Hydrologic similarity: Bridging the gap between hyper-resolution and hydrologic ensemble prediction

Posted on August 15, 2017 by Andy Wood

Contributed by:  Nate Chaney (Princeton University) and Andy Newman (NCAR)

The ever-increasing volume of global environmental data and the continual increase in computational power continue to drive a push towards fully distributed modeling of the hydrologic cycle at hyper-resolutions (10-100 meters) [Wood et al., 2011]. In principle, this has the potential to increase model fidelity and lead to more locally-relevant hydrologic predictions (e.g., soil moisture at the farm level).

However, for the foreseeable future, due to computational constraints this modeling approach will not be suitable for large ensemble frameworks—a pre-requisite for reliable operational applications given the unavoidable uncertainties in model structure, model parameters, and meteorological forcing.

However, this does not mean that hydrologic ensemble prediction should continue to rely on over-simplistic hydrologic models simply to maintain computational efficiency. It is undeniable that providing field-scale hydrologic predictions can have the potential to significantly advance the use of hydrologic models (e.g., precision agriculture).

Furthermore, the important role of the physical environment and human management in hydrologic response necessitates a more explicit representation of the spatial drivers of heterogeneity in hydrologic models. Therefore, there is a need for a modeling approach that can provide field-scale predictions while approximating the computational efficiency of existing hydrologic models used in ensemble frameworks. Contemporary applications of hydrologic similarity can satisfy both objectives.

Hydrologic similarity

Hydrologic similarity aims to harness the observed covariance between a system’s physical environment (topography, soil, land cover, and climate) and its hydrologic response to assemble robust reduced-order models.

Although originally limited to one-dimensional binning of over-simplistic metrics of hydrologic response (e.g., topographic index), recent advances have taken hydrologic similarity a step further; a system’s most representative hydrologic response units (HRUs) are defined by clustering the high dimensional environmental data space [Newman et al., 2014]—the petabytes of readily available high resolution global environmental data make this feasible over the globe. Semi-distributed models can then be built to simulate these HRUs and their spatial interactions (e.g., HydroBlocks, Chaney et al., 2016).

Within the clustered spatial domain, each fine-scale grid cell (~30 meters) is associated with a specific HRU through its environmental characteristics. This then makes it possible to map out the HRU simulations onto the fine-scale grid to approximate the fully distributed simulation (see Figure 1 for an example).

Using this approach, ongoing work continues to show that the fully distributed simulation can be closely reproduced using around 1/1000 of the number of HRUs; each grid cell is a unique HRU in the fully distributed simulation. In other words, the semi-distributed model can effectively provide the same hydrologic information as the hyper-resolution fully distributed model with only a fraction of the computation.

This equates to being able to run roughly 1000 ensemble members of the semi-distributed model in the time it would take to run the fully distributed model once; all while being assured that each ensemble member closely approximates its corresponding fully distributed solution.

In summary, contemporary implementations of hydrologic similarity provide a unique opportunity to bridge the gap between physically-based hyper-resolution modeling efforts and hydrologic ensemble prediction. It enables robust ensemble frameworks to provide locally-relevant information while ensuring they can robustly characterize the unavoidable uncertainties due to model structure, model parameters, and meteorological forcing.

References

  • Chaney, N., P. Metcalfe, and E. F. Wood (2016), HydroBlocks: A Field-scale Resolving Land Surface Model for Application Over Continental Extents, Hydrol. Process., doi:10.1002/hyp.10891.
  • Newman, A. J., M. P. Clark, A. Winstral, D. Marks, and M. Seyfried (2014), The Use of Similarity Concepts to Represent Subgrid Variability in Land Surface Models: Case Study in a Snowmelt-Dominated Watershed, J. Hydrometeorol., 15, 1717–1738.
  • Wood, E. F. et al. (2011), Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrial water, Water Resour. Res., 47(5).
Posted in ensemble techniques, forecast techniques, hydrologic models | Leave a comment

Quiz: Can you guess the river from the space?

Posted on August 1, 2017 by Maria-Helena Ramos

Contributed by Calum Baugh, Maria-Helena Ramos and Florian Pappenberger

Here are four rivers seen from Google Earth. Can you recognize them?

River 1:

Check the answer here

River 2:

Check the answer here


River 3:

Check the answer here

River 4:

Check the answer here

 

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Which scales matter for water resources management?

Posted on July 18, 2017 by Maria-Helena Ramos

Contributed by Andreas Hartmann, Axel Bronstert, Bettina Schaefli

The discussion about which scale is the most relevant for water resources management is an increasingly important debate of hydrological modelling principles over the last decade.

The session “(Ir‑)relevant scales in hydrology: Which scales matter for water resources management?” convened at this year’s EGU General Assembly 2017 tried to put some new light (and fire) into this ongoing debate.

