On the perils of Lake Sarez (Usoi) in Tajikistan

Science this week has an article (Stone 2009) on the perils associated with Lake Sarez in the Pamirs. Sarez is a huge lake (56 km long and with a volume of 17 billion cubic metres of water) that was formed by a landslide triggered by the 1911 earthquake in Tajikistan (see image below).

Google Earth image of Lake Sarez. The landslide dam is to west (left).

Google Earth image of the landslide dam at Usoi. The source of the landslide was to the north of the current deposit.

The landslide dam (see image above) stands 567 metres tall. To put that in perspective, the image below shows Taipei 101, until recently the world's tallest building. It is 501 metres tall:

Taipei 101 (source Wikipedia)

Since its creation Lake Sarez has been steadily filling, which has long been a concern. There are an estimated 5.5 million people living downstream of the dam in the Amu Darya river valley, which flows through Tajikistan, Afghanistan, Turkmenistan, and Uzbekistan. There are really three key concerns with this dam:

1. The dam could fail through seepage - a few years ago water started to seep through the landslide deposit, the concern is that this will erode out the core of the landslide;
2. The dam could fail in an earthquake - this is a seismically-active zone, but the threat is considered to be quite low as the dam is considered to be quite stable;
3. The dam could fail as a result of another landslide going into the lake, creating a displacement wave (similar to the Vaiont landslide) that causes the dam to overtop. Of course this is most likely to be triggered by an earthquake landslide.
   

The article points out that the third of these is the most likely, such that the site has a sizable warning system just in case.

The article points out that given the number of people downstream the risks are now considered to be too high. The dam itself cannot be stabilised, so there is a need to draw down the level of the lake by at least 50 m. However, there can be little doubt that this falls in the "easier said than done" category.

The key component of the article is highlighting that there are a range of views as to the level of danger at this site, both in terms of the possibility of another landslide and of the stability of the dam itself. The article quotes a number of notable landslide experts:

• Jorg Hanisch is quoted as saying that "the probability is 1 in a million,"of the dam being overtopped by a wave created by a landslide. He also rules out any possibility of the dame being eroded by seepage.
  
• Jean Schneider from BOKU in Vienna is quoted as saying that "The risk of even a partial outbreak is exaggerated...the dam will only possibly be overtopped in the far future."
• On the other hand, Kadam Maskaev (deputy director of the emergency situations committee in Tajikistan) views the seepage in a different way: "The filtration regime of the dam is changing, and that makes me nervous."
• Kyoji Sassa, the chair of the International Consortium on Landslides, has a different view again. The article claims that he argues that the threat from a further landslide is significant.
  

The suggested optimum mitigation approach is a diversion tunnel that would be used to generate hydroelectric power, with the water also being made available to downstream communities. However, the costs are high ($500 million) and such a project is not without risks. In the sort term it appears that there will be a research campaign that will culminate in a conference in 2011, the 100th anniversary of the dam. That would be an interesting meeting to attend!

Reference
Stone, R. (2009). Peril in the Pamirs Science, 326 (5960), 1614-1617 DOI: 10.1126/science.326.5960.1614

The link between rainfall intensity and global temperature

The aftermath of a landslide in Taiwan caused by very heavy rainfall

One of the most interesting aspects of the global landslide database that we maintain at Durham is the way in which it has highlighted the importance of rainfall intensity in the triggering of fatal landslides. Generally speaking, to kill people a landslide needs to move quickly rapid, and rapid landslides appear to be primarily (but note not always) triggered by intense rainfall events (indeed in the reports the term "cloudburst" often crops up). So, a key component of trying to understand the impacts of human-induced global climate change on landslides is the likely nature of changes in rainfall intensity, rather than that of rainfall total. Put another way, it is possible that the average annual rainfall for an area might decrease but the occurrence of landslides increase if the rainfall arrives in more intense bursts.

There is of course a certain intuitive logic in the idea that rainfall intensity might increase with temperature. Warmer air is able to hold more moisture (as anyone who has been in the subtropics in the summer will know only too well!) and of course increased temperatures also drive greater convection, responsible for thunderstorm rainfall. Of course this is a very simplistic way to look at a highly complex system, so it is not enough to rely upon this chain of logical thought. However, until now there have been surprisingly few studies to actually quantify whether there is a relationship between global temperature and precipitation intensity, which has meant that for landslides understanding the likely impact of climate change has been quite difficult.

