نوع مقاله : مقاله پژوهشی
نویسندگان
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چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Among various approaches for mapping isohyets are regression analyses techniques that use relationship between precipitation and geographical factors. Current study was carried out to compare global regression methods (multi polynomial regression and ordinary least square methods), local regression methods (local polynomial regression, geographically weighted regression) and decision tree regression. Average of 20 years annually precipitation data of 185 meteorological observations over Gilan Province and its neighboring stations were used for modeling of spatial distribution variations of mean annual precipitation by using other variables like elevation and point locations from the sea level. Comparison between results using cross validation technique showed that geographically weighting regression method has the highest accuracy to estimate mean annual precipitation (R2=87 and RMSE=147mm) and can be used to map isohyets in Gilan province.