Photo taken during the session at EGU 2017 by Axel Bronstert

Solicited speakers representing the plot scale, hillslope and catchment scale, and the large-scale provided valuable insights into their research experience and provided opinions about the session topic.

  • Hans-Joerg Vogel provided a list of questions that may be answered at the plot scale. For instance, to what detail do we need to know the basic soil hydraulic properties? And how useful are sophisticated lab measurements to predict what is happening in the field? Also, methods to handle the highly non-linear change in flow paths as a function of the hydraulic state and its history may be developed at the plot scale. However, how soil water dynamics integrate over the scales of hillslopes or catchments is still an open question cannot solely be answered at the plot scale. How far can approaches like Richard’s equation that were developed at the plot scale be transferred to those larger scales?
  • This question was picked up by the following presenter, Theresa Blume, who advocated for more research for understanding the link between plot and catchment scales. Nested monitoring programmes with monitored catchments that envelop different monitoring plots, as applied within the Catchments As Organised Systems (CAOS) project, may provide promising advances in our understanding how plot scale dynamics integrate to hillslopes and catchments. When such measurement design is applied in a comparative approach, generalized knowledge about hydrological processes across different types of hydrological landscapes could be obtained. But how to integrate the derived understanding into models that can be applied at test sites with less information?
  • The modeller’s point of view was picked up by Jens Christian Refsgaard. Stating that it It is recognised that there is a mismatch of spatial scales between our process knowledge, the modelling grids of our distributed catchment models (50 – 500 m) and the water management problems, where the relevant scale often is claimed to be the catchment (e.g. 10 – 5000 km2). Groundwater pollution may even occur on larger scales (several 10,000 km²) while mitigation measures have to be applied locally. Hence, relevant scales vary from one issue to another (plot to large scale) and for some issues (e.g. mitigation measures) are in the order of 100 m when for instance the European Water Framework Directive (EWFD) is applied. Although distributed models are technically able to simulate the hydrological behaviour on such small scales, how can we evaluate them for their realism if now operations are available?
  • The challenge of evaluating hydrological models that operate on scales even larger than the catchments scale was also picked up by Thorsten Wagener. We increasingly build and apply hydrologic models that simulate systems beyond the catchment scale. Such model can provide opportunities for new scientific insights, for instance, the consideration of intercatchment flow. Also, large-scale models can help us to understand changes to water resources from larger scale activities like agriculture or from hazards such as droughts. However, these models also require us to rethink how we build and evaluate them given that some of the unsolved problems from the catchment scale have not gone away. So what opportunities for solving these problems are there? Are there possibilities that have not yet been utilized?
  • An increasing source of information for large-scale model applications are global archives of hydrological observations, as stated by Lena Tallaksen. These may allow a more detailed development and evaluation of hydrological models for the purpose of water resource assessments and climate change impact studies at the global and continental scale. Recent research has been providing improved knowledge of the present state of global water resources and variability across large spatial domains, the role of terrestrial hydrology in earth system models, the influence of climate variability and change on continental hydrology (including extremes), and the representation of subsurface hydrology and land-surface atmosphere feedback processes. Large-scale models are more and more adapted to include multiple types of input data such as remote sensing processes. However, a lack of ground truthing especially in less developed regions, the representation of hydrological variability below the modelling scale and uncertainties in downscaling large-scale climate forcings to the model scale still limit the applicability of large-scale models. Despite these challenges, large-scale models may represent a useful source of information for continental-scale hydrological assessments and evidence-based policy making. To increase their reliability, transfer of knowledge across scales is essential to improve hydrologic predictions at different spatial scales in an ever-changing world.

Overall, by the excellent presentations and discussion during the session, we found that each scale has its own relevance for water management. Experimental research at the plot and catchment scales brings advances in hydrological process understanding that can improve our simulation tools, while comparative hydrology and large scale modelling can provide quantitative information at larger scales to support water governance and policy making.

The key question in the near future is certainly how to further improve collaboration and foster discussions across all hydrological scales, especially in the context of ever more complex models at all scales. One option would certainly be to organize regular cross-cutting conference sessions. Another interesting initiative that has been presented at EGU2017 is the data and model sharing platform https://www.hydroshare.org/.

Posted in activities, announcements-events, water management | Leave a comment

The role of Early Career Scientists in community research

Posted on June 28, 2017 by Florian Pappenberger

Contributed by Florian Pappenberger and Maria-Helena Ramos (both considerably beyond the early career stages, they admit)

(this post can also be seen in the Young Hydrologic Society Portal)

Science and forecasting practice are the foundations of the HEPEX community. These are certainly the routine of many of us during our office hours and while spending time in front of your computers.

But this community is also based on individuals, and this is often what really makes it fun to go to meetings, workshops and conferences. Face-to-face interactions often bring new ideas into form (see also this previous post from CSIRO team), while also helping us to further develop interpersonal skills.

