In this work, we explored the effect of combining microscopic-rich and macroscopic-rich information into a training set of experimental observables used to automatically optimize classical three-site water models. In particular, as the microscopic target observables, we use the experimental g OO , g OH , and g HH radial distribution functions of liquid water at various temperatures that, altogether, contain information not only of how strongly the water molecules interact but also on how the molecules are organized in space respect to each other. A first optimization of the water model under standard conditions (298 K and 1 bar) using only such a bottom-up (microscopic) reference demonstrated how such microscopic information alone is insufficient to obtain an experimentally consistent reproduction of all other screened macroscopic observables for the liquid phase of water, especially for what pertains to the density and dielectric constant of liquid water.