56 Years of Tornado Tracks

For the storm chasers (and streamchasers) out there- here is IDV's map of tornado tracks across the US using freely available information from data.gov. Each streak connects tornado's touchdown and lift-off location (the actual tornadoes meandered around a bit more than is shown here). The brightness is how violent it was. There is also a high resolution version.

Tornado tracks

The National Weather Service also has plenty more visualizations of this tornado data including maps of the tornadoes that happened in each year. It would be interesting to animate this like has been done with paths of airplane flights.

How much money are US hydrologists earning?

How many hydrologists and meteorologists work for the US federal government? Which agencies do they work for? And how much money do they get? How does this compare to weather forecasters?

The bottom line first

For the busy readers, here’s my overall impression: the typical mid-career NOAA river forecasting hydrologist makes about $100k (US dollars per year, which is about 80k euros). This is a few thousand dollars per year more than meteorologists. Hydrologists that work outdoors earn less than those with desk jobs (e.g. the typical Forest Service hydrologist earns $70k). The positions (i.e. hydrologic technicians) that don’t require a degree, earn about $30k less than otherwise.

I hope those numbers are in metric. (source)

The database

Let’s take a tour of the online database of what nearly everyone in the US government is earning. The database is a good source for statistics so I wrote a little computer program to pull down the numbers and see what was there. That said, it can seem voyeuristic to be able to search for individual employees by name and find out their salaries and bonuses. In three clicks you can find out who the highest paid hydrologist in the government is. In four clicks you can find some of the lowest paid workers (Soil Conservation Technicians in Wyoming, we feel for you!)

Job titles for hydrologists

Here is the government’s job description of a Hydrologist (series GS-1315):

This series includes positions that involve professional work in hydrology, the science concerned with the study of water in the hydrologic cycle. The work includes basic and applied research on water and water resources; the collection, measurement, analysis, and interpretation of  information on water resources; the forecast of water supply and water flows; and the  development of new, improved or more economical methods, techniques, and instruments.

The “Meteorologist” position is similar, except substitute “weather” for “water” in the above paragraph. There is also “Hydrologic Technician”… Technicians are typically the people that install, maintain and repair instruments out in the field, but also spend time in the office reviewing and cleaning up data. Hydrologists typically need to have an advanced degree, whereas technicians do not.

Note that this doesn’t capture all the people that may work on water topics but are not themselves hydrologists, such as computer specialists, economists, natural resource conservationists, or people doing “general physical science”.

Also, while all river forecasters are hydrologists, there are many hydrologists that are not river forecasters. There are hydrologists that are focused on water quality and groundwater and many other sub-fields. This analysis does include river forecasters that work for federally owned hydropower companies (such as Bonneville Power) but not those in the private sector (such as Salt River Project). It also doesn’t include state and local government, only federal. 

It is easy to get distracted by all the other government job titles like “Sewing Machine Operator” or “Nuclear Materials Courier”. I can only imagine what a “Wiper” or an “Oiler” does, or if they get along with each other? How about the “Messengers” (of which there are 10 serving a city of 5,000 people in Arizona)? There are “Barbers”, “Buffers”, “Bakers” and even “Bulk Money Handlers”.

How many hydrologists are there?

For a country of 313 million people, there are 2.6 million federal employees, 177 thousand of which work in natural resources. There are 2,342 hydrologists, 2,789 meteorologists and 1,602 hydrologic technicians. It’s a rare profession indeed- if you introduced yourself to 20 strangers a day in the US, it would take on average over 18 years to meet a government hydrologist. Strangely, the government hires about as many Meteorological Technicians (371) as it does Funeral Directors (345).

Number of US Federal Employees described as Hydrologists, Hydrologic Technicians, Meteorologists and Meteorological Technicians in 2011.