It is thus not really a surprise when members of the community get together after meetings and write (sometimes successful) research proposals together. One example is the IMPREX project, funded under the EU H2020 programme, where many partners already knew each other from HEPEX before participating in IMPREX.

The ‘EX’ that HEPEX and IMPREX have in common does not express the same idea at all, but several challenges of HEPEX are part of the research tasks of IMPREX:  for instance, improving hydrological models and data assimilation for forecasting extremes, or estimating the economic value of forecasts in the water sector.

IMPREX stands for IMproving PRedictions and management of hydrological EXtremes. The project targets improving the quality of short-to-medium hydro-meteorological predictions, enhancing the reliability of future climate projections, applying this information to strategic sectoral and pan-European surveys at different scales, and evaluating and adapting current risk management strategies.

But this post is not about IMPREX. What in fact has (gladly) attracted our attention in this project and we would like to talk about here is the active participation of early career scientists (ECS).

Intergenerational engagement in research projects

Many research programmes call for the multiple benefits of stakeholder and public engagement, but what about “intergenerational engagement” between the early career scientists and the well-established ones?

If we look closely, the age group distribution in IMPREX, and in HEPEX as well, is extremely diverse. It ranges from early career scientists (usually MSc or PhD candidates) to well-established researchers, both sides with particular skills (from analytical to computer programming skills) and viewpoints (for carrying out science experiments but also succeed in multi-cultural team leadership, for instance). This diversity is not always fully explored in research projects, but the case seems to be different in IMPREX.

ECSs in IMPREX have tasks and are in charge of presentations in all project meetings. They have their place in the agenda and are encouraged to get involved in the consortium. They also have their place in the project’s online blog to communicate anything they want: their science achievements, activities, new discoveries, participation in meetings or just general reflections.

They produce posts about topics which are interesting for them and describe them from their perspective. New perspectives are always exciting to read. And new perspectives which are untainted by ‘old’ ideas (sometimes disguised under what is called ‘experience’) are even more interesting.

So far, there have been a number of IMPREX ECS blog posts that are closely related to HEPEX topics and certainly worth reading:

  1. An ecologist’s viewpoint of hydrological forecasting (as far as we can remember, we never had a blog post in HEPEX from that angle – read the discussion!)
  2. An interesting post presenting an insider’s point of view of four forecasting services active in Germany, The Netherlands, Spain and at the pan-European scale.
  3. A flood decision-making experiment, where we can step in the boots of a flood manager with the help of IMPREX ECSs.
  4. And a friendly report of their participation in the 2017 EGU General Assembly (notably, check the very nice way they present their photos at the end of the post!)

We are eagerly awaiting the next ones!

Posted in activities | 2 Comments

Risk aversion and decision making using ensemble forecasts

Posted on June 6, 2017 by Marie-Amélie Boucher

by Marie-Amélie Boucher and Vincent Boucher

Assessing the value of forecasts is a very popular topic among the HEPEX community. The assessment of forecast value is highly dependent on the purpose served by the forecasts. For the specific problem of decision-making related to flood mitigation, Murphy (1976, 1977) proposed the use of the cost-loss ratio framework. The vast majority of papers related to the assessment of forecast value for flood mitigation adopt this framework, so one could think that everything is pretty much solved… except that the cost-lost ratio has very important flaws!

One such flaws is the fact that the cost-loss ratio assumes that the decision maker is risk neutral. Risk neutral individuals only care about the expected outcome, and disregard the spread of the distribution of outcomes. Risk neutral individuals are very rarely encountered in real life. Indeed, most of us are risk averse. That is, for the same expected outcome, we prefer less risky distributions. This is (among other things) why we buy insurance. Informally, most people dislike risk and would be willing to spend resources (e.g. money) in order to reduce the amount of risk faced.

Utility theory

Economists (and statisticians and mathematicians) have been studying those issues for a long time, and came up with many models and concepts which could be used in hydrology, as an alternative to the cost-loss ratio. The central framework is based on “utility theory”. To put it’s development a bit in a context, here is a (very) pseudo-historical adaptation of a conversation between Nicolau I Bernoulli and his cousin Daniel [1]:

It didn’t happen exactly like that, but the general idea is preserved. The game that Nicolau is referring to is now known as the St-Petersburg paradox and was first described in a letter. The first person to present it more formally was Daniel Bernoulli in 1738. He was also the first to suggest the idea of risk aversion and exposed (without any mathematics) that different persons faced with the same decision problem and the same information could take different decisions, because of different preferences.

It is only much later, in 1944, that the concept of risk-based individual preferences was formalized as a mathematical theory, by John von Neumann and Oskar Morgenstern [2]:

Utility theory is not perfect (and indeed, many generalizations and extensions exist), but it has at least two advantages over the cost-loss ratio:

  1. It allows for decisions to consider a finite number or a continuum of decisions (e.g. “protect” vs “don’t protect” for floods, or alternatively, “amount spent in protection”).
  1. It allows to account explicitly for the decision maker’s level of risk aversion in the assessment of forecasts value.

