The WordPress.com stats helper monkeys prepared a 2012 annual report for this blog.
Here’s an excerpt:
600 people reached the top of Mt. Everest in 2012. This blog got about 5,400 views in 2012. If every person who reached the top of Mt. Everest viewed this blog, it would have taken 9 years to get that many views.
Click here to see the complete report.
This afternoon, at the FloodRisk2012 conference in Rotterdam, I will present on the findings of the Probabilistic Forecast Use project that we’re currently finalising.
There is a strong theoretical rationale for using probabilistic rather than deterministic forecasts. Currently, however, there exist no best practices for effectively using probability forecasts. In the project, we tried to contribute to the development thereof. I think we achieved quite a lot. The main findings I am presenting on this afternoon are:
- Hydrological forecasting community supplies hazards whereas often, users are more interested in consequences
- Manipulating – not understanding – probabilities is an issue; asking the right question of a forecast largely resolves this.
- Disclaimers apply to the risk rationale
There’s more to say about the topic, obviously. Have a look at attached presentation slides and let me know what you think! If you can make it to the conference: today, Wednesday November 21st, 4pm, room 6.
Wednesday update: there has been an eruption alright… of neighbouring Tongariro!
A few years ago my partner and I hiked a six-day tour of Mt Ruapehu. This is a beautiful mountain, probably best known outside of New Zealand for its role as Mount Doom in one of the Lord of the Ring films.To the geological community, it is known as an active volcano which’ eruptions has lead to lahars in the past, sometimes with many fatalities as a result.
The title of this blog post is an exaggeration of the truth, of course, but the fact is that the NZ Department of Conservation has issued a warning:
A Volcanic Alert Bulletin issued today by GNS Science summarising recent measurements at Ruapehu indicates the likelihood of eruptions from the mountain has increased.
There is no certainty that an eruption will take place of course, and I am guessing that the uncertainty cannot be characterised by a probability estimate.
Below image was posted on Twitter yesterday by Environment’s Agency David Troup. I like it a lot. To me, it gives an instant overview of flow levels across England and Wales. I’d love to have a similar graphic available in the two forecasting systems I use (the Dutch system for Rhine and Meuse, and EFAS, the European Flood Awareness System).
Some thoughts on below picture:
- I wonder who the target audience for this graphic is. The percentiles are maybe a bit complicated for those not used to it.
- The colours used are different from what I would use. For my application (flood forecasting), I’d express flooding as red, not black.
- More and more often, I see observations and forecasts of hydrological variables expressed as relative values to some reference, rather than in absolute values. Here, the baseline is the climatology of flow at the hydrological stations. In the US, forecasts are often expressed relative to “normal”. This development, I think, comes from Anglo-Saxon environments.
- This overview is well suited if there are not too many stations on the map.
- The map does not indicate whether these flow levels cause flooding or not. At different locations, flooding may occur at
- If similar graphs were to be used for forecasting, one will quickly run out of available dimensions. Forecasts would require the leadtime dimension to be indicated somehow, and also the uncertainty in the forecast. Edwin Welles -a colleague of mine at Deltares- and I have developed some ideas about this, which I’ll share later.
Again, I think Dave’s map is a great way of showing spatially variable information. Above items should be seen as considerations in case similar graphs were to be implemented in the systems I use.
November 12 update: Dave let me know that these maps are used to show water resources situation. Makes perfect sense!
Last January, water board Noorderzijlvest experienced near-flooding. Large amounts of precipitation coincided with above normal tides. For a few days, the water board was unable to use its pumping stations for drainage, and the polders gradually filled with water. At some point, emergency managers decided to evacuate some of the polders and villages. As this doesn’t happen very often, this was widely reported in the national media.
The regional security authorities (“Veiligheidsregio Groningen“) made a 15 minute video (in Dutch only) about this event. It’s interesting to see that a lot of elements of flood risk management come together:
- flood hazard and flood risk
- flood stage and levee strength
- warning and response
- managing uncertainties in decision making
(if you like the science of hydrology and decision-making, check out this page)
For almost a year now, I’ve been a member of the Dutch River Forecasting Service, which is responsible for monitoring and forecasting of water levels and discharges of rivers Rhine and Meuse. For this, we have a wonderful tool available: FEWS Rivers. The tool imports meteorological as well as hydrological observations and forecasts and allows one to run these through hydrological and hydrodynamic rivers to produce estimates of future stage and flow. There is really a wealth of information available, making it difficult sometimes to find one’s way.
Rhine-Meuse delta, just downstream of my forecasting locations
So how do I go about making a forecast? Rather than simply looking at the latest available forecasts and choosing one that fits my beliefs, I try to dig a little deeper. Here’s the list of questions I try to answer:
- What does the meteorological history look like?
- What do the meteorological forecasts say?
- What’s the hydrological history?
- What do the hydrological models say?
- What is the current action level? What are the criteria for moving to the next level and have these been met?
Typically, this analysis will take about one hour for each of the two rivers. Usually I only do this at the beginning of my shift, though. Once I (think I) know what the situation is like, I can suffice by looking at incremental information only, which takes a lot less time. Obviously, this is true only if nothing much is happening. If any flood waves are coming my way, analysis takes longer.
If I can find the time, I’ll go a bit deeper into each of above questions.
Hydrology isn’t practised in isolation. Rather, hydrological analyses are used as input to decision processes. How can forecasts, predictions, scenarios, outlooks and foresights best serve these decisions? How should uncertainties be managed? What is the relative weight of hydrological considerations in comparison to other, non-hydrological considerations? At EGU2013, we are organising a session on these topics. The session is described in enclosed session leaflet. Abstracts can be submitted until January 8, 2013. A report on the 2012 edition of this session is available from here.
November 12 update: we are pleased to announce that Prof Rob Wilby has agreed to speak in our session. His contribution is titled “Decision- rather than scenario-centred downscaling: smarter use of climate model outputs”.
Session leaflet. Click to open/download pdf version (opens in new window).