摘要
The distribution of potential evaporation is highly unstable due to complex human activities and climate changes. Therefore, it is of great significance for further understanding hydrological cycle to estimate potential evaporation distribution. Reasonable regionalization of potential evaporation will help to improve the efficiency of irrigation and increase the ability of drought relief, which is of great importance to irrigation planning and management. Hence, the spatio-temporal changes in potential evaporation distribution at monthly and annual scales are investigated based on the modified Mann-Kendall trend test method and the entropy theory in the Wei River Basin. A nonparametric method as an attractive alternative to empirical and parametric approaches is proposed to calculate the univariate and bivariate probability distribution of potential evaporation. The directional information transfer index (DITI) is employed to estimate the similarity among the meteorological stations, and the k-means cluster analysis is used to classify the meteorological stations into several distribution zones with distinct features. Based on the monthly potential evaporation from 1960 to 2008 at 21 meteorological stations, the basin is ultimately classified into 8 zones with their own distinct spatio-temporal distribution features. In view of the distinct spatio-temporal distribution features, the DITI-based model combined with the nonparametric probability estimation method and the k-means cluster analysis offers a more precise classification of potential evaporation distribution zones.