In hydrology

Krzysztofowicz suggested using utility theory in hydrology as early as in 1986. It is not a miraculous solution to the problem of assessing the value of forecasts for flood mitigation, but it would be an improvement over the cost-loss ratio. It can explain real-life behaviors that the cost-loss ratio cannot. This was the case in our recent application for the assessment of forecasts value on the Montmorency River in Canada (Matte et al. 2017). Other examples of accounting for risk-aversion for decision-making in hydrology and meteorology include Shorr (1966), and Cerdá and Quiroga Gómez (2008).

References:

  • Bernoulli D. (1738) Specimen Theoriae Novae de Mensura Sortis, Commentarii academiae scientiarum imperialis Petropolitanae, 5, 175-192.
  • Cerdá Tena E. and Quiroga Gómez S. (2008) Cost-Loss Decision Models with Risk Aversion, Working paper no. 01, Instituto Complutense de Estudios Internaciolales, 28 pages.
  • Krzysztofowicz R. (1986) Expected utility, benefit, and loss criteria for seasonal water supply planning, Water Resources Research, 22(3), 303-312.
  • Matte S., Boucher M-A, Boucher V. and Fortier-Filion T-C (2017) Moving beyond the cost-loss ratio, economic assessment of streamflow forecasts for a risk-averse decision maker, Hydrology and Earth System Sciences (Accepted)
  • Murphy A.H. (1977) Value of climatological, categorical and probabilistic forecasts in cost-loss ration situation, Monthly Weather Review, 105(7), 803-816
  • Murphy A.H. (1976) Decision-making models in cost-loss ratio situation and measures of values of probability forecasts, Monthly Weather Review, 104(8), 1058-1065
  • Shorr B. (1966) The cost/loss utility ratio, Journal of Applied Meteorology, 5(6), 501-803.
  • von Neumann J. and Morgenstern O. (1944) Theory of games and economic behavior, vol. 60, Princeton University Press Princeton, 625 pages.

Figure captions:

[1] The original pictures were taken from these websites: http://www.famous-mathematicians.com/daniel-bernoulli/ (right) and http://www2.stetson.edu/~efriedma/periodictable/html/Bi.html (left). The schematic drawing of D. Bernoulli’s blood pressure experiment apparatus was taken from https://plus.maths.org/content/daniel-bernoulli-and-making-fluid-equation

[2] The original pictures were taken from these websites: http://www.tinbergen.nl/oskar-morgenstern-and-john-von-neumann-shelby-white-and-leon-levy-archives-center/ (left) and http://www.karbosguide.com/books/pcarchitecture/chapter02.htm (right)

Posted in decision making, economic value | 2 Comments

The elusive optimal decision rule and the impact of forecasting

Posted on May 23, 2017 by Maria-Helena Ramos

Contributed by Micha Werner, IHE Delft and Deltares

This winter just passed I was faced with the kind of dilemma of the type I am sure many find all too familiar. I was the designated driver one weekend for my daughter’s hockey team away match.

Parents take turns to drive to away matches, and so I was all set to head off with four excitedly chatting thirteen year-olds. At breakfast, I saw on the internet that KNMI, the Dutch national meteorological agency had earlier that morning issued an amber alert. It had been well below zero for a couple of days and the roads were cold. A warm front from the West was now pushing its way through, and there was a high risk of black ice, leading to very slippery roads and potentially dangerous situations.

All non-essential trips were strongly discouraged, particularly on motorways in the west of the country that had been as yet little used that Sunday morning. The warning indicated that the risks would diminish by 9:30. I had to leave by 9 to make it on time and my route included a section of motorway. What was I to do? Should I heed the warning? Was this trip essential or was it non-essential?

Having professionally dabbled with the concept of costs and losses, the decision seemed obvious. The risks were high, and the consequences of a potential accident severe. So the obvious rational decision was not to go. But there were also consequences to not going. The match would need to be called off if the four girls I had with me did not show. Would the opposing team claim victory for a no-show? That could be embarrassing, and moreover could knock our team out of the top of the pool. Would other parents decide not to go; or rather would they go and be let down by my decision to stay at home?

A furtive discussion on our team WhatsApp group ensued. Finally an agreement was reached. Yes, I explained to a concerned mother, yes I had invested in winter tyres. The decision was made. We were off.

Making decisions based on warning information

This little story reflects the difficulty of making decisions based on warning information. Even when provided with quite specific information such as I received that morning, which not only targeted the road type but also provided specific details as to the timing. This is the level of detail that impact based warnings set out to achieve. Information contained in the forecast that is personally relevant to the consumer of the forecast. And yet making the decision that would seem obvious on paper is not easy in practice.

