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Conifers capture the snow, but do they intercept it?

Cross-posted at Highly Allochthonous

split figure with snow covered conifer on left with bare ground underneath. On right, snow covered ground with snowy deciduous forest in background.

Conifers (left) capture much more snow than grass (right foreground) or deciduous forest (right background). But will they keep the ground dry all winter? (Photo by A. Jefferson, 2017)

If you’ve walked through the forest on a rainy day and noticed that it’s drier under the trees, you’ve experienced interception.

In hydrology, interception is when water gets hung up on vegetative leaves, needles, or branches and never makes it to the ground. The precipitation gets evaporated (if liquid) or sublimated (if solid) back into water vapor directly from the vegetative surface before it gets a chance to hit the ground and infiltrate or run off. (If the water hangs out in the vegetation for a while but eventually makes it to the ground, we call it stemflow or throughfall depending on whether it ran down the tree trunk or not.)

Interception can be a pretty significant component of the water budget. In forests, the vegetation can intercept 20-40+% of precipitation. In grasslands, the numbers are in the 10-20% range. Even litter, the dead plant material covering the soil, can cause interception. Interception rates depend on plant type and density, but also how much rain you get, how fast it falls, and how much evaporation can occur during and between storms.

In the winter, interception still happens during snowfall, but now vegetation type really matters. Since deciduous trees shed their leaves in the winter, they become pretty useless for interception. In the picture above, you can’t really see the difference between the deciduous forest and the lawn — they are both fully snow-covered. On the other hand, since conifers retain their needles, they can capture a lot of snow — and you can see that in the bare ground under the trees at left.

Whether the conifers truly intercept all that snow is more complicated. Conifers can initially hold large snow loads, but wind can blow that snow onto the ground, it can be dumped off in large clumps, and melting within the snowpack on the branches can allow the water to drip to the ground. In order to effectively intercept the water and return it to the atmosphere, we’d need sublimation to happen faster than those other processes. But does that happen?

In a study in Oregon’s Umpqua National Forest (Storck et al., 2002), mature conifers initially captured up to 60% of the snowfall (up to at least 40 mm). When conditions were warm and conducive to snowmelt after the snowstorm, 70% of the water left the canopy as meltwater drip and 30% left as masses of snow falling to the ground. Only if the weather remained below freezing after snowfall, could sublimation work to reduce the snow storage in the trees. But that goes slowly, at an average rate of ~1 mm/day. If the weather got above freezing, then melting and dumping took over. Overall, the study site got about 2000 mm of precipitation in the winter and the ground in the forested areas experienced about 100 mm less than the ground in the open areas, giving a winter interception rate of about 5%.

Of course, that’s only one study and other modeling and experimental work adds more nuance and complication. Climate and solar radiation affect sublimation rates. Canopy density affects sheltering by wind and interception. And more. High spatial resolution modeling of two sites in Colorado and New Mexico gives interception values of 19% and 25%, respectively (Broxton et al., 2015). When they consider all of the processes happening to redistribute snow around a patchy forest, they conclude that the driest areas are under tree canopies and the wettest areas are <15 m from the edge of the canopy. If you get farther out into an open area, it gets drier again, though not as dry as under the forest cover. And the differences are not small, snow water input can be 30-40% higher near the edge of the canopy than underneath it. So next time you walk through a forest in the rain or snow, be impressed by the hydrologic work the trees are doing to keep you dry, and know that interception adds up to a significant amount of water. But if it's a warm winter day, don't be surprised to feel a cold meltwater drip from the pine tree above you -- or get a load of snow dumped on your head -- because even conifers can't hang onto the snow long enough to keep the ground dry forever.
Read more:
Broxton, P. D., Harpold, A. A., Biederman, J. A., Troch, P. A., Molotch, N. P., and Brooks, P. D. (2015) Quantifying the effects of vegetation structure on snow accumulation and ablation in mixed-conifer forests. Ecohydrol., 8: 1073–1094. doi: 10.1002/eco.1565. (pdf available via ResearchGate)

Storck, P., D. P. Lettenmaier, and S. M. Bolton, Measurement of snow interception and canopy effects on snow accumulation and melt in a mountainous maritime climate, Oregon, United States, Water Resour. Res., 38(11), 1223, doi:10.1029/2002WR001281. (open access)

#365climateimpacts: Snow, ice, flooding, and football (February 1-15)

In January, I launched the #365climateimpacts project, in which I’ll spend a year tweeting stories of the many ways climate change is impacting people, ecosystems, and the earth; ideas for how to communicate about climate change more effectively; and analyses of technologies and policy proposals that show promise for combatting climate change. Here’s what I’ve shared in the last two weeks.

