The characterization of the variables through continuous surfaces is one of the most important activities in the area of Climatology. To carry out this graphic representation, it is necessary to resort to different methods of interpolation to estimate the value of the variable from a discrete number of observations. In the literature there is a great amount of proposals to carry out this process in relation to the precipitation variable. The objective of this work was to compare four methods to analyze the accumulative rainfall data. The methods used in this study were Kriging, Cressman, Barnes and the inverse distance weighted method (IDW). The Kriging method uses the structure of spatial correlation captured from the variogram for the estimation of weights. In the Cressman method the weights depend on the distance between the point to be estimated and the neighbors that are within a radius of proximity R. The Barnes method is an improvement of the Cressman method. IDW uses as weights the weighted inverse distances between the point to be estimated and that of the points with information. To carry out this comparison, different measures of prediction errors were calculated for each method. To determine these errors the estimated values from the generated images in the information points were taken into account. These maps were obtained from the average values observed in the points belonging to different regular grids. Once the best method was selected, the accumulative rainfall map of the province of Santa Cruz was constructed.