There has been some research on the process of an individual making a decision based on an advisory of flooding, or severe weather, or other (natural) hazards.

  • Does the warning apply to me? Do I trust it?
  • Am I inherently risk averse, or rather risk acceptant?
  • How is my decision influenced by the potential losses?
  • And in making a decision are these losses balanced against the cost of taking measures?

A decision making “serious-game”: the Shopkeepers Dilemma Game

The latter question listed above is the reasoning that underlies the rational decision making principle. It was also the question what was asked participants in a decision making “serious-game” we played at the 2016 European Geophysical Union during the Ensemble Hydro-meteorological Forecasting session. Some readers may also recall playing the game at the 2016 HEPEX conference in Quebec City, Canada, or at the Royal Meteorological Society Conference in Manchester, England. It was also played with a group of students in a flood management course at IHE Delft.

Micha Werner and his poster at EGU 2017

This year’s EGU saw a poster presenting the results, and a paper will further explore the details but is still in preparation (I had of course intended to write the paper earlier, and may have found more time to do so if only I had heeded more warnings and stayed at home, instead of going to weekend sports matches with my kids!)

In the game, three different shop-keepers were presented with a series of seven forecasts, each providing participants with the forecast probability that they and their shop could be flooded. They were asked to make one of three decisions for each forecast; choosing between taking no action; raising temporary defences on the embankment between their shop and the river; or moving their inventory. Except for doing nothing, all actions came at a cost. But flooding also caused a loss.

What was also important was that if the shop could stay open for business then a profit could be made. Obviously the shop could not stay open for business if flooded, or if the decision to move the inventory had been taken. However, if the demountable defences were raised, and these were not subsequently overtopped, then it was business as usual and a profit could be made.

The three shops selected in the game had quite different costs and losses:

  • One shop sold Ferraris, with significant losses when flooded, as well as high costs when moving the inventory. But profits when the shop stayed open for business were also high.
  • The second type of shop was a grocery store, with lower losses when flooded; but also lower costs to move inventory, and lower profits when staying open for business.
  • The third shop sold gravestones. Losses due to flooding gravestones were low; and lower or equal to the cost of raising the defences or moving the inventory. Of course when raising the embankments the shop could stay open for business if the embankments were not overtopped, making a modest profit.

At each step, after the decision on the bulletin was made, the actual outcome of the event was shown and participants asked to tally their results. The winner was the participant who had the lowest expected expense at the end of the game, due either to taking measures, which at times were taken in vain when the forecast flood did not materialise, or due to losses incurred when either no action, or inadequate action was taken.

The game material and publications are publicly available here in the Resources Page of the Hepex Portal, together with other games and lectures provided by the community.

A couple of interesting patterns

Reviewing the results of the 215 participants that played the game across the four sessions revealed a couple of interesting patterns. I will leave the full assessment of those results to the full paper, but some interesting thoughts came forward that may be worth mentioning.

  1. Choices made by those selling Ferraris were more or less as expected. They were keen to act on the forecasts; and the most likely to take action in response to the forecasts, with a clear relationship between the probability of forecasting and the inclination to take action. The forecast was of clear value to them.
  2. This was also more or less the case for those with grocery stores, though they did not take action quite as often.
  3. What was interesting though was the behaviour of those selling gravestones. Though these was little need to respond to the forecasts for them, as the cost of unnecessary action was very high compared to the losses when no action was taken, the gravestone sellers seemed overly keen to respond to the forecasts. Their behaviour was more or less the same as the grocery store participants. It would appear that they were prepared to take the risk of getting it wrong despite the cost, preferring to invest to avoid being flooded.  Such behaviour is often considered to be risk adverse, influencing decisions to be made that stray from the rule that would be prescribed by the rational cost-loss theory.

But not all decisions made in risky situations are necessarily risk adverse. The quite well known prospect theory, first described by Kahneman and Tversky (1979) outlines how decision makers may be risk seeking, or rather how they may be risk averse, depending on how information informing the risk based decision is framed.

Generally, in the game it seemed that the prospect of being flooded caused the decision to take protective action to be taken more often than necessary. This could also be considered loss aversion. People are prepared to invest in taking measures, just to avoid the displeasure of being flooded, which given the disgruntled mutters of participants in the room when flooded after deciding not to take action, clearly gives rise to negative emotions.

The role of emotion in the framing of a decision

Emotion is clearly an important factor in the framing of a decision, as outlined by Druckman and Mcdermott (2008). They go on to discuss how different emotions may influence decisions. Maybe a bit too much to discuss in a blog post that started short but just kept growing; and definitely a topic that is increasingly out of reach of a hydrologist such as myself. However, they also shed some light on my little dilemma. Clearly, the negative emotion connected to not going to the match, as well as my own preference confidence led to the taking of what was a risk-seeking decision.