Agency	Division	Hydro	Hydro Tech	Meteo	Meteo Tech
Commerce	NOAA (Natl Ocean Atmo Admin)	295	2	2,667	365
USDA	Agricultural Research Service	33	42	4
	Forest Service	303	155	27	6
	NRCS (Nat Res Consv Serv)	31	17	1
	Office of the Chief Economist			7
Interior	USGS (Geologic Survey)	1,398	1,252
	National Park Service	52	24	7
	Fish And Wildlife Service	37	8	4
	Surface Mining	18
	Bureau of Reclamation	28	64	2
	Indian Affairs	9	3	1
	Bureau of Land Management	68	17	7
	Bureau of Ocean Energy			4
EPA	EPA (Environ Protect Agency)	42	3	5
NRC	Nuclear Regulatory Commission	17		2
DOE	Department of Energy	6		5
Other	Other	5	15	46	0
	Total	2,342	1,602	2,789	371

What agencies do these people work for?

Far and away, the Geologic Survey (USGS) is the largest federal employer of hydrologists (60%) and hydrologic technicians (78%). This is the agency that maintains the stream gage network in the US and also works on mapping groundwater, among other things. 

Similarly, if you want to be a government meteorologist, the National Oceanic and Atmospheric Administration (NOAA) is where 98% of the jobs in that field are. NOAA contains the National Weather Service. Meteorologists outnumber hydrologists 9 to 1 at NOAA.

Other places where a good number of hydrologists work include the USDA, National Parks Service, Bureau of Land Management, Forest Service, the Bureau of Reclamation and the Environmental Protection Agency.

How much money do they make?

Salary and bonuses of Hydrologists, by government agency, sorted by median income per year in 2011. Redder colors mean relatively more money.

Division	9 in 10*	Median pay ($1000s/yr)	1 in 10*
EPA	69	113	135
NOAA	79	100	130
USGS	59	91	136
Agricultural Research Service	67	90	146
National Park Service	70	90	115
U.S. Fish and Wildlife Service	66	86	108
NRCS	57	85	114
Bureau of Reclamation	63	80	90
Forest Service	51	71	94
Bureau of Land Management	57	69	89

*“9 in 10” (or 1 in 10) people in the agency make more than this amount

The columns on the left and right give a range of the salaries within the agency. For example, if you look at the first row, 8 in 10 hydrologists at the Environmental Protection Agency make between $69k and $135k per year, with half of the people making more than $113k. For reference, median income of all wage earners in the US in 2010 was about $26k per year (not including bonuses). Bonuses for hydrologists are typically not much, often less than a thousand per year.

In other words, EPA and NOAA hydrologists earn about $30 thousand a year more than those at the Forest Service. Another standout is the Agricultural Research Service (ARS). It only employed 33 hydrologists but many of them were very well compensated. Two of the top three highest paid hydrologists in the country work for the ARS, making more than $170 thousand per year.

Salary and bonuses of Hydrologic Technicians

Division	9 in 10*	Median pay ($1000s/yr)	1 in 10*
USGS Geological Survey	29	52	77
Agricultural Research Service	28	51	62
Bureau of Reclamation	31	49	69
National Park Service	37	43	48
Forest Service	28	35	56

*“9 in 10” (or 1 in 10) people in the agency make more than this amount

Here’s the same table, except for hydro techs (for agencies with substantial numbers of them). All in all, hydrologic technicians make a little more than half what regular hydrologists make. Again, the main difference is that hydrologic technicians typically do not need an advanced degree.

Hydrologists versus Meteorologists

If you remove the top 25% of earners in each category (i.e. you just consider the typical employee and those just starting) meteorologists earn about $5-$10 thousand more per year than hydrologists. This is likely because meteorology is more of a desk job and there are many hydrologists (e.g. at the National Park Service and Forest Service) that spend about half their time outdoors collecting data.

Therefore, it would be more apples-to-apples to compare hydrologists and meteorologists only within NOAA. These hydrologists are likely to be operational forecasters working for the National Weather Service (NWS) River Forecast Centers. Here, the median salary for hydrologists is more than meteorologists ($100k and $97k respectively). The difference gets bigger towards the low end, i.e. 1 in 20 NOAA hydrologists earn less than $69k, whereas 1 in 20 meteorologists make less than $50k). I suspect that there’s a large pool of junior meteorologists within the NWS and some of them branch out into a hydrology specialty. The difference in pay may reflect a difference in seniority and time with the agency.

