1, while there was not a statistically significant linearity problem. Through the use of statistical control limits, it is shown that means of the RI measurements stabilized on the actual RI value. A detailed investigation on RT bucket weight measurements revealed a time delay in bucket weight measurements, which causes notable errors in reported RI measurements under dynamic rainfall conditions. To demonstrate the potentiality of large errors in Pluvio2’s real-time RI measurements, a set of equations was developed that faithfully reproduced the Pluvio2’s internal (hidden) algorithm, and results from dynamic laboratory and in situ rainfall scenarios were simulated. The results of this investigation show the necessity of modifying the present Pluvio2 RI algorithm to enhance its performance and show the possibility of postprocessing the existing Pluvio2 RI datasets for improved measurement accuracies.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Firat Y. Testik, firat.testik@utsa.edu

Abstract

This study investigates the OTT Pluvio2 weighing precipitation gauge’s random and systematic error components as well as stabilization of the measurements on time-varying rainfall intensities (RI) under laboratory conditions. A highly precise programmable peristaltic pump that provided both constant and time-varying RI was utilized in the experiments. Abrupt, gradual step, and cyclic step changes in the RI values were evaluated. RI readings were taken in real time (RT) at different time resolutions (6–60 s) for the RI range of 6–70 mm h−1. Our analysis indicates that the lower threshold for the OTT Pluvio2’s real-time RI measurements should be redefined as 7 mm h−1 at a 1-min resolution. Tolerance intervals containing 95% of the repeated measurements with a probability of 0.95 are given. It is shown that the measurement variances are unequal over the range of RI and the measurement repeatability is not uniform. A statistically significant negative bias was observed for the RI values of 7 and 8 mm h−1, while there was not a statistically significant linearity problem. Through the use of statistical control limits, it is shown that means of the RI measurements stabilized on the actual RI value. A detailed investigation on RT bucket weight measurements revealed a time delay in bucket weight measurements, which causes notable errors in reported RI measurements under dynamic rainfall conditions. To demonstrate the potentiality of large errors in Pluvio2’s real-time RI measurements, a set of equations was developed that faithfully reproduced the Pluvio2’s internal (hidden) algorithm, and results from dynamic laboratory and in situ rainfall scenarios were simulated. The results of this investigation show the necessity of modifying the present Pluvio2 RI algorithm to enhance its performance and show the possibility of postprocessing the existing Pluvio2 RI datasets for improved measurement accuracies.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Firat Y. Testik, firat.testik@utsa.edu
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