February 1:
The Climate Feedback project looks like an awesome way to see how scientists read climate change news.

The most recent analysis on the site is of an article called "The big melt: global sea ice at a record low", published by USA Today.

The most recent analysis on the site is of an article called “The big melt: global sea ice at a record low”, published by USA Today.

February 2 (Groundhog Day):
Climate Change versus Groundhogs: Even Common Species Will Suffer. (Not pictured: the groundhog who is digging up by back garden.)

February 3:
Melting glaciers affect water supply in Andes of Peru & scientists are on it. Video by @LaurenDSomers.

February 4:
Screen Shot 2017-02-12 at 4.01.04 PM

I see a trend – and my eyes don’t deceive. Great Lakes annual average ice cover declined 71% from 1973-2010.

February 5 (Superbowl Sunday):
Is Climate Change Making Temperatures Too Hot for High School Football? Will it get too hot for football in the South? State rules aim to prevent heat deaths.

February 6:
Screen Shot 2017-02-12 at 2.55.54 PM
What does a graph like this mean? It means ocean is taking up heat that CO2 emissions would otherwise add to atmosphere.

February 7:
I got a bit gif happy with today’s #365climateimpacts tweetstream, so you should really head over to twitter to enjoy the thread. I like snow. I like to sled, build snowmen, snowshoe, and how pretty snow is. Loss of snow is one reason I care about climate change. Today it is 57 F and raining steadily here in NE Ohio. I keep thinking about how we’d have a foot of snow if it were cold enough. Instead, I spent an hour in my class talking about the fun ways hydrologists have of measuring snow. With bare ground outside.

The average US snow season shortened by 2 weeks since 1972. Snow covered area is decreasing. The figure below is from the US EPA’s great Climate Change Indicators site, under the heading “Snow Cover.

This figure shows the timing of each year’s snow cover season in the contiguous 48 states and Alaska, based on an average of all parts of the country that receive snow every year. The shaded band spans from the first date of snow cover until the last date of snow cover.

This figure shows the timing of each year’s snow cover season in the contiguous 48 states and Alaska, based on an average of all parts of the country that receive snow every year. The shaded band spans from the first date of snow cover until the last date of snow cover.

Climate normals say that my area averages 45″ of snow per winter, but I haven’t seen anywhere near that most of the 5 years I’ve lived here. Of course, 5 years isn’t long enough to identify any trend (I’m not arguing it is), but my experience fits in the pattern of less snowy winters that are being observed across the United States. Here’s some data stretching 60 years. The figure below is from the US EPA’s great Climate Change Indicators site, under the heading “Snowfall.” Red is less snow, more rain.

This figure shows the average rate of change in total snowfall from 1930 to 2007 at 419 weather stations in the contiguous 48 states. Blue circles represent increased snowfall; red circles represent a decrease.

This figure shows the average rate of change in total snowfall from 1930 to 2007 at 419 weather stations in the contiguous 48 states. Blue circles represent increased snowfall; red circles represent a decrease.

(PDF versions of the Snow Cover and Snowfall pages)

February 8 (National Kite Flying Day):
Good morning, Twitter. It’s National Kite Flying Day! Do you think I can tie that to climate change?
President Obama has been appreciating kite flying, recently.
Back in the day, it wasn’t just surfboards powered by wind. It was big ships. Admittedly, with sails, not kites, but I’m doing the best I can to tie to #nationalkiteflyingday.
Modern shipping produces huge amounts of greenhouse gas emissions and wind is a renewable, carbon-free energy source.
One idea is to attach big kites to ships to provide free & CO2-free energy.

February 9:
It’s the middle of winter & something is seriously wrong with Arctic sea ice. Sea ice hit record low extents in November, December, and January. Nice reporting at Mashable by Andrew Freedman.

February 10 (National Umbrella Day):I
Climate change intensifies the water cycle, increasing heavy rainfall events. The figure below is from the US EPA’s great Climate Change Indicators site, under the heading “Heavy Precipitation”.