However, an important and rather useful paper examining exactly this issue has sneaked under the radar in the last few months. The paper, by Liu et al (2009) (see reference below), was published in Geophysical Research Letters a couple of months ago. The paper uses data from the Global Precipitation Climatology Project (GPCP). These data can be accessed online here (so no claims that climate scientists don't publish their data, please!) The dataset provides daily rainfall totals for 2.5 x 2.5 degree grid squares across the globe, extending back almost 50 years. Liu et al. (2009) looked at the data from 1979 to 2007, comparing precipitation density with global temperature in this time period.

Their results are both unsurprising and surprising. The unsurprising part is that they found that the occurrence of the most intense precipitation events does increase with temperature. The surprising part is the magnitude of the change - they found that a 1 degree Kelvin (Centigrade) increase in global temperature causes a 94% increase in the most intense rainfall events, with a decrease in the moderate to light rainfall events. Indeed the median rainfall increased from 4.3 mm day⁻¹ to 18 mm day⁻¹, which is a surprisingly high shift as well.

So why is this important in the context of landslides? Well, I think that there are probably two key implications:

1. It has long been speculated that anthropogenic warming will lead to an increase in landslides, but with little real quantitative evidence to confirm or deny this. The demonstration that higher global temperatures does lead to increased precipitation intensity starts to put some meat on the bones of this idea. Furthermore, if it is possible to directly link rainfall intensity to landslide occurrence (and there is some evidence both from my own work and from that of others that this may be possible), then it should be possible to start to examine the likely increase in landslides as warming proceeds.
2. The current global climate models assume a much lower increase overall in precipitation intensity with increasing temperature than Liu et al. (2009) suggest. Indeed most of the models assume about a 7% increase per degree Kelvin (Centigrade) warming. For the most intense precipitation events this means that the models predict about a 9% increase, which is an order of magnitude lower Liu et al. (2009) found. This suggests that the rainfall projections that are derived from the models are probably overly-conservative, and possibly very much so, which is a concern. If so, then forecasts of landslide occurrence that are derived from these models are likely to under-estimate the true impact.

Of course, this is only one study, and it should also be noted that the most intense rainfall events are usually associated with tropical areas and with those in the path of hurricanes and in particular typhoons. There is a great deal more work to do on this topic, but the initial results provide real cause for concern.

Reference
Liu, S., Fu, C., Shiu, C., Chen, J., & Wu, F. (2009). Temperature dependence of global precipitation extremes Geophysical Research Letters, 36 (17) DOI: 10.1029/2009GL040218

The ten greatest landslide papers?

Whilst pushing my five year old daughter on the swing the other day (a task that leaves plenty of time to think!), I was pondering upon the greatest landslide papers of all time. I thought that it would be interesting to compile a list and invite suggestions of alternatives. So, here is my list, in no particular order:

1. Terzaghi on the principle of effective stress
In 1936 Karl von Terzaghi laid the foundation for modern soil mechanics, and the basis of our understanding of how landslides move, by stating the principle of effective stress. The recognition that pore water pressures control the frictional resistance of slopes remains the most important concept in understanding landslide behaviour.
Reference: Terzaghi, K., 1936. "The Shear Resistance of Saturated Soils". Proceedings of the first International Conference on Soil Mechanics and Foundation Engineering, Cambridge, U. S. A., 1, 54-56.

2. Keefer on earthquakes caused by landslides
Dave Keefer's 1984 paper on landslides triggered by earthquakes was a remarkable analysis. Taking a huge dataset of earthquake-triggered landslide inventories, Keefer demonstrated both the simplicity and the complexity of the relationship between numbers and areas of landslides and the earthquake parameters. The approach taken in this paper has been much reproduced since; remarkably it the core conclusions are essentially unaltered.
Reference: Keefer, D.K., 1984, Landslides caused by earthquakes. Geological Society of America Bulletin, 95, 406-421.

