Sensitivity analysis is a method to determine the effects of different parameter values and inputs has on simulation outputs. This process can be done before or after calibration (Ronald 2016). +
“Fig Row” refers to the row in S5 Fig. The indicated parameter for each family is drawn at random from the listed values, and the “first”, “second”, and “third” columns refer to the respective x value
A rank is assigned to each parameter according to how much it impacts the model output total variance. Parameter groups are assigned a score given by the sum of the ranks of their member parameters. T
– parameters K4 and K6 seem to have similar sensitivity, however K4 is highly sensitive (according to raw values from A), and K6 is not sensitive at all; D. improved average ranks (IAR) of A – here th