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

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Beyond PPS25 Workshop Report
added on 21 10 2010 by Clare Black
Workshop report   Tuesday 28th September 2010 at Lancaster Environment Centre Our event on September 28th, in conjunction with the RTPI Development Read more..

Workshop report


Tuesday 28th September 2010 at Lancaster Environment Centre

Our event on September 28th, in conjunction with the RTPI Development Planning Network prompted a discussion across the planning community around developing a general framework and practical guidance for dealing with uncertainty, with a particular focus on flood data, modelling and mapping. Uncertainty could be particularly important in trying to project the impacts of future land use and climate change on flood risk, and the visualisation and communication of this uncertainty could have an impact on decision making within the planning and development communities.

The event attracted almost 30 delegates with a varied range of interest and responsibilities across flood risk mapping and development planning.  Despite being very well advertised by RTPI, few actual planning professionals attended with the majority of delegates present involved in directly in the production/interpretation of flood risk maps.

The day began with an overview of the background to uncertainty estimation methods in flood risk mapping by Keith Beven followed by an overview from Kate Donovan of Project FOSTER – a KE project centred on communicating flood science to a group of Local Authorities in Central England.

Presentations from the meeting are available to view


 The facilitated group Discussion Sessions (led by Simon McCarthy) allowed us to explore what aspects of visualising an uncertain flood risk are of particular importance to the planning and development community.

 Discussion Session I dealt with ‘uncertainty in practice’ and 4 broad pre-selected groups (Government Agencies, Planners and Development Practitioners, Academics and Environmental Consultants) were asked to identify how and in what form they incorporated uncertainty into flood risk mapping and how that uncertainty was represented.

The planning group felt that there was no admission and therefore discussion of uncertainty across the profession. It was considered an admission of weakness to admit to ‘not knowing’ and the topic added ’grey areas’ to decision making which relied on definitive yes/no answers. The technical knowledge needed to understand and process the flood map information and construction was well beyond traditional planning knowledge and therefore expert guidance was always needed via Environment Agency staff. Nevertheless it was felt by some delegates that the planning process – as a process of negotiation – could embrace discussions around uncertainty and use them as an opportunity, particularly to incorporate green infrastructure and sustainable regeneration options across vulnerable urban areas.

This view was reinforced by the consultants group who raised the issue that PPS25, and the initial 90 day decision limit, did not allow for adequate negotiation of projects.   Inclusion of uncertainty into the process might help more sensible decisions to be made – albeit that it might take more time and cost more.  It would also help counteract the false impression of precision given by the use of standard prediction packages and the resulting crisp maps – although it is normal practice to carry out some sensitivity analysis of results based on professional judgment, even if results are not often communicated to users.

Subsequent Discussion Sessions were conducted in mixed delegate groups.  The first of these aimed to identify sources of uncertainty and highlight which of these were most difficult to quantify. The second examined communicating and interpreting flood risk messages using mapping tools and the third centred on the need for guidelines for the development and planning community to help them embrace uncertainty within decision making.   There was felt to be a concern that including uncertainty might simply lead to the use of worse case scenarios (i.e. less successful planning applications). There is still a need for standards to work to for different purposes, but including uncertainty might reduce the inflexibility of the current process that allows a crisp line on a map to dominate local knowledge.  It would be important to communicate the assumptions used in producing uncertain flood risk maps to properly evaluate risk and choices.

It was felt that guidelines were most useful for the flood risk assessment professionals who are charged with producing flood risk maps.  Future training opportunities that covered a non-technical overview of flood risk mapping methods was the preferred way forward for the planning community. It was also highlighted that the impact of flood risk on development and decision making as a discrete topic should be embraced across Planning Schools and planning qualifications to ensure looking forward that there is an improved understanding of the implications of flood risk across the profession.

Other research has found that based on such measures as social and emotional growth and physical health, young mexican-american children are similar to white children

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Phosphorus world tour: A view from the chair
added on 06 10 2010 by Clare Black
It has been a busy couple of weeks for me attending both the in Beijing followed by the in Seville. Personally I found the former more stimulating, perhaps Read more..

It has been a busy couple of weeks for me attending both the in Beijing followed by the in Seville. Personally I found the former more stimulating, perhaps because it was more out of my comfort zone – closer to the plant than the water – with some interesting papers talking about the molecular advances in plants and how these can help potentially increase the efficiency of P use in a world with decreasing P reserves. Moreover, apart from the obvious guilt I feel for my carbon footprint, it seems such a shame that we had two P conferences on different sides of the world within a few days of one another.