3. Hutchinson and Bhandari on undrained loading
Undrained loading is one of those concepts that makes you go "of sourse" when it is explained to you. The idea is that the sudden application of a load (such as for example a rockfall from a cliff onto an mudslide below) drives a dramatic increase in pore pressures, which can't dissipate quickly. This reduces the effective normal stress, allowing the slope to move. It explains landslides in many settings - a crucial step forward.
Reference: Hutchinson, J. N. & Bhandari, R. K. 1972. Undrained loading, a fundamental mechanism of mudflows and other mass movements. Geotechnique 21, 353-358

4. Caine on thresholds associated with landslide initiation
Almost all of the working large area landslide warning systems are based on this paper. Caine set out to understand the rainfall thresholds at which landslides occur, recognising that it is a combination of medium term low intensity rainfall (to get the ground wet) and short duration rainfall (to get initiate movement) that is the key. This is literally the paper that launched a thousand studies - and more appear every year. There is even a website dedicated to this type of work: http://rainfallthresholds.irpi.cnr.it/threshold_info.htm
Reference: Caine, N., 1980. The rainfall intensity-duration control of shallow landslides and debris flows. Geografiska Annaler, 62A, 23-27.

5. Skempton on the principle of residual strength
Residual strength is a key idea within landslide science. Skempton's work was prompted by the difficulties of explaining why low gradient slopes were failing. The idea that materials have a residual strength that is less than the peak strength is key - slopes that have in previous times been reduced to this lower strength will fail much more easily when disturbed. This concept really made Skempton's career, and he was ultimately knighted for his scientific contributions.
Reference: Skempton, A.W. 1964. Long term stability of clay slopes. Geotechnique, 14, 77-101 (the fourth Rankine lecture).

6. Carson and Petley on the existence of threshold slopes
In case you are wondering, this Petley is not me, but shall we say that when I was a child I spent a great deal of time with him (and continue to do so, but more rarely now). In many ways the dataset in this paper is not comprehensive, but the ideas that it introduced are fundamental. The paper suggested that in any environment a slope will relax to a constant gradient that reflects its stength and the conditions to which it is exposed. The idea was spot on, and is just being rediscovered by geophysicists!
Reference: Carson, M.A., and Petley, D.J., 1970, Existence of threshold hillslopes in denudation of
landscape. Transactions of the Institute of British Geographers, 49, 71–95.

7. Carrara on the evaluation of landslide hazardLandslide hazard assessment is big business these days. Carrara's paper was not the very first to do this, but it was a pioneering study in terms of using the rapidly evolving technologies that were becoming available. The myriad of factor and suchlike based studies that have followed over the last 26 years all owe a great deal to this study.
Reference: Carrara, A. 1983. Multivariate models for landslide hazard evaluation. Journal of the International Association for Mathematical Geology, 15, 403-426.

8. Hoek and Bray on rock slope engineering
This is the only item on my top ten that is a book rather than a paper. The stability of rockslopes is primarily controlled by the properties, orientations and interactions of discontinuities rather than by the intact material strength. This book brought together for the first time the principles of rockslope stability and design. It has been revised and reprinted on numerous occasions, and remains the bible of rock slope engineers.
Reference: Hoek, E. and Bray, J. 1974. Rock slope engineering. Institution of Mining and Metallurgy, 309 pp.

9. Bjerrum on progressive failure
The principles and processes of progressive failure remain poorly understood, but Bjerrum's 1967 examination of this key topic remains the salient work in this area. Bjerrum proposed a model for the weakening of slopes with time as a crack grows through the base. The concepts remain fresh and valid today - there is surely a great opportunity for someone to take this issue and produce the definitive follow-up on how this process actually operates.
Reference: Bjerrum L. 1967. Progressive failure in slopes of overconsolidated plastic clay and clay shales. Journal of the Soil Mechanics and Foundations Division, ASCE, 93, 1-49.

10. Bishop and Wesley on soil testing
Without laboratory testing of laboratory materials slope engineering would still be in the dark ages. The key research machine in every geotechnical laboratory is the triaxial cell, and research purposes the stress path cell is the most important tool. This paper described just such a machine, opening the way to our fundamental understanding of soil behaviour.
Reference: Bishop, A.W. and Wesley, L.D. 1975. A hydraulic triaxial apparatus for controlled stress path testing. Geotechnique 25, 657-670.
I'm sure that you don't agree with me, so please tell me why I am wrong, and suggest alternatives. I am worried that there is nothing since 1984 - surely there must have been great papers in the intervening 25 years. What have I missed?

On the dangers of Rhododendrons!

