While I agree with the gist of this, the ones to finally call the shots on such projects are always in a bad spot.

They underprovision and an anomaly happens. Now they are the ones who did everything wrong and should be blamed. The overprovision and nothing ever comes close to the theoretical limit of the structure. Now they have wasted huge amounts of money and again, should obviously be blamed. The easiest way out: Plan exactly to what is considered standard. No one will blame you in either case, even if you know that it is insufficient or stupid.

This is something that will probably hold true in many different industries, the consequences for dams are just a little worse..

> Now they are the ones who did everything wrong and should be blamed.

Is it possible to develop a blame-free (or at least blame-avoiding) culture that also can still look for root cause problems? I'd like to think so but have never seen such a thing at scale.

This is the question that has been going through my head after I wrote the parent comment.

I have never been in such a situation (at least not one where the stakes were relevant), so take this with a grain of salt. Blaming under these kind of circumstances might arise because the people who do it:

* Either do not have access to the information necessary in order to develop a sufficient understanding of the problem at hand

* Or are incapable of understanding the problem at hand to a sufficient degree (because the project is too big for a single person to grasp or whatever)

So, they resort to assuming some simplifications in order to make everything understandable to them, but these simplifications are likely to be wrong. Consequently, they start blaming people they think to be at fault under their own flawed model of the situation.

A blame-free culture? Explain the situation to such a degree that the decision making around the root cause is easily understandable for everyone. For example, if a bridge fails, there will likely be experts that identify what has caused the failure. If the decision makers for the bridge now say that due to circumstances they disregarded a certain load situation, because x and y and this is an acceptable argumentation (to whoever is judging the situation), there will be less/no blaming as it is now understandable why things have been done that way.

But at a cultural level? I think that this would require everyone to ultimately only judge situations once they have understood the problem at hand. At that point, why do we even talk to each other? Everything we say is based on incomplete information anyways..

You've missed a third bullet point:

* They are capable of understanding the problem, and have access to the information necessary in order to understand the problem, but will advance their career/campaign by pushing their opponent under the bus.

Politicians don't get elected based on objective past results, they get elected based on how well they can spin promises of the future.

And, as the saying goes, you get what you measure.

https://en.wikipedia.org/wiki/Just_culture "Just culture is a concept related to systems thinking which emphasizes that mistakes are generally a product of faulty organizational cultures, rather than solely brought about by the person or persons directly involved. In a just culture, after an incident, the question asked is, “What went wrong?” rather than “Who caused the problem?”. A just culture is the opposite of a blame culture."

Also "Just Culture: Restoring Trust and Accountability in Your Organization" by Sidney Dekker

I believe you're talking about Human Factors which is an entire field of study in complex systems and psychology. The book The Field Guide to Understanding Human Error might be of interest.

I think that single person electorates and direct voting for the executive branch are not exactly helping this situation.

I wonder if it would be batter if the primary power was in the hands of a multi-party, proportionally elected assembly with representation greater the 1 assembly member per a population of 20.000 residents (for both national and local governments) and no executive branch (or perhaps executive branch being experts hired by the assembly). There would certainly be less room to blame here (or at least the blame would be on the entire governing body; which could be voted out proportionally rather then individual representatives).

In general, I want to understand what happened and since most issues have a human component, that often means understanding which human under-performed, how and, ideally, why.

In that sense, I want us to understand where the responsibility for the failure (aka the blame) lies. That’s different from punishing based on any single incident.

You absolutely can have blame without punishment.

The issue is that human interactions are largely based on reputation. If a person is blamed, immediately their reputation suffers. Hence blame=punishment.

As mentioned in other comments, if you are close enough to know and understand then qualifying facts may remove the reputational damage in your mind, and you may fully trust that person to do similar work in future.

But in society wide incidents few of us are that close to the event of concern.

Yes. The NTSB is such a culture.

Yes, it's possible, as long as you are willing to give up democracy. I'm not sure you want to make that trade-off.