The more I think about these isues the more important it is that we seek a unified and integrated view on these issues, rather than fragmenting into the ‘soil-plant’ and the ‘soil-water’ world. Perhaps we need a conference entitled simply ‘Phosphorus’ next?


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Deliberating risk and uncertainty in Cambridge
added on 06 10 2010 by Clare Black
It seems that trying to provide estimates of the uncertainty associated with predictions of catchment change may not be enough as an input to the decision Read more..

It seems that trying to provide estimates of the uncertainty associated with predictions of catchment change may not be enough as an input to the decision making process.  At a meeting this week on Challenging Models in the Face of Uncertainty, organized by the Centre for Research in the Arts, Social Sciences and Humanities (CRASSH) in Cambridge, it was suggested in a succession of talks that all such outcomes are culturally conditioned – both in the assumptions that are made and in the interpretation of the results.  These will depend, following the Cultural Theory grid/group characterisations of Mary Douglas, on whether you are a combination of hierarchist or egalitarian, individualist or collectivist.   I have a beard so I must be a egalitarian collectivist.  Different groups will frame decisions in quite different ways and since it is impossible to be totally rationalist about the application of science to real world problems (in part because of the incomplete knowledge and epistemic uncertainties discussed in earlier blogs), there is plenty of scope for doing so. 

The issue of climate change underlay a lot of the discussions, but many other policy areas were used as examples, from badger culls to GM crops and security against terrorism.   A particular issue in respect of climate change resonating with the blog after Hydropredict2010 was the choice of discounting rate in cost-benefit analysis.   We do not know what future discounting rates should be but different assumptions might make a lot of difference to the ranking of options.   It is also easy to see how the choice of parameters in any model of catchment change might also be influenced by desired outcomes.   Steve Raynor (Oxford) gave the example of the Chesapeake Bay study.   He suggested that the (highly complex) model of the system and its catchment areas shows a steady increase in water quality in the bay as a result of the improvement measures that have been taken.  He also suggested, however, that the observations gave no such evidence of any increase in quality.  The modeled improvements were, however, politically expedient in getting continued Congressional funding for the project from year to year.

So there was much discussion about how to avoid the conflicts between world views that this post-normal framing of scientific rationality implies.   Suggestions in different presentations ranged from opening up the dialogue to a plurality of views in a deliberative discourse to invoking a context of common interest in defending national security or interest.

A model and its predictions might be just one element in a deliberative discourse between different groups who might choose to use it (or equivalent models) in different ways.  While no model could possibly capture the full complexity of a catchment system (which might itself provide an element of surprise in its responses to forcings that have not been observed before), to my mind that really does not mean that the modeler should not be as rational as possible in providing advice to decision makers.  We should always, of course, reflect on the fact that this rationality is conditional; it depends on the particular perceptual models of those who use it, models which have been shaped by histories particular to individuals, and the particular observations available for evaluation.   There is no common agreement about how catchments should be modeled, only a wide range of software packages that might be used for different purposes.

So being rational then comes down to using models that, as far as possible, get the right results for the right reasons.   This is a valid endeavor in itself, even in a post-normal science world with culturally conditioned assumptions.   There remain many issues about how to test whether we can get the right results for the right reasons (see, for example, Beven, 2010) and in communicating the assumptions and limitations of the model predictions to users, but this is the nature of trying to do science properly.   An uncertainty analysis can then provide a framework for both testing models as hypotheses and being explicit about assumptions.   I have the impression that some sociologists of science would see this as only another means of the scientist trying to establish power and authority in shaping policy (with some implication that this authority might not be justified).  To me, it is simply an exercise in being as scientifically honest as possible.  How the resulting predictions might then get used in a (more or less) inclusive deliberative decision process is a quite different issue but what we should not do is to conceal the limitations and uncertainties of model predictions.  That would not be a good long term strategy.   As Andy Stirling (Sussex) put it:  there is widespread empathy for humility in the role that science can legitimately play in decision making.