This figure shows the percentage of the land area of the contiguous 48 states where a much greater than normal portion of total annual precipitation has come from extreme single-day precipitation events. The bars represent individual years, while the line is a nine-year weighted average.

This figure shows the percentage of the land area of the contiguous 48 states where a much greater than normal portion of total annual precipitation has come from extreme single-day precipitation events. The bars represent individual years, while the line is a nine-year weighted average.

(pdf version of the Heavy Precipitation Climate Change Indicators page)

February 11:
The first year’s results from NASA Project OMG (Oceans Melting Greenland) reveal that Greenland’s thick glaciers in deep water are most affected by warmer ocean waters. Follow the project lead scientist Josh Willis @omgnasa on Twitter.

February 12:
Suburbs are increasingly threatened by wildfires due to climate change. The wildland-urban ecotone is where warmer winters longer droughts & climate change consequences flare up.

February 13:
With lots of attention focused on the massive rainfall, flooding, and dam and levee safety issues in California, it seemed like a good time to find out how climate change is expected to alter rainfall patterns in the state. Sure enough, “pineapple express” storms (that bring lots of rain to high elevation areas where it normally snows) are expected to increase as the climate warms.

Satellite image showing narrow band of clouds stretching from Hawaii to California

A “pineapple express” atmospheric river takes aim at California in December 2014. (NOAA/NASA GOES image)

February 14:
Minnesota Public Radio ran a fantastic feature on how climate change is affecting ice cover on Lake Superior between Bayfield and Madeling Island, Wisconsin. For 250 year-round residents of the island, winter offers an ice road and the freedom to move back and forth without being tied to the ferry schedule. Except that, for two years running, the ice hasn’t been thick enough to drive on and the ferry has run all winter. This story is personal for me, because my family has owned land on Madeline Island for 4 generations, and I remember the thrill and terror of driving the ice road on winter visits.

The view from our family's land on Madeline Island, February 3rd, 2017. Photo courtesy of J. Jarvis.

The view from our family’s land on Madeline Island, February 3rd, 2017. Photo courtesy of J. Jarvis.

February 15:
The New York Times highlights a rare Republican call to climate action, in which the “elder statesmen” of the Climate Leadership Council calls for a carbon tax. A report out earlier this month from the Yale Program on Climate Change Communication, shows that 62% of Trump voters support either taxation or regulation of greenhouse gases. The question is: Will Republican politicians listen to the elders or the voters, or will they continue to deny climate change and obstruct meaningful actions to slow its course.

How low will they go? The response of headwater streams in the Oregon Cascades to the 2015 drought

From a distance, Anne has been watching an incredibly unusual summer play out in the Pacific Northwest, following a winter with far less snow (but more rain) than usual. Folks on the ground in Oregon have been collecting data on the response of the Oregon Cascades streams to “no snow, low flow” conditions. Anne is making minor contributions to the following poster, to be presented in Session No. 291, Geomorphology and Quaternary Geology (Posters) at Booth# 101 on Wednesday, 4 November 2015: 9:00 AM-6:30 PM.


LEWIS, Sarah L.1, GRANT, Gordon E.2, NOLIN, Anne W.1, HEMPEL, Laura A.1, JEFFERSON, Anne J.3 and SELKER, John S.4, (1)College of Earth Ocean and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, (2)Pacific Northwest Research Station, USDA Forest Service, 3200 SW Jefferson Way, Corvallis, OR 97331-8550, (3)Department of Geology, Kent State University, Kent, OH 44242, (4)Biological & Ecological Engineering, Oregon State University, Corvallis, OR 97331,

