Open AccessEstimation method of spatial geostatistical data : Application to rainfall data
Author(s) -
Hamid Reza Erfanian,
Samaneh Barati
Publication year - 2017
Publication title -
international journal of advanced statistics and probability
Language(s) - English
Resource type - Journals
ISSN - 2307-9045
DOI - 10.14419/ijasp.v5i2.7824
Subject(s) - zoning , water resources , environmental science , geostatistics , estimation , agriculture , hydrology (agriculture) , water resource management , meteorology , spatial variability , statistics , geography , geology , mathematics , civil engineering , ecology , management , archaeology , geotechnical engineering , engineering , economics , biology
Restriction of water resources for agricultural and non-agricultural purposes has caused major difficulties and rainfall is considered as one of the most important water resources. Therefore, predicting rainfall and estimating its rate monthly or annually for each region as one of the most important atmospheric parameters, is of particular importance in optimized usage of water resources.In this paper in addition to the presenting application of novel statistical methods, prediction of rainfall amount has been performed for the entire map of Iran. In this analysis, data of average rainfall of 108 pluviometry stations in different cities of Iran have been used and zoning of rainfall has been prepared for the country.