Résumé
Estimating the transmissivity or hydraulic conductivity field to characterize the heterogeneity 10 of a crystalline aquifer is particularly difficult because of the wide variations of the 11 parameters. We developed a new approach based on the analysis of a dense network of water-12 table data. It is based on the concept that large-scale variations in hydraulic head may give 13 information on large-scale aquifer parameters. The method assumes that flux into the aquifer 14 is mainly sub-horizontal and that the water table is mostly controlled by topography, rather 15 than recharge. It is based on an empirical statistical relationship between field data on 16 transmissivity and the inverse slope values of a topography-reduced water-table map. This 17 relationship is used to compute a transmissivity map that must be validated with field 18 measurements. The proposed approach can provide a general pattern of transmissivity, or 19 hydraulic conductivity, but cannot correctly reproduce strong variations at very local scale 20 (less than10 metres), and will face of some uncertainties where vertical flows cannot be 21 neglected. 22 The method was tested on a peridotite (ultramafic rock) aquifer of 3.5 km 2 in area located in 23 New Caledonia. The resulting map shows transmissivity variations over about 5 orders of 24 magnitude (average LogT:-5.2±0.7). Comparison with a map based on measured water-level 25 data (n=475) shows that the comparison between LogT-computed values and LogT data 26 deduced from 28 hydraulic tests is estimated with an error less than 20% in 71% of cases 27 (LogT±0.4), and with an error less than 10% (LogT±0.2 on average) in 39% of cases. From 28 this map a hydraulic-conductivity map has been computed showing values ranging over 8 29 orders of magnitude. The repeatability of the approach was tested on a second data set of 30 hydraulic-head measurements (n=543); the mean deviation between both LogT maps is about 31 11%. These encouraging results show that the method can give valuable parameter estimates, 32 and can characterize aquifer heterogeneity. The computed LogT and LogK maps highlight the 33 spatial distribution of parameters that show a pattern clearly controlled by the fault network of 34 this ultramafic massif. However, the faults are mainly characterized by low-permeability 35 zones; this differs from results on other crystalline aquifers and may be due to the fact that 36 weathering products of peridotite are clay-like materials. 37 The resulting transmissivity map can be used as a starting point for modelling or to direct 38 additional fieldwork.