Rhododendrons are one of those plants that, when planted well, can create an amazing garden:

(from: http://www.kelleriisgaarden.dk/rhododendron-eng.html)

However, it might surprise you to hear that they can be a major cause of landslides. As the image below shows, rhododendrons are increasingly grown on the mountain slopes of the Appalachians:

(from: http://toursinthesmokymountains.com/SmokyMountainsInDepth.aspx)

As well as creating a somewhat beautiful landscape, rhododendrons have been grown in the Appalachians as a result of logging and fire suppression policies. Forest fires have long been perceived as a major hazard, and fire-exposed land is highly prone to landslides (a major fear in California given the fires in this El Nino year). The Appalachians have a long landslide history - in 1969 for example heavy rainfall associated with the passage of the remnants of a hurricane triggered 3700 debris flows, causing 150 fatalities and $116 million of economic losses.

In a recently published paper, Tristan Hales (now at Cardiff University) and colleagues (2009) looked at the role of roots in providing strength to the soil in the Appalachians. The results are quite interesting. It is clear that in many Appalachian slopes the key thing that prevents landslides is the strength provided to the soil by the roots of the trees and shrubs. Therefore, anything that causes a reduction in this strength will lead to an increased chance of landslides. Hales et al. (2009) set out to measure the strength provided by different plants and trees in plots on slopes in the Appalachians. They found that different varieties of trees had broadly similar root strengths, but that for the native rhododendron species was markedly lower. Furthermore, the roots tend to be concentrated in the upper layers of the soil (tree roots extend much deeper), the rhododendrons are less effective at removing and transpiring water from the soil than are trees, and the thick bushy vegetation starves the forest floor of light, which prevents tree sapling growth.

All of this is of course bad news in terms of landslides. Hales et al. (2009) are keen to stress that this should not be seen as a definitive indication that rhododendrons are responsible for landslide initiation in the Appalachians, but they do note that in the last large landslide event, in 2004, many of the landslides were initiated in thickets of rhododendrons.

Reference
Hales, T., Ford, C., Hwang, T., Vose, J., & Band, L. (2009). Topographic and ecologic controls on root reinforcement Journal of Geophysical Research, 114 (F3) DOI: 10.1029/2008JF001168

Are satellite-based landslide hazard algorithms useful?

In some parts of the world, such as the Seattle area of the USA, wide area landslide warning systems are operated on the basis of rainfall thresholds. These are comparatively simple in essence - basically the combination of short term and long term rainfall that is needed to trigger landslides is determined, often using historical records of landslide events. A critical threshold is determined for the combination of these two rainfall amounts - so for example, it might require 100 mm of rainfall in hours after a dry spell, but 50 mm after a wet period. These threshold rainfall levels have been determined for many areas; indeed, there is even a website dedicated to the thresholds!

In 1997 NASA and JAXA launched a satellite known as TRMM (Tropical Rainfall Monitoring Mission), which uses a suite of sensors to measure rainfall in the tropical regions. Given that it orbits the Earth 16 times per day most tropical areas get pretty good coverage. A few years ago Bob Adler, Yang Hong and their colleagues started to work on the use of TRMM for landslide warnings using a modified version of rainfall thresholds. Most recently, this work has been developed by Dalia Bach Kirschbaum - and we have all watched the development of this project with great interest. The results have now been published in a paper (Kirschbaum et al. 2009) in the EGU journal Natural Hazards and Earth Systems Science - which is great because NHESS is an open access journal, meaning that you can download it for free from here.

Of course a rainfall threshold on its own doesn't tell you enough about the likelihood of a landslide. For example, it doesn't matter how hard it rains, if the area affected is in a flat, lowland plain then a landslide is not going to occur. To overcome this, the team generated a simple susceptibility index based upon weighted, normalised values of slope, soil type, soil texture, elevation, land cover and drainage density. The resulting susceptibility map is shown below, with landslides that occurred in 2003 and 2007 indicated on the map:


A simple rainfall threshold was then applied as shown below:

Thus, if an area is considered to have high landslide susceptibility and to lie above the threshold line shown above based upon an analysis using 3-hour data from TRMM, then a warning can be issued.

Kirschbaum et al. (2009) have analysed the results of their study using the landslide inventory datasets shown in the map above. Great care is needed in the interpretation of these datasets as they are derived primarily from media reports, which of course are heavily biased in many ways. Examination of the map above does show this - look for example at the number of landslide reports for the UK compared with New Zealand. The apparent number is much higher than in NZ, even though the latter is far more landslide prone. However, in New Zealand the population is small, the news media is lower profile, and landslides are an accepted part of life. However, so long as one is aware of these limitations then this is a reasonable starting point for analysing the effectiveness of the technique.