Beven, K J, 2010, Preferential flows and travel time distributions: defining adequate hypothesis tests for hydrological process models, Hydrol. Process. 24: 1537-1547 Com/marina zlochin and we cannot simply assume that english will remain the world’s dominant language

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CCN at Hydropredict 2010
added on 27 09 2010 by Clare Black
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Instead, people of color today are subject to a host of implicit biases and stereotypes that, collectively, may add up to a residual see the forum plague of cultural and institutional racism

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Reaction to Hydropredict 2010: how to be precautionary in planning for the catchment futures?
added on 27 09 2010 by Clare Black
I believe in climate change.   I am very concerned, however, that the projections of (the current generation of) global and regional  climate models Read more..

I believe in climate change.   I am very concerned, however, that the projections of (the current generation of) global and regional  climate models are not hydrologically believable.   Comparisons of their predictions with the normal control period (1961-1990) show that they often exhibit strong bias.  They are inadequate predictors of the control period in many parts of the world, even where there are ensemble predictions of regional scale, dynamic downscaling models.   In the UK, the UKCP09 outputs at show many different aspects of the predicted changes at 25km scale.   They do not show any comparison of the predictions with the control period (despite posing an official question asking for these to be made available.   Can I encourage others to log on and pose the same question!).  Indeed, the UKCP09 weather generator (for which predicted realizations of weather at the 5 km scale can be obtained, uses the regional future climate projections only by making local bias corrections and RCM model derived change factors into the future.   We expect, of course, that with more research money devoted to climate modelling, more computer power devoted to climate modelling at finer grid scales, better land surface parameterisations in the models (that is the hydrology and hydrologists should still wince about how it is being represented!), and improved understanding of other process representations in the models, the projections of the next generation of climate models might well be better.   But in the meantime, there is an awful lot of research time, effort and money being devoted to impact studies based on the projections of the current generation of models.  The question is whether any of this work is fit for the purpose of adapting to, or managing for, the future?

Let us assume for the sake of argument (and to provoke a response) that it is not.  I should not then consider the projections of climate models to be an adequate basis for impact studies  (so that a lot of research time, effort and money is being wasted).  This is not to deny that there might be an anthropogenic effect on climate.   I believe in climate change.  I am also worried about the possibility that the climate system, as nonlinear dynamic system, might be subject to mode of behaviour shifts instigated by variability that is not being predicted by the current generation of GCMs.  We know that there have been rapid modal shifts in the past, before any significant anthropogenic greenhouse gas inputs to the atmosphere.     That suggests that we should plan to adapt to the possibility of change, despite the fact that we might have little faith in climate model projections.  How should we then proceed?

The wrong reaction is to do nothing just because the climate projections have little credibility (or large uncertainty).  It would be better to be precautionary by taking action.   The question is how to be precautionary, given a lack of believable impact predictions?    This depends on how risk averse or risk accepting we are prepared to be.  Being risk averse will generally require more expensive measures than being risk accepting.  But we can consider how expensive the required adaptation might be for different scenarios of future change, more or less extreme, quite independently of any climate model projections.   In that way it is possible to plan a response to different magnitudes of change in terms of costs (and benefits).

Ideally we would wish to evaluate the probability associated with each magnitude of change.   UKCP09 is presented in this way, with quantiles of change factors for various model predicted variables mapped across the country, conditional on assumed emissions scenarios.   It is important, however, to  remember that these projections are not a representation of the odds of climate actually turning out that way – they are rather the empirical probabilities of the ensemble model projections (with some Gaussian interpolation to compensate for the limited number of ensemble members in a high dimensional model space).  This difference is important.   Making use of these probabilities is to treat them as if the model was correct and the range of potential outcomes was complete.  This is not the case.

To ignore those probabilistic estimates and deal with the magnitudes of change factors directly (without the need for climate simulations) therefore precludes a complete risk-based strategy but places the focus directly on what is considered to be affordable in being precautionary.   

A particular case in point is protection against flooding.  If a changing climate is intensifying the hydrological cycle we expect the frequency of floods of a given magnitude to be changing (even if, given the nature of extremes this has proven to be difficult to demonstrate from the available observations).  There have been a number of studies that have invoked the change factors produced by climate models to examine how flow frequencies might change.   This is straightforward to do so if it can be assumed that the parameters calibrated to represent catchment response might not change with changing inputs.   It is much more difficult to do so if it is thought that the change in inputs or land use and management might require that parameters sets be changed to represent new sets of conditions.