Emotions may also lead to paralysis in decision making, resulting in no decision being made. That reminded me of a discussion I recently had with a certain Dr Stephen Hussey. He leads an NGO called the Dabane Trust that works with communities in Southern Zimbabwe. What he has found somewhat confounding is that despite clear and acknowledged signs of oncoming drought conditions provided by a seasonal forecast product, that it was very difficult to change what was considered to be normal behaviour by the communities. They could easily plant a less drought sensitive crop than the traditional maize; but they had always planted maize and changing that was not easily done.  Changing behaviour could perhaps be done if a champion for change could be found in the community, but otherwise it proved to be very difficult.

Of course I need not tell the reader that the true value of any forecast will depend on how that forecast is used to influence behaviour and take protective action. Impact based forecasting has recently emerged as a step towards personalising forecasts and through this influencing what an individual should do to get themselves and their property out of harm’s way in the face of natural hazards. That is no doubt a good thing, but the impact of a forecast ultimately depends on the behavioural change that it influences.

This calls to my mind for branching out to research on behavioural change, working with psychologists, social scientists, and economists, as well as many others; on thinking how to frame forecast information. We cannot do this as hydrologists alone. I myself always like to find analogies from my own experiences in decision making in my personal life, wondering how this may help explain the behaviour of recipients of forecasts.

There were no real issues with the roads that Sunday morning. We left a bit earlier than planned, took caution and arrived well on time. That day the team did reasonably; of the two matches they had to play they won one, and lost the other.

Some game-addicted members of the Hepex community at EGU 2017 (from left to right): Micha Werner, Hannah Cloke, Louise Arnal, Andy Wood, Louise Crochemore, Maria-Helena Ramos and Ilias Pechlivanidis). The poster in the back can be found here.

References

Posted in decision making, forecast communication, forecast users | 1 Comment

A platform: Community of Users on Secure, Safe and Resilient Societies

Posted on May 10, 2017 by Florian Pappenberger

The “Community of Users on Secure, Safe and Resilient Societies” (CoU) is an efficient platform of exchanges among different actors of different branches of security and crisis management. The CoU initiative came as a response to the complexity of the security and crisis management policy framework and the wide variety of research capacity-building and training initiatives that led to a lack of awareness about policies and/or research project outputs by users, namely policy-makers, scientists, industry/SMEs and practitioners (e.g. civil protection units, medical emergency services and police departments).

There is an High-Level Practitioners Event, taking place on 15 May 2017 [see program here] – or watch the live stream.

WHO ARE THE USERS?

Fields concerned by security, safety and resilience for societies are themselves scattered into many different disciplines and sectors.

WHY AND HOW PARTICIPATING?

Registered members [register here] have obviously different interests in being part of the network, in particular keeping up to date with policy and research developments, information sharing among different actors and networking. Most of the information sharing / update is carried out on line without the necessity to attend meetings, although meetings may also be useful for networking purposes and synergy building.

About attending meetings in person, the following considerations may apply:

You are a Policy-maker

Interactions may be of relevance to you in plenary sessions to share general information about your respective policy areas and get feedback from other actors. Participation in thematic workshops will allow to get in-depth insights into the areas concerned.

As an example, the CoU network involves UN representatives dealing with fight against crime and terrorism (UNICRI), disaster risk reduction (UN-ISDR), and transboundary industrial accidents (UN/ECE), EU Policy DGs such as DGs HOME, ECHO, SANTE, GROW, ENV, CLIMA, ENER, MOVE, TAXUD, as well as the JRC.

In addition, EU and intergovernmental agencies such as FRONTEX, EUROPOL, EEAS, EDA, are also involved. Moreover, representations at Member State’s level are through Ministries of Defence, Interior, Foreign Affairs, Civil Protection, Environment, Research and Industry, as well as Agencies and Regional Authorities.

Your are a Scientist

Representatives of research projects will find possible interest in getting information on policies in the respective areas to better understand needs related to technical implementation of various policies. Scientific findings may be discussed among different actors / users in the CoU framework, and project synergies are strongly encouraged, including the possibility to hold demonstrations.

You are an Industry (including SMEs) representative

Similarly to scientists, you will have possible interest in getting information on policies in the respective areas to better understand needs related to technical implementation of various policies, as well as meeting research project representatives and share with different actors views about innovation needs and perspectives.

You are a Practitioner

First responders, i.e. fire brigades, emergency services, police forces, civil protection units, military units, laboratories, etc. will find an interest to attend for getting updated information about EU policy and research developments and express their views about the tools, technologies, etc. development and their possible involvement in research and demonstrations.

Your are NGOs or Consultant

The CoU provides a large range of policy and research information that are of potential usefulness to NGOs, Civil Society Organisations, consultancy companies, etc.

General public

Interest to participate in person is less obvious for the general public owing to the highly technical level of discussions, but some events might be tailor-made to citizens, which is envisaged in the future.