So, how did the technique do? Well, at a first look not so well:



In many cases the technique failed to forecast many of the landslides that actually occurred, whilst it also over-forecasted (i.e. forecasted landslides in areas in which there were none recorded) dramatically. However, one must bear in mind the limitations of the dataset. It is very possible that landslides occurred but were not recorded, so at least to a degree the real results are probably better than the paper indicates. Otherwise, the authors admit that the susceptibility tool is probably far too crude and the rainfall data to imprecise to get the level of precision that is required. However, against this one should note that the algorithm does very well (as indicated by the green pixels on the map above) in some of the key landslide-prone areas - e.g. along the Himalayan Arc, in Java, in SW India, the Philippines, the Rio de Janeiro area, parts of the Caribbean, and the mountains around the Chengdu basin. In places there is marked under-estimation - e.g. in Pakistan, Parts of Europe and N. America. In other places there was dramatic over-estimation, especially in the Amazon Basin, most of India, Central Africa and China.

All of this suggests that the algorithm is not ready for use as an operational landslide warning system. Against that though the approach does show some real promise. I suspect that an improved algorithm for susceptibility would help a great deal (maybe using the World bank Hotspots approach), perhaps together with a threshold that varies according to area (i.e. it is clear that the threshold rainfall for Taiwan is very different to that of the UK). Kirschbaum et al. (2009) have have produced a really interesting piece of work that represents a substantial step along the way. One can only hope that this is developed further and that, in due course, an improved version of TRMM is launched (preferably using a constellation of satellites to give better temporal and spatial coverage). That would of course be a far better use of resource than spending $4,500 million on the James Webb Space Telescope.

Reference
Kirschbaum, D. B., Adler, R., Hong, Y., and Lerner-Lam, A. 2009. Evaluation of a preliminary satellite-based landslide hazard algorithm using global landslide inventories. Natural Hazards and Earth System Science, 9, 673-686.

The role of landslides in global warming

A rather extraordinary paper has just been published in Geophysical Research Letters about landslides triggered by the Wenchuan (Sichuan) earthquake. Why is it extraordinary - well, let me quote from the abstract. The paper suggests that the landslides caused destruction of vegetation such that "the cumulative CO₂ release to the atmosphere over the coming decades is comparable to that caused by hurricane Katrina 2005 (~105 Tg) and equivalent to ~2% of current annual carbon emissions from global fossil fuel combustion."

Wow! In case you are struggling to decode the above, this suggests that the landslides triggered by the earthquake caused a massive loss of vegetation that will now decay. In decaying it will release CO2, which will add to the effects of global warming. This is a pretty interesting result - and it has already been picked up by the mainstream media.

So, how do the authors reach these remarkable conclusions, and are they valid? Well, I am afraid that I have some serious doubts about this study, which seem to be based on some misunderstandings of earthquake-induced landslides. Lets base the analysis on Fig 2 of the paper, reproduced below, in which the authors highlight one of the landslides that blocked the valley on the river upstream of Beichuan:


So why do I object so strongly to the paper? Well first, the use of terminology is inexcusably weak. For example, the authors describe the landslides thus (referring to Fig 2a): " (a) Living carbon scars left by mudslides, which indicates the geographical locations of the landslides for this region." NO - these are not mudslides - these are clearly shallow rockslides - a very different beast. Of Figure 2b they say "A quake surface wave triggered basal sliding that initiated the movement through liquefying the top ~2 m slab." NO. Failure was not due to liquefaction, and even the most cursory view of the image shows that more than 2 m of material was displaced. Finally, they say of Fig. 2d "An aerial photo taken on May 26, 2008, showing the landslide mud that formed the Tangjiashan quake lake". No again - this is most definitely not mud (see image below) - it is bouldery / fragmented debris (if it was mud then the problems would have been far less serious). They say that there model suggests that "The material reaches a maximum speed of 5 m s⁻¹ but only briefly because the resistance stress is strong for the still coherent sliding material. " Again, this is poppycock. 5 m/sec is 18 km/hour - there is no way that this failure was as slow as that - look at how the debris fragmented and at how it spread across the valley (see image of the landslide deposit being excavated for the drainage channel below):

This is not a deposit that was emplaced at 5 m/sec, and nor is it mud. Pretty poor stuff, frankly. Note finally that figs 2b and 2d are supposed to represent the same area. However, in 2d the debris is clearly in the valley floor, with the source being the slopes above. In 2d the debris is above the 1155 m contour line. There is no debris between 1100 m and 1155 m - so the deposit areas are completely different.