Larger rivers draining the Oregon Cascades are sourced from headwater systems with two distinct runoff regimes: surface-flow dominated watersheds with flashy hydrographs, rapid baseflow recession, and very low summer flows; and spring-fed systems, with slow-responding hydrographs, long baseflow recession, and summer flow sustained by deep groundwater fed coldwater springs. Our previous research has explored these differences on both the wet west-side and dry east-side of the Cascade crest, as expressed in contrasting discharge and temperature regimes, drainage efficiency, low and peak flow dynamics, and sensitivity to snowpack and climate change scenarios. In 2015, record low winter snowpack combined with an anomalously dry spring resulted in historically low flows across our research sites and throughout Oregon. These extreme meteorological conditions, equivalent to a 4°C warming scenario, offer an exceptional opportunity to witness how these contrasting stream networks might respond to anticipated changes in amount and timing of recharge.
Conceptually, channel network response to decreasing discharge may involve both lateral and longitudinal contraction. Lateral contraction, the decrease of wetted channel width and depth, occurs in both surface-flow and spring-fed streams as flows diminish. Longitudinal contraction may be expressed as (a) a gradual drying of the stream channel and downstream retreat of the channel head, (b) a “jump” of the channel head downstream to the next spring when an upper spring goes dry, or (c) no change in channel head despite diminishing flows. We hypothesize that while individual stream channels may display a combination of these dynamics, surface-flow and spring-fed watersheds will have distinctive and different behaviors. We field test our hypothesis by monitoring channel head locations in 6 watersheds during the low flow recession of 2015, and repeatedly measuring discharge, water quality and hydraulic geometry at a longitudinal array of sites along each surface-flow or spring-fed channel. The resulting data set can be used to explore the fundamental processes by which drainage networks accommodate decreasing flows.

Sensitivity of precipitation isotope meteoric water lines and seasonal signals to sampling frequency and location

Allison ReynoldsThis work is being conducted by undergraduate lab member, Allison Reynolds. Allison presented her work as part of the CUAHSI/USGS Virtual Workshop on applications of laser specs to hydrology and biogeochemistry. From that workshop, she will have an extended abstract published in a USGS open file report, and her poster will continue to be viewable on-line. She will also be presenting results at the inaugural Kent State Undergraduate Research Symposium in April. And of course, she’s going to keep working on new data and analyses and aiming for publication. Go Aly!

Sensitivity of precipitation isotope meteoric water lines and seasonal signals to sampling frequency and location
Allison R. Reynolds ( and Anne J. Jefferson (advisor)
Department of Geology, Kent State University, Kent, OH 44242

Our purpose is to compare seasonal signal and local meteoric water line (LMWL) generated by analyzing hydrogen and oxygen isotopes in precipitation for one year of event-based sampling to those from multi-year monthly sampling at the closest Global Network of Isotopes in Precipitation (GNIP) stations. The question we seek to answer is whether data from different sampling strategies, periods, and locations within the eastern Great Lakes region on a regional-scale LMWL and seasonal signal. We collected precipitation samples after each event in Kent, OH. Samples were analyzed with a Picarro L-2130i. The closest GNIP sites are Coshocton, Ohio and Simcoe, Ontario. LMWLs and seasonal signals derived from monthly samples were broadly similar along a 300 km north-south transect in the US eastern Great Lakes Region. Monthly volume-weighted averages of event precipitation under-represent event scale isotopic variability, based on samples from Kent, Ohio.

New paper: Seasonal versus transient snow and the elevation dependence of climate sensitivity in maritime mountainous regions

Snowline near Skykomish, Washington (photo on Flickr by RoguePoet, used under Creative Commons)

Snowline near Skykomish, Washington (photo on Flickr by RoguePoet, used under Creative Commons)

Jefferson, A. 2011. Seasonal versus transient snow and the elevation dependence of climate sensitivity in maritime mountainous regions, Geophysical Research Letters, 38, L16402, doi:10.1029/2011GL048346.


In maritime mountainous regions, the phase of winter precipitation is elevation dependent, and in watersheds receiving both rain and snow, hydrologic impacts of climate change are less straightforward than in snowmelt-dominated systems. Here, 29 Pacific Northwest watersheds illustrate how distribution of seasonal snow, transient snow, and winter rain mediates sensitivity to 20th century warming. Watersheds with >50% of their area in the seasonal snow zone had significant (? ? 0.1) trends towards greater winter and lower summer discharge, while lower elevations had no consistent trends. In seasonal snow-dominated watersheds, runoff occurs 22–27 days earlier and minimum flows are 5–9% lower than in 1962, based on Sen’s slope over the period. Trends in peak streamflow depend on whether watershed area susceptible to rain-on-snow events is increasing or decreasing. Delineation of elevation-dependent snow zones identifies climate sensitivity of maritime mountainous watersheds and enables planning for water and ecosystem impacts of climate change.

Bacteria in the sky, making it rain, snow, and hail

ResearchBlogging.orgCross-posted at Highly Allochthonous

Even though we all think of the freezing point of water as 0 °C, very pure water remains a liquid until about -40 °C. Water crystallizes to ice in the presence of tiny nucleation particles in the atmosphere. These particles can be sea spray, soot, dust … and bacteria.

