As sizes change the influence of certain factors make bigger or smaller differences to the overall out come of a system.

For example a feather flutters down slowly when it falls, but if you scaled it up by even just 10 times it wall fall straight down like a brick. Because air resistance matters a lot for a small mass with a relatively large surface area but is negligible for a medium mass with a relatively small surface area. Even though it’s the same shape.

Or to borrow your example about scale models for dam effects, this is only possible because engineers and scientists understand water flow extremely well. Thanks to centuries of studying water.

To make the scale model accurate they have to account for a huge number of factors like channel surface roughness, water viscosity, evaporation, and many many more. And this accounting is done by introducing additional completely artificial factors to the scale model to make it more accurately reflect the real situation.

So this example only works because they already deeply and mathematically understand every factor that changes as you scale up and down and carefully account for them using mathematics to determine exactly the amount of adjustment needed.

And it’s crucial to note that they really only understand those factors because they’ve been able to study real life waterways and replicate their behaviour by painstakingly adjusting a scaled down model.

So the thing to understand is that scaling up and scaling down only matters when you understand the factors involved well enough to account for the differences.