What is BS EN 17277 - Rainfall intensity measuring instruments for hydrometry about?
BS EN 17277 discusses measurement requirements and classification of rainfall intensity measuring instruments for hydrometry. BS EN 17277 considers liquid atmospheric precipitation and defines the procedures and equipment to perform laboratory and field tests, in steady-state conditions, for the calibration, check, and metrological confirmation of liquid precipitation measurement instruments.
BS EN 17277 provides a classification of catching-type measurement instruments based on their laboratory performance. The classification does not relate to the physical principle used for the measurement; nor does it refer to the technical characteristics of the instrument assembly but is solely based on the instrument calibration.
BS EN 17277 also provides a quantitative standardized method to declare the achievable measurement accuracy to provide guidance on the suitability for a particular purpose while meeting the user’s requirements.
Note: Attribution of a given class to an instrument is not intended as a high/low ranking of its quality.
Who is BS EN 17277 - Rainfall intensity measuring instruments for hydrometry for?
BS EN 17277 on rainfall intensity measuring instruments is useful for:
- Rainfall intensity measuring instrument manufacturers
- Hydrologist
- Test centres for hydrometry instruments
- Regulatory authorities
Why should you use BS EN 17277- Rainfall intensity measuring instruments for hydrometry?
Precipitation gauges are one of the basic components of world hydro-metrological networks. A requirement for more accurate instruments is crucial for many applications including water resources management, public safety, and disaster mitigation.
BS EN 17277 provides specifications on user requirements for rainfall intensity measurements, measurement of rainfall intensity, classification of rainfall intensity gauges for rainfall intensity measuring instruments. This will allow your customers to buy and use a rainfall intensity gauge knowing that it will perform to a specific class of performance before it is deployed to the field.