Bacteria are particularly good at ice nucleation (IN), causing it to occur at temperatures as high as -2 °C. As Ed Yong described 3 years ago:

Ice-forming bacteria like Pseudomonas syringae rely on a unique protein that studs their surfaces. Appropriately known as ice-nucleating protein, its structure mimics the surface of an ice crystal. This structure acts as a template that forces neighbouring water molecules into a pattern which matches that of an ice lattice. By shepherding the molecules into place, the protein greatly lowers the amount of energy needed for ice crystals to start growing.

USDA photo of ice on flowers

Ice on fruit tree flowers. There because of bacteria? (USDA photo)

The fact that bacteria like P. syringae nucleate ice crystals has been known for decades. They can be used for gee-whiz science demonstrations, and, at a much larger scale, as one method for creating artificial snow. On the flip side, the presence of P. syringae is also also makes plants more likely to be frost damaged at temperatures just below freezing. Only in the last several years, though, has the role of bacteria in producing precipitation from the atmosphere begun to be appreciated.

First, Brent Christner and colleagues discovered that every freshly fallen snow sample they collected, even in Antarctica, contained these ice nucleating bacteria. In the resulting 2008 Science paper, they noted:

The samples analyzed were collected during seasons and in locations (e.g., Antarctica) devoid of deciduous plants, making it likely that the biological IN we observed were transported from long distances and maintained their ice-nucleating activity in the atmosphere…our results indicate that these particles are widely dispersed in the atmosphere, and, if present in clouds, they may have an important role in the initiation of ice formation, especially when minimum cloud temperatures are relatively warm.

Then researchers in the Amazon rainforest discovered that primary biological aerosol (PBA) particles, including plant fragments, fungal spores…and yes, bacteria, were a dominant contributor to ice nucleation in clouds above the rainforest. (Even the though the Earth surface is hot in the Amazon, high enough in the troposphere, it’s still below freezing.) As Pöschl and colleagues reported in Science in 2010:

Measurements and modeling of IN concentrations during AMAZE-08 suggest that ice formation in Amazon clouds at temperatures warmer than –25°C is dominated by PBA particles… Moreover, the supermicrometer particles can also act as “giant” [cloud condensation nuclei] CCN, generating large droplets and inducing warm rain without ice formation.

The latest contribution to the growing understanding of bacteria’s role in precipitation was recently presented at the American Society of Microbiology meeting. Alexander Michaud studied hailstones that fell on his Montana State University campus, and as reported by the BBC:

He analysed the hailstones’ multi-layer structure, finding that while their outer layers had relatively few bacteria, the cores contained high concentrations. “You have a high concentration of ‘culturable’ bacteria in the centres, on the order of thousands per millilitre of meltwater,” he told the meeting.

What all of this adds up to is that we now know that bacteria and other biological particles are prevalent in the atmosphere around the world and are stimulating multiple forms of precipitation. As a hydrologist, I think I can wrap my head around this. But what’s really wild is the feedback between biological productivity and precipitation and the possibility that the ice nucleating bacteria moving in the atmosphere may be an evolutionary trait.

Precipitation stimulated by ice nucleation above an ecosystem where the bacteria or other biological particles were emitted sustains the ecosystem that created those particles. As Pöschl et al write:

Accordingly, the Amazon Basin can be pictured as a biogeochemical reactor using the feedstock of plant and microbial emissions in combination with high water vapor, solar radiation, and photo-oxidant levels to produce [secondary organic aerosols] SOA and PBA particles (31, 32). The biogenic aerosol particles serve as nuclei for clouds and precipitation, sustaining the hydrological cycle and biological reproduction in the ecosystem.

Or, in discussion of the recent hailstone findings [from the BBC]:

Dr Christner, also present at the meeting, said the result was another in favour of the bio-precipitation idea – that the bacteria’s rise into clouds, stimulation of precipitation, and return to ground level may have evolved as a dispersal mechanism. … “We know that biology influences climate in some way, but directly in such a way as this is not only fascinating but also very important.”

