Sometime around 6 AM on December 4, 2011, the Coal River, a small river in the southwest corner of Utah, jumped from five feet to fourteen feet, in under an hour. Flood stage for the river is 8.5 feet, and the Major Flood Stage is 10.2 feet. Unlike some flood gauges, the Coal River station at Cedar City doesn't have a record mark, but this is probably a record flood for the river at this point. Before the flood, the river was running at a trickle: probably under a hundred cubic feet per second. It is hard to say what it is running at currently, since the cubic feet per second measure stops at 10 feet and 2400 cfs, but following the exponential increase of flow along with height, it would probably be running at around 10,000 cfs: meaning that in the space of an hour, its flow rate increased a hundred-fold.
There are three other interesting things of note in regards to this record-breaking flood: there was only a trace of rainfall in the area in the past day, and only a tenth of an inch in the past week. None of the other watercourses in the area have grown larger, and there are no news stories about this catastrophic flood.
Which is probably because this flood didn't happen. And is not happening. But this is not something I am making up: this is data that I have recovered from the National Weather Service's Advanced Hydrological Prediction Service. Every day, 4,950 gauges on streams and rivers around the country make a report, which is then made into an automated map that can be perused by the concerned or the curious. There is also a tab on the map for river predictions, and one for precipitation, given at various time intervals.
For reference, the map is here:
http://water.weather.gov/ahps/
Since I am a frequent visitor to the map, I have noticed that it is not uncommon to have a single purple spot "Major" Flooding, amongst a flood of green "Normal" rivers. And usually, upon clicking on those spots, it shows a sudden, record breaking flood, that almost always returns to normal in a few hours. Since these floods don't seem to be correlated with precipitation, and are never mentioned elsewhere, they seem to just be the result of spurious data.
So what? Why have I written so much about a data error relating to a small river in southwestern Utah?
There is, of course, a larger issue involved. There is a long-standing epistemological discussion about the difference between fact and opinion, but it is often bogged down by overblown arguments about whether the refrigerator light is on when we close the door, and whether Esta frase se encuentra en Inglés, cuando usted no está buscando. But instead, I am going to talk about fact and theory with an actual real life example, the flood of the Coal River.
How do I know that the Coal River didn't flood? According to the methodology of science, as defined at the high school level, a scientific theory is shaped by facts. A scientific theory has to fit all available facts. And, here, I have a fact: the Coal River is currently at 13.82 feet. This fact is attested to by an official meteorological reporting agency. So isn't my job, as a scientist, to come up with a theory that explains this fact, rather than thinking up reasons not to accept this fact? Is it unscientific of me to think of reasons to dismiss this fact based on common sense and the like?
I have good reasons for not believing that this is a fact. Mathematically speaking, for the river to have 100 times as much water coursing through it would require 100 times the normal rainfall to suddenly fall. That water can not have appeared from nowhere. Going further, I could use equations of how much water can be held in air to prove that much rainfall couldn't even theoretically fall. There is also a lack of corroborating data from eyewitnesses, since presumably a river that had flooded that quickly would be threatening the nearby town, and would be a threat.
Sometimes, in science, there are various facts, and the best theory is the one that fits them best. But I am moving beyond that: I am saying that theory disproves this fact. Not only theory, but common sense, tells me that this observation or data point or whatever we want to call it, is not a true fact, but a pseudofact. According to our best basic science lessons, facts are supposed to prove or disprove theories, but sometimes theories can prove or disprove facts.
And I use this as an example because it comes from a real situation. Someone might be doing a project where they take summations of how many gauges are in flood conditions, and if they paying attention, they will automatically subtract these data points from their studies (although probably with a note they are doing so). Because in working science, there is no simple building of facts into theories, but an interplay between the two.