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EGU Twitter page

Posted on April 24, 2017 by Maria-Helena Ramos

This week, the HEPEX traveling circus will descend on Vienna, home of the annual convention of the European Geosciences Union. HEPEX-ers will be tweeting their way through the conference – and these Tweets will be assembled in below Twitter stream. Feel free to add your thoughts, ideas and observations – just make sure they’re summarized in 160 characters max – and don’t forget to include the #hepex tag!


Posted in Unclassified | 1 Comment

What will happen next week at EGU 2017 in hydrological forecasting?

Posted on April 19, 2017 by Maria-Helena Ramos

The EGU 2017 Annual General Assembly will take place next week, from 23–28 April 2017 in Vienna. Once again, researchers, professors, early career scientists and practitioners interested in any of the fields covered by geosciences, including hydrological sciences, atmospheric sciences and natural hazards, will be together to present and discuss their work.

The meeting program includes about 1,000 sessions and over 17,500 abstracts, of which over 200 contributions will be presented in 8 scientific and operational-focused sessions organized by the sub-division on Hydrological Forecasting.

Here you can find a list of what will be presented in relation to hydrological forecasting and of some main events to guide you through the week in Vienna:

On the first day, after the first morning coffee break, join us at the flash floods session, which will start with 6 oral presentations at 10:30 and will display 21 posters at the end of the day in Hall A:

  • 10:30–12:00 / Room 2.31: Flash floods and associated hydro-geomorphic processes – Learn more about flash flood characterization with an X-Band weather radar in the Eastern Mediterranean region, the geomorphic response associated to four large floods in Northern Italy, flash flood risk assessment in France and Germany, or flash flood forecasting and early warning systems over Europe.
  • POSTER SESSION 17:30–19:00 / Hall A: Come to discuss with poster presenters and meet colleagues of the Hydrological Forecasting sub-division.

On the second day, we do not have specific sessions organized by the Hydrological Forecasting sub-division, but several other sub-divisions are offering a rich program. Just as examples, see, for instance:

This is the day of our operational forecasting and warning system PICO session (as already mentioned in a previous blog post by Mike Cranston).

  • 08:30–12:00 / PICO Spot A: Operational forecasting and warning systems for natural hazards – This year, we have 28 interactive presentations at PICO screens. Several applications will be presented and we will also have the “traditional” game presentation, which, this year, was prepared by Louise Arnal et al.: Pathways to designing and running an operational flood forecasting system: an adventure game. Just come and try it yourself!
NEW!!   Short course on Hydrological Forecasting

It is co-organized by HEPEX and the Early Career Scientists (ECS), convened by Shaun Harrigan. The course will be given by Marie-Amélie Boucher and Jan Verkade. Check the blog post recently published for more details. Attendance is open to everybody and will be on the basis of first come, first served!

Wed, 26 Apr, 17:30–20:00 at Room -2.91

A long day with several Hydrological Forecasting sessions is waiting for you on Thursday:

The Division meeting for Hydrological Sciences (HS) will be convened by Elena Toth, on Thu, 27 Apr, 12:15–13:15 / Room B. It is the opportunity  to learn more about the way sessions related to Hydrological Sciences  are organized at the EGU Assembly. You’re all welcome!

Scientific sessions continue in the afternoon:

  • POSTER SESSION 17:30–19:00, will be mainly in Hall A, but also in Hall X4 (post-processing) and Hall X3 (coupled systems) for the co-organized sessions above.
  • Another tradition in Vienna: the HEPEX social gathering @ EGU. As in last year, it will be co-organized with partners of the IMPREX H2020 project. It will take place on Thursday evening at 8pm (restaurant will be confirmed at EGU). Since reservations have to be made in advance, and places are limited, please, contact Louise Arnal or Rebecca Emerton before Monday 24 April if you want to join us.

Last day of the EGU Assembly and again a full day of presentations:

  • 08:30–12:00 / Room 2.95: From sub-seasonal forecasting to climate projections: predicting hydrologic extremes and servicing water managers, with presentations on society vulnerability to extremes and the use of seasonal forecasts to improve water resources management.
The  meeting of the Sub-Division on Hydrological Forecasting will be convened by MH Ramos, on Fri, 28 Apr, 12:15–13:15 / Room 2.83
It is open to everybody. Come and join us, notably if you want to meet colleagues or get more involved in the organization of sessions and short courses related to hydrological forecasting at EGU in 2018.

Scientific sessions continue in the afternoon:

  • 13:30–17:00 / Room 2.95: Ensemble hydro-meteorological forecasting. Our traditional HEPEX session will be opened by Andy Wood’s talk on “Over-The-Loop ensemble streamflow forecasting in US watersheds”. It will be followed by talks on ensemble calibration, sensitivity analysis, ensemble nowcasting, and the use of satellites and tweets in flood disaster management. After a coffee break, you will have the opportunity to learn more about two projects, EDgE and GloFAS-Seasonal, and on recent progress on the skill of seasonal hydrological forecasts.

