Red staff gauge.

Have you ever tried to explain the semantic difference between stage, gauge height and water level? Or why the distinction is even needed or useful? Water level seems obvious enough and I use this term for any still pool (e.g. reservoir) where the height of the water surface is uniform. I use the term stage where the height of a flowing water surface is a function...

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Hydrometric Information graphic.

I have written previously about the measurement of measurement uncertainty (Dec 9, 2011). The inverse of this problem is the measurement of the information contained in the data. One way of thinking about this is to imagine that our sensors are robotic students who are assigned the task of learning everything they can about some environmental condition. We then ask them to tell us what they have...

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OGC graphic.

I am writing this over the Atlantic Ocean on my way home from the ratings, gaugings and cross sections intensive workshop in Reading, England. This Open Geospatial Consortium (OGC) workshop marks the launch of a project to develop WaterML2.0 part 2. In a concurrent meeting in Exeter, the OGC formally adopted WaterML2.0 part 1, the part that deals with time-series data, as an official international standard. The...

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Yellow ruler.

I was asked the other day if I thought that the USGS would ever go metric. I am unqualified to answer this question but I care about the implications of the issue. I started my field career working in Imperial units (also known as English) before the Water Survey of Canada converted to the International System of units (SI, commonly known as metric) in 1980 so...

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Stream flowing over rocks through a forest.

How much confidence should you have in your measurements? For a discharge measurement result of 50.0 m3s-1, is the true value is between 49.95 and 50.05, as inferred by the trailing zero?  Maybe the true value is anywhere between 47.5 and 52.5 (+/- 5%), a range commonly used to determine ‘goodness of fit’ to a rating curve. Perhaps the measurement wasn’t made under ‘ideal conditions’, which...

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Congo River.

High quality data are accurate, timely, meaningful and complete. Fitness-for-purpose is achieved if the stated or implied needs, or expectations, of the end-user of the data are met. The design of a quality management system starts with specification of end-user needs and expectations. These expectations are inter-dependent. Consider the situational irony of the sign stating: “Our data are timely, affordable and accurate – pick any two out...

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