More resources

The US Geologic Survey employs the most hydrologists of any agency and have a description of what hydrologists do. Elsewhere on the web are also descriptions of salaries of hydrologists (in 2010), advice on how to become a hydrologist. My top pick is stateuniversity.com’s page of hydrology career facts. The salary numbers on those pages may be lower than what I mention because they may only include entry-level positions?

A river of trash (Cairo, Egypt)

In a few days I’ll have a feature post on France’s environmental science webpage based on the most popular post from my travels. That post was a photo essay of our attempts to find the dirtiest spot on the dirtiest river in the world (Citarum River, upstream of Jakarta). (Edit: The link to that story ""Le Citarum, un fleuve de déchets" (the Citarum: A River of Trash) is now live).

There was only one other river that we saw that rivaled the Citarum and that was a drain in Giza, Egypt in western Cairo. This site was only 1-2 kilometers from the Pyramids and the Sphinx.

The floating barrels keep the surface trash from passing by, while letting the water through.

On the opposite bank you can see a broken part of the wall where people pour their garbage in. From these pictures I can see: plastic bags, two car tires, plastic bottles, Styrofoam packaging, a traffic light, a chair, broken concrete, paper plates, a hubcap, a table, potato chip bags, and a few shoes.

My original post about Jakarta’s dirty river said:
One of the local people with us suggested that there is a culture of throwing trash out the back of houses in Indonesia. No one sees the river from the street, so it is out of sight, out of mind. Maybe we should turn the houses around and put the road by the river instead.
It seems that here’s a case in Egypt where the road is next to the river and the houses are set back. Even though the pollution is in plain sight, the garbage is still thick.

Vertigo is something other than the fear of falling

We had a quick discussion about if my travel insurance covered “falling down a well”. That’s not usually the kind of thing that happens accidentally, but we suspected it would be covered. Still, there were second thoughts when research scientist Mojtaba Pakparvar and field technician Gholamali Nekooian pulled back the heavy metal lid to their measurement well.

The cap to the well

The Kowsar Floodwater Spreading Experimental Station wanted to know how much of the captured floods were actually reaching the water table below. They made a series of hand-dug wells so they could measure soil moisture at various depths beneath the land surface. The walls of this well were a series of concrete rings, each with a horizontal piece of rebar serving as a step in a ladder to the bottom. The instruments were inserted into small windows into the soil along the well’s sides. 

Gholamali Nekooian demonstrates how the data is downloaded from the sensors. Each of the metal cables on the right is connected to a soil moisture sensor below.

There’s no light in the hole, no ventilation and no safety lines. Sound seemed to go down but not come back up. The flashlight couldn’t see the bottom but we were told it was about 30 meters (100 feet) deep. When asked if we wanted to go down and see what it is like, Kitty enthusiastically volunteered to go first.

After a minute or two of climbing, she echoed up some of the lessons that she learned from watching documentaries about climbing Mt Everest. Specifically, people surge with adrenaline as they strive to reach the summit, but then don’t give enough thought to how the journey is only half complete at that point. They still need to return to base camp and it is on the descent that most injuries happen.

Here, the case was reversed. She wanted to scramble down to the bottom, but didn’t know how she would feel climbing back to the top. I thought it was a great metaphor for the idea of forecasting (i.e. predicting how you’ll behave in a situation you’ve never been in before), or the practice of having to pace your work during a long event. Just as she nearly disappeared from view, she called up that her arms were feeling shaky and that she was coming back up. 

What’s that Lassie, Kitty’s fallen down the well?

I went down next, but didn’t make it as far. I never used to have vertigo until I read this Milan Kundera quote from The Unbearable Lightness of Being:

What is vertigo? Fear of falling? Then why do we feel it even when the observation tower comes equipped with a sturdy handrail? No, vertigo is something other than the fear of falling. It is the voice of the emptiness below us, which tempts and lures us, it is the desire to fall, against which, terrified, we defend ourselves.

Kitty made it about half way down climbing. This couldn’t compare to what digging the well must have been like, or working down it during the heat of summer. This wasn’t even the deepest well on site. When we asked Mojtaba and Gholamali how they managed to do it, they said that this was nothing compared to what the Qanat diggers must have gone through 100, 500 or 2000 years ago.

