Abstract:
The geographical condition of Karst mountainous areas is complicated,which,together with the influence of obvious peak clusters,causes an unbalance of the spatial and temporal distribution of rainfalls.In particular,the distribution of precipitation in wet season has a direct impact on local economic crop growth and the occurrence of geological disasters.Based on the 77 weather stations in Guizhou within 30 years (1981—2010),and on the data of monthly precipitation in analysis of the terrain factors (elevation,gradient,slope direction) and meteorological factors (site pressure,relative humidity,sea level pressure) and the correlation of rainfall in Karst region,Guizhou Province,four Kriging interpolation methods have been explored in light of a comparative study.The results show that firstly,when using Pearson correlation analysis correlation between precipitation and various factors,respectively,the slope is 0.998,and the slope is of strongest correlation with precipitation.Secondly,through the association and the different half the variation function model (stable model,index model,spherical model and gaussian model) contrast,it is found that the mean difference between spherical model is minimum (MAE=-0.0004),and the consistency coefficient of optimal is best(RMSE=0.864).Results from comprehensive comparisons of different model predicted values and measured values show that the best way to carry out interpolation of precipitation in Guizhou Karst area is applying Co-Kriging interpolation with semi variation functioning as the spherical model,which can help enhance the efficiency in identifying the spatial distribution of preoccupation in Karst area during wet season.