As an experiment I tried using NMinimize on the sum of the squares of your seven equations with options Method->"RandomSearch" and MaxIterations->1000. That returned estimated parameters and a minima that was far from zero.
I then used the seven reported parameter values as starting locations in FindRoot with option MaxIterations->1000. I then evaluated the left hand side of the seven equations with the revised parameter values that it found and again some of the results were not close to zero.
I then used FindRoot again with the seven revised parameters for starting values and MaxIterations->1000, evaluated the left hand side of the seven equations with the newly estimated parameter values and found that all the results were very close to zero.
Because there is a random element in this the results may vary from one attempt to another.
I also tried adding broad constraints on the ranges of the parameters in NMinimize, to see if I might guide it to finding solutions with smaller parameter values. That was not as successful.
You might try this and see if you get similar results.
This does not deal with local minima or how many solutions there might be or unrealistic parameter values.