Estuarine areas are sensitive to rapid and punctual contamination linked to heavy rainfall inducing rapid fresh water input. Thus, the increase of seawater contamination may be linked to a salinity decrease. The objective of this study was to measure salinity variation as a proxy to evaluate the risk of faecal contamination. Salinity sensors were set up on shellfish beds in Daoulas estuary (Bay of Brest) and monitored every 10 min over a four year period. Precipitation and river flows were also recorded. Moreover E. coli concentrations and salinity were measured in the estuarine surface water during different hydrodynamic conditions and seasons. The results indicated a significant relationship between E. coli concentration and salinity in the estuary. Mathematical models were then selected and validated to assess and predict salinity variations. In the upper estuary, statistical analysis shows that variation in salinity is a function of the rainfall of the previous day (first model with r2= 0.66). The second model established a relationship between salinity and precipitation which reproduced 95% of the events, but failed to reproduce salinity variations during low rainfall (<1mm/day).