Rainfall characteristics, which include spatial variability, exert a major influence on runoff properties. Many techniques have been proposed for determining the spatial distribution of daily rainfall. One of these techniques is spatial modeling, based on rainfall data measured by rain-gauge networks. In this study, application of different interpolation methods in the GIS environment, for estimating the spatial distribution of daily rainfall in the southwest of Iran with low rain-gauge density, have been compared on a regional scale. The cross validation technique was selected as an accuracy index and statistical parameters, such as MAE (Mean Absolute Error) and MBE (Mean Bias Error), were used for comparing the results of cross validation.
The ranking of MAE and MBE values was used for determining the best interpolation method. The interpolation methods that were studied for mappingthe spatial distribution of daily rainfall include nearest point, moving average, moving surface, trend surface and kriging. Since the spatial pattern of daily rainfall is random, the moving average method, with inverse distance weight function, was determined as the best method for interpolating daily rainfall data in the region of study.