Measuring streamflow is a type of war [Floodwater spreading part 3]

(Be sure to read parts 1 and 2 to get background on the place in Southeast Iran where researchers are doing experiments on how to best capture flood flows and store them underground). In post 2 I wrote about the challenges of figuring how much water a tree uses, today is about the challenges of measuring streamflow).

Later that day we visited where the river’s flow is measured at a four-way intersection. From one spot, three streamgages with cableways can be seen. One measures the total river flow upstream, and two measure where the flow is diverted into the experimental fields (one to the east and one to the west). The fourth option is an overflow channel in case the floods get too large for the project to handle.

There was no flow in the river when we were there, but debris (e.g. grass and sticks) up on the banks at chest-height suggested some high water had rumbled through here.

There were pools of water left in the river from a flood that had come through five days ago. Ripples in the riverbed showed where there would have been waves.

Think you’ve chosen a difficult life? Imagine how the bush that took root in the riverbed feels. 

Naturally, where there’s water there’s life and there was lots of evidence of animals going from pool to pool as the water eventually disappeared into the soil.

There were fresh footprints of birds…

There were also hoofprints, possibly from a wild pig.

The earth cracks as the soil dries up.

Each streamgage is a tall metal tower out at the end of a concrete walkway. 

On the right is the automatic streamgage. The tall tube is called a stilling well. On the top is the instrument shelter. The white strip along the side is called a staff gage, marked like a ruler so someone can read how deep the water is. In the background is the cableway.

The technician unlocked the door at the end of the walkway to the streamgage. Inside was a sealed metal box with a beaded chain dropping into a 10 meter long tube. At the end of the chain was a bobber resting on the dry river bed below. A sensor in the metal box was measuring the length of the chain to the water surface.

Looking down inside the stilling well. The weight at the bottom is resting on the ground. Watch out for spiders!

As the river rose and fell, so did the bobber and so did a pen marking a line on a rotating drum of graph paper, similar to a seismograph or an EKG. This was an old-school recorder that the technicians had to wind up like a wristwatch to make the drum turn. They tried using a computer (i.e. digital device without paper), but the results weren’t that good.

Automatic recorder for measuring flow. The chain on the right turns, rotating a wheel and it moves the pen on the paper back and forth as the river goes up and down. The paper turns at a steady rate, going from one roll to another. 

Although there are many techniques for storing and transmitting the data, nearly every automated station measures streamflow in the same way, by measuring the distance from some baseline to the water level surface. This just measures water depth, not actual river flow. Real flow is river area (i.e. depth by width) times flow speed (i.e. how quickly the water is passing by).

Measuring real flow is not easy and must be done by hand. If the river is low enough, technicians wade across the river but otherwise they lower their instruments into the water from a bridge or a cableway. A dozen or more times at different points between one riverbank and the other the technicians use a pole to measure how far the bottom is and then how high the surface is relative to that. Then at different depths (near the surface, half way down, near the bottom, etc) a flow meter measures the water’s speed. Older flow meters looked a bit like pinwheels, but now there are electronic equivalents.

Measuring flow by hand with a current-meter. An underwater device measures flow speed.

Measuring rivers can be dangerous work, especially when the flow is high. In graduate school I was part of a group measuring streamflow below a medium-sized dam. The releases were cranked up in an experiment so we could measure an artificial floodwave passing through. The river had been full of algae and scum and when the flood finally hit, there was pandemonium. Large mats of yuck clogged our instruments and carried away backpacks left onshore. Students struggled to stand in the fast moving flow. One fell, neatly cricking his back over a small boulder. And we weren’t even dangling from the cableway like the professionals do.

But technicians have to supplement the continuous automated depth measurements from the streamgage with occasional manual measurements to figure out the relationship between depth and flow volume. In theory, when a river is deep it should carry more flow volume than when it is shallow. In simple river channels, like concrete-lined canals or the Log Flume at Disneyland, there is a one-to-one relationship between depth and flow, called a “rating curve”. The problem is that in real rivers out in the wild this relationship is always changing, even during a single flood.