Edit: This seems to be negative karma bait, so let me express in clear terms - in a democratic system, all else being equal, a challenger who does play the blame game will prevail over an incumbent, who let a disaster take place on their watch.

I would argue that we would indeed need more democracy (see sibling comment).

The current situation in many of the world’s leading democracies is that representation is abysmal and the democratic process is gamified in such a way as to encourage this kind of blame-game. I’m pretty sure there exists a way to optimize the democratic process in such a way that this blame-game doesn’t happen.

I think this is similar to what happened in Fukushima, where the original architects of the Daiichi plant suggested building a much higher protective wall against tsunamis, but were forced to build a lower wall because such a catastrophic tsunami was deemed too improbable. (Then it came, of course.)

That may or may not be true but as per the article, building standards like that are defined in terms of 1 in 100 or 1 in 1000 year events etc. The years bit in Japan will be defined already in their standard for designing a protection for tsunami events. Now, I don't know what 1 in n years is used but I suspect that it would be 1 in 500 or 1000 years. If a 1 in 10000 years event turns up then the inevitable happens.

So all we have to look up is the standard and the event and compare. Even then you have to design to account for what to do and what happens in the event of your wall's failure and that is probably where things went really wrong.

You could always read things like this: https://www-pub.iaea.org/MTCD/Publications/PDF/Pub1710-Repor...

Yeah, exactly. The thing is, where do you draw the line of what is statistically so unlikely that you can deem it improbable?

If we run multiple different climate models through some sort of Monte Carlo simulation, I suppose each model would output a different probability of such an event occuring. In the case where all models predict a very low probability, it may be easy to say that it is unlikely. But what if two predict a very low and one predicts a low probability? Is this now applicable and should we build to be able to sustain such an event?

These are hard questions and I currently do not see any way to get better data for the future as the different models still do not agree in many points

In that case it could be interesting to plan for future reinforcements, and continue to run the simulations as time passes and the situation evolves.

I don't know if it's due to models and computing environments not being stable enough, but I haven't heard of such a thing, while it is the obvious thing to do: even without reinforcing a dam, you could tell when it becomes dangerous to operate it.

> In that case it could be interesting to plan for future reinforcements, and continue to run the simulations as time passes and the situation evolves.

While I agree that the idea is good, I imagine that at a point where you are planning to extend your dam by another 20m, you already have to implement the required changes in your foundation and general structure and additionally, turbines and emergency vents have to be upsized for the extended heights. So the only thing you are now missing during build is the extra 20m of dam, as the rest has to be built anyways. This leads back to my initial point of the right amount of over-/underprovisioning..

I am not sure if I understood the second point correctly, but you can obviously tell when a dam becomes too dangerous. This can either be because the foundation has set and you now have increased structural stress, the amount of water has increased beyond the maximum allowed levels or a multitude of other reasons, but they are actively monitored.

> Yeah, exactly. The thing is, where do you draw the line of what is statistically so unlikely that you can deem it improbable?

Important question, because otherwise your costs are absurd and something important (like a power source) never gets built.

Some fields, like road construction, have a cost model built in and at some point are willing to either pull the plug or decide that a few unlikely (originally autocorrected to "unlucky!") fatalities are acceptable.

There are branches of probability theory that deal with these questions rigorously.

https://en.m.wikipedia.org/wiki/Large_deviations_theory https://en.m.wikipedia.org/wiki/Extreme_value_theory

That's what reinsurance actuaries are for. Of course extremely rare events that have not occurred in living memory are harder to model for than life insurance tables.

I am sorry to bring it up, but this is about the same as the way I view the response to COVID by our (Western) leaders.

The gist of this is that everything gets more expensive. Our environment was basically tailored to us. Moving away from that, and losing stability to boot adds costs.

It’s another short run vs long run tradeoff. Fossil fuels brought and bring us immense short term benefits. But increasingly the benefits now will lead to larger costs in the future, both in adaptation and also in attempting to reverse the costs by taking co2 out of the air.

The best solution would be to bring future costs into the present and charge for co2 emissions. That way the truly valuable uses could still happen and the more optional uses of co2 would be discouraged.

