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Understanding, communicating and managing uncertainty and risk related to future changes in catchments.

CCN News

Virtual Catchments and CCN
added on 30 11 2009 by Clare Black
It is the end of a long intense week at the NERC Virtual Observatory Sandpit.  The aim of a sandpit is to bring together a collection of researchers Read more..

It is the end of a long intense week at the NERC Virtual Observatory Sandpit.  The aim of a sandpit is to bring together a collection of researchers (including a number of others with links to CCN: Phil Haygarth, Sim Reaney, Paul Quinn) to produce a draft consortium proposal that is then assessed by a committee as to whether it should go to a full proposal.  The committee, in this case, included a number of potential users of the virtual observatory, for example, Defra, the EA, and Water Industry.  The first issue at the sandpit was, of course, to try and clarify what might be meant by the concept of a virtual observatory (VO).  There was a common vision of the long term concept: a readily accessible representation of the landscape processes in the UK that could be used to inform a wide variety of users (from farmers to schools to the water industry to national policy) making use of the latest techniques in computer science, particularly cloud computing concepts.  The objectives of the VO would include making data readily available to different communities; allowing what-if scenario evaluations in management, planning and policy; hypothesis testing of model process representations; and building up different portals and “communities of practice” for different types of application.

Initially the project proposal will be only for a proof of concept over a period of two years.  This will not be long enough for all the issues of making data readily available to be sorted out, nor for all the issues of defining realistic process representations at the local scales needed to be resolved. Thus, the capability of the system will be developed within a synthetic, virtual, catchment (although it might well be based on the characteristics of an existing research catchment or one of the new Defra Demonstration Test Catchments).

At the end of the sandpit, the project team were given the go-ahead to develop a full proposal which should lead to a project to start next year.  The long term potential of the VO project to provide tools for evaluating the impacts of catchment change will clearly overlap with the aims of CCN and hopefully there may be the possibility of organising some joint workshops in the near future for the overlapping communities of practice.

The sandpit was my second one this year (the first led to the EQUIP climate impacts project). In each case the process was facilitated in a way that produced lots of post-it notes but not much clarity about what research problems needed to be addressed to make real progress -or perhaps more correctly the problems may have been identified on the post-its but there was no real opportunity to discuss them in depth.   Perhaps it was the collection of people involved in each case, perhaps it was the nature of the facilitation programme, perhaps it was the constraints of the particular subject areas but in both sandpits the process led to a collaborative proposal within the “normal paradigm” of the science. This was a little frustrating, particularly in the case of the VO project (I realised during the week that I published my first virtual hillslope paper in 1977, and a full virtual catchment study of the 500 km2 Little Washita catchment in 2002, and have thought a lot about some of the issues in implementing the “models of everywhere” that the VO will require).  It certainly left the feeling that the process could have been organised better as a science workshop to focus on some of those difficult research issues…though whether this would have led to a better proposal for the initial phase of the VO is probably debateable.

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[Jan 14] Bridging Troubled Waters: Hydrology and Spatial Planning
added on 23 11 2009 by Clare Black
In recent years attention to issues concerning water and planning has been rising. Faced with a climate of increasing extremes with a greater need to manage Read more..

In recent years attention to issues concerning water and planning has been rising. Faced with a climate of increasing extremes with a greater need to manage water resources sustainably, to maintain and improve water quality, set against the projected increase of 252,000 new households a year in England (DCLG, 2009) – reveals the significant challenge that the spatial planning system faces when considering water management.

The sheer complexity of the issues around water management and the increasing technical knowledge required means partnership working is essential to achieve a sustainable, integrated approach. Yet there can be a considerable misunderstanding between disciplines, often concerning the organisational and cultural context in which the various parties operate, which hinders progress. How can planners embed critical hydrological issues in regional and local plans, in decisions on individual planning applications and seek opportunities through redevelopment and regeneration initiatives to achieve sustainable water management? How can hydrologists better understand the institutional context to deliver workable, comprehensible advice and solutions that meet multiple social, environmental and economic objectives? How can researchers better inform integrated policy and implementation?