When the technician unrolled the streamgage’s paper, the line showed that the river had been dry for quite some time (right of the graph) but then a knee-deep wall of water appeared in a matter of minutes and continued to rise for the next four hours (hours are marked along the bottom, time goes from right to left). Then the line slowly decayed as the river tapered off back to nothing.

The tale of the tape. The paper record of the recent flood. Before is on the right, after is on the left. A higher line means deeper water.   

Then the line stopped.

Why?

Because there wasn’t any more flow. The flood was over. They turned off the gage.

But according to the streamgage there was still about a foot of water left. The river had stopped flowing, it was just that the gage was sitting in one of those remnant pools of water. The water depth was dropping because that pool was evaporating and soaking into the ground, not because the flow was getting any smaller.  

Notice how I have one leg lower than the other.
Stagnant water pools around the gage after floods.

So what about the rating curve, what about that relationship between river depth and river flow? “I think for every [flood] event they need a [new] curve. It’s not easy.” said Mojtaba. In other countries, the technicians typically spot-check the river every few weeks or every few months. If the budget is tight, they don’t check it at all. Five days ago, the depth for zero flow changed a foot over the course of a few hours, different from when the river was rising as it was when it was falling.   

The could try and fix the problem by moving the whole gage up or down or somewhere else. Already they raised the gage by three feet and moved the gravel around in the riverbed. This makes it hard to compare any new measurements with the old ones though. It’s damned if you do, damned if you don’t, balancing consistency with accuracy. Also, nature is going to do its thing and move the gravel around on its own. The river may even decide to relocate by carving a channel out on the other bank, leaving this gage high and dry, literally.

You fight the river and the river fights you. “[Streamgaging] is a type of war” Mojtaba said. “When there’s rainfall here, the technicians are called out into the showers, to do something ahead of the flood. They are often in danger.” There were stories of them being attacked by dead tree trunks floating down the river. There’s that anticipation that the flood is coming, we gotta prepare, we gotta get our boots on and get out there. Mojtaba paused for a moment before adding “The technicians are our heros”.

Later, one of the technicians showed us how he could throw a stone 55 meters (180 feet) from one bank to the other. It was a running straight arm pitch, like a cricket bowler.

A few months ago I was sitting in my office, trying to figure out if the measurements for a river in Australia were good or bad. If they were bad I would have to come up with my own estimates. The data was particularly erratic when the flow was low. I agonized over if the flow value should be 0.10 or 0.09 or 0.01 or 0.001 or just 0? In reality, it was probably anyone’s guess, plus or minus.

“We should arrange for you to meet Dr Kowsar so you can talk to him in person”. Kowsar was the charismatic leader of the experimental station beginning in the 1980s. He was a legend among hydrologists and Mojtaba was going to arrange for me to visit Kowsar in his home the night before I would have to leave the country.

[As a post-script, the USGS has an excellent set of technical documents on the web that describe the set of best practices they use to measure river depth (stage) and flow volume (discharge) in the US. They are here: Stage Measurements at Gaging Stations and Discharge Measurements at Gaging Stations].

How much water do the trees use? How do you believe the data? (Floodwater Spreading part 2)

In the middle of the desert, floodwaters are diverted into terraces so that more water can seep into the ground and be used by people later. Immediately adjacent to scrubby wastelands, these experimental plots support a thriving eucalyptus forest. But how much water do the trees use? The answers are not always easy. Near the end I write about the subjective (and sometimes controversial) process that scientists use to question data.

Read part one of this series for more background on the Kowsar Floodwater Spreading Experimental Research Station

To show us how deep these eucalyptus tree roots go, research scientist Mojtaba Pakparvar brought us to a metal door on the ground. He lifted the lid to a large hole, a hand-dug well wide enough to climb down, but so deep we couldn’t hear something when dropped to the bottom. The darkness was impenetrable. The walls of the well were lined with layers upon layers of fine roots. This is how I imagined Rapunzel’s hair to look. Mojtaba has found roots at the bottom of this 30 meter (90 foot) well, so who knows how deep they eventually go?

Metal door to well under the forest

Hairy roots that got thicker with depth

The experimental station has many different configurations, some using floodwater spreading with trees and some without. When the floods come through they carry fine silt that settles into the ground. For the plots without trees, this silt clogs the soil’s pores making it harder for the water to pass through. However, the ground beneath the trees is churning and changing so much (because of bug burrows) that this clogging doesn’t happen.