But it is known that climate models do rather poorly in representing extremes, particularly of rainfalls, under control period conditions.  They get the wrong result, and are known to get the wrong result, presumably for the wrong reasons (whether that be the result of scale effects, sub-grid rain, snow and cloud parameterisations, the simplicity of land surface parameterisations, inadequate representations of heat exchange with the oceans, etc).   What is clear, however, is that we should not be assuming stationarity in estimating flood characteristics  and we therefore need to plan for change.

A number of strategies are possible so as not to exacerbate the problem: avoiding new developments on flood plains; improving flood defences; flood proofing of existing buildings; breaching of existing defences to make more storage; building flood detention basins.   In most cases these solutions will be robust in the sense of not precluding future adaptive management strategies but they all have a greater or lesser cost.   So what is the cost-benefit of protecting against different levels of change.  How precautionary are we prepared to pay to be?  

This is, essentially a political decision.   The science comes in estimating costs and benefits rather than in estimating the magnitudes of change.  Even if some of the evident problems of the current generation of climate models will be (hopefully) less apparent in the next generation, the path towards have a realistic model still seems long and tortuous.    So should we continue to do local bias corrections and use change factors in impact studies just because the funders of research and decision makers are asking for “evidence” of how great the impacts of change might be; or should we change the nature of the game into something more overtly political before the “evidence” becomes to be seen as based on insubstantial foundations.

In case you are worried about your current research funding, this need not lead to less impact studies.  Indeed a wider range of potential outcomes might need to be considered rather than the just the latest grand ensemble of predicted change factors.   It is just that the evidence does not now depend on climate models but rather on the range of potential future conditions that decision makers want to consider. 

Are there any difficulties in this approach? Yes.  Climate models provide projections in space and time constrained by energy, momentum and mass balances.   These projections are consistent in so far as the approximations of the numerical solutions allow.  It could be argued therefore that any study of the potential impacts of change that only supposes the magnitude of change and consequent impacts will be inherently subjective, unscientific and providing inadequate evidence.   This would be to totally misunderstand the arguments presented above.   However, there is an associated problem of providing suitable scenarios for patterns of change factors in catchments that are complex in their patterns of precipitations and other characteristics (we might note that this is already an issue in current practice, since the need to make (often large) bias corrections in the local application of climate change projections is already inconsistent with the energy, mass and momentum balances of the original models).

So we could still accept that climate model projections (together with any necessary bias corrections) are just one way of producing plausible patterns of change factors into the future, but then modify the patterns of change factors in assessing costs and benefits for precautionary action.   In doing so, we should also take account of any uncertainty in the impact modelling.   Where the disbenefits are a nonlinear function of the projected change this might make an important difference to the decision that might be made.

Do we reduce the strength of the arguments to induce a reaction in politicians to mitigate the effects of climate change by such a strategy?   Perhaps – even if they might believe in climate change, the potential costs of adaptation might be considered politically unacceptable, particularly in a time of economic recession and increasing unemployment. Governments have made that argument in the past, most notably both Bush administrations in the USA.  However, to do nothing is then to be risk accepting (or even irresponsible) to a possibly dangerous degree.

In addition, there are other factors that might also affect future hydrological responses (urbanisation, agricultural intensification, deforestation/afforestation, river training and re-naturalisation,…..).   There are certainly model-based predictions of the effects of potential changes in different factors, mostly deterministic in nature, even though we know that process representations of such factors are subject to considerable uncertainty.  In this case, the sensitivity of response to assumed future change is generally evaluated (also, like the climate case, a form of scenario analysis) but mostly without an assessment of the cost of possible adaptation strategies.   Such changes could also be evaluated in the form of the cost-benefit strategy to be precautionary suggested here. 

People will not agree about how to assess appropriate costs and benefits for different types of impact and mitigation strategies, particularly in respect of future socioeconomic scenarios affecting future risk assessment.   More science and understanding is required to reduce the uncertainties in doing so.  That does not, however, preclude the use of such an approach.  I believe in climate change, and the potential impacts of other catchment changes, but I would suggest that we need better, and more scientifically honest, ways of deciding how precautionary to be in planning for the future.

Keith Beven

Lancaster Environmental Centre,  Lancaster University, Lancaster LA1 4YQ, UK


A Report of  “CCN at Hydropredict 2010” can be found I’ve not only come across great ideas in these chats, i’ve connected with like-minded teachers across the world and learned more about what’s working for them and their students

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