Tara Smith lolbacteria

and ur rainz and ur hailz (image created by Tara Smith on the Aetiology blog)

Christner, B., Morris, C., Foreman, C., Cai, R., & Sands, D. (2008). Ubiquity of Biological Ice Nucleators in Snowfall Science, 319 (5867), 1214-1214 DOI: 10.1126/science.1149757

Pöschl U, Martin ST, Sinha B, Chen Q, Gunthe SS, Huffman JA, Borrmann S, Farmer DK, Garland RM, Helas G, Jimenez JL, King SM, Manzi A, Mikhailov E, Pauliquevis T, Petters MD, Prenni AJ, Roldin P, Rose D, Schneider J, Su H, Zorn SR, Artaxo P, & Andreae MO (2010). Rainforest aerosols as biogenic nuclei of clouds and precipitation in the Amazon. Science (New York, N.Y.), 329 (5998), 1513-6 PMID: 20847268

Snow, water, digital imaging, metamorphism…and a guillotine!

Cross-posted at Highly Allochthonous

When water infiltrates past the ground surface and begins to percolate through the soil’s unsaturated zone, it doesn’t move downward like an even sheet. Instead, fast fingers of water move downward along pores, roots and other places where flow is easier than through the soil matrix, and water lenses accumulate horizontally where there are changes to less permeable soil horizons. The same principles apply to snow, with the added bonus that the water flowing and the matrix is flowing through are made up of the same substance, separated only by a temperature threshold. So you can get some really complicated dissolution/melting and precipitation/freezing reactions going on throughout the snow profile.

A good way to see these patterns is to apply dyed water to the land or snow surface and then dig a soil or snow pit to examine where the dye ends up. Now Williams et al. (2010) have devised a really cool device for taking sequential, thin, uniform slices of snow off the wall of a snow pit, so that they can see and measure the 3-D structure of preferential flow within the snow profile. They call their device a snow guillotine, because it is basically a sharp blade mounted on a frame that sits on top of the snow surface. A camera is also attached to the frame, at fixed distance from the blade. The blade and camera are mounted on a slider, so after taking a slice and an image of the snow and dye, the scientists can slide it a specified distance and take another slice exposing a new snow surface. (Of course, being good field scientists, all of this can be packed into a remote site, as shown below.)

Figure 4 from Williams et al (2010)
Image from Williams et al (2010) showing the snow guillotine in operation in a dyed snowpack in Colorado. Ski boot for scale.

After the scientists have taken all the slices and photos they want, they can go back to their warm, cozy offices and apply digital image processing techniques to the photos to quantify the 3-D patterns of preferential flow. The vertical images are rectified and can be stacked together into data cubes, allowing the researchers to examine the horizontal centimeter-meter scale patterns as well. You can see this in animated movie of one of their snowpacks in the supplemental materials (no paywall!).

This paper details the results of two dye experiments conducted in Colorado in May and June 2003. Both experiments occurred in isothermal (0 C) snowpacks, but in the second experiment the snow had been isothermal for a longer period of time and had ablated (melted + sublimated) more extensively than in the first dye application. The first experiment showed significant vertical and horizontal heterogeneity, particularly in the upper 20-55 cm of the snowpack, where there were up to 300 distinct vertical preferential flowpaths per square meter. At interfaces between snow layers (i.e., snow that fell at different times) there was significant lateral flow, probably as a result of permeability changes at those boundaries. In lower parts of the snowpack, downward flow was somewhat more evenly distributed and the preferential flowpaths tended to be larger. In the second experiment, more snow metamorphism had occurred, resulting in larger grain sizes and open spaces. In this snowpack, there was still some preferential flow, but, in general, flow was much more evenly distributed throughout the matrix. This finding brings into focus how the snow’s thermal history controls meltwater pathways.

All together then, the dye experiments, cut and photographed by the guillotine setup, and digitally processed in the lab emphasize the importance the small scale (cm to m) heterogeneity on flow through porous media. This isn’t super surprising to people who have spent time studying water flow through soils, but when you are dealing with snow, you add thermodynamics and a matrix that can dramatically metamorphose over time scales of hours to days to weeks to the mix. That adds a level of complexity that makes my mind boggle a little bit, yet Williams et al. have found a simple method to collect to field measurements and process the images in a way that lets them quantitatively describe these flowpaths and will hopefully contribute to a better understanding of the processes and interactions between snowpacks and snowmelt.