This article is talking about building for the next few decades, but the non-stationarity problem will only grow if we keep emitting.

> The best solution would be to bring future costs into the present and charge for co2 emissions. That way the truly valuable uses could still happen and the more optional uses of co2 would be discouraged.

Yep. A price on carbon is actually the most powerful lever we have to bring down emissions. Very nice visualization when you move the carbon price slider here: https://en-roads.climateinteractive.org/scenario.html?v=2.7....

And you can make it both equitable and politically viable if you use the money from the carbon fee to provide direct payments to households, then combine with a border adjustment to maintain trade competitiveness. https://econstatement.org/

Ultimately we just need something in place that corrects this obvious market failure with as few side effects as possible, and carbon fee and dividend does that. https://en.wikipedia.org/wiki/Carbon_fee_and_dividend

Yep, carbon taxes that are split evenly amongst everyone is ideal. If you use less carbon than the average person, you will make money.

It acts as both an incentive to use less carbon and an easy way to even out the wealth gap.

In theory I agree with the idea of charging for Co2 emissions, the problem always comes down to the execution, which in general means some kind of "carbon tax" system

The problem with the carbon tax systems I have seen most of them are setup in a way not to actually change climate or anything to do with climate change but instead set up to fund unrelated agenda's and often end up being counter productive to the actual goal of reducing carbon emissions / other population.

That part about funding unrelated agendas is partially why many leading economists recommend returning the revenue as a flat dividend. The revenue from the carbon tax is just divvied up and given back to everyone as a monthly direct deposit. https://econstatement.org

This also addresses the other concerns you pointed out below. The dividend helps to both (a) allow you to invest in improving your energy efficiency or (b) soften the blow where you can't. You may remember the Yellow Vest movement when France tried to apply a carbon tax. If France had given money back to the people, they probably would have had a lot more success with it.

Please share said tax systems. Everything I’ve seen is an upstream tax on each ton of emissions. Its not about funding things, its about disincentivizing emissions by forcing the cost of externalities onto the production itself.

Well those systems that do not have alternative funding goals also end up being very regressive, if my Power or Nat. Gas bill increased by 30% well I will complain online, and be frustrated every-time I have to pay it, but I will not have to choose between paying the utility or buying food. Nor will it modify my consumption of it, it just means more expenses. I use the amount of energy I need today, no more, no less. Charging me more for it will not change my consumption.

That can not be said for others. Carbon Tax's on power generation and home heating have the nasty impact of being very regressive impacting the poorest among us disproportionately

We need to improve Alt. Energy to make it cost competitive with Fossil Fuels, and not by artificially raising the prices on Fossil fuels which harms the poor.

Carbon Tax systems also end up not actually reducing carbon, but instead allow "trading" of carbon heavily producers with monopoly lock in can simply gouge their customers with higher prices to pay for "offsets", it is akin to wealth redistribution but rather with carbon

Carbon dividends offset the regressive nature of a carbon tax. In fact, even if you exclude the benefits of cleaner air and just look at how the carbon dividend offsets the carbon fee, folks at the lowest incomes tend to come out way ahead, at least under the Energy Innovation and Carbon Dividend Act: https://citizensclimatelobby.org/wp-content/uploads/2018/06/...

> Carbon Tax systems also end up not actually reducing carbon, but instead allow "trading" of carbon heavily producers with monopoly lock in can simply gouge their customers with higher prices to pay for "offsets", it is akin to wealth redistribution but rather with carbon

You're confusing carbon taxes with cap and trade and carbon credits. There are no pollution permits to trade under a typical carbon tax regime. Please check your facts before sharing inaccurate information.

"planners used historical climate data ...the water no longer flowed there."

This article implies the water changes were driven by climate change, but it appears the changes were from overpumping the aquifer that fed the surface water.

"The source of the Beaver River is the vast, underground Ogallala Aquifer, which reaches into eight western states. Agricultural and population growth in this part of the country meant more pressure on the aquifer, dropping its water level and reducing the river to little more than a trickle." -- https://stateimpact.npr.org/oklahoma/2013/03/28/the-lessons-...