This one day meeting will bring together a variety of stakeholders to explore the linkages and gain a deeper understanding of integrating water issues in spatial planning. The primary focus of the meeting is on the commonly experienced challenges of interdisciplinary working; how to promote communication, collaboration and knowledge transfer to yield workable solutions to the problems we face. It is hoped new relationships and further interdisciplinary research and practice opportunities will emerge from this agenda.

This BHS meeting aims to promote: (1) interdisciplinary communication and collaborations and (2) knowledge transfer between scientists, water managers and planners.

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[Apr 26] Integrated River Basin Management Conference - Action Programmes and Adaptation to Climate Change-
added on 19 11 2009 by Clare Black
The conference will review technical challenges faced by Member States, stakeholder organisations and scientists, while developing the first River Basin Read more..

The conference will review technical challenges faced by
Member States, stakeholder organisations and scientists,
while developing the first River Basin Management Plan
under the Water Framework Directive (WFD). It will focus
on aspects of integration, looking at the way cross-sectoral
and multidisciplinary co-operation has developed, and how
emerging issues such as adaptation to climate changes
will be considered in the future.
www.WFDLille2010.org

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Human perversity and serendipity
added on 26 10 2009 by Clare Black
It was nice to see a very first response to these blogs,...I hope there will be more in future so that it will be even more interesting when we come to Read more..

It was nice to see a very first response to these blogs,…I hope there will be more in future so that it will be even more interesting when we come to look back at the end of the project.

The role of human perversity and serendipity in the management of risk highlighted by Adrian Macdonald’s comment on the last entry is, of course, a fascinating one.There are many other examples  – the demountable defences on their way to Upton-on-Severn in 2007 that got stuck in the traffic jam caused by the floods on the M5, so that they got diverted to – what turned out in hindsight -to a much more useful purpose in protecting an electricity sub-station, is one positive example of serendipity.

One way of looking at this is in the terms of Frank Knight, who published a book on Risk, Uncertainty and Profit back in 1921.  He saw risks and uncertainties from an insurance industry perspective and differentiated between those types of uncertainties that an insurer would be prepared to take odds on, and those that he would not. The second type he called the “real uncertainties” that could not be expressed in this way.  They are what are now often called the epistemic uncertainties due to lack of knowledge or understanding.  Some people also differentiate epistemic uncertainties that might be reducible by further observation or experiment and those uncertainties that we have not even recognised yet (the unknown unknowns of Donald Rumsfeld). It is because of the epistemic uncertainties that we should expect that models will do less well in prediction than in calibration, and that the real system might respond in a surprising way. Sometimes those surprises are treated as only “rogue” observations but might be evidence of such real uncertainty (the filtering of zero concentration observations of ozone in the Antarctic is a prime example of this).

I recently came across some nice quotes relevant to these issues written by Bertrand Russell in 1950 in his essay Philosophy for the Layman:

What philosophy should dissipate is certainty, whether of knowledge or of ignorance. Knowledge is not so precise a concept as is commonly thought…

For it is not enough to recognise that all our knowledge is, in a greater or lesser degree, uncertain and vague; it is necessary at the same time to act on the best hypothesis without dogmatically believing it. …… Scientific laws may be very nearly certain, or only slightly probable, according to the state of the evidence. When you act upon a hypothesis which you know to be uncertain, your action should be such as will not have very harmful results if your hypothesis is false.

So some of the concepts about uncertainty in predictions of change are not at all new. Decision making has always been made under uncertainty, and there has always been a limitation as to far assessing that uncertainty can be made free from irrational or unknown human (or other) influences. And, even if that has always been understood, it has not stopped people from being too confident in their hypotheses and making decisions that have had rather harmful consequences (including the over development of flood plains).