So now lets turn to the modelling. The paper is ridiculously short of proper detail of what they have actually done - I cannot understand how the editors/referees let this through. It states that they have used an "advanced modeling tool—a scalable and extensible geo-fluid model—that explicitly accounts for soil mechanics, vegetation transpiration and root mechanical reinforcement, and relevant hydrological processes. The model considers non-local dynamic balance of the three dimensional topography, soil thickness profile, basal conditions, and vegetation coverage ... in determining the prognostic fields of the driving and resistive forces, and describes the flow fields and the dynamic evolution of thickness profiles of the medium considered, be it granular or plastic."

Hmmm! Not sure what this means really. However, they do state that "we need to use the finest possible digital elevation model (DEM) and soil profile data". However, they have actually used the SRTM data-set, which has a spatial resolution of 30 metres at best, and possibly 90 metres (!). I cannot believe that this is anything like good enough. Where velocity exceeded 1m/s in their model they assume that vegetation is destroyed. They have used this to determine the total amount of vegetation lost, and then calculated the contribution of the CO2 to the atmosphere.

There are several problems with this. First, the landslide model appears to be erroneous, as described above. Second, they seem to omit to include the uptake of CO2 by vegetation as it re-establishes on the slide scars, which will in the long term balance that emitted. Finally, note that they say 2% of CO2 emitted by burning fossil fuels, not 2% of all anthropogenic sources. This makes the contribution sound larger than it actually is. Indeed, 2% of annual anthropogenic emissions spread over a substantial period (it doesn't say how long) indicates a comparatively minor annual total.

In my view the basis of the paper is iffy, although it would have helped if the methodology had been properly outlined. Unfortunately, the work is already being picked up the climate change denier community. Read this and weep. The logic used by Paul Fuhr in this opinion piece makes no sense at all to me, but the fact that he can use this paper in this way is deeply unfortunate, providing yet more ammunition for the pseudo-science community of climate change deniers.

Reference
Diandong Ren, Jiahu Wang, Rong Fu, David J. Karoly, Yang Hong, Lance M. Leslie, Congbin Fu, Gang Huang (2009). Mudslide-caused ecosystem degradation following Wenchuan earthquake 2008 Geophysical Research Letters, 36 (5) DOI: 10.1029/2008GL036702

Future British seasonal precipitation extremes - implications for landslides

One of the great questions of the age is of course the ways in which climate change will affect the weather patterns that we are likely to see in the future. In the case of landslides the key issue is the ways in which precipitation patterns will alter, especially the most intensive rainfall events that are responsible for many of the most damaging landslides. One of the most significant steps forward over the last few years has been the ability of global climate models to handle these extreme events, meaning that at last we are starting to develop some capability.

This week an important paper has been published by Fowler and Ekstrom (2009), which seeks to look at the likely changes to very intense rainfall events in the UK. Helen Fowler, is based just up the road from me at Newcastle (the city with the chronically under-performing football team), and her co-author have used modelling ensembles to examine how UK precipitation regimes are likely to change in the time period 2070 to 2100 under the SRES A2 emissions scenario, which is currently effectively our best estimate as to how carbon dioxide emissions will change with time (Fig. 1).

Fig 1: SRES Emissions Scenarios. A2, as used in this study, is shown in Fig. (b). Source: http://www.grida.no/publications/other/ipcc_sr/?src=/Climate/ipcc/emission/014.htm

Ensemble modelling looks at the results of a series of different climate models to examine the range of outputs. Each model operates in a slightly different way, meaning that there will always be a range of results. Therefore, papers presenting ensemble model outcomes always present a range. One of the key issues of interest is whether there is some consistency between them. In this study. Of course the results of such modelling runs are highly complex - in this paper the authors have looked at the 1 day and 10 day precipitation events with a current return period of 25 years. The 1 day event can be thought of as the impact of an intense storm; the 10 day probably simulates a series of low pressure systems tracking across the country, as has happened several times in the last few of years. In landslide terms the 1 day storms might trigger the catastrophic debris flow and sallow failure events, whilst the 10 day events might trigger deeper seated and large slope failures.