That doesn't mean climate change isn't concern, but this example is not caused by climate change, but rather by overuse of a limited water resource.

I learned this the hard way when engineering microwave links to withstand rain rates based on historical data.

Many of my links that the calculators said would have >99.999% availability saw a cumulative downtime in 2020 over 1hr due to much higher peak rain rates than historically measured.

I now engineer the links to handle double the historically measured rain rates.

Was that because the data was not actually peak _instantaneous_ rain rates, but rather rates averaged over a period of time (likely hours or longer)?

Seems like microwave links would be most sensitive to instantaneous rate along specific paths, but any historical data would be measuring accumulated precipitation (averages over time) at specific locations.

This is true -- most vendors supply a calculator tool that attempts to take this into consideration. Over the past 10yrs or so I've found them to be generally accurate, but have noticed a significant deviation in late 2019-2020 from expected vs observed effects.

I don't know what method is used but would expect it to be some sort of extrapolation from the average to predict peak rates

How does this manifest in costs? Is it noticeable?

And does rain rate mean the frequency of distinct rain events over hours/days or the intensity of a single rainfall?

Just curious, maybe you can shed some light on this

Sure --

It manifests in both cost and capability. For the same throughput you generally need more expensive equipment to obtain the same level of reliability.

Where with the previous calculations it may cost X dollars for equipment, using the new calculations you may need to use a larger antenna or a more power transmitter, costing sometimes 2-3x, if it's even possible at all. Many times the link is just no longer viable at the required reliability.

Rain rates are typically measured in mm/hr but it's an instantaneous rate, but what I've observed in 2020 is instantaneous peak rates easily 50% higher (indicated by signal attenuation levels) than 2019/2018. I'm not aware of any standard meteorological way to measure this as it seems most measurements are done as cumulative over minutes/hours/days, when the effects on microwave signals are in the seconds and minute scales.

Certainly can't establish as causal relationship with climate change, especially since my observations are on the scale of just a few years, but it shows the danger in simply relying on low resolution historical 10/50/100yr data for infrastructure design.

At this point, we should be throwing our money at geoengineering and technology in order to try and deus ex machina our way out of the pending climate crisis. We've wasted so much time that now there really is almost no other option. No one is going to lead on this issue, so it's our only hope left.

That said, I am optimistic that once the economic incentives align scientists/engineers will be able to save us from the worst effects of climate change, and down the road even reverse the effects.

We've been throwing our money at geoengineering our way into this for decades in the form of oil (and other) subsidies.

We could start by eliminating those.

There's a pretty good Kurzgesagt video about this.[1] Broadly speaking, there are no known existing plans that don't have massive unknowns or potential adverse consequences.

1. https://www.youtube.com/watch?v=dSu5sXmsur4

My wild conspiracy theory is that this is a solved problem but admitting it has problematic geopolitical implications.

Seems like quite a big hope when this is what we're dealing with.

Ignore the Reddit comment section. Saw this video at least a year ago, likely more. Weird for it to pop up on Reddit today.

https://old.reddit.com/r/PublicFreakout/comments/l43m5f/a_fa...

Culture of don't give a fuck and swindling the non-maliciously ignorant. USA will be in for rough times

> "Our drain pipes, reservoirs, power lines, roads, sewage systems, and more are all designed based on past climate data."

Not only past climate data, but traditional work arrangements. WFH shifts demands on infrastructure as well. Power, sewage, and so on. Mind you, WFH will eventually fade a bit. Non the less, it does change the lens of how past data / need should be interpreted.

I posted this not only because of the topic of the article itself but because it makes my think about systems planning (e.g. are we overprovisioning our back end for demand that may never occur?) and business plans.

Well, there is no future climate data.

Actually there is. If you view all data as statistical probability, data from the past is simply a 1.0 possibility of occurring, and future data is less than 1.0. We can easily see this by looking at weather forecasting, as a common example which both exemplifies the possibility and serves as an example of why it’s not perfect.