Of course there’s a downside- trees use water and the whole purpose of floodwater spreading is to get the water to soak into the ground as much as possible. At the end of the day, is the water taken from the river just being used to grow a forest and there is no extra water going into the aquifer? There’s debate about how much water is truly saved, making this technology somewhat controversial.

The supporters think that eucalyptus may not be the best trees to use, perhaps something else would use less water but still have the same benefit. The experimental station just picked eucalyptus because that’s what the inventors of floodwater spreading used back in Australia. Maybe something different would be better for Iran. More research is required.

Trench in the experimental plot

Regardless, Mojtaba contends that the evaporation is going to be less than from a dam- that’s just open water exposed to the sky. Furthermore, the benefits of the experimental station to the environment are undeniable. “Before the project, you couldn’t stand here because of the sandstorms” Mojtaba indicated. Now the area was a thriving and complex ecosystem.

To show us how the water-use by trees is quantified, Mojtaba led us to a stand of eucalyptus where one had a gouge in its trunk and some metal wires. He was measuring its sap-flow, the rate of water flowing up or down the trunk. The rate is different from one tree to another and varies by time of the day and seasonally, according to the weather and the amount of water in the soil.

Mojtaba pointing to his sap-flow sensor. 

Basically there are three needles inserted into the trunk, lined up vertically. The middle prong sends out pulses of heat that make the sap warmer. If the sap is rapidly going up then the upper prong will get warmer than the lower prong. It is called the “heat ratio method”. Imagine three friends are in the ocean and the middle friend wets his suit. We can tell the direction and speed of the current based on how quickly one of the neighboring friends feels warm.

When asked how much the tree was using, Mojtaba said he doesn’t know for sure. The sensor was measuring way too high (100 mm per day in summertime) and he was going to send it back to Australia for repairs. Our conversation went like this (paraphrased):

But how do you know it’s too high? How do you know that you’ve installed it correctly? How do you know it’s not a little too high? It’ll always be either too high or too low, these things are not exact… So you mean you don’t just go out there and measure truth?

We never measure truth, we just make observations and then try and guess which ones are bad. They’re all bad, of course, it’s more a matter of more bad or less bad. This is just one tree in a forest. The others could give a different answer. 

Mojtaba compared his results with what most other scientists measured for this species of eucalyptus and it was well out of that range. Maybe nobody else had measured this exact tree, or even this type of tree in this type of climate, but by comparing to others he guessed it was a factor of 10 too high.

There are so many things that could have caused the bad readings. It could have been a bad sensor from the factory. It could have got damaged on its way to the site. Mojtaba has years of experience so he is skilled at installing sensors like this and knows how to interpret the results, but what about someone that was doing it for the first time?

When I was an early grad student, I thought installing environmental sensors in the field was simple and that all data was created equal. It turns out that putting a sensor out in the wild and having it collect good data is about as difficult and individual as taking a proper photograph. Sure, sometimes the automatic settings are enough to get something passable. And of course, like photography, some scientists get caught up in a lust for expensive equipment. But there are also natural talents like composition, lighting, retouching that separate the professionals from the amateurs. There is a long processing of learning from mistakes. As Niels Bohr said “An expert is a person who has found out by his own painful experience all the mistakes that one can make in a very narrow field”.

Lets just consider for a second that the high readings were real and the tree itself was unusual, an outlier?   

The hardest thing about outliers it that they are sometimes real. No theory can survive if it denies the existence of strange things that have actually been found. Case in point: roly-poly bugs caused a four-fold increase in infiltration at the experimental site in recent years. Scientists would have never guessed the ground could suck down water so quickly if they were just looking at maps of soils and geology.

As much as they are scorned like unpopular teenagers in high school, outliers are the ones that put up the biggest challenges to our theories and therefore teach us the most. I say, if you don’t fit in, then happily let your freak flag fly; you’re one of the most valuable people out there.

That said, every outlier can’t be right, not every neighborhood crank can be a prophet. Otherwise, it would be total chaos. Someone has to keep the trains running on time.