First the model is run for the a control period (1961-1990) to check that they can realistically simulate observed conditions. They can. The models are then run to look at what would happen in the period between 2070 and 2100, and the results are then pooled using a fairly interesting approach. Well, the first thing to say is that the Global Climate Models (GCMs) do predict a much warmer climate - global mean temperatures are predicted to be 3.1 to 3.56 degrees warmer than at present. Interestingly though the occurrence of these intense rainfall events also greatly increases for three of the four seasons:
Winter: Increases in occurrence of extreme precipitation of 5 to 30%
Spring: Increases in occurrence of extreme precipitation of 10 to 25%
Summer: Very varied results, with some models suggesting decreases and other increases. More work is needed
Autumn (Fall): Increases in occurrence of extreme precipitation of 5 to 25%

A few of the models do predict larger (and smaller) increases - look at the paper for the full detail. Overall, the authors conclude that "Nevertheless, importantly for policy makers, the multi-model ensembles of change project increases in extreme precipitation for most UK regions in winter, spring and autumn. This change is physically consistent with warmer air in the future climate being able to hold more moisture. The use of multi-day extremes and return periods also showed that short-duration extreme precipitation is projected to increase more than longer-duration extreme precipitation, where the latter is associated with narrower uncertainty ranges."

The implications for landslides are stark. Increases on this level of the occurrence of extreme precipitation events will inevitably increase the occurrence of slope failures. Therefore, we should expect to see an increase in the occurrence of slope failures. Unfortunately, as landslides are triggered by just a small proportion of our existing rainstorm events, increases in this range are likely to have a disproportionate impact.

Of course the next thing to do will be to build the outputs of these models into slope stability models. This will be a fascinating exercise.

Reference:
H. J. Fowler, M. Ekström (2009). Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes International Journal of Climatology DOI: 10.1002/joc.1827

Spatial patterns of deaths from natural hazards in the US

There is a very interesting paper in press in the International Journal of Health Geographics on the spatial patterns of mortality (deaths) from Natural Hazards in the United States. The paper, entitled "Spatial Patterns of Natural Hazards Mortality in the United States" by Borden and Cutter is in pre-print form but can be downloaded as a PDF here. First up, lets be clear that the authors are reputable - Susan Cutter in particular has made a massive contribution to our understanding of the social impacts of natural hazards and, unlike many working in this field, she has managed to keep her materials sensible, balanced and approachable.

The paper looks at the spatial pattern of mortality from hazards using an improved dataset orginally based upon the Spatial Hazard Event and Loss Database (SHELDUS), which is available at http://sheldus.org), covering the period 1970-2004. Much of the paper relates to the reliability of the data and the quality of the database, but there are also some interesting outcomes in terms of the spatial distribution and also the cause of death.

First, the spatial distribution is perhaps not what one would expect (Fig. 1). Intuitively one might say that the highest level of mortailty would be on the west coast given the earthquake hazard, but in fact the map shows no clear spatial pattern, with pockets of high mortality occurring across the whole of the country. There is a slighlty higher level of mortality in the midwest than in the east, reflecting the pattern if temperature extremes perhaps.

Figure 1: The map of the spatial distribution of mortality across the USA for the period 1970-2004. This map is Fig. 3 from Borden and Cutter (2009) (Biomed Central Ltd).

The reason for this is that there is a vast range of causes of death in natural hazards in the USA, with temperature-related deaths (either from heat or cold) dominating.

So what of landslides? Well, the combined datasets indicate 170 landslide fatalities out of a total of 19,958, which is 0.85% of the total. In comparison, geophysical hazards (presumably earthquakes and volcanoes) provide 302 deaths (1.5% of the total).

One of the things that the study highlights, although does not really discuss explicitly, the key importance of time in such a study, bearing in mind the low frequency but high magnitude nature of natural hazards. For instance, the time period does not include the occurrence of Hurricane Mitch in 2005 - I suspect that the map might look a little different if the >1800 fatalities in this event were included. Similarly, the map does not include a very large earthquake in California or on the Cascadia subduction zone. Therefore, great care must be taken in the use of such data to evaluate risk rather than impact.

The paper finishes by acknowledging that much work is needed on this type of analysis. The paper presented here is a very useful step along the way.

Reference
Borden, K.A. and Cutter, S.L. 2008 in press. Spatial Patterns of Natural Hazards Mortality in the United States. International Journal of Health Geographics, 7:64. doi:10.1186/1476-072X-7-64 .