The modern struggle with uncertainty, however, has two aspects that have changed recently. The first is that there is a push to make more explicit account of uncertainty in a quantifiable way.  Sometimes that does not recognise the non-quantifiable aspects of real uncertainties in, for example, interpreting the outputs of an ensemble as probabilities that sum to unity (implying all other possibilities are excluded). The second is in the requirement for predictions of future changes – at the heart of the CCN initiative) when the future boundary conditions for flood risk, water quality and water scarcity may be subject to real uncertainties. Hopefully, CCN might be able to through some light on both of these issues as it develops.. Кроме этого, пульпа является мощным барьером skyortho.com.ua/ на пути попадания инфекций и бактерий в зубную полость

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Handling Uncertainties in Catastrophe Modelling
added on 07 10 2009 by Clare Black
I am on the train on the way back from a meeting at Lloyd's of London on Handling Uncertainties in Catastrophe Modelling for Natural Hazard Impact. The Read more..

I am on the train on the way back from a meeting at Lloyd’s of London on Handling Uncertainties in Catastrophe Modelling for Natural Hazard Impact. The meeting was organised by another Knowledge Transfer Network on Industrial Mathematics Special Interest Group (SIG) for Environmental Risk Management, which is also supported by NERC. The SIG has prioritized the insurance industry in this area and the meeting brought together both academics and representatives from underwriting companies and risk modelling companies.

The morning talks gave a perspective on handling uncertainties from the insurance industry perspective. It is clear that they know only too well that their predictions of expected losses from extreme natural events are often based on rather uncertain input data and model components (and exposure to losses not currently included in models) but that they are already looking forward to being able to take account of some of the relevant uncertainties.   One of the issues in doing so however was that some of the current models will take a week or two to run a single deterministic loss calculation. There was some hope that a new generation of computer technology, such as the use of graphics processing units (GPUs), would reduce model run-times sufficiently to allow some assessment of uncertainty (they clearly have not tried programming a GPU yet, though this is getting easier!). One presentation suggested that being able to make more and more runs would allow uncertainties to be reduced.  Over lunch I asked what he really meant by this… it seemed that it was only that the estimation of probabilities for a given set of assumptions could be made more precise given more runs.

There was a demonstration of this in the afternoon in an interesting study to estimate the uncertainty in losses due to hurricanes in Florida.  5 insurance modelling companies had been given the same data and asked to estimate both the expected loss for given return periods of events (up to 1000 years) and a 90% confidence range.Two of the companies had run multiple long term realisations of a given sample distribution of events based on the prior distributions of event parameters.  Their confidence limits became smaller as the number of realisations increased and improved the integration over the possible distribution of events allowed by the fixed prior distributions. Two other companies had taken a different strategy, running realisations of a length consistent with historical data periods and resulting in much wider uncertainty limits.  Uncertainty estimations, particularly when not conditioned on historical data, will always depend directly on the assumptions on which they are based!  An analysis of the Florida hurricane study had suggested that the uncertainty in the estimated hazard was more important than uncertainty in the estimated vulnerability. I am not sure that this would necessarily be the case in estimating flood risk.

There was some discussion of how to convey these assumptions to the people who actually take the risk for insurance companies in committing to contracts, and whether they should be allowed to play with dials that would allow sensitivities of estimated losses to vary with different parameters.  Given long model run times and short decision times in the real world this was generally not considered feasible (although more flexibility to explore model sensitivities rather than the ‘black box’ results provided currently, was suggested). There was also a suggestion that it was as important to “understand what is not in the models” as to understand sensitivities to what was in the models and that “adding more science” would not necessarily be considered advantageous in an industry with a 300 year old tradition.

One thought that came to me during the meeting was inspired by a passing mention of the verification of uncertainty estimates.  It seems to me that this would (a) be very difficult with any form of extreme event and (b) would never happen anyway because data from a new extreme event will be used to revise estimates of prior probabilities that might have been used in estimating uncertainties.  We know that this happens in flood risk estimation when every new extreme flood is used to revise the estimates of the probabilities of exceedence at a site.  Enough for now, it was an early start this morning!!

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