Our aim was to establish a viticultural zoning, based on precision viticulture techniques, and to investigate the relationships with grapevine susceptibility and epidemiological development of downy and powdery mildews. Two independent and key variables in the grapevine production system were used with a geographical information system (GIS): i) the soil electrical resistivity and ii) the grapevine biomass index NDVI. In one Medoc estate "chateau", mapping of the whole vineyard allowed us to define different classes of a-priori homogeneous “Physiological Functioning Units” (PFU) by combining the two key variables. Per cultivar (cv.), Merlot noir and Cabernet sauvignon, 3 and 6 PFUs classes were studied, respectively. Monitoring of incidence and severity of the two pathogens was performed as well as that of other key viticultural variables (yield components, topography, fruit maturity, altitude, distance to the Gironde river, vines age, row orientation…). Moreover, the overall multi-pathogens indicator, Assessment Indicator of Damage in Bunches "AIDB", was calculated. A Principal component analysis (PCA) was performed to evaluate and visualize relationships between the AIDB indicator, and all the other plant/environmental/plot variables. The results from two seasons 2015 and 2016 were based mostly on downy mildew epidemics that was the main disease in this study. The first PCA axis represented the components of the yield, year of planting and production of grapevine biomass (NDVI) in both years (corresponding to younger and more vigorous grapevine plants). In sum, this first axis reflected vegetative and reproductive vigour. The second axis showed a clear opposition (negative correlation) between the multi-pathogens pressure (AIDB) and the resistivity of the soil. As expected, the yield loss was correlated positively with the AIDB indicator, confirming the major deleterious effect of these diseases on the yield achievement, notably when no specific fungicides were sprayed. The altitude was closely related to the resistivity which is consistent because the plots a little bit higher in altitude may be drier. In addition, the distance to the Gironde estuary was opposed to the yield and to the AIDB multi-pathogens indicator. Thus, an important distance to the estuary and a high resistivity were two variables reflecting a potential lower availability of water in the soil. As water may promote disease development and higher yields, it seems rational to show negative relationships between, on one side, higher resistivity (= less water in the soil), plot higher altitude and greater distance to the river, versus, on an opposite side, both increased multipathogens’ pressure and yield potential.