Spatial models of variations in the stable isotopic composition (isoscapes) of water resources have become a key tool to portray factors influencing the hydrological cycle across the landscape. Although isoscapes could contribute significantly to the water management of water resources in different environmental contexts, the performance of interpolation methods should be addressed in the light of the data structure, but also of topographic complexities. Here, we evaluated the influence of low-density data and abrupt and rugged relief on the performance of geostatistical (ordinary kriging - OK) and mechanistic (Inverse Distance Weighted -IDW) interpolation methods in estimating spatial variations in and values of meteoric waters across the western slope of the Andes (17.5º-24.5ºS). Specifically, we focused on the Atacama Desert -the world´s driest desert-. That is, we generated a regional database that gathers pre-existing and novel stable oxygen and hydrogen isotope measurements of regional meteoric waters. The irregular spatial distribution of these data led us to test the performance of interpolators by generating independent oxygen and hydrogen isoscapes for two distinct zones within our study area: Zone I (18°S-21°S) and Zone II (22º-24ºS). These zones were defined according to the density of oxygen and hydrogen stable isotopic data. Our results point to a higher performance of the IDW interpolator compared to OK approaches. We indeed evince that the IDW isoscapes capture quite well the predictable elevation effect on the distribution of oxygen and hydrogen stable isotope values across the southern portion of the Zone I, but also distinct isotopic enrichments over Altiplano basins as well as the coastal area of both hydrological zones. This method, however, fails in predicting the elevational distribution of 18O/16O and 2H/1H ratios over the northern Zone I and the entire Zone II due to the irregular spatial distribution of data. Although such limitations exist, the IDW interpolator appears as the best tool for generating oxygen and hydrogen isoscapes in our study area. This is consistent with other studies demonstrating that IDW is a superior interpolator when dealing with spatially uneven grids. In this sense, we challenge the prevailing notion that the geostatistical OK approach is invariably the most effective technique for spatial analyses of stable isotopes, and in turn the default method to implement isoscapes.