Several lumped parameter, or zero-dimensional (0-D), models of the microcirculation are coupled in the time domain to the nonlinear, one-dimensional (1-D)
equations of blood flow in large arteries. A linear analysis of the coupled system, together with *in vivo* observations, shows that: (i) an inflow resistance that matches the
characteristic impedance of the terminal arteries is required to avoid non-physiological
wave reflections; (ii) periodic mean pressures and flow distributions in large arteries
depend on arterial and peripheral resistances, but not on the compliances and inertias of the system, which only affect instantaneous pressure and flow waveforms; (iii)
peripheral inertias have a minor effect on pulse waveforms under normal conditions;
and (iv) the time constant of the diastolic pressure decay is the same in any 1-D model
artery, if viscous dissipation can be neglected in these arteries, and it depends on all
the peripheral compliances and resistances of the system. Following this analysis, we
propose an algorithm to accurately estimate peripheral resistances and compliances
from *in vivo* data. This algorithm is verified against numerical data simulated using
a 1-D model network of the 55 largest human arteries, in which the parameters of the
peripheral windkessel outflow models are known *a priori*. Pressure and flow waveforms in the aorta and the first generation of bifurcations are reproduced with relative
root-mean-square errors smaller than 3%.