Geostatistical and Spatial Statistical Modelling of Precipitation Varia-tions in Iran

Abstract

See, stats, and : https : / / www. researchgate . net / publication / 303785363 Geostatistical of Article DOI : 10 . 4172 / 2165 - 784X . 1000230 READS 15 1 : Majid Payame 5 SEE All - text , letting . Available : Majid Retrieved : 07 Volume 6 • Issue 3 • 1000230 J Civil Environ Eng ISSN : 2165 - 784X JCEE , an open access journal Abstract This study examines the geostatistics and spatial relationships between annual , seasonal and monthly rainfall in Iran for the period 1975 - 2014 . Precipitation variation models were com - pared in Iran deriving from six geostatis - tical , four regression and five spatial models , using monthly data . A geostatistical and spatial statistical analysis consisting of two measurement sub - models was created based on monthly accumulated precipitation ; the data was the monthly and seasonal amounts for the period 1975 - 2014 , and were estimated from 140 stations . The results of the new geostatistical - spatial statistical analysis model showed that average monthly precipitation se - ries in Iran were revealed to follow Gaussian distribution given their histogram plots and closeness of their mean and median values . On average , monthly precipitation ranged from 3 . 22 mm in April to 47 . 157 mm in December in Iran . The suitable interpolation of monthly precipitation indicates that the accuracy of spring precipitation interpolation (RMSE=0 . 558) can be applied by IDW (Cross - validation) . The kriging interpolation of monthly precipitation indicates that the accuracy of autumn precipitation interpolation (RMSE=0 . 0822) can be applied by probability kriging of autumn precipitation . The empirical Bayesian kriging interpolation of monthly precipitation indicates that the accuracy of autumn precipitation interpolation (RMSE=0 . 357) can be applied by empirical Bayesian kriging of autumn precipitation . The temporal - spatial distribution of the precipitation station locations has been studied using the ANN tool of the spatial statistics toolbox of ArcGIS 10 . 3 . Based on the calculated Moran ' s Index , approximately all months ' precipitation (with the exception of February) has the monthly spatial distribution of the clustered type . The High / Low Clustering of stations ' monthly precipitation has been studied using the HLC tool . Based on the calculated g - index , approximately all months ' precipitation (except for February and March) has the monthly spatial distribution of the high - clusters type .