Scientists collecting data are extremely reluctant to declare that they have found something new and different from what everyone else has found. The potential for embarrassment is so high and nobody wants to say “I’m right and everyone else is wrong” when they have simply miscalibrated a sensor or installed something upside down. The problem is all that harder when the measurements are out in the environment where factors can’t be controlled like they can in the lab. Most of the field-scientists I know medicate themselves with extremely heavy doses of self-doubt and are never completely satisfied with their work.

Yet, breakthrough discoveries in science are the baseball equivalent of home-runs. There are powerful personal and professional incentives to be the one that finds that thing that everyone else has overlooked. This causes some scientists to swing for the fences, often vigorously and dramatically striking out in the process. One can’t help but dream of knocking one out of the park and popping the celebratory champagne. That World Series victory ring is going to look great on my finger. Good science doesn’t work like baseball, however, where the individual personalities are larger than life. A team sport like soccer is a better model… but that’s a different story.

Steven Goldman, lecturer “The Science Wars: What Scientists Know and How They Know It” has a great description of this phenomenon of questioning data and declaring results to be “true” or not. He discusses a book written by two sociologists that watched scientists in a medical research lab as they were making a Nobel-Prize winning discovery. They documented the scientists’ behaviors and interactions with each other like anthropologists would observe a tribe living in the wilderness. To quote Goldman (my emphasis added),

“What they show in the book [Laboratory Life] is the way in which doing science is a process that is not merely a function of reasoning about data. There are all kinds of complexities associated with, "Is the instrument working correctly? How do we know that that's working correctly? I don't think that data's reliable; I didn't like the way the meter was fluctuating there. Or somebody put the reagent in too quickly." Then the way they talk about, "What's Schally doing today? Does anybody know what Schally is planning to publish? I hear he's giving a paper here." Then, on the phone and saying, "Look, we have some interesting results. I want you to know about it first. I want you to know about it second." …[Scientists] create a framework of allies who, by the time you make your announcement, are already committed to say, "That's good work!"

“So, what [the sociologists] argued, was that …individual scientists working within the community, in some sense make scientific knowledge…Truth is determined by the scientific community standing up and saying, "Yes! Yes, they did it!” Then we give them the Nobel Prize for that, which guarantees that what they did was correct, as it were—it doesn't of course; the Nobel Prize has sometimes been given for work that subsequently was decided was not correct, but they don't take back the Nobel Prize.”

Mojtaba’s case was a no-brainer; he thought the data was obviously bad, completely implausible. But what about more subtle problems with data? Instead of 1000% errors, what about 10% errors? What about sensors that started fine but slowly drifted and decayed?

Not far away there was a case of that where the technicians were struggling with measuring the flow of the river…

[Hang on for part 3!]

Flash flood in Nepal kills at least 15

Seti River flash flood near Annapurna

This story was on the American Geophysical Union landslide blog


Yesterday the Seti River in Kaski District in Nepal was affected by a catastrophic and very sudden flash flood.... To date 15 people are confirmed to have been killed, but the toll will inevitably rise.  Initial estimates are that there are a further 36 people missing, including three tourists. 


The Sydney Morning Herald had quotes from a witness

"There was nothing unusual. People were enjoying picnics, some were relaxing in the hot spring pools by the river and others working," he told the Kathmandu Post. "Out of nowhere came this swelling dark murky water with debris, sweeping away many people."


There is also video of the flood-wave on the Nepal Times that describes it like so


Amateur videos of Saturday morning’s flashflood roaring down the Seti River showed a wall of dirty brown water carrying floating debris that reminded us of pictures of the Japan tsunami. Shocking as these images were, they pale in comparison to what happened 800 years ago on this same river.



Some of the news coverage says that the fatalities are so high because of all the activities that now happen right in the river bed (i.e. mining of gravel), but other coverage says that many fatalities were because the river jumped its banks by a popular recreation spot for locals and tourists. 


That video is from Pokhara near the Annapurna Range. Only a few months ago we visited near this site: "Fewa Lake and the Black Himalayas" (and part 2). Those posts describe the concerns of a local water manager and include a visit to a dam that broke and was later rebuilt.