Williams, M., Erickson, T., & Petrzelka, J. (2010). Visualizing meltwater flow through snow at the centimetre-to-metre scale using a snow guillotine Hydrological Processes, 24` (15), 2098-2110 DOI: 10.1002/hyp.7630

When it rains a lot and the mountains fall down

Cross-posted at Highly Allochthonous

2006 debris flow deposit in the Eliot Glacier drainage, north flank of Mount Hood (Photo by Anne Jefferson)

The geo-image bonanza of this month’s Accretionary Wedge gives me a good reason to make good on a promise I made a few months ago. I promised to write about what can happen on the flanks of Pacific Northwest volcanoes when a warm, heavy rainfall hits glacial ice at the end of a long melt season. The image above shows the result…warm heavy rainfall + glaciers + steep mountain flanks + exposed unconsolidated sediments are a recipe for debris flows in the Cascades. Let me tell you the story of this one.

It was the first week of November 2006, and a “pineapple express” (warm, wet air from the tropic Pacific) had moved into the Pacific Northwest. This warm front increased temperatures and brought rain to the Cascades…a lot of rain. In the vicinity of Mt. Hood, there was more than 34 cm in 6 days, and that’s at elevations where we have rain gages. Higher on the mountain, there may even have been more rain…and because it was warm, it was *all* rain. Normally, at this time of year, the high mountain areas would only get snow.

While it was raining, my collaborators and I were sitting in our cozy, dry offices in Corvallis, planning a really cool project to look at the impact of climate change on glacial meltwater contributions to the agriculturally-important Hood River valley. Outside, nature was opting to make our on-next field season a bit more tricky. We planned to install stream gages at the toe of the Eliot and Coe glaciers on the north flank of Mt. Hood, as well as farther downstream where water is diverted for irrigation. But instead of nice, neat, stable stream channels, when we went out to scout field sites the following spring, we were greeted by scenes like the one above.

Because sometime on 6 or 7 November, the mountain flank below Eliot Glacier gave way…triggering a massive debris flow that roared down Eliot Creek, bulking up with sediment along the way and completely obliterating any signs of the pre-existing stream channel. By the time the flow reached the area where the irrigation diversion occur, it had traveled 7 km in length and 1000 m in elevation, and it had finally reached the point where the valley opens up and the slope decreases. So the sediment began to drop out. And debris flows can carry some big stuff (like the picture below) and like the bridge that was washed out, carried downstream 100 m and turned sideways.

2006 Eliot Glacier debris flow deposit (photo by Anne Jefferson)

2006 Eliot Glacier debris flow deposit (photo by Anne Jefferson)

In this area, the deposit is at least 300 m wide and at least a few meters deep.

Eliot Creek, April 2007 (photo by Anne Jefferson)

Eliot Creek, April 2007 (photo by Anne Jefferson)

With all the big debris settling out, farther downstream the river was content to just flood…

Youtube video from dankleinsmith of the Hood River flooding at the Farmers Irrigation Headgates

and flood…

West Fork Hood River flood, November 2006 from

West Fork Hood River flood, November 2006 from For the same view during normal flows, take a look at my picture from April 2007:

and create a new delta where Hood River enters the Columbia.

Hood River delta created in November 2006 (photo found at

Hood River delta created in November 2006 (photo found at

And it wasn’t just Mt. Hood’s Eliot Glacier drainage that took a beating in this event. Of the 11 drainages on Mt. Hood, seven experienced debris flows, including a rather spectacular one at White River that closed the main access to a popular ski resort. And every major volcano from Mt. Jefferson to Mt. Rainier experienced debris flows, with repercussions ranging from downstream turbidity affecting the water supply for the city of Salem to the destruction of popular trails, roads, and campgrounds in Mt. Rainier National Park (pdf, but very cool photos).

In the end, our project on climate change and glacial meltwater was funded, we managed to collect some neat data in the Eliot and Coe watersheds in the summer of 2007, and the resulting paper is wending its way through review. The November 2006 debris flows triggered at least two MS thesis projects and some serious public attention to debris flow hazards in the Pacific Northwest. They also gave me some really cool pictures.

Snowfall map from 1-2 March 2009

The National Weather Service has produced a pretty map of snowfall totals from the storm a few weeks ago.  Mecklenburg County (Charlotte) got around 4″, which is a hair more than I measured at home on Monday morning (~3.5″ plus an ice layer). At our field site in Gaston County, the land owner told me he got ~5″ of snow, and that’s what the map shows as well.