SPATIAL-ANALYSIS FOR MONTHLY RAINFALL IN SOUTH FLORIDA

Several methods have been developed to interpolate point rainfall data and integrate areal rainfall data from any network of stations. From previous studies, it can be concluded that models for spatial analysis of rainfall are dependent on topography, area of analysis, type of ra infall, and density of gauging network. The purpose of this study is t o evaluate a set of six appropriate models for point and areal rainfal l estimations over a 4000 square mile area in South Florida. In this s tudy, a case of developing spatial continuity model for monthly rainfa ll from a database that had various lengths of records and missing dat a is documented. The spatial correlation and variogram models for mont hly rainfall were developed. Six methods of spatial interpolation were applied and the results validated with historical observations. The r esults of the study indicate that the multiquadric, kriging, and optim al interpolation schemes are the best three methods for interpolation of monthly rainfall within the study area. The optimal and kriging met hods have the advantage of providing estimates of the error of interpo lation. The optimal interpolation method uses the spatial correlation function and the kriging method uses the variogram function. The two s patial functions are related. Either of the two methods provide good e stimates of monthly point and areal rainfall in the study area.