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Updated: Jul 15, 2026
10:35
A Protocol for Conducting Rainfall Simulation to Study Soil Runoff
Published on: April 3, 2014
The effect of rainfall measurement uncertainties on rainfall-runoff processes modelling
1Department of Sanitary and Ecological Engineering, Czech Technical University, Thakurova 7, 166 29 Prague, Czech Republic. stransky@fsv.cvut.cz
Summary
Accurate rainfall measurement is vital for urban drainage. Tipping bucket rain gauge (TBR) calibration minimizes underestimation, with uncalibrated gauges causing up to 30% error. Regular calibration ensures reliable data for wet weather modeling.
Area of Science:
- Hydrology
- Environmental Engineering
- Metrology
Background:
- Rainfall data are essential for urban drainage and wet weather analysis.
- Measurement errors in rainfall data, particularly from tipping bucket rain gauges (TBRs), lead to underestimation of rainfall volume.
- Assessing the credibility of measured rainfall data and the impact of errors on urban drainage modeling is critical.
Purpose of the Study:
- To assess the credibility of measured rainfall data.
- To evaluate the effect of measurement errors on urban drainage modeling.
- To define and assess the methodology of tipping bucket rain gauge (TBR) calibration and uncertainty analysis.
Main Methods:
- Calibrated a set of 18 TBRs and compared results to previous calibrations to assess gauge aging.
- Performed uncertainty analysis on TBR methodology.
- Propagated calibration and systematic errors through a rainfall-runoff model on an experimental catchment.
Main Results:
- TBR calibration is crucial for tasks involving peak flow values and high flow durations.
- Omission of calibration can result in up to 30% underestimation of rainfall volume.
- Additional systematic errors can contribute a further 15% underestimation.
Conclusions:
- Regular TBR calibration, recommended every two years, is necessary to account for mechanical aging.
- Adjusting dynamic test duration proportionally to rainfall intensity is advised.
- Accurate rainfall data is vital for reliable urban drainage modeling.
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