But first, can we predict how many lives will be lost in the event of a dam failure?
Here we have an formula that Curtiss A. Brown and Wayne J. Graham published in 1988 to estimate the loss of life due to a dam failure.
In their analysis of the threat to human life by dam failures, Brown and Graham developed a formula that would calculate the potential risk at hand for each dam. Creating the formula first required an analysis of previous dam failures.
Brown and Graham looked at three characteristics for each dam:
By measuring the loss of life against the total population of each previous dam failure, Brown and Graham were able to construct graphs of their findings. One graph was created for the insufficient warning times, i.e. those under an hour and a half, and another was created for the sufficient warning times. The warning time is the amount of time before the dam fails that the people at risk realize the dam is going to fail; in other words, it is the time between when the people find out the dam is going to fail and when the dam actually fails, usually in hours.
What is the amount of warning time (in hours) before the dam fails? (time less than 0.75 hrs won't work due to the nature of the equation)
Using the graphs, they were able to determine rough estimates for the potential loss of life using the slopes of their two graphs. For dam failures with insufficient warning times, the unadjusted estimate is equal to the population taken to the 0.6 power. For example, with a population of 1000 people, the unadjusted estimated death rate would be about 63. However if there is enough warning time, then the unadjusted estimate is equal to .0002 times the population size. That means that if the same group of people is given ample warning time, then there should not be a single death.
But the graph estimates were not always consistant. Brown and Graham found that areas with a warning time below an hour and a half had an average fatality rate of 13%. Those with a warning time above an hour and a half had an average fatality rate of .04%. They found that there was a large difference between the low and high in each average. Upon further investigation, Brown and Graham linked this to the surrounding landscape of the dam. Areas that can be flooded easily, such as canyons, had a higher fatality rate than did the flatlands, or plains.
What is the landscape around your dam like? Canyon Plain
They then devised a formula to estimate the loss of life with the four crucial variables:
X is equal to 4.012 for canyon terrain and 0 for flatlands.