POSTER SESSION 17:30–19:00 in Hall A. NOTE: If you played last year’s game on Weighing costs and losses with Micha Werner (or also if you didn’t), you may be curious to learn more about the results that he will show in his poster. Come to the poster Hall A to get information and exchange ideas on the topic.

As you can see there is plenty to see and do in Vienna. See you there!

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Understanding public responses to flood warnings

Posted on April 12, 2017 by Maria-Helena Ramos

Contributed by Michael Cranston, RAB Consultants, Scotland

The Winter 2015 floods in the United Kingdom and Ireland led to severe and widespread flooding for many communities.  The introduction of storm naming by the Met Office and Met Eireann the same year has since led to the names of Desmond, Frank and Eva becoming synonymous with the flooding that was experienced during that winter. Storm Desmond (5 December) brought major flooding to Cumbria and southern Scotland with a new 24-hour UK rainfall record of 341.4 mm being recorded at Honister Pass in Cumbria. Storm Eva (24 December) brought further flooding to parts of northern England, whilst Storm Frank (29/30 December) brought severe damage to communities in Newton Stewart and Ballater.

Severe flooding from the River Dee in Ballater (Source: Evening Express)

This series of major floods led to a UK Government review on National Flood Resilience which is summarised by Louise Arnal in this HEPEX article on what we should learn from the winter 2015 floods.  However, the UK has seen significant investment in improved flood forecasting in the 10 years post-Pitt and this account of the short and medium range forecasts ahead of Storm Frank highlights that flood forecasting tools and models are starting to support much earlier warning of significant flooding impacts.

Flood alerts and warnings in Scotland are now sent to over 25,000 members of the public since the Scottish Environment Protection Agency (SEPA) introduced the new service in 2011.  During the Winter floods, SEPA’s service saw 300,000 individual messages being issued to alert and warn of potential flooding.  Following this, SEPA, through the Centre of Expertise for Waters (CREW), subsequently commissioned research to understand public responses to warnings and to assess how effective the flood warning service is for reducing the impacts of flooding.

A research team at the School of Social Sciences the University of Dundee were commissioned to undertake this project in 2016. The primary method of collating information on public response was through a web-based questionnaire of registered customers of the service.  This survey was designed to assess associations between multiple customer characteristics, including location, type of message received, prior experience of flooding, risk awareness, and demographics.  1341 customers provided a response to the survey invitation, and crucially 1290 of those provided a postcode to allow for geocoding of their responses.  The information provided through the questionnaire response was further enhanced through several community group meetings held by the research team.

The research to understand public responses to flood warnings involved consultation with members of the public and community groups across Scotland, including this taken in the Speyside

The research results are starting to deliver some interesting findings around the public response to flood warnings.  It is clear from the results that the service is valued by those at risk of flooding with 66% of the respondents satisfied with the warnings they are provided.  Many take mitigating actions, of note: 62% of those who said flooding of land was important to them subsequently moved livestock on receipt of a warning; 71% of those that stated they had bought these measures, deployed property level protection; and 42% of all respondents at some time removed vehicles on the receipt of a warning.

Less effective elements of the service focus on those members of the public that are not engaged with the service, possibly the ‘flood unaware’ and elements that are not locally specific enough to encourage action.  For example, the least content of customers are those that do not receive regular messages. Also, those who receive regional Flood Alerts are less likely to act given the lack of locally specific information, which is typically misunderstood by members of the public as a part of the service that they consider should offer more local relevant flooding information. This theme was one of several that were explored further during the community workshops with some referring to the need for local reference points in warnings, a discussion which featured as part of the flood memory and historical references HEPEX article last year.

Work continues to conclude this research which will be published by CREW this summer with recommendations for future development of the flood warning service.  However, a summary of the results will be provided at the forthcoming EGU General Assembly as a PICO presentation as part of the Hydrological Sciences Division, in co-organization with the Natural Hazards Division, on a session of the Hydrological Forecasting Sub-Division on operational forecasting and warning for natural hazards.

This work will be presented as part of the PICO session on operational forecasting and warning systems for natural hazards: PICO spot A, Wednesday 26th April between 08:30 and 12:00 (see programme here)

This work would not have been possible without the efforts of the Dundee University research team of Dr. Alistair Geddes, Dr. Andrew Black and Alice Ambler and the guidance of SEPA’s Project Manager Cordelia Menmuir.

Michael Cranston is an Honorary Research Fellow with the School of Social Sciences at Dundee University and a consultant in flood early warning with RAB Consultants in Scotland.  Prior to this he was an operational flood forecaster and Manager of the Flood Forecasting and Warning team at SEPA.

Posted in decision making, floods, forecast communication, forecast